diff options
| author | Sergey Sharybin <sergey.vfx@gmail.com> | 2016-01-04 16:11:12 +0300 |
|---|---|---|
| committer | Sergey Sharybin <sergey.vfx@gmail.com> | 2016-01-04 17:39:13 +0300 |
| commit | 6fb6a08bf84d5d16ebac35527a77bec37112494e (patch) | |
| tree | 9315b37d5022881ada9efcc8bc42a7387500ff0c /extern/libmv | |
| parent | 0b856dd97e43cf116ac136b74bc3a559c679522e (diff) | |
Move Ceres to extern/
Even tho it's currently only used by Libmv we might use it for something
else in the future. Plus, it's actually where it logically belongs to.
Diffstat (limited to 'extern/libmv')
263 files changed, 9 insertions, 47608 deletions
diff --git a/extern/libmv/CMakeLists.txt b/extern/libmv/CMakeLists.txt index c4d27c24f09..375031fd1cb 100644 --- a/extern/libmv/CMakeLists.txt +++ b/extern/libmv/CMakeLists.txt @@ -37,22 +37,9 @@ set(SRC libmv-capi.h ) -TEST_SHARED_PTR_SUPPORT() -if(SHARED_PTR_FOUND) - if(SHARED_PTR_TR1_MEMORY_HEADER) - add_definitions(-DCERES_TR1_MEMORY_HEADER) - endif() - if(SHARED_PTR_TR1_NAMESPACE) - add_definitions(-DCERES_TR1_SHARED_PTR) - endif() -else() - message(FATAL_ERROR "Unable to find shared_ptr.") -endif() - add_definitions(${GFLAGS_DEFINES}) add_definitions(${GLOG_DEFINES}) - -add_subdirectory(third_party) +add_definitions(${CERES_DEFINES}) if(WITH_LIBMV) list(APPEND INC diff --git a/extern/libmv/bundle.sh b/extern/libmv/bundle.sh index da465e5f93c..273365bb31a 100755 --- a/extern/libmv/bundle.sh +++ b/extern/libmv/bundle.sh @@ -17,10 +17,7 @@ git clone -b $BRANCH $repo $tmp/libmv git --git-dir $tmp/libmv/.git --work-tree $tmp/libmv log -n 50 > ChangeLog find libmv -type f -exec rm -rf {} \; -find third_party -type f \ - -not -iwholename '*third_party/ceres*' \ - -not -iwholename '*third_party/CMakeLists.txt*' \ - -exec rm -rf {} \; +find third_party -type f -exec rm -rf {} \; cat "files.txt" | while read f; do mkdir -p `dirname $f` @@ -32,13 +29,13 @@ rm -rf $tmp sources=`find ./libmv -type f -iname '*.cc' -or -iname '*.cpp' -or -iname '*.c' | grep -v _test.cc | grep -v test_data_sets | sed -r 's/^\.\//\t\t/' | sort -d` headers=`find ./libmv -type f -iname '*.h' | grep -v test_data_sets | sed -r 's/^\.\//\t\t/' | sort -d` -third_sources=`find ./third_party -type f -iname '*.cc' -or -iname '*.cpp' -or -iname '*.c' | grep -v ceres | sed -r 's/^\.\//\t\t/' | sort -d` -third_headers=`find ./third_party -type f -iname '*.h' | grep -v ceres | sed -r 's/^\.\//\t\t/' | sort -d` +third_sources=`find ./third_party -type f -iname '*.cc' -or -iname '*.cpp' -or -iname '*.c' | sed -r 's/^\.\//\t\t/' | sort -d` +third_headers=`find ./third_party -type f -iname '*.h' | sed -r 's/^\.\//\t\t/' | sort -d` tests=`find ./libmv -type f -iname '*_test.cc' | sort -d | awk ' { name=gensub(".*/([A-Za-z_]+)_test.cc", "\\\\1", $1); printf("\t\tBLENDER_SRC_GTEST(\"libmv_%s\" \"%s\" \"libmv_test_dataset;extern_libmv;extern_ceres\")\n", name, $1) } '` src_dir=`find ./libmv -type f -iname '*.cc' -exec dirname {} \; -or -iname '*.cpp' -exec dirname {} \; -or -iname '*.c' -exec dirname {} \; | sed -r 's/^\.\//\t\t/' | sort -d | uniq` -src_third_dir=`find ./third_party -type f -iname '*.cc' -exec dirname {} \; -or -iname '*.cpp' -exec dirname {} \; -or -iname '*.c' -exec dirname {} \; | grep -v ceres | sed -r 's/^\.\//\t\t/' | sort -d | uniq` +src_third_dir=`find ./third_party -type f -iname '*.cc' -exec dirname {} \; -or -iname '*.cpp' -exec dirname {} \; -or -iname '*.c' -exec dirname {} \; | sed -r 's/^\.\//\t\t/' | sort -d | uniq` src="" win_src="" for x in $src_dir $src_third_dir; do @@ -119,28 +116,13 @@ set(SRC libmv-capi.h ) -TEST_SHARED_PTR_SUPPORT() -if(SHARED_PTR_FOUND) - if(SHARED_PTR_TR1_MEMORY_HEADER) - add_definitions(-DCERES_TR1_MEMORY_HEADER) - endif() - if(SHARED_PTR_TR1_NAMESPACE) - add_definitions(-DCERES_TR1_SHARED_PTR) - endif() -else() - message(FATAL_ERROR "Unable to find shared_ptr.") -endif() - -add_definitions(-DGOOGLE_GLOG_DLL_DECL=) -add_definitions(-DGFLAGS_DLL_DEFINE_FLAG=) -add_definitions(-DGFLAGS_DLL_DECLARE_FLAG=) -add_definitions(-DGFLAGS_DLL_DECL=) - -add_subdirectory(third_party) +add_definitions(\${GFLAGS_DEFINES}) +add_definitions(\${GLOG_DEFINES}) +add_definitions(\${CERES_DEFINES}) if(WITH_LIBMV) list(APPEND INC - ../gflags + ../gflags/src ../glog/src third_party/ceres/include third_party/ceres/config diff --git a/extern/libmv/third_party/CMakeLists.txt b/extern/libmv/third_party/CMakeLists.txt deleted file mode 100644 index e54d5fbc5cf..00000000000 --- a/extern/libmv/third_party/CMakeLists.txt +++ /dev/null @@ -1,26 +0,0 @@ -# ***** BEGIN GPL LICENSE BLOCK ***** -# -# This program is free software; you can redistribute it and/or -# modify it under the terms of the GNU General Public License -# as published by the Free Software Foundation; either version 2 -# of the License, or (at your option) any later version. -# -# This program is distributed in the hope that it will be useful, -# but WITHOUT ANY WARRANTY; without even the implied warranty of -# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -# GNU General Public License for more details. -# -# You should have received a copy of the GNU General Public License -# along with this program; if not, write to the Free Software Foundation, -# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. -# -# The Original Code is Copyright (C) 2016, Blender Foundation -# All rights reserved. -# -# Contributor(s): Sergey Sharybin. -# -# ***** END GPL LICENSE BLOCK ***** - -if(WITH_LIBMV) - add_subdirectory(ceres) -endif() diff --git a/extern/libmv/third_party/ceres/CMakeLists.txt b/extern/libmv/third_party/ceres/CMakeLists.txt deleted file mode 100644 index 024fcdef806..00000000000 --- a/extern/libmv/third_party/ceres/CMakeLists.txt +++ /dev/null @@ -1,350 +0,0 @@ -# ***** BEGIN GPL LICENSE BLOCK ***** -# -# This program is free software; you can redistribute it and/or -# modify it under the terms of the GNU General Public License -# as published by the Free Software Foundation; either version 2 -# of the License, or (at your option) any later version. -# -# This program is distributed in the hope that it will be useful, -# but WITHOUT ANY WARRANTY; without even the implied warranty of -# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -# GNU General Public License for more details. -# -# You should have received a copy of the GNU General Public License -# along with this program; if not, write to the Free Software Foundation, -# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. -# -# The Original Code is Copyright (C) 2012, Blender Foundation -# All rights reserved. -# -# Contributor(s): Blender Foundation, -# Sergey Sharybin -# -# ***** END GPL LICENSE BLOCK ***** - -# NOTE: This file is automatically generated by bundle.sh script -# If you're doing changes in this file, please update template -# in that script too - -set(INC - . - include - internal - config - ../../../gflags/src - ../../ -) - -set(INC_SYS - ${EIGEN3_INCLUDE_DIRS} -) - -set(SRC - internal/ceres/array_utils.cc - internal/ceres/blas.cc - internal/ceres/block_evaluate_preparer.cc - internal/ceres/block_jacobian_writer.cc - internal/ceres/block_jacobi_preconditioner.cc - internal/ceres/block_random_access_dense_matrix.cc - internal/ceres/block_random_access_diagonal_matrix.cc - internal/ceres/block_random_access_matrix.cc - internal/ceres/block_random_access_sparse_matrix.cc - internal/ceres/block_sparse_matrix.cc - internal/ceres/block_structure.cc - internal/ceres/callbacks.cc - internal/ceres/c_api.cc - internal/ceres/cgnr_solver.cc - internal/ceres/compressed_col_sparse_matrix_utils.cc - internal/ceres/compressed_row_jacobian_writer.cc - internal/ceres/compressed_row_sparse_matrix.cc - internal/ceres/conditioned_cost_function.cc - internal/ceres/conjugate_gradients_solver.cc - internal/ceres/coordinate_descent_minimizer.cc - internal/ceres/corrector.cc - internal/ceres/covariance.cc - internal/ceres/covariance_impl.cc - internal/ceres/dense_normal_cholesky_solver.cc - internal/ceres/dense_qr_solver.cc - internal/ceres/dense_sparse_matrix.cc - internal/ceres/detect_structure.cc - internal/ceres/dogleg_strategy.cc - internal/ceres/dynamic_compressed_row_jacobian_writer.cc - internal/ceres/dynamic_compressed_row_sparse_matrix.cc - internal/ceres/evaluator.cc - internal/ceres/file.cc - internal/ceres/generated/partitioned_matrix_view_d_d_d.cc - internal/ceres/generated/schur_eliminator_d_d_d.cc - internal/ceres/gradient_checking_cost_function.cc - internal/ceres/gradient_problem.cc - internal/ceres/gradient_problem_solver.cc - internal/ceres/implicit_schur_complement.cc - internal/ceres/iterative_schur_complement_solver.cc - internal/ceres/lapack.cc - internal/ceres/levenberg_marquardt_strategy.cc - internal/ceres/linear_least_squares_problems.cc - internal/ceres/linear_operator.cc - internal/ceres/linear_solver.cc - internal/ceres/line_search.cc - internal/ceres/line_search_direction.cc - internal/ceres/line_search_minimizer.cc - internal/ceres/line_search_preprocessor.cc - internal/ceres/local_parameterization.cc - internal/ceres/loss_function.cc - internal/ceres/low_rank_inverse_hessian.cc - internal/ceres/minimizer.cc - internal/ceres/normal_prior.cc - internal/ceres/parameter_block_ordering.cc - internal/ceres/partitioned_matrix_view.cc - internal/ceres/polynomial.cc - internal/ceres/preconditioner.cc - internal/ceres/preprocessor.cc - internal/ceres/problem.cc - internal/ceres/problem_impl.cc - internal/ceres/program.cc - internal/ceres/reorder_program.cc - internal/ceres/residual_block.cc - internal/ceres/residual_block_utils.cc - internal/ceres/schur_complement_solver.cc - internal/ceres/schur_eliminator.cc - internal/ceres/schur_jacobi_preconditioner.cc - internal/ceres/scratch_evaluate_preparer.cc - internal/ceres/solver.cc - internal/ceres/solver_utils.cc - internal/ceres/sparse_matrix.cc - internal/ceres/sparse_normal_cholesky_solver.cc - internal/ceres/split.cc - internal/ceres/stringprintf.cc - internal/ceres/triplet_sparse_matrix.cc - internal/ceres/trust_region_minimizer.cc - internal/ceres/trust_region_preprocessor.cc - internal/ceres/trust_region_strategy.cc - internal/ceres/types.cc - internal/ceres/wall_time.cc - - include/ceres/autodiff_cost_function.h - include/ceres/autodiff_local_parameterization.h - include/ceres/c_api.h - include/ceres/ceres.h - include/ceres/conditioned_cost_function.h - include/ceres/cost_function.h - include/ceres/cost_function_to_functor.h - include/ceres/covariance.h - include/ceres/crs_matrix.h - include/ceres/dynamic_autodiff_cost_function.h - include/ceres/dynamic_numeric_diff_cost_function.h - include/ceres/fpclassify.h - include/ceres/gradient_checker.h - include/ceres/gradient_problem.h - include/ceres/gradient_problem_solver.h - include/ceres/internal/autodiff.h - include/ceres/internal/disable_warnings.h - include/ceres/internal/eigen.h - include/ceres/internal/fixed_array.h - include/ceres/internal/macros.h - include/ceres/internal/manual_constructor.h - include/ceres/internal/numeric_diff.h - include/ceres/internal/port.h - include/ceres/internal/reenable_warnings.h - include/ceres/internal/scoped_ptr.h - include/ceres/internal/variadic_evaluate.h - include/ceres/iteration_callback.h - include/ceres/jet.h - include/ceres/local_parameterization.h - include/ceres/loss_function.h - include/ceres/normal_prior.h - include/ceres/numeric_diff_cost_function.h - include/ceres/ordered_groups.h - include/ceres/problem.h - include/ceres/rotation.h - include/ceres/sized_cost_function.h - include/ceres/solver.h - include/ceres/types.h - include/ceres/version.h - internal/ceres/array_utils.h - internal/ceres/blas.h - internal/ceres/block_evaluate_preparer.h - internal/ceres/block_jacobian_writer.h - internal/ceres/block_jacobi_preconditioner.h - internal/ceres/block_random_access_dense_matrix.h - internal/ceres/block_random_access_diagonal_matrix.h - internal/ceres/block_random_access_matrix.h - internal/ceres/block_random_access_sparse_matrix.h - internal/ceres/block_sparse_matrix.h - internal/ceres/block_structure.h - internal/ceres/callbacks.h - internal/ceres/casts.h - internal/ceres/cgnr_linear_operator.h - internal/ceres/cgnr_solver.h - internal/ceres/collections_port.h - internal/ceres/compressed_col_sparse_matrix_utils.h - internal/ceres/compressed_row_jacobian_writer.h - internal/ceres/compressed_row_sparse_matrix.h - internal/ceres/conjugate_gradients_solver.h - internal/ceres/coordinate_descent_minimizer.h - internal/ceres/corrector.h - internal/ceres/covariance_impl.h - internal/ceres/cxsparse.h - internal/ceres/dense_jacobian_writer.h - internal/ceres/dense_normal_cholesky_solver.h - internal/ceres/dense_qr_solver.h - internal/ceres/dense_sparse_matrix.h - internal/ceres/detect_structure.h - internal/ceres/dogleg_strategy.h - internal/ceres/dynamic_compressed_row_finalizer.h - internal/ceres/dynamic_compressed_row_jacobian_writer.h - internal/ceres/dynamic_compressed_row_sparse_matrix.h - internal/ceres/evaluator.h - internal/ceres/execution_summary.h - internal/ceres/file.h - internal/ceres/gradient_checking_cost_function.h - internal/ceres/gradient_problem_evaluator.h - internal/ceres/graph_algorithms.h - internal/ceres/graph.h - internal/ceres/implicit_schur_complement.h - internal/ceres/integral_types.h - internal/ceres/iterative_schur_complement_solver.h - internal/ceres/lapack.h - internal/ceres/levenberg_marquardt_strategy.h - internal/ceres/linear_least_squares_problems.h - internal/ceres/linear_operator.h - internal/ceres/linear_solver.h - internal/ceres/line_search_direction.h - internal/ceres/line_search.h - internal/ceres/line_search_minimizer.h - internal/ceres/line_search_preprocessor.h - internal/ceres/low_rank_inverse_hessian.h - internal/ceres/map_util.h - internal/ceres/minimizer.h - internal/ceres/mutex.h - internal/ceres/parameter_block.h - internal/ceres/parameter_block_ordering.h - internal/ceres/partitioned_matrix_view.h - internal/ceres/partitioned_matrix_view_impl.h - internal/ceres/polynomial.h - internal/ceres/preconditioner.h - internal/ceres/preprocessor.h - internal/ceres/problem_impl.h - internal/ceres/program_evaluator.h - internal/ceres/program.h - internal/ceres/random.h - internal/ceres/reorder_program.h - internal/ceres/residual_block.h - internal/ceres/residual_block_utils.h - internal/ceres/schur_complement_solver.h - internal/ceres/schur_eliminator.h - internal/ceres/schur_eliminator_impl.h - internal/ceres/schur_jacobi_preconditioner.h - internal/ceres/scratch_evaluate_preparer.h - internal/ceres/small_blas.h - internal/ceres/solver_utils.h - internal/ceres/sparse_matrix.h - internal/ceres/sparse_normal_cholesky_solver.h - internal/ceres/split.h - internal/ceres/stl_util.h - internal/ceres/stringprintf.h - internal/ceres/suitesparse.h - internal/ceres/triplet_sparse_matrix.h - internal/ceres/trust_region_minimizer.h - internal/ceres/trust_region_preprocessor.h - internal/ceres/trust_region_strategy.h - internal/ceres/visibility_based_preconditioner.h - internal/ceres/wall_time.h -) - -if(WITH_LIBMV_SCHUR_SPECIALIZATIONS) - list(APPEND SRC - internal/ceres/generated/partitioned_matrix_view_2_2_2.cc - internal/ceres/generated/partitioned_matrix_view_2_2_3.cc - internal/ceres/generated/partitioned_matrix_view_2_2_4.cc - internal/ceres/generated/partitioned_matrix_view_2_2_d.cc - internal/ceres/generated/partitioned_matrix_view_2_3_3.cc - internal/ceres/generated/partitioned_matrix_view_2_3_4.cc - internal/ceres/generated/partitioned_matrix_view_2_3_6.cc - internal/ceres/generated/partitioned_matrix_view_2_3_9.cc - internal/ceres/generated/partitioned_matrix_view_2_3_d.cc - internal/ceres/generated/partitioned_matrix_view_2_4_3.cc - internal/ceres/generated/partitioned_matrix_view_2_4_4.cc - internal/ceres/generated/partitioned_matrix_view_2_4_8.cc - internal/ceres/generated/partitioned_matrix_view_2_4_9.cc - internal/ceres/generated/partitioned_matrix_view_2_4_d.cc - internal/ceres/generated/partitioned_matrix_view_2_d_d.cc - internal/ceres/generated/partitioned_matrix_view_4_4_2.cc - internal/ceres/generated/partitioned_matrix_view_4_4_3.cc - internal/ceres/generated/partitioned_matrix_view_4_4_4.cc - internal/ceres/generated/partitioned_matrix_view_4_4_d.cc - internal/ceres/generated/schur_eliminator_2_2_2.cc - internal/ceres/generated/schur_eliminator_2_2_3.cc - internal/ceres/generated/schur_eliminator_2_2_4.cc - internal/ceres/generated/schur_eliminator_2_2_d.cc - internal/ceres/generated/schur_eliminator_2_3_3.cc - internal/ceres/generated/schur_eliminator_2_3_4.cc - internal/ceres/generated/schur_eliminator_2_3_6.cc - internal/ceres/generated/schur_eliminator_2_3_9.cc - internal/ceres/generated/schur_eliminator_2_3_d.cc - internal/ceres/generated/schur_eliminator_2_4_3.cc - internal/ceres/generated/schur_eliminator_2_4_4.cc - internal/ceres/generated/schur_eliminator_2_4_8.cc - internal/ceres/generated/schur_eliminator_2_4_9.cc - internal/ceres/generated/schur_eliminator_2_4_d.cc - internal/ceres/generated/schur_eliminator_2_d_d.cc - internal/ceres/generated/schur_eliminator_4_4_2.cc - internal/ceres/generated/schur_eliminator_4_4_3.cc - internal/ceres/generated/schur_eliminator_4_4_4.cc - internal/ceres/generated/schur_eliminator_4_4_d.cc - ) -else() - add_definitions(-DCERES_RESTRICT_SCHUR_SPECIALIZATION) -endif() - -if(WIN32) - list(APPEND INC - ../../../glog/src/windows - ) - - if(NOT MINGW) - list(APPEND INC - ../msinttypes - ) - endif() -else() - list(APPEND INC - ../../../glog/src - ) -endif() - -add_definitions( - -DCERES_HAVE_PTHREAD - -DCERES_NO_SUITESPARSE - -DCERES_NO_CXSPARSE - -DCERES_NO_LAPACK - -DCERES_HAVE_RWLOCK -) - -if(WITH_OPENMP) - add_definitions( - -DCERES_USE_OPENMP - ) -endif() - -TEST_UNORDERED_MAP_SUPPORT() -if(HAVE_STD_UNORDERED_MAP_HEADER) - if(HAVE_UNORDERED_MAP_IN_STD_NAMESPACE) - add_definitions(-DCERES_STD_UNORDERED_MAP) - else() - if(HAVE_UNORDERED_MAP_IN_TR1_NAMESPACE) - add_definitions(-DCERES_STD_UNORDERED_MAP_IN_TR1_NAMESPACE) - else() - add_definitions(-DCERES_NO_UNORDERED_MAP) - message(STATUS "Replacing unordered_map/set with map/set (warning: slower!)") - endif() - endif() -else() - if(HAVE_UNORDERED_MAP_IN_TR1_NAMESPACE) - add_definitions(-DCERES_TR1_UNORDERED_MAP) - else() - add_definitions(-DCERES_NO_UNORDERED_MAP) - message(STATUS "Replacing unordered_map/set with map/set (warning: slower!)") - endif() -endif() - -blender_add_lib(extern_ceres "${SRC}" "${INC}" "${INC_SYS}") diff --git a/extern/libmv/third_party/ceres/ChangeLog b/extern/libmv/third_party/ceres/ChangeLog deleted file mode 100644 index 0e6c195174c..00000000000 --- a/extern/libmv/third_party/ceres/ChangeLog +++ /dev/null @@ -1,659 +0,0 @@ -commit aef9c9563b08d5f39eee1576af133a84749d1b48 -Author: Alessandro Gentilini <agentilini@gmail.com> -Date: Tue Oct 6 20:43:45 2015 +0200 - - Add test for Bessel functions. - - Change-Id: Ief5881e8027643d7ef627e60a88fdbad17f3d884 - -commit 49c86018e00f196c4aa9bd25daccb9919917efee -Author: Alessandro Gentilini <agentilini@gmail.com> -Date: Wed Sep 23 21:59:44 2015 +0200 - - Add Bessel functions in order to use them in residual code. - - See "How can I use the Bessel function in the residual function?" at - https://groups.google.com/d/msg/ceres-solver/Vh1gpqac8v0/NIK1EiWJCAAJ - - Change-Id: I3e80d9f9d1cadaf7177076e493ff46ace5233b76 - -commit dfb201220c034fde00a242d0533bef3f73b2907d -Author: Simon Rutishauser <simon.rutishauser@pix4d.com> -Date: Tue Oct 13 07:33:58 2015 +0200 - - Make miniglog threadsafe on non-windows system by using - localtime_r() instead of localtime() for time formatting - - Change-Id: Ib8006c685cd8ed4f374893bef56c4061ca2c9747 - -commit 41455566ac633e55f222bce7c4d2cb4cc33d5c72 -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Mon Sep 28 22:43:42 2015 +0100 - - Remove link-time optimisation (LTO). - - - On GCC 4.9+ although GCC supports LTO, it requires use of the - non-default gcc-ar & gcc-ranlib. Whilst we can ensure Ceres is - compiled with these, doing so with GCC 4.9 causes multiple definition - linker errors of static ints inside Eigen when compiling the tests - and examples when they are not also built with LTO. - - On OS X (Xcode 6 & 7) after the latest update to gtest, if LTO - is used when compiling the tests (& examples), two tests fail - due to typeinfo::operator== (things are fine if only Ceres itself is - compiled with LTO). - - This patch disables LTO for all compilers. It should be revisited when - the performance is more stable across our supported compilers. - - Change-Id: I17b52957faefbdeff0aa40846dc9b342db1b02e3 - -commit 89c40005bfceadb4163bd16b7464b3c2ce740daf -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Sun Sep 27 13:37:26 2015 +0100 - - Only use LTO when compiling Ceres itself, not tests or examples. - - - If Ceres is built as a shared library, and LTO is enabled for Ceres - and the tests, then type_info::operator==() incorrectly returns false - in gtests' CheckedDowncastToActualType() in the following tests: - -- levenberg_marquardt_strategy_test. - -- gradient_checking_cost_function_test. - on at least Xcode 6 & 7 as reported here: - https://github.com/google/googletest/issues/595. - - This does not appear to be a gtest issue, but is perhaps an LLVM bug - or an RTTI shared library issue. Either way, disabling the use of - LTO when compiling the test application resolves the issue. - - Allow LTO to be enabled for GCC, if it is supported. - - Add CMake function to allow easy appending to target properties s/t - Ceres library-specific compile flags can be iteratively constructed. - - Change-Id: I923e6aae4f7cefa098cf32b2f8fc19389e7918c9 - -commit 0794f41cca440f7f65d9a44e671f66f6e498ef7c -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Sat Sep 26 14:10:15 2015 -0700 - - Documentation updates. - - 1. Fix a typo in the Trust Region algorithm. - 2. Add ARL in the list of users. - 3. Update the version history. - - Change-Id: Ic286e8ef1a71af07f3890b7592dd3aed9c5f87ce - -commit 90e32a8dc437dfb0e6747ce15a1f3193c13b7d5b -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Mon Sep 21 21:08:25 2015 +0100 - - Use old minimum iOS version flags on Xcode < 7.0. - - - The newer style, which are more specific and match the SDK names - are not available on Xcode < 7.0. - - Change-Id: I2f07a0365183d2781157cdb05fd49b30ae001ac5 - -commit 26cd5326a1fb99ae02c667eab9942e1308046984 -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Mon Sep 21 10:16:01 2015 +0100 - - Add gtest-specific flags when building/using as a shared library. - - - Currently these flags are only used to define the relevant DLL export - prefix for Windows. - - Change-Id: I0c05207b512cb4a985390aefc779b91febdabb38 - -commit c4c79472112a49bc1340da0074af2d15b1c89749 -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Sun Sep 20 18:26:59 2015 +0100 - - Clean up iOS.cmake to use xcrun/xcodebuild & libtool. - - - Substantial cleanup of iOS.cmake to use xcrun & xcodebuild to - determine the SDK & tool paths. - - Use libtool -static to link libraries instead of ar + ranlib, which - is not compatible with Xcode 7+, this change should be backwards - compatible to at least Xcode 6. - - Force locations of unordered_map & shared_ptr on iOS to work around - check_cxx_source_compiles() running in a forked CMake instance without - access to the variables (IOS_PLATFORM) defined by the user. - - Minor CMake style updates. - - Change-Id: I5f83a60607db34d461ebe85f9dce861f53d98277 - -commit 155765bbb358f1d19f072a4b54825faf1c059910 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Wed Sep 16 06:56:08 2015 -0700 - - Import the latest version of gtest and gmock. - - Change-Id: I4b686c44bba823cab1dae40efa99e31340d2b52a - -commit 0c4647b8f1496c97c6b9376d9c49ddc204aa08dd -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Wed Sep 16 20:01:11 2015 +0100 - - Remove FAQ about increasing inlining threshold for Clang. - - - Changing the inlining threshold for Clang as described has a minimal - effect on user performance. - - The problem that originally prompted the belief that it did was - due to an erroneous CXX flag configuration (in user code). - - Change-Id: I03017241c0f87b8dcefb8c984ec3b192afd97fc2 - -commit f4b768b69afcf282568f9ab3a3f0eb8078607468 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Mon Sep 14 13:53:24 2015 -0700 - - Lint changes from William Rucklidge - - Change-Id: I0dac2549a8fa2bfd12f745a8d8a0db623b7ec1ac - -commit 5f2f05c726443e35767d677daba6d25dbc2d7ff8 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Fri Sep 11 22:19:38 2015 -0700 - - Refactor system_test - - 1. Move common test infrastructure into test_util. - 2. system_test now only contains powells function. - 3. Add bundle_adjustment_test. - - Instead of a single function which computes everything, - there is now a test for each solver configuration which - uses the reference solution computed by the fixture. - - Change-Id: I16a9a9a83a845a7aaf28762bcecf1a8ff5aee805 - -commit 1936d47e213142b8bf29d3f548905116092b093d -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Tue Sep 8 23:27:42 2015 +0100 - - Revert increased inline threshold (iff Clang) to exported Ceres target. - - - Increasing the inline threshold results in very variable performance - improvements, and could potentially confuse users if they are trying - to set the inline threshold themselves. - - As such, we no longer export our inline threshold configuration for - Clang, but instead document how to change it in the FAQs. - - Change-Id: I88e2e0001e4586ba2718535845ed1e4b1a5b72bc - -commit a66d89dcda47cefda83758bfb9e7374bec4ce866 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Sat Sep 5 16:50:20 2015 -0700 - - Get ready for 1.11.0RC1 - - Update version numbers. - Drop CERES_VERSION_ABI macro. - - Change-Id: Ib3eadabb318afe206bb196a5221b195d26cbeaa0 - -commit 1ac3dd223c179fbadaed568ac532af4139c75d84 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Sat Sep 5 15:30:01 2015 -0700 - - Fix a bug in CompressedRowSparseMatrix::AppendRows - - The test for CompressedRowSparseMatrix::AppendRows tries to add - a matrix of size zero, which results in an invalid pointer deferencing - even though that pointer is never written to. - - Change-Id: I97dba37082bd5dad242ae1af0447a9178cd92027 - -commit 67622b080c8d37b5e932120a53d4ce76b80543e5 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Sat Sep 5 13:18:38 2015 -0700 - - Fix a pointer access bug in Ridders' algorithm. - - A pointer to an Eigen matrix was being used as an array. - - Change-Id: Ifaea14fa3416eda5953de49afb78dc5a6ea816eb - -commit 5742b7d0f14d2d170054623ccfee09ea214b8ed9 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Wed Aug 26 09:24:33 2015 -0700 - - Improve performance of SPARSE_NORMAL_CHOLESKY + dynamic_sparsity - - The outer product computation logic in SparseNormalCholeskySolver - does not work well with dynamic sparsity. The overhead of computing - the sparsity pattern of the normal equations is only amortized if - the sparsity is constant. If the sparsity can change from call to call - SparseNormalCholeskySolver will actually be more expensive. - - For Eigen and for CXSparse we now explicitly compute the normal - equations using their respective matrix-matrix product routines and solve. - Change-Id: Ifbd8ed78987cdf71640e66ed69500442526a23d4 - -commit d0b6cf657d6ef0dd739e958af9a5768f2eecfd35 -Author: Keir Mierle <mierle@gmail.com> -Date: Fri Sep 4 18:43:41 2015 -0700 - - Fix incorrect detect structure test - - Change-Id: I7062f3639147c40b57947790d3b18331a39a366b - -commit 0e8264cc47661651a11e2dd8570c210082963545 -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Sat Aug 22 16:23:05 2015 +0100 - - Add increased inline threshold (iff Clang) to exported Ceres target. - - - When compiled with Clang, Ceres and all of the examples are compiled - with an increased inlining-threshold, as the default value can result - in poor Eigen performance. - - Previously, client code using Ceres would typically not use an - increased inlining-threshold (unless the user has specifically added - it themselves). However, increasing the inlining threshold can result - in significant performance improvements in auto-diffed CostFunctions. - - This patch adds the inlining-threshold flags to the interface flags - for the Ceres CMake target s/t any client code using Ceres (via - CMake), and compiled with Clang, will now be compiled with the same - increased inlining threshold as used by Ceres itself. - - Change-Id: I31e8f1abfda140d22e85bb48aa57f028a68a415e - -commit a1b3fce9e0a4141b973f6b4dd9b08c4c13052d52 -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Mon Aug 31 14:14:56 2015 +0100 - - Add optional export of Ceres build directory to new features list. - - Change-Id: I6f1e42b41957ae9cc98fd9dcd1969ef64c4cd96f - -commit e46777d8df068866ef80902401a03e29348d11ae -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Mon Aug 31 12:41:54 2015 +0100 - - Credit reporters of buildsystem bugs in version history. - - Change-Id: I16fe7973534cd556d97215e84268ae0b8ec4e11a - -commit 01548282cb620e5e3ac79a63a391cd0afd5433e4 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Sun Aug 30 22:29:27 2015 -0700 - - Update the version history. - - Change-Id: I29873bed31675e0108f1a44f53f7bc68976b7f98 - -commit 2701429f770fce69ed0c77523fa43d7bc20ac6dc -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Sun Aug 30 21:33:57 2015 -0700 - - Use Eigen::Dynamic instead of ceres::DYNAMIC in numeric_diff.h - - Change-Id: Iccb0284a8fb4c2160748dfae24bcd595f1d4cb5c - -commit 4f049db7c2a3ee8cf9910c6eac96be6a28a5999c -Author: Tal Ben-Nun <tbennun@gmail.com> -Date: Wed May 13 15:43:51 2015 +0300 - - Adaptive numeric differentiation using Ridders' method. - - This method numerically computes function derivatives in different - scales, extrapolating between intermediate results to conserve function - evaluations. Adaptive differentiation is essential to produce accurate - results for functions with noisy derivatives. - - Full changelist: - -Created a new type of NumericDiffMethod (RIDDERS). - -Implemented EvaluateRiddersJacobianColumn in NumericDiff. - -Created unit tests with f(x) = x^2 + [random noise] and - f(x) = exp(x). - - Change-Id: I2d6e924d7ff686650272f29a8c981351e6f72091 - -commit 070bba4b43b4b7449628bf456a10452fd2b34d28 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Tue Aug 25 13:37:33 2015 -0700 - - Lint fixes from William Rucklidge - - Change-Id: I719e8852859c970091df842e59c44e02e2c65827 - -commit 887a20ca7f02a1504e35f7cabbdfb2e0842a0b0b -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Wed Aug 12 21:41:43 2015 +0100 - - Build position independent code when compiling Ceres statically. - - - Previously, when Ceres was built as a static library we did not - compile position independent code. This means that the resulting - static library could not be linked against shared libraries, but - could be used by executables. - - To enable the use of a static Ceres library by other shared libraries - as reported in [1], the static library must be generated from - position independent code (except on Windows, where PIC does not - apply). - - [1] https://github.com/Itseez/opencv_contrib/pull/290#issuecomment-130389471 - - Change-Id: I99388f1784ece688f91b162d009578c5c97ddaf6 - -commit 860bba588b981a5718f6b73e7e840e5b8757fe65 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Tue Aug 25 09:43:21 2015 -0700 - - Fix a bug in DetectStructure - - The logic for determing static/dynamic f-block size in - DetectStructure was broken in a corner case, where the very first - row block which was used to initialize the f_block_size contained - more than one f blocks of varying sizes. The way the if block - was structured, no iteration was performed on the remaining - f-blocks and the loop failed to detect that the f-block size - was actually changing. - - If in the remaining row blocks, there were no row blocks - with varying f-block sizes, the function will erroneously - return a static f-block size. - - Thanks to Johannes Schonberger for providing a reproduction for this - rather tricky corner case. - - Change-Id: Ib442a041d8b7efd29f9653be6a11a69d0eccd1ec - -commit b0cbc0f0b0a22f01724b7b647a4a94db959cc4e4 -Author: Johannes Schönberger <hannesschoenberger@gmail.com> -Date: Thu Aug 20 14:21:30 2015 -0400 - - Reduce memory footprint of SubsetParameterization - - Change-Id: If113cb4696d5aef3e50eed01fba7a3d4143b7ec8 - -commit ad2a99777786101411a971e59576ca533a297013 -Author: Sergey Sharybin <sergey.vfx@gmail.com> -Date: Sat Aug 22 11:18:45 2015 +0200 - - Fix for reoder program unit test when built without suitesparse - - This commit fixes failure of reorder_program_test when Ceres is built without - any suitesparse. - - Change-Id: Ia23ae8dfd20c482cb9cd1301f17edf9a34df3235 - -commit 4bf3868beca9c17615f72ec03730cddb3676acaa -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Sun Aug 9 15:24:45 2015 -0700 - - Fix a bug in the Schur eliminator - - The schur eliminator treats rows with e blocks and row with - no e blocks separately. The template specialization logic only - applies to the rows with e blocks. - - So, in cases where the rows with e-blocks have a fixed size f-block - but the rows without e-blocks have f-blocks of varying sizes, - DetectStructure will return a static f-block size, but we need to be - careful that we do not blindly use that static f-block size everywhere. - - This patch fixes a bug where such care was not being taken, where - it was assumed that the static f-block size could be assumed for all - f-block sizes. - - A new test is added, which triggers an exception in debug mode. In - release mode this error does not present itself, due to a peculiarity - of the way Eigen works. - - Thanks to Werner Trobin for reporting this bug. - - Change-Id: I8ae7aabf8eed8c3f9cf74b6c74d632ba44f82581 - -commit 1635ce726078f00264b89d7fb6e76fd1c2796e59 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Wed Aug 19 00:26:02 2015 -0700 - - Fix a bug in the reordering code. - - When the user provides an ordering which starts at a non-zero group id, - or has gaps in the groups, then CAMD, the algorithm used to reorder - the program can crash or return garbage results. - - The solution is to map the ordering into grouping constraints, and then - to re-number the groups to be contiguous using a call to - MapValuesToContiguousRange. This was already done for CAMD based - ordering for Schur type solvers, but was not done for SPARSE_NORMAL_CHOLESKY. - - Thanks to Bernhard Zeisl for not only reporting the bug but also - providing a reproduction. - - Change-Id: I5cfae222d701dfdb8e1bda7f0b4670a30417aa89 - -commit 4c3f8987e7f0c51fd367cf6d43d7eb879e79589f -Author: Simon Rutishauser <simon.rutishauser@pix4d.com> -Date: Thu Aug 13 11:10:44 2015 +0200 - - Add missing CERES_EXPORT to ComposedLoss - - Change-Id: Id7db388d41bf53e6e5704039040c9d2c6bf4c29c - -commit 1a740cc787b85b883a0703403a99fe49662acb79 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Tue Aug 11 18:08:05 2015 -0700 - - Add the option to use numeric differentiation to nist and more_garbow_hillstrom - - Change-Id: If0a5caef90b524dcf5e2567c5b681987f5459401 - -commit ea667ede5c038d6bf3d1c9ec3dbdc5072d1beec6 -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Sun Aug 9 16:56:13 2015 +0100 - - Fix EIGENSPARSE option help s/t it displays in CMake ncurses GUI. - - - Shorten description for EIGENSPARSE to a single line, as otherwise - it is not correctly displayed in the ncurses CMake GUI. - - Made explicit in description that this results in an LGPL licensed - version of Ceres (this is also made clear in the CMake log output if - EIGENSPARSE is enabled). - - Change-Id: I11678a9cbc7a817133c22128da01055a3cb8a26d - -commit a14ec27fb28ab2e8d7f1c9d88e41101dc6c0aab5 -Author: Richard Stebbing <richie.stebbing@gmail.com> -Date: Fri Aug 7 08:42:03 2015 -0700 - - Fix SparseNormalCholeskySolver with dynamic sparsity. - - The previous implementation incorrectly cached the outer product matrix - pattern even when `dynamic_sparsity = true`. - - Change-Id: I1e58315a9b44f2f457d07c56b203ab2668bfb8a2 - -commit 3dd7fced44ff00197fa9fcb1f2081d12be728062 -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Sun Aug 9 16:38:50 2015 +0100 - - Remove legacy dependency detection macros. - - - Before the new CMake buildsystem in 1.8, Ceres used non-standard - HINTS variables for dependencies. For backwards compatibility CMake - macros were added to translate these legacy variables into the new - (standard) variables. - - As it has now been multiple releases since the legacy variables - were used and they no longer appear in any of the documentation - support for them has now expired. - - Change-Id: I2cc72927ed711142ba7943df334ee008181f86a2 - -commit 8b32e258ccce1eed2a50bb002add16cad13aff1e -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Sun Aug 9 15:42:39 2015 +0100 - - Fix failed if() condition expansion if gflags is not found. - - - If a CMake-ified version of gflags is not detected, then - gflags_LIBRARIES is not set and the TARGET condition within a - multiconditional if() statement prevents configuration. - - Change-Id: Ia92e97523d7a1478ab36539726b9540d7cfee5d0 - -commit cc8d47aabb9d63ba4588ba7295058a6191c2df83 -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Sun Aug 9 15:18:42 2015 +0100 - - Update all CMake to lowercase function name style. - - - Updated to new CMake style where function names are all lowercase, - this will be backwards compatible as CMake function names are - case insensitive. - - Updated using Emacs' M-x unscreamify-cmake-buffer. - - Change-Id: If7219816f560270e59212813aeb021353a64a0e2 - -commit 1f106904c1f47460c35ac03258d6506bb2d60838 -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Sun Aug 9 14:55:02 2015 +0100 - - Update minimum iOS version to 7.0 for shared_ptr/unordered_map. - - - In order to correctly detect shared_ptr (& unordered_map) - the iOS version must be >= 7.0 (Xcode 5.0+). This only affects the - SIMULATOR(64) platform builds, as the OS (device) build uses the - latest SDK which is now likely 8.0+. - - Change-Id: Iefec8f03408b8cdc7a495f442ebba081f800adb0 - -commit 16ecd40523a408e7705c9fdb0e159cef2007b8ab -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Sat Aug 8 17:32:31 2015 +0100 - - Fix bug in gflags' <= 2.1.2 exported CMake configuration. - - - gflags <= 2.1.2 has a bug in its exported gflags-config.cmake: - https://github.com/gflags/gflags/issues/110 whereby it sets - gflags_LIBRARIES to a non-existent 'gflags' target. - - This causes linker errors if gflags is installed in a non-standard - location (as otherwise CMake resolves gflags to -lgflags which - links if gflags is installed somewhere on the current path). - - We now check for this case, and search for the correct gflags imported - target and update gflags_LIBRARIES to reference it if found, otherwise - proceed on to the original manual search to try to find gflags. - - Change-Id: Iceccc3ee53c7c2010e41cc45255f966e7b13d526 - -commit 56be8de007dfd65ed5a31c795eb4a08ad765f411 -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Thu Jun 25 21:31:00 2015 +0100 - - Add docs for new CXX11 option & mask option for Windows. - - - The CXX11 option has no effect on Windows, as there, any new C++11 - features are enabled by default, as such to avoid confusion we only - present the option for non-Windows. - - Change-Id: I38925ae3bb8c16682d404468ba95c611a519b9b9 - -commit cf863b6415ac4dbf3626e70adeac1ac0f3d87ee5 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Thu Aug 6 14:52:18 2015 -0700 - - Remove the spec file needed for generating RPMs. - - Now that ceres is part of RawHide, there is no need to carry - this spec file with the ceres distribution. - - Change-Id: Icc400b9874ba05ba05b353e2658f1de94c72299e - -commit 560940fa277a469c1ab34f1aa303ff1af9c3cacf -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Sat Jul 11 22:21:31 2015 -0700 - - A refactor of the cubic interpolation code - - 1. Push the boundary handling logic into the underlying array - object. This has two very significant impacts: - - a. The interpolation code becomes extremely simple to write - and to test. - - b. The user has more flexibility in implementing how out of bounds - values are handled. We provide one default implementation. - - Change-Id: Ic2f6cf9257ce7110c62e492688e5a6c8be1e7df2 - -commit dfdf19e111c2b0e6daeb6007728ec2f784106d49 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Wed Aug 5 15:20:57 2015 -0700 - - Lint cleanup from Jim Roseborough - - Change-Id: Id6845c85644d40e635ed196ca74fc51a387aade4 - -commit 7444f23ae245476a7ac8421cc2f88d6947fd3e5f -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Mon Aug 3 12:22:44 2015 -0700 - - Fix a typo in small_blas.h - - The reason this rather serious looking typo has not - caused any problems uptil now is because NUM_ROW_B is - computed but never actually used. - - Thanks to Werner Trobin for pointing this out. - - Change-Id: Id2b4d9326ec21baec8a85423e3270aefbafb611e - -commit 5a48b92123b30a437f031eb24b0deaadc8f60d26 -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Sat Jul 4 17:59:52 2015 +0100 - - Export Ceres build directory into local CMake package registry. - - - Optionally use CMake's export() functionality to export the Ceres - build directory as a package into the local CMake package registry. - - This enables the detection & use of Ceres from CMake *without* - requiring that Ceres be installed. - - Change-Id: Ib5a7588446f490e1b405878475b6b1dd13accd1f - -commit d9790e77894ea99d38137d359d6118315b2d1601 -Author: Sameer Agarwal <sameeragarwal@google.com> -Date: Sun Jul 12 19:39:47 2015 -0700 - - Add ProductParameterization - - Often a parameter block is the Cartesian product of a number of - manifolds. For example, a rigid transformation SE(3) = SO(3) x R^3 - In such cases, where you have the local parameterization - of the individual manifolds available, - ProductParameterization can be used to construct a local - parameterization of the cartesian product. - - Change-Id: I4b5bcbd2407a38739c7725b129789db5c3d65a20 - -commit 7b4fb69dad49eaefb5d2d47ef0d76f48ad7fef73 -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Sun Jun 28 21:43:46 2015 +0100 - - Cleanup FindGflags & use installed gflags CMake config if present. - - - Split out gflags namespace detection methods: - check_cxx_source_compiles() & regex, into separate functions. - - Use installed/exported gflags CMake configuration (present for - versions >= 2.1) if available, unless user expresses a preference not - to, or specifies search directories, in which case fall back to manual - search for components. - -- Prefer installed gflags CMake configurations over exported gflags - build directories on all OSs. - - Remove custom version of check_cxx_source_compiles() that attempted - to force the build type of the test project. This only worked for - NMake on Windows, not MSVC as msbuild ignored our attempts to force - the build type. Now we always use the regex method on Windows if - we cannot find an installed gflags CMake configuration which works - even on MSVC by bypassing msbuild. - - Add default search paths for gflags on Windows. - - Change-Id: I083b267d97a7a5838a1314f3d41a61ae48d5a2d7 - -commit b3063c047906d4a44503dc0187fdcbbfcdda5f38 -Author: Alex Stewart <alexs.mac@gmail.com> -Date: Wed Jul 15 20:56:56 2015 +0100 - - Add default glog install location on Windows to search paths. - - Change-Id: I083d368be48986e6780c11460f5a07b2f3b6c900 diff --git a/extern/libmv/third_party/ceres/LICENSE b/extern/libmv/third_party/ceres/LICENSE deleted file mode 100644 index 2e3ead5ed45..00000000000 --- a/extern/libmv/third_party/ceres/LICENSE +++ /dev/null @@ -1,27 +0,0 @@ -Ceres Solver - A fast non-linear least squares minimizer -Copyright 2010, 2011, 2012 Google Inc. All rights reserved. -http://code.google.com/p/ceres-solver/ - -Redistribution and use in source and binary forms, with or without -modification, are permitted provided that the following conditions are met: - -* Redistributions of source code must retain the above copyright notice, - this list of conditions and the following disclaimer. -* Redistributions in binary form must reproduce the above copyright notice, - this list of conditions and the following disclaimer in the documentation - and/or other materials provided with the distribution. -* Neither the name of Google Inc. nor the names of its contributors may be - used to endorse or promote products derived from this software without - specific prior written permission. - -THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. diff --git a/extern/libmv/third_party/ceres/README b/extern/libmv/third_party/ceres/README deleted file mode 100644 index 8dd8ccf91a1..00000000000 --- a/extern/libmv/third_party/ceres/README +++ /dev/null @@ -1,3 +0,0 @@ -Ceres Solver - A non-linear least squares minimizer -================================================== -Please see ceres.pdf in docs/ for a tutorial and reference. diff --git a/extern/libmv/third_party/ceres/bundle.sh b/extern/libmv/third_party/ceres/bundle.sh deleted file mode 100755 index 85da4f2afc9..00000000000 --- a/extern/libmv/third_party/ceres/bundle.sh +++ /dev/null @@ -1,201 +0,0 @@ -#!/bin/sh - -if [ "x$1" = "x--i-really-know-what-im-doing" ] ; then - echo Proceeding as requested by command line ... -else - echo "*** Please run again with --i-really-know-what-im-doing ..." - exit 1 -fi - -repo="https://ceres-solver.googlesource.com/ceres-solver" -branch="master" -#tag="1.4.0" -tag="" -tmp=`mktemp -d` -checkout="$tmp/ceres" - -GIT="git --git-dir $tmp/ceres/.git --work-tree $checkout" - -git clone $repo $checkout - -if [ $branch != "master" ]; then - $GIT checkout -t remotes/origin/$branch -else - if [ "x$tag" != "x" ]; then - $GIT checkout $tag - fi -fi - -$GIT log -n 50 > ChangeLog - -for p in `cat ./patches/series`; do - echo "Applying patch $p..." - cat ./patches/$p | patch -d $tmp/ceres -p1 -done - -find include -type f -not -iwholename '*.svn*' -exec rm -rf {} \; -find internal -type f -not -iwholename '*.svn*' -exec rm -rf {} \; - -cat "files.txt" | while read f; do - mkdir -p `dirname $f` - cp $tmp/ceres/$f $f -done - -rm -rf $tmp - -sources=`find ./include ./internal -type f -iname '*.cc' -or -iname '*.cpp' -or -iname '*.c' | sed -r 's/^\.\//\t/' | \ - grep -v -E 'schur_eliminator_[0-9]_[0-9d]_[0-9d].cc' | \ - grep -v -E 'partitioned_matrix_view_[0-9]_[0-9d]_[0-9d].cc' | sort -d` -generated_sources=`find ./include ./internal -type f -iname '*.cc' -or -iname '*.cpp' -or -iname '*.c' | sed -r 's/^\.\//\t\t/' | \ - grep -E 'schur_eliminator_[0-9]_[0-9d]_[0-9d].cc|partitioned_matrix_view_[0-9]_[0-9d]_[0-9d].cc' | sort -d` -headers=`find ./include ./internal -type f -iname '*.h' | sed -r 's/^\.\//\t/' | sort -d` - -src_dir=`find ./internal -type f -iname '*.cc' -exec dirname {} \; -or -iname '*.cpp' -exec dirname {} \; -or -iname '*.c' -exec dirname {} \; | sed -r 's/^\.\//\t/' | sort -d | uniq` -src="" -for x in $src_dir $src_third_dir; do - t="" - - if test `echo "$x" | grep -c glog ` -eq 1; then - continue; - fi - - if test `echo "$x" | grep -c generated` -eq 1; then - continue; - fi - - if stat $x/*.cpp > /dev/null 2>&1; then - t="src += env.Glob('`echo $x'/*.cpp'`')" - fi - - if stat $x/*.c > /dev/null 2>&1; then - if [ -z "$t" ]; then - t="src += env.Glob('`echo $x'/*.c'`')" - else - t="$t + env.Glob('`echo $x'/*.c'`')" - fi - fi - - if stat $x/*.cc > /dev/null 2>&1; then - if [ -z "$t" ]; then - t="src += env.Glob('`echo $x'/*.cc'`')" - else - t="$t + env.Glob('`echo $x'/*.cc'`')" - fi - fi - - if [ -z "$src" ]; then - src=$t - else - src=`echo "$src\n$t"` - fi -done - -cat > CMakeLists.txt << EOF -# ***** BEGIN GPL LICENSE BLOCK ***** -# -# This program is free software; you can redistribute it and/or -# modify it under the terms of the GNU General Public License -# as published by the Free Software Foundation; either version 2 -# of the License, or (at your option) any later version. -# -# This program is distributed in the hope that it will be useful, -# but WITHOUT ANY WARRANTY; without even the implied warranty of -# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -# GNU General Public License for more details. -# -# You should have received a copy of the GNU General Public License -# along with this program; if not, write to the Free Software Foundation, -# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. -# -# The Original Code is Copyright (C) 2012, Blender Foundation -# All rights reserved. -# -# Contributor(s): Blender Foundation, -# Sergey Sharybin -# -# ***** END GPL LICENSE BLOCK ***** - -# NOTE: This file is automatically generated by bundle.sh script -# If you're doing changes in this file, please update template -# in that script too - -set(INC - . - include - internal - config - ../gflags - ../../ -) - -set(INC_SYS - \${EIGEN3_INCLUDE_DIRS} -) - -set(SRC -${sources} - -${headers} -) - -if(WITH_LIBMV_SCHUR_SPECIALIZATIONS) - list(APPEND SRC -${generated_sources} - ) -else() - add_definitions(-DCERES_RESTRICT_SCHUR_SPECIALIZATION) -endif() - -if(WIN32) - list(APPEND INC - ../glog/src/windows - ) - - if(NOT MINGW) - list(APPEND INC - ../msinttypes - ) - endif() -else() - list(APPEND INC - ../glog/src - ) -endif() - -add_definitions( - -DCERES_HAVE_PTHREAD - -DCERES_NO_SUITESPARSE - -DCERES_NO_CXSPARSE - -DCERES_NO_LAPACK - -DCERES_HAVE_RWLOCK -) - -if(WITH_OPENMP) - add_definitions( - -DCERES_USE_OPENMP - ) -endif() - -TEST_UNORDERED_MAP_SUPPORT() -if(HAVE_STD_UNORDERED_MAP_HEADER) - if(HAVE_UNORDERED_MAP_IN_STD_NAMESPACE) - add_definitions(-DCERES_STD_UNORDERED_MAP) - else() - if(HAVE_UNORDERED_MAP_IN_TR1_NAMESPACE) - add_definitions(-DCERES_STD_UNORDERED_MAP_IN_TR1_NAMESPACE) - else() - add_definitions(-DCERES_NO_UNORDERED_MAP) - message(STATUS "Replacing unordered_map/set with map/set (warning: slower!)") - endif() - endif() -else() - if(HAVE_UNORDERED_MAP_IN_TR1_NAMESPACE) - add_definitions(-DCERES_TR1_UNORDERED_MAP) - else() - add_definitions(-DCERES_NO_UNORDERED_MAP) - message(STATUS "Replacing unordered_map/set with map/set (warning: slower!)") - endif() -endif() - -blender_add_lib(extern_ceres "\${SRC}" "\${INC}" "\${INC_SYS}") -EOF diff --git a/extern/libmv/third_party/ceres/config/ceres/internal/config.h b/extern/libmv/third_party/ceres/config/ceres/internal/config.h deleted file mode 100644 index 1cf034ded5f..00000000000 --- a/extern/libmv/third_party/ceres/config/ceres/internal/config.h +++ /dev/null @@ -1,48 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: alexs.mac@gmail.com (Alex Stewart) - -// Default (empty) configuration options for Ceres. -// -// IMPORTANT: Most users of Ceres will not use this file, when -// compiling Ceres with CMake, CMake will configure a new -// config.h with the currently selected Ceres compile -// options in <BUILD_DIR>/config, which will be added to -// the include path for compilation, and installed with the -// public Ceres headers. However, for some users of Ceres -// who compile without CMake (Android), this file ensures -// that Ceres will compile, with the user either specifying -// manually the Ceres compile options, or passing them -// directly through the compiler. - -#ifndef CERES_PUBLIC_INTERNAL_CONFIG_H_ -#define CERES_PUBLIC_INTERNAL_CONFIG_H_ - - -#endif // CERES_PUBLIC_INTERNAL_CONFIG_H_ diff --git a/extern/libmv/third_party/ceres/files.txt b/extern/libmv/third_party/ceres/files.txt deleted file mode 100644 index f49f1fb0ded..00000000000 --- a/extern/libmv/third_party/ceres/files.txt +++ /dev/null @@ -1,252 +0,0 @@ -include/ceres/autodiff_cost_function.h -include/ceres/autodiff_local_parameterization.h -include/ceres/c_api.h -include/ceres/ceres.h -include/ceres/conditioned_cost_function.h -include/ceres/cost_function.h -include/ceres/cost_function_to_functor.h -include/ceres/covariance.h -include/ceres/crs_matrix.h -include/ceres/dynamic_autodiff_cost_function.h -include/ceres/dynamic_cost_function_to_functor.h -include/ceres/dynamic_numeric_diff_cost_function.h -include/ceres/fpclassify.h -include/ceres/gradient_checker.h -include/ceres/gradient_problem.h -include/ceres/gradient_problem_solver.h -include/ceres/internal/autodiff.h -include/ceres/internal/disable_warnings.h -include/ceres/internal/eigen.h -include/ceres/internal/fixed_array.h -include/ceres/internal/macros.h -include/ceres/internal/manual_constructor.h -include/ceres/internal/numeric_diff.h -include/ceres/internal/port.h -include/ceres/internal/reenable_warnings.h -include/ceres/internal/scoped_ptr.h -include/ceres/internal/variadic_evaluate.h -include/ceres/iteration_callback.h -include/ceres/jet.h -include/ceres/local_parameterization.h -include/ceres/loss_function.h -include/ceres/normal_prior.h -include/ceres/numeric_diff_cost_function.h -include/ceres/numeric_diff_options.h -include/ceres/ordered_groups.h -include/ceres/problem.h -include/ceres/rotation.h -include/ceres/sized_cost_function.h -include/ceres/solver.h -include/ceres/types.h -include/ceres/version.h -internal/ceres/array_utils.cc -internal/ceres/array_utils.h -internal/ceres/blas.cc -internal/ceres/blas.h -internal/ceres/block_evaluate_preparer.cc -internal/ceres/block_evaluate_preparer.h -internal/ceres/block_jacobian_writer.cc -internal/ceres/block_jacobian_writer.h -internal/ceres/block_jacobi_preconditioner.cc -internal/ceres/block_jacobi_preconditioner.h -internal/ceres/block_random_access_dense_matrix.cc -internal/ceres/block_random_access_dense_matrix.h -internal/ceres/block_random_access_diagonal_matrix.cc -internal/ceres/block_random_access_diagonal_matrix.h -internal/ceres/block_random_access_matrix.cc -internal/ceres/block_random_access_matrix.h -internal/ceres/block_random_access_sparse_matrix.cc -internal/ceres/block_random_access_sparse_matrix.h -internal/ceres/block_sparse_matrix.cc -internal/ceres/block_sparse_matrix.h -internal/ceres/block_structure.cc -internal/ceres/block_structure.h -internal/ceres/callbacks.cc -internal/ceres/callbacks.h -internal/ceres/c_api.cc -internal/ceres/casts.h -internal/ceres/cgnr_linear_operator.h -internal/ceres/cgnr_solver.cc -internal/ceres/cgnr_solver.h -internal/ceres/collections_port.h -internal/ceres/compressed_col_sparse_matrix_utils.cc -internal/ceres/compressed_col_sparse_matrix_utils.h -internal/ceres/compressed_row_jacobian_writer.cc -internal/ceres/compressed_row_jacobian_writer.h -internal/ceres/compressed_row_sparse_matrix.cc -internal/ceres/compressed_row_sparse_matrix.h -internal/ceres/conditioned_cost_function.cc -internal/ceres/conjugate_gradients_solver.cc -internal/ceres/conjugate_gradients_solver.h -internal/ceres/coordinate_descent_minimizer.cc -internal/ceres/coordinate_descent_minimizer.h -internal/ceres/corrector.cc -internal/ceres/corrector.h -internal/ceres/covariance.cc -internal/ceres/covariance_impl.cc -internal/ceres/covariance_impl.h -internal/ceres/cxsparse.h -internal/ceres/dense_jacobian_writer.h -internal/ceres/dense_normal_cholesky_solver.cc -internal/ceres/dense_normal_cholesky_solver.h -internal/ceres/dense_qr_solver.cc -internal/ceres/dense_qr_solver.h -internal/ceres/dense_sparse_matrix.cc -internal/ceres/dense_sparse_matrix.h -internal/ceres/detect_structure.cc -internal/ceres/detect_structure.h -internal/ceres/dogleg_strategy.cc -internal/ceres/dogleg_strategy.h -internal/ceres/dynamic_compressed_row_finalizer.h -internal/ceres/dynamic_compressed_row_jacobian_writer.cc -internal/ceres/dynamic_compressed_row_jacobian_writer.h -internal/ceres/dynamic_compressed_row_sparse_matrix.cc -internal/ceres/dynamic_compressed_row_sparse_matrix.h -internal/ceres/evaluator.cc -internal/ceres/evaluator.h -internal/ceres/execution_summary.h -internal/ceres/file.cc -internal/ceres/file.h -internal/ceres/generated/partitioned_matrix_view_2_2_2.cc -internal/ceres/generated/partitioned_matrix_view_2_2_3.cc -internal/ceres/generated/partitioned_matrix_view_2_2_4.cc -internal/ceres/generated/partitioned_matrix_view_2_2_d.cc -internal/ceres/generated/partitioned_matrix_view_2_3_3.cc -internal/ceres/generated/partitioned_matrix_view_2_3_4.cc -internal/ceres/generated/partitioned_matrix_view_2_3_6.cc -internal/ceres/generated/partitioned_matrix_view_2_3_9.cc -internal/ceres/generated/partitioned_matrix_view_2_3_d.cc -internal/ceres/generated/partitioned_matrix_view_2_4_3.cc -internal/ceres/generated/partitioned_matrix_view_2_4_4.cc -internal/ceres/generated/partitioned_matrix_view_2_4_8.cc -internal/ceres/generated/partitioned_matrix_view_2_4_9.cc -internal/ceres/generated/partitioned_matrix_view_2_4_d.cc -internal/ceres/generated/partitioned_matrix_view_2_d_d.cc -internal/ceres/generated/partitioned_matrix_view_4_4_2.cc -internal/ceres/generated/partitioned_matrix_view_4_4_3.cc -internal/ceres/generated/partitioned_matrix_view_4_4_4.cc -internal/ceres/generated/partitioned_matrix_view_4_4_d.cc -internal/ceres/generated/partitioned_matrix_view_d_d_d.cc -internal/ceres/generated/schur_eliminator_2_2_2.cc -internal/ceres/generated/schur_eliminator_2_2_3.cc -internal/ceres/generated/schur_eliminator_2_2_4.cc -internal/ceres/generated/schur_eliminator_2_2_d.cc -internal/ceres/generated/schur_eliminator_2_3_3.cc -internal/ceres/generated/schur_eliminator_2_3_4.cc -internal/ceres/generated/schur_eliminator_2_3_6.cc -internal/ceres/generated/schur_eliminator_2_3_9.cc -internal/ceres/generated/schur_eliminator_2_3_d.cc -internal/ceres/generated/schur_eliminator_2_4_3.cc -internal/ceres/generated/schur_eliminator_2_4_4.cc -internal/ceres/generated/schur_eliminator_2_4_8.cc -internal/ceres/generated/schur_eliminator_2_4_9.cc -internal/ceres/generated/schur_eliminator_2_4_d.cc -internal/ceres/generated/schur_eliminator_2_d_d.cc -internal/ceres/generated/schur_eliminator_4_4_2.cc -internal/ceres/generated/schur_eliminator_4_4_3.cc -internal/ceres/generated/schur_eliminator_4_4_4.cc -internal/ceres/generated/schur_eliminator_4_4_d.cc -internal/ceres/generated/schur_eliminator_d_d_d.cc -internal/ceres/generate_eliminator_specialization.py -internal/ceres/generate_partitioned_matrix_view_specializations.py -internal/ceres/gradient_checking_cost_function.cc -internal/ceres/gradient_checking_cost_function.h -internal/ceres/gradient_problem.cc -internal/ceres/gradient_problem_evaluator.h -internal/ceres/gradient_problem_solver.cc -internal/ceres/graph_algorithms.h -internal/ceres/graph.h -internal/ceres/householder_vector.h -internal/ceres/implicit_schur_complement.cc -internal/ceres/implicit_schur_complement.h -internal/ceres/integral_types.h -internal/ceres/iterative_schur_complement_solver.cc -internal/ceres/iterative_schur_complement_solver.h -internal/ceres/lapack.cc -internal/ceres/lapack.h -internal/ceres/levenberg_marquardt_strategy.cc -internal/ceres/levenberg_marquardt_strategy.h -internal/ceres/linear_least_squares_problems.cc -internal/ceres/linear_least_squares_problems.h -internal/ceres/linear_operator.cc -internal/ceres/linear_operator.h -internal/ceres/linear_solver.cc -internal/ceres/linear_solver.h -internal/ceres/line_search.cc -internal/ceres/line_search_direction.cc -internal/ceres/line_search_direction.h -internal/ceres/line_search.h -internal/ceres/line_search_minimizer.cc -internal/ceres/line_search_minimizer.h -internal/ceres/line_search_preprocessor.cc -internal/ceres/line_search_preprocessor.h -internal/ceres/local_parameterization.cc -internal/ceres/loss_function.cc -internal/ceres/low_rank_inverse_hessian.cc -internal/ceres/low_rank_inverse_hessian.h -internal/ceres/map_util.h -internal/ceres/minimizer.cc -internal/ceres/minimizer.h -internal/ceres/mutex.h -internal/ceres/normal_prior.cc -internal/ceres/parameter_block.h -internal/ceres/parameter_block_ordering.cc -internal/ceres/parameter_block_ordering.h -internal/ceres/partitioned_matrix_view.cc -internal/ceres/partitioned_matrix_view.h -internal/ceres/partitioned_matrix_view_impl.h -internal/ceres/polynomial.cc -internal/ceres/polynomial.h -internal/ceres/preconditioner.cc -internal/ceres/preconditioner.h -internal/ceres/preprocessor.cc -internal/ceres/preprocessor.h -internal/ceres/problem.cc -internal/ceres/problem_impl.cc -internal/ceres/problem_impl.h -internal/ceres/program.cc -internal/ceres/program_evaluator.h -internal/ceres/program.h -internal/ceres/random.h -internal/ceres/reorder_program.cc -internal/ceres/reorder_program.h -internal/ceres/residual_block.cc -internal/ceres/residual_block.h -internal/ceres/residual_block_utils.cc -internal/ceres/residual_block_utils.h -internal/ceres/schur_complement_solver.cc -internal/ceres/schur_complement_solver.h -internal/ceres/schur_eliminator.cc -internal/ceres/schur_eliminator.h -internal/ceres/schur_eliminator_impl.h -internal/ceres/schur_jacobi_preconditioner.cc -internal/ceres/schur_jacobi_preconditioner.h -internal/ceres/scratch_evaluate_preparer.cc -internal/ceres/scratch_evaluate_preparer.h -internal/ceres/small_blas.h -internal/ceres/solver.cc -internal/ceres/solver_utils.cc -internal/ceres/solver_utils.h -internal/ceres/sparse_matrix.cc -internal/ceres/sparse_matrix.h -internal/ceres/sparse_normal_cholesky_solver.cc -internal/ceres/sparse_normal_cholesky_solver.h -internal/ceres/split.cc -internal/ceres/split.h -internal/ceres/stl_util.h -internal/ceres/stringprintf.cc -internal/ceres/stringprintf.h -internal/ceres/suitesparse.h -internal/ceres/triplet_sparse_matrix.cc -internal/ceres/triplet_sparse_matrix.h -internal/ceres/trust_region_minimizer.cc -internal/ceres/trust_region_minimizer.h -internal/ceres/trust_region_preprocessor.cc -internal/ceres/trust_region_preprocessor.h -internal/ceres/trust_region_strategy.cc -internal/ceres/trust_region_strategy.h -internal/ceres/types.cc -internal/ceres/visibility_based_preconditioner.h -internal/ceres/wall_time.cc -internal/ceres/wall_time.h -config/ceres/internal/config.h diff --git a/extern/libmv/third_party/ceres/include/ceres/autodiff_cost_function.h b/extern/libmv/third_party/ceres/include/ceres/autodiff_cost_function.h deleted file mode 100644 index e7893e4828e..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/autodiff_cost_function.h +++ /dev/null @@ -1,227 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Create CostFunctions as needed by the least squares framework, with -// Jacobians computed via automatic differentiation. For more -// information on automatic differentation, see the wikipedia article -// at http://en.wikipedia.org/wiki/Automatic_differentiation -// -// To get an auto differentiated cost function, you must define a class with a -// templated operator() (a functor) that computes the cost function in terms of -// the template parameter T. The autodiff framework substitutes appropriate -// "jet" objects for T in order to compute the derivative when necessary, but -// this is hidden, and you should write the function as if T were a scalar type -// (e.g. a double-precision floating point number). -// -// The function must write the computed value in the last argument -// (the only non-const one) and return true to indicate -// success. Please see cost_function.h for details on how the return -// value maybe used to impose simple constraints on the parameter -// block. -// -// For example, consider a scalar error e = k - x'y, where both x and y are -// two-dimensional column vector parameters, the prime sign indicates -// transposition, and k is a constant. The form of this error, which is the -// difference between a constant and an expression, is a common pattern in least -// squares problems. For example, the value x'y might be the model expectation -// for a series of measurements, where there is an instance of the cost function -// for each measurement k. -// -// The actual cost added to the total problem is e^2, or (k - x'k)^2; however, -// the squaring is implicitly done by the optimization framework. -// -// To write an auto-differentiable cost function for the above model, first -// define the object -// -// class MyScalarCostFunctor { -// MyScalarCostFunctor(double k): k_(k) {} -// -// template <typename T> -// bool operator()(const T* const x , const T* const y, T* e) const { -// e[0] = T(k_) - x[0] * y[0] + x[1] * y[1]; -// return true; -// } -// -// private: -// double k_; -// }; -// -// Note that in the declaration of operator() the input parameters x and y come -// first, and are passed as const pointers to arrays of T. If there were three -// input parameters, then the third input parameter would come after y. The -// output is always the last parameter, and is also a pointer to an array. In -// the example above, e is a scalar, so only e[0] is set. -// -// Then given this class definition, the auto differentiated cost function for -// it can be constructed as follows. -// -// CostFunction* cost_function -// = new AutoDiffCostFunction<MyScalarCostFunctor, 1, 2, 2>( -// new MyScalarCostFunctor(1.0)); ^ ^ ^ -// | | | -// Dimension of residual -----+ | | -// Dimension of x ---------------+ | -// Dimension of y ------------------+ -// -// In this example, there is usually an instance for each measumerent of k. -// -// In the instantiation above, the template parameters following -// "MyScalarCostFunctor", "1, 2, 2", describe the functor as computing a -// 1-dimensional output from two arguments, both 2-dimensional. -// -// AutoDiffCostFunction also supports cost functions with a -// runtime-determined number of residuals. For example: -// -// CostFunction* cost_function -// = new AutoDiffCostFunction<MyScalarCostFunctor, DYNAMIC, 2, 2>( -// new CostFunctorWithDynamicNumResiduals(1.0), ^ ^ ^ -// runtime_number_of_residuals); <----+ | | | -// | | | | -// | | | | -// Actual number of residuals ------+ | | | -// Indicate dynamic number of residuals --------+ | | -// Dimension of x ------------------------------------+ | -// Dimension of y ---------------------------------------+ -// -// The framework can currently accommodate cost functions of up to 10 -// independent variables, and there is no limit on the dimensionality -// of each of them. -// -// WARNING #1: Since the functor will get instantiated with different types for -// T, you must to convert from other numeric types to T before mixing -// computations with other variables of type T. In the example above, this is -// seen where instead of using k_ directly, k_ is wrapped with T(k_). -// -// WARNING #2: A common beginner's error when first using autodiff cost -// functions is to get the sizing wrong. In particular, there is a tendency to -// set the template parameters to (dimension of residual, number of parameters) -// instead of passing a dimension parameter for *every parameter*. In the -// example above, that would be <MyScalarCostFunctor, 1, 2>, which is missing -// the last '2' argument. Please be careful when setting the size parameters. - -#ifndef CERES_PUBLIC_AUTODIFF_COST_FUNCTION_H_ -#define CERES_PUBLIC_AUTODIFF_COST_FUNCTION_H_ - -#include "ceres/internal/autodiff.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/sized_cost_function.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { - -// A cost function which computes the derivative of the cost with respect to -// the parameters (a.k.a. the jacobian) using an autodifferentiation framework. -// The first template argument is the functor object, described in the header -// comment. The second argument is the dimension of the residual (or -// ceres::DYNAMIC to indicate it will be set at runtime), and subsequent -// arguments describe the size of the Nth parameter, one per parameter. -// -// The constructors take ownership of the cost functor. -// -// If the number of residuals (argument kNumResiduals below) is -// ceres::DYNAMIC, then the two-argument constructor must be used. The -// second constructor takes a number of residuals (in addition to the -// templated number of residuals). This allows for varying the number -// of residuals for a single autodiff cost function at runtime. -template <typename CostFunctor, - int kNumResiduals, // Number of residuals, or ceres::DYNAMIC. - int N0, // Number of parameters in block 0. - int N1 = 0, // Number of parameters in block 1. - int N2 = 0, // Number of parameters in block 2. - int N3 = 0, // Number of parameters in block 3. - int N4 = 0, // Number of parameters in block 4. - int N5 = 0, // Number of parameters in block 5. - int N6 = 0, // Number of parameters in block 6. - int N7 = 0, // Number of parameters in block 7. - int N8 = 0, // Number of parameters in block 8. - int N9 = 0> // Number of parameters in block 9. -class AutoDiffCostFunction : public SizedCostFunction<kNumResiduals, - N0, N1, N2, N3, N4, - N5, N6, N7, N8, N9> { - public: - // Takes ownership of functor. Uses the template-provided value for the - // number of residuals ("kNumResiduals"). - explicit AutoDiffCostFunction(CostFunctor* functor) - : functor_(functor) { - CHECK_NE(kNumResiduals, DYNAMIC) - << "Can't run the fixed-size constructor if the " - << "number of residuals is set to ceres::DYNAMIC."; - } - - // Takes ownership of functor. Ignores the template-provided - // kNumResiduals in favor of the "num_residuals" argument provided. - // - // This allows for having autodiff cost functions which return varying - // numbers of residuals at runtime. - AutoDiffCostFunction(CostFunctor* functor, int num_residuals) - : functor_(functor) { - CHECK_EQ(kNumResiduals, DYNAMIC) - << "Can't run the dynamic-size constructor if the " - << "number of residuals is not ceres::DYNAMIC."; - SizedCostFunction<kNumResiduals, - N0, N1, N2, N3, N4, - N5, N6, N7, N8, N9> - ::set_num_residuals(num_residuals); - } - - virtual ~AutoDiffCostFunction() {} - - // Implementation details follow; clients of the autodiff cost function should - // not have to examine below here. - // - // To handle varardic cost functions, some template magic is needed. It's - // mostly hidden inside autodiff.h. - virtual bool Evaluate(double const* const* parameters, - double* residuals, - double** jacobians) const { - if (!jacobians) { - return internal::VariadicEvaluate< - CostFunctor, double, N0, N1, N2, N3, N4, N5, N6, N7, N8, N9> - ::Call(*functor_, parameters, residuals); - } - return internal::AutoDiff<CostFunctor, double, - N0, N1, N2, N3, N4, N5, N6, N7, N8, N9>::Differentiate( - *functor_, - parameters, - SizedCostFunction<kNumResiduals, - N0, N1, N2, N3, N4, - N5, N6, N7, N8, N9>::num_residuals(), - residuals, - jacobians); - } - - private: - internal::scoped_ptr<CostFunctor> functor_; -}; - -} // namespace ceres - -#endif // CERES_PUBLIC_AUTODIFF_COST_FUNCTION_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/autodiff_local_parameterization.h b/extern/libmv/third_party/ceres/include/ceres/autodiff_local_parameterization.h deleted file mode 100644 index 27397e20d3b..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/autodiff_local_parameterization.h +++ /dev/null @@ -1,154 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sergey.vfx@gmail.com (Sergey Sharybin) -// mierle@gmail.com (Keir Mierle) -// sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_PUBLIC_AUTODIFF_LOCAL_PARAMETERIZATION_H_ -#define CERES_PUBLIC_AUTODIFF_LOCAL_PARAMETERIZATION_H_ - -#include "ceres/local_parameterization.h" -#include "ceres/internal/autodiff.h" -#include "ceres/internal/scoped_ptr.h" - -namespace ceres { - -// Create local parameterization with Jacobians computed via automatic -// differentiation. For more information on local parameterizations, -// see include/ceres/local_parameterization.h -// -// To get an auto differentiated local parameterization, you must define -// a class with a templated operator() (a functor) that computes -// -// x_plus_delta = Plus(x, delta); -// -// the template parameter T. The autodiff framework substitutes appropriate -// "Jet" objects for T in order to compute the derivative when necessary, but -// this is hidden, and you should write the function as if T were a scalar type -// (e.g. a double-precision floating point number). -// -// The function must write the computed value in the last argument (the only -// non-const one) and return true to indicate success. -// -// For example, Quaternions have a three dimensional local -// parameterization. It's plus operation can be implemented as (taken -// from internal/ceres/auto_diff_local_parameterization_test.cc) -// -// struct QuaternionPlus { -// template<typename T> -// bool operator()(const T* x, const T* delta, T* x_plus_delta) const { -// const T squared_norm_delta = -// delta[0] * delta[0] + delta[1] * delta[1] + delta[2] * delta[2]; -// -// T q_delta[4]; -// if (squared_norm_delta > T(0.0)) { -// T norm_delta = sqrt(squared_norm_delta); -// const T sin_delta_by_delta = sin(norm_delta) / norm_delta; -// q_delta[0] = cos(norm_delta); -// q_delta[1] = sin_delta_by_delta * delta[0]; -// q_delta[2] = sin_delta_by_delta * delta[1]; -// q_delta[3] = sin_delta_by_delta * delta[2]; -// } else { -// // We do not just use q_delta = [1,0,0,0] here because that is a -// // constant and when used for automatic differentiation will -// // lead to a zero derivative. Instead we take a first order -// // approximation and evaluate it at zero. -// q_delta[0] = T(1.0); -// q_delta[1] = delta[0]; -// q_delta[2] = delta[1]; -// q_delta[3] = delta[2]; -// } -// -// QuaternionProduct(q_delta, x, x_plus_delta); -// return true; -// } -// }; -// -// Then given this struct, the auto differentiated local -// parameterization can now be constructed as -// -// LocalParameterization* local_parameterization = -// new AutoDiffLocalParameterization<QuaternionPlus, 4, 3>; -// | | -// Global Size ---------------+ | -// Local Size -------------------+ -// -// WARNING: Since the functor will get instantiated with different types for -// T, you must to convert from other numeric types to T before mixing -// computations with other variables of type T. In the example above, this is -// seen where instead of using k_ directly, k_ is wrapped with T(k_). - -template <typename Functor, int kGlobalSize, int kLocalSize> -class AutoDiffLocalParameterization : public LocalParameterization { - public: - AutoDiffLocalParameterization() : - functor_(new Functor()) {} - - // Takes ownership of functor. - explicit AutoDiffLocalParameterization(Functor* functor) : - functor_(functor) {} - - virtual ~AutoDiffLocalParameterization() {} - virtual bool Plus(const double* x, - const double* delta, - double* x_plus_delta) const { - return (*functor_)(x, delta, x_plus_delta); - } - - virtual bool ComputeJacobian(const double* x, double* jacobian) const { - double zero_delta[kLocalSize]; - for (int i = 0; i < kLocalSize; ++i) { - zero_delta[i] = 0.0; - } - - double x_plus_delta[kGlobalSize]; - for (int i = 0; i < kGlobalSize; ++i) { - x_plus_delta[i] = 0.0; - } - - const double* parameter_ptrs[2] = {x, zero_delta}; - double* jacobian_ptrs[2] = { NULL, jacobian }; - return internal::AutoDiff<Functor, double, kGlobalSize, kLocalSize> - ::Differentiate(*functor_, - parameter_ptrs, - kGlobalSize, - x_plus_delta, - jacobian_ptrs); - } - - virtual int GlobalSize() const { return kGlobalSize; } - virtual int LocalSize() const { return kLocalSize; } - - private: - internal::scoped_ptr<Functor> functor_; -}; - -} // namespace ceres - -#endif // CERES_PUBLIC_AUTODIFF_LOCAL_PARAMETERIZATION_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/c_api.h b/extern/libmv/third_party/ceres/include/ceres/c_api.h deleted file mode 100644 index df7c9b6d671..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/c_api.h +++ /dev/null @@ -1,146 +0,0 @@ -/* Ceres Solver - A fast non-linear least squares minimizer - * Copyright 2015 Google Inc. All rights reserved. - * http://ceres-solver.org/ - * - * Redistribution and use in source and binary forms, with or without - * modification, are permitted provided that the following conditions are met: - * - * - Redistributions of source code must retain the above copyright notice, - * this list of conditions and the following disclaimer. - * - Redistributions in binary form must reproduce the above copyright notice, - * this list of conditions and the following disclaimer in the documentation - * and/or other materials provided with the distribution. - * - Neither the name of Google Inc. nor the names of its contributors may be - * used to endorse or promote products derived from this software without - * specific prior written permission. - * - * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" - * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE - * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE - * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE - * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR - * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF - * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS - * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN - * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) - * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE - * POSSIBILITY OF SUCH DAMAGE. - * - * Author: mierle@gmail.com (Keir Mierle) - * - * A minimal C API for Ceres. Not all functionality is included. This API is - * not intended for clients of Ceres, but is instead intended for easing the - * process of binding Ceres to other languages. - * - * Currently this is a work in progress. - */ - -#ifndef CERES_PUBLIC_C_API_H_ -#define CERES_PUBLIC_C_API_H_ - -#include "ceres/internal/port.h" -#include "ceres/internal/disable_warnings.h" - -#ifdef __cplusplus -extern "C" { -#endif - -/* Init the Ceres private data. Must be called before anything else. */ -CERES_EXPORT void ceres_init(); - -/* Equivalent to CostFunction::Evaluate() in the C++ API. - * - * The user may keep private information inside the opaque user_data object. - * The pointer here is the same one passed in the ceres_add_residual_block(). - */ -typedef int (*ceres_cost_function_t)(void* user_data, - double** parameters, - double* residuals, - double** jacobians); - -/* Equivalent to LossFunction::Evaluate() from the C++ API. */ -typedef void (*ceres_loss_function_t)(void* user_data, - double squared_norm, - double out[3]); - -/* Create callback data for Ceres' stock loss functions. - * - * Ceres has several loss functions available by default, and these functions - * expose those to the C API. To use the stock loss functions, call - * ceres_create_*_loss_data(), which internally creates an instance of one of - * the stock loss functions (for example ceres::CauchyLoss), and pass the - * returned "loss_function_data" along with the ceres_stock_loss_function to - * ceres_add_residual_block(). - * - * For example: - * - * void* cauchy_loss_function_data = - * ceres_create_cauchy_loss_function_data(1.2, 0.0); - * ceres_problem_add_residual_block( - * problem, - * my_cost_function, - * my_cost_function_data, - * ceres_stock_loss_function, - * cauchy_loss_function_data, - * 1, - * 2, - * parameter_sizes, - * parameter_pointers); - * ... - * ceres_free_stock_loss_function_data(cauchy_loss_function_data); - * - * See loss_function.h for the details of each loss function. - */ -CERES_EXPORT void* ceres_create_huber_loss_function_data(double a); -CERES_EXPORT void* ceres_create_softl1_loss_function_data(double a); -CERES_EXPORT void* ceres_create_cauchy_loss_function_data(double a); -CERES_EXPORT void* ceres_create_arctan_loss_function_data(double a); -CERES_EXPORT void* ceres_create_tolerant_loss_function_data(double a, double b); - -/* Free the given stock loss function data. */ -CERES_EXPORT void ceres_free_stock_loss_function_data(void* loss_function_data); - -/* This is an implementation of ceres_loss_function_t contained within Ceres - * itself, intended as a way to access the various stock Ceres loss functions - * from the C API. This should be passed to ceres_add_residual() below, in - * combination with a user_data pointer generated by - * ceres_create_stock_loss_function() above. */ -CERES_EXPORT void ceres_stock_loss_function(void* user_data, - double squared_norm, - double out[3]); - -/* Equivalent to Problem from the C++ API. */ -struct ceres_problem_s; -typedef struct ceres_problem_s ceres_problem_t; - -struct ceres_residual_block_id_s; -typedef struct ceres_residual_block_id_s ceres_residual_block_id_t; - -/* Create and destroy a problem */ -/* TODO(keir): Add options for the problem. */ -CERES_EXPORT ceres_problem_t* ceres_create_problem(); -CERES_EXPORT void ceres_free_problem(ceres_problem_t* problem); - -/* Add a residual block. */ -CERES_EXPORT ceres_residual_block_id_t* ceres_problem_add_residual_block( - ceres_problem_t* problem, - ceres_cost_function_t cost_function, - void* cost_function_data, - ceres_loss_function_t loss_function, - void* loss_function_data, - int num_residuals, - int num_parameter_blocks, - int* parameter_block_sizes, - double** parameters); - -CERES_EXPORT void ceres_solve(ceres_problem_t* problem); - -/* TODO(keir): Figure out a way to pass a config in. */ - -#ifdef __cplusplus -} -#endif - -#include "ceres/internal/reenable_warnings.h" - -#endif /* CERES_PUBLIC_C_API_H_ */ diff --git a/extern/libmv/third_party/ceres/include/ceres/ceres.h b/extern/libmv/third_party/ceres/include/ceres/ceres.h deleted file mode 100644 index 64ffb99798a..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/ceres.h +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// This is a forwarding header containing the public symbols exported from -// Ceres. Anything in the "ceres" namespace is available for use. - -#ifndef CERES_PUBLIC_CERES_H_ -#define CERES_PUBLIC_CERES_H_ - -#include "ceres/autodiff_cost_function.h" -#include "ceres/autodiff_local_parameterization.h" -#include "ceres/cost_function.h" -#include "ceres/cost_function_to_functor.h" -#include "ceres/covariance.h" -#include "ceres/crs_matrix.h" -#include "ceres/dynamic_autodiff_cost_function.h" -#include "ceres/dynamic_numeric_diff_cost_function.h" -#include "ceres/gradient_problem.h" -#include "ceres/gradient_problem_solver.h" -#include "ceres/iteration_callback.h" -#include "ceres/jet.h" -#include "ceres/local_parameterization.h" -#include "ceres/loss_function.h" -#include "ceres/numeric_diff_cost_function.h" -#include "ceres/ordered_groups.h" -#include "ceres/problem.h" -#include "ceres/sized_cost_function.h" -#include "ceres/solver.h" -#include "ceres/types.h" -#include "ceres/version.h" - -#endif // CERES_PUBLIC_CERES_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/conditioned_cost_function.h b/extern/libmv/third_party/ceres/include/ceres/conditioned_cost_function.h deleted file mode 100644 index 29597d935cb..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/conditioned_cost_function.h +++ /dev/null @@ -1,99 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: wjr@google.com (William Rucklidge) -// -// This file contains a cost function that can apply a transformation to -// each residual value before they are square-summed. - -#ifndef CERES_PUBLIC_CONDITIONED_COST_FUNCTION_H_ -#define CERES_PUBLIC_CONDITIONED_COST_FUNCTION_H_ - -#include <vector> - -#include "ceres/cost_function.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/types.h" -#include "ceres/internal/disable_warnings.h" - -namespace ceres { - -// This class allows you to apply different conditioning to the residual -// values of a wrapped cost function. An example where this is useful is -// where you have an existing cost function that produces N values, but you -// want the total cost to be something other than just the sum of these -// squared values - maybe you want to apply a different scaling to some -// values, to change their contribution to the cost. -// -// Usage: -// -// // my_cost_function produces N residuals -// CostFunction* my_cost_function = ... -// CHECK_EQ(N, my_cost_function->num_residuals()); -// vector<CostFunction*> conditioners; -// -// // Make N 1x1 cost functions (1 parameter, 1 residual) -// CostFunction* f_1 = ... -// conditioners.push_back(f_1); -// ... -// CostFunction* f_N = ... -// conditioners.push_back(f_N); -// ConditionedCostFunction* ccf = -// new ConditionedCostFunction(my_cost_function, conditioners); -// -// Now ccf's residual i (i=0..N-1) will be passed though the i'th conditioner. -// -// ccf_residual[i] = f_i(my_cost_function_residual[i]) -// -// and the Jacobian will be affected appropriately. -class CERES_EXPORT ConditionedCostFunction : public CostFunction { - public: - // Builds a cost function based on a wrapped cost function, and a - // per-residual conditioner. Takes ownership of all of the wrapped cost - // functions, or not, depending on the ownership parameter. Conditioners - // may be NULL, in which case the corresponding residual is not modified. - ConditionedCostFunction(CostFunction* wrapped_cost_function, - const std::vector<CostFunction*>& conditioners, - Ownership ownership); - virtual ~ConditionedCostFunction(); - - virtual bool Evaluate(double const* const* parameters, - double* residuals, - double** jacobians) const; - - private: - internal::scoped_ptr<CostFunction> wrapped_cost_function_; - std::vector<CostFunction*> conditioners_; - Ownership ownership_; -}; - -} // namespace ceres - -#include "ceres/internal/reenable_warnings.h" - -#endif // CERES_PUBLIC_CONDITIONED_COST_FUNCTION_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/cost_function.h b/extern/libmv/third_party/ceres/include/ceres/cost_function.h deleted file mode 100644 index f051a897c0d..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/cost_function.h +++ /dev/null @@ -1,147 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// keir@google.m (Keir Mierle) -// -// This is the interface through which the least squares solver accesses the -// residual and Jacobian of the least squares problem. Users are expected to -// subclass CostFunction to define their own terms in the least squares problem. -// -// It is recommended that users define templated residual functors for use as -// arguments for AutoDiffCostFunction (see autodiff_cost_function.h), instead of -// directly implementing the CostFunction interface. This often results in both -// shorter code and faster execution than hand-coded derivatives. However, -// specialized cases may demand direct implementation of the lower-level -// CostFunction interface; for example, this is true when calling legacy code -// which is not templated on numeric types. - -#ifndef CERES_PUBLIC_COST_FUNCTION_H_ -#define CERES_PUBLIC_COST_FUNCTION_H_ - -#include <vector> -#include "ceres/internal/macros.h" -#include "ceres/internal/port.h" -#include "ceres/types.h" -#include "ceres/internal/disable_warnings.h" - -namespace ceres { - -// This class implements the computation of the cost (a.k.a. residual) terms as -// a function of the input (control) variables, and is the interface for users -// to describe their least squares problem to Ceres. In other words, this is the -// modelling layer between users and the Ceres optimizer. The signature of the -// function (number and sizes of input parameter blocks and number of outputs) -// is stored in parameter_block_sizes_ and num_residuals_ respectively. User -// code inheriting from this class is expected to set these two members with the -// corresponding accessors. This information will be verified by the Problem -// when added with AddResidualBlock(). -class CERES_EXPORT CostFunction { - public: - CostFunction() : num_residuals_(0) {} - - virtual ~CostFunction() {} - - // Inputs: - // - // parameters is an array of pointers to arrays containing the - // various parameter blocks. parameters has the same number of - // elements as parameter_block_sizes_. Parameter blocks are in the - // same order as parameter_block_sizes_.i.e., - // - // parameters_[i] = double[parameter_block_sizes_[i]] - // - // Outputs: - // - // residuals is an array of size num_residuals_. - // - // jacobians is an array of size parameter_block_sizes_ containing - // pointers to storage for jacobian blocks corresponding to each - // parameter block. Jacobian blocks are in the same order as - // parameter_block_sizes, i.e. jacobians[i], is an - // array that contains num_residuals_* parameter_block_sizes_[i] - // elements. Each jacobian block is stored in row-major order, i.e., - // - // jacobians[i][r*parameter_block_size_[i] + c] = - // d residual[r] / d parameters[i][c] - // - // If jacobians is NULL, then no derivatives are returned; this is - // the case when computing cost only. If jacobians[i] is NULL, then - // the jacobian block corresponding to the i'th parameter block must - // not to be returned. - // - // The return value indicates whether the computation of the - // residuals and/or jacobians was successful or not. - // - // This can be used to communicate numerical failures in jacobian - // computations for instance. - // - // A more interesting and common use is to impose constraints on the - // parameters. If the initial values of the parameter blocks satisfy - // the constraints, then returning false whenever the constraints - // are not satisfied will prevent the solver from moving into the - // infeasible region. This is not a very sophisticated mechanism for - // enforcing constraints, but is often good enough. - // - // Note that it is important that the initial values of the - // parameter block must be feasible, otherwise the solver will - // declare a numerical problem at iteration 0. - virtual bool Evaluate(double const* const* parameters, - double* residuals, - double** jacobians) const = 0; - - const std::vector<int32>& parameter_block_sizes() const { - return parameter_block_sizes_; - } - - int num_residuals() const { - return num_residuals_; - } - - protected: - std::vector<int32>* mutable_parameter_block_sizes() { - return ¶meter_block_sizes_; - } - - void set_num_residuals(int num_residuals) { - num_residuals_ = num_residuals; - } - - private: - // Cost function signature metadata: number of inputs & their sizes, - // number of outputs (residuals). - std::vector<int32> parameter_block_sizes_; - int num_residuals_; - CERES_DISALLOW_COPY_AND_ASSIGN(CostFunction); -}; - -} // namespace ceres - -#include "ceres/internal/reenable_warnings.h" - -#endif // CERES_PUBLIC_COST_FUNCTION_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/cost_function_to_functor.h b/extern/libmv/third_party/ceres/include/ceres/cost_function_to_functor.h deleted file mode 100644 index 6c67ac0f937..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/cost_function_to_functor.h +++ /dev/null @@ -1,682 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// CostFunctionToFunctor is an adapter class that allows users to use -// SizedCostFunction objects in templated functors which are to be used for -// automatic differentiation. This allows the user to seamlessly mix -// analytic, numeric and automatic differentiation. -// -// For example, let us assume that -// -// class IntrinsicProjection : public SizedCostFunction<2, 5, 3> { -// public: -// IntrinsicProjection(const double* observation); -// virtual bool Evaluate(double const* const* parameters, -// double* residuals, -// double** jacobians) const; -// }; -// -// is a cost function that implements the projection of a point in its -// local coordinate system onto its image plane and subtracts it from -// the observed point projection. It can compute its residual and -// either via analytic or numerical differentiation can compute its -// jacobians. -// -// Now we would like to compose the action of this CostFunction with -// the action of camera extrinsics, i.e., rotation and -// translation. Say we have a templated function -// -// template<typename T> -// void RotateAndTranslatePoint(const T* rotation, -// const T* translation, -// const T* point, -// T* result); -// -// Then we can now do the following, -// -// struct CameraProjection { -// CameraProjection(const double* observation) -// : intrinsic_projection_(new IntrinsicProjection(observation)) { -// } -// template <typename T> -// bool operator()(const T* rotation, -// const T* translation, -// const T* intrinsics, -// const T* point, -// T* residual) const { -// T transformed_point[3]; -// RotateAndTranslatePoint(rotation, translation, point, transformed_point); -// -// // Note that we call intrinsic_projection_, just like it was -// // any other templated functor. -// -// return intrinsic_projection_(intrinsics, transformed_point, residual); -// } -// -// private: -// CostFunctionToFunctor<2,5,3> intrinsic_projection_; -// }; - -#ifndef CERES_PUBLIC_COST_FUNCTION_TO_FUNCTOR_H_ -#define CERES_PUBLIC_COST_FUNCTION_TO_FUNCTOR_H_ - -#include <numeric> -#include <vector> - -#include "ceres/cost_function.h" -#include "ceres/dynamic_cost_function_to_functor.h" -#include "ceres/internal/fixed_array.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" - -namespace ceres { - -template <int kNumResiduals, - int N0, int N1 = 0, int N2 = 0, int N3 = 0, int N4 = 0, - int N5 = 0, int N6 = 0, int N7 = 0, int N8 = 0, int N9 = 0> -class CostFunctionToFunctor { - public: - // Takes ownership of cost_function. - explicit CostFunctionToFunctor(CostFunction* cost_function) - : cost_functor_(cost_function) { - CHECK_NOTNULL(cost_function); - CHECK(kNumResiduals > 0 || kNumResiduals == DYNAMIC); - - // This block breaks the 80 column rule to keep it somewhat readable. - CHECK((!N1 && !N2 && !N3 && !N4 && !N5 && !N6 && !N7 && !N8 && !N9) || - ((N1 > 0) && !N2 && !N3 && !N4 && !N5 && !N6 && !N7 && !N8 && !N9) || - ((N1 > 0) && (N2 > 0) && !N3 && !N4 && !N5 && !N6 && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && !N4 && !N5 && !N6 && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && !N5 && !N6 && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && !N6 && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && (N6 > 0) && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && (N6 > 0) && (N7 > 0) && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && (N6 > 0) && (N7 > 0) && (N8 > 0) && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && (N6 > 0) && (N7 > 0) && (N8 > 0) && (N9 > 0))) // NOLINT - << "Zero block cannot precede a non-zero block. Block sizes are " - << "(ignore trailing 0s): " << N0 << ", " << N1 << ", " << N2 << ", " - << N3 << ", " << N4 << ", " << N5 << ", " << N6 << ", " << N7 << ", " - << N8 << ", " << N9; - - const std::vector<int32>& parameter_block_sizes = - cost_function->parameter_block_sizes(); - const int num_parameter_blocks = - (N0 > 0) + (N1 > 0) + (N2 > 0) + (N3 > 0) + (N4 > 0) + - (N5 > 0) + (N6 > 0) + (N7 > 0) + (N8 > 0) + (N9 > 0); - CHECK_EQ(parameter_block_sizes.size(), num_parameter_blocks); - - CHECK_EQ(N0, parameter_block_sizes[0]); - if (parameter_block_sizes.size() > 1) CHECK_EQ(N1, parameter_block_sizes[1]); // NOLINT - if (parameter_block_sizes.size() > 2) CHECK_EQ(N2, parameter_block_sizes[2]); // NOLINT - if (parameter_block_sizes.size() > 3) CHECK_EQ(N3, parameter_block_sizes[3]); // NOLINT - if (parameter_block_sizes.size() > 4) CHECK_EQ(N4, parameter_block_sizes[4]); // NOLINT - if (parameter_block_sizes.size() > 5) CHECK_EQ(N5, parameter_block_sizes[5]); // NOLINT - if (parameter_block_sizes.size() > 6) CHECK_EQ(N6, parameter_block_sizes[6]); // NOLINT - if (parameter_block_sizes.size() > 7) CHECK_EQ(N7, parameter_block_sizes[7]); // NOLINT - if (parameter_block_sizes.size() > 8) CHECK_EQ(N8, parameter_block_sizes[8]); // NOLINT - if (parameter_block_sizes.size() > 9) CHECK_EQ(N9, parameter_block_sizes[9]); // NOLINT - - CHECK_EQ(accumulate(parameter_block_sizes.begin(), - parameter_block_sizes.end(), 0), - N0 + N1 + N2 + N3 + N4 + N5 + N6 + N7 + N8 + N9); - } - - bool operator()(const double* x0, double* residuals) const { - CHECK_NE(N0, 0); - CHECK_EQ(N1, 0); - CHECK_EQ(N2, 0); - CHECK_EQ(N3, 0); - CHECK_EQ(N4, 0); - CHECK_EQ(N5, 0); - CHECK_EQ(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - - return cost_functor_(&x0, residuals); - } - - bool operator()(const double* x0, - const double* x1, - double* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_EQ(N2, 0); - CHECK_EQ(N3, 0); - CHECK_EQ(N4, 0); - CHECK_EQ(N5, 0); - CHECK_EQ(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const double*> parameter_blocks(2); - parameter_blocks[0] = x0; - parameter_blocks[1] = x1; - return cost_functor_(parameter_blocks.get(), residuals); - } - - bool operator()(const double* x0, - const double* x1, - const double* x2, - double* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_EQ(N3, 0); - CHECK_EQ(N4, 0); - CHECK_EQ(N5, 0); - CHECK_EQ(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const double*> parameter_blocks(3); - parameter_blocks[0] = x0; - parameter_blocks[1] = x1; - parameter_blocks[2] = x2; - return cost_functor_(parameter_blocks.get(), residuals); - } - - bool operator()(const double* x0, - const double* x1, - const double* x2, - const double* x3, - double* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_EQ(N4, 0); - CHECK_EQ(N5, 0); - CHECK_EQ(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const double*> parameter_blocks(4); - parameter_blocks[0] = x0; - parameter_blocks[1] = x1; - parameter_blocks[2] = x2; - parameter_blocks[3] = x3; - return cost_functor_(parameter_blocks.get(), residuals); - } - - bool operator()(const double* x0, - const double* x1, - const double* x2, - const double* x3, - const double* x4, - double* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_NE(N4, 0); - CHECK_EQ(N5, 0); - CHECK_EQ(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const double*> parameter_blocks(5); - parameter_blocks[0] = x0; - parameter_blocks[1] = x1; - parameter_blocks[2] = x2; - parameter_blocks[3] = x3; - parameter_blocks[4] = x4; - return cost_functor_(parameter_blocks.get(), residuals); - } - - bool operator()(const double* x0, - const double* x1, - const double* x2, - const double* x3, - const double* x4, - const double* x5, - double* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_NE(N4, 0); - CHECK_NE(N5, 0); - CHECK_EQ(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const double*> parameter_blocks(6); - parameter_blocks[0] = x0; - parameter_blocks[1] = x1; - parameter_blocks[2] = x2; - parameter_blocks[3] = x3; - parameter_blocks[4] = x4; - parameter_blocks[5] = x5; - return cost_functor_(parameter_blocks.get(), residuals); - } - - bool operator()(const double* x0, - const double* x1, - const double* x2, - const double* x3, - const double* x4, - const double* x5, - const double* x6, - double* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_NE(N4, 0); - CHECK_NE(N5, 0); - CHECK_NE(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const double*> parameter_blocks(7); - parameter_blocks[0] = x0; - parameter_blocks[1] = x1; - parameter_blocks[2] = x2; - parameter_blocks[3] = x3; - parameter_blocks[4] = x4; - parameter_blocks[5] = x5; - parameter_blocks[6] = x6; - return cost_functor_(parameter_blocks.get(), residuals); - } - - bool operator()(const double* x0, - const double* x1, - const double* x2, - const double* x3, - const double* x4, - const double* x5, - const double* x6, - const double* x7, - double* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_NE(N4, 0); - CHECK_NE(N5, 0); - CHECK_NE(N6, 0); - CHECK_NE(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const double*> parameter_blocks(8); - parameter_blocks[0] = x0; - parameter_blocks[1] = x1; - parameter_blocks[2] = x2; - parameter_blocks[3] = x3; - parameter_blocks[4] = x4; - parameter_blocks[5] = x5; - parameter_blocks[6] = x6; - parameter_blocks[7] = x7; - return cost_functor_(parameter_blocks.get(), residuals); - } - - bool operator()(const double* x0, - const double* x1, - const double* x2, - const double* x3, - const double* x4, - const double* x5, - const double* x6, - const double* x7, - const double* x8, - double* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_NE(N4, 0); - CHECK_NE(N5, 0); - CHECK_NE(N6, 0); - CHECK_NE(N7, 0); - CHECK_NE(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const double*> parameter_blocks(9); - parameter_blocks[0] = x0; - parameter_blocks[1] = x1; - parameter_blocks[2] = x2; - parameter_blocks[3] = x3; - parameter_blocks[4] = x4; - parameter_blocks[5] = x5; - parameter_blocks[6] = x6; - parameter_blocks[7] = x7; - parameter_blocks[8] = x8; - return cost_functor_(parameter_blocks.get(), residuals); - } - - bool operator()(const double* x0, - const double* x1, - const double* x2, - const double* x3, - const double* x4, - const double* x5, - const double* x6, - const double* x7, - const double* x8, - const double* x9, - double* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_NE(N4, 0); - CHECK_NE(N5, 0); - CHECK_NE(N6, 0); - CHECK_NE(N7, 0); - CHECK_NE(N8, 0); - CHECK_NE(N9, 0); - internal::FixedArray<const double*> parameter_blocks(10); - parameter_blocks[0] = x0; - parameter_blocks[1] = x1; - parameter_blocks[2] = x2; - parameter_blocks[3] = x3; - parameter_blocks[4] = x4; - parameter_blocks[5] = x5; - parameter_blocks[6] = x6; - parameter_blocks[7] = x7; - parameter_blocks[8] = x8; - parameter_blocks[9] = x9; - return cost_functor_(parameter_blocks.get(), residuals); - } - - template <typename JetT> - bool operator()(const JetT* x0, JetT* residuals) const { - CHECK_NE(N0, 0); - CHECK_EQ(N1, 0); - CHECK_EQ(N2, 0); - CHECK_EQ(N3, 0); - CHECK_EQ(N4, 0); - CHECK_EQ(N5, 0); - CHECK_EQ(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - return cost_functor_(&x0, residuals); - } - - template <typename JetT> - bool operator()(const JetT* x0, - const JetT* x1, - JetT* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_EQ(N2, 0); - CHECK_EQ(N3, 0); - CHECK_EQ(N4, 0); - CHECK_EQ(N5, 0); - CHECK_EQ(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const JetT*> jets(2); - jets[0] = x0; - jets[1] = x1; - return cost_functor_(jets.get(), residuals); - } - - template <typename JetT> - bool operator()(const JetT* x0, - const JetT* x1, - const JetT* x2, - JetT* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_EQ(N3, 0); - CHECK_EQ(N4, 0); - CHECK_EQ(N5, 0); - CHECK_EQ(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const JetT*> jets(3); - jets[0] = x0; - jets[1] = x1; - jets[2] = x2; - return cost_functor_(jets.get(), residuals); - } - - template <typename JetT> - bool operator()(const JetT* x0, - const JetT* x1, - const JetT* x2, - const JetT* x3, - JetT* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_EQ(N4, 0); - CHECK_EQ(N5, 0); - CHECK_EQ(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const JetT*> jets(4); - jets[0] = x0; - jets[1] = x1; - jets[2] = x2; - jets[3] = x3; - return cost_functor_(jets.get(), residuals); - } - - template <typename JetT> - bool operator()(const JetT* x0, - const JetT* x1, - const JetT* x2, - const JetT* x3, - const JetT* x4, - JetT* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_NE(N4, 0); - CHECK_EQ(N5, 0); - CHECK_EQ(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const JetT*> jets(5); - jets[0] = x0; - jets[1] = x1; - jets[2] = x2; - jets[3] = x3; - jets[4] = x4; - return cost_functor_(jets.get(), residuals); - } - - template <typename JetT> - bool operator()(const JetT* x0, - const JetT* x1, - const JetT* x2, - const JetT* x3, - const JetT* x4, - const JetT* x5, - JetT* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_NE(N4, 0); - CHECK_NE(N5, 0); - CHECK_EQ(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const JetT*> jets(6); - jets[0] = x0; - jets[1] = x1; - jets[2] = x2; - jets[3] = x3; - jets[4] = x4; - jets[5] = x5; - return cost_functor_(jets.get(), residuals); - } - - template <typename JetT> - bool operator()(const JetT* x0, - const JetT* x1, - const JetT* x2, - const JetT* x3, - const JetT* x4, - const JetT* x5, - const JetT* x6, - JetT* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_NE(N4, 0); - CHECK_NE(N5, 0); - CHECK_NE(N6, 0); - CHECK_EQ(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const JetT*> jets(7); - jets[0] = x0; - jets[1] = x1; - jets[2] = x2; - jets[3] = x3; - jets[4] = x4; - jets[5] = x5; - jets[6] = x6; - return cost_functor_(jets.get(), residuals); - } - - template <typename JetT> - bool operator()(const JetT* x0, - const JetT* x1, - const JetT* x2, - const JetT* x3, - const JetT* x4, - const JetT* x5, - const JetT* x6, - const JetT* x7, - JetT* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_NE(N4, 0); - CHECK_NE(N5, 0); - CHECK_NE(N6, 0); - CHECK_NE(N7, 0); - CHECK_EQ(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const JetT*> jets(8); - jets[0] = x0; - jets[1] = x1; - jets[2] = x2; - jets[3] = x3; - jets[4] = x4; - jets[5] = x5; - jets[6] = x6; - jets[7] = x7; - return cost_functor_(jets.get(), residuals); - } - - template <typename JetT> - bool operator()(const JetT* x0, - const JetT* x1, - const JetT* x2, - const JetT* x3, - const JetT* x4, - const JetT* x5, - const JetT* x6, - const JetT* x7, - const JetT* x8, - JetT* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_NE(N4, 0); - CHECK_NE(N5, 0); - CHECK_NE(N6, 0); - CHECK_NE(N7, 0); - CHECK_NE(N8, 0); - CHECK_EQ(N9, 0); - internal::FixedArray<const JetT*> jets(9); - jets[0] = x0; - jets[1] = x1; - jets[2] = x2; - jets[3] = x3; - jets[4] = x4; - jets[5] = x5; - jets[6] = x6; - jets[7] = x7; - jets[8] = x8; - return cost_functor_(jets.get(), residuals); - } - - template <typename JetT> - bool operator()(const JetT* x0, - const JetT* x1, - const JetT* x2, - const JetT* x3, - const JetT* x4, - const JetT* x5, - const JetT* x6, - const JetT* x7, - const JetT* x8, - const JetT* x9, - JetT* residuals) const { - CHECK_NE(N0, 0); - CHECK_NE(N1, 0); - CHECK_NE(N2, 0); - CHECK_NE(N3, 0); - CHECK_NE(N4, 0); - CHECK_NE(N5, 0); - CHECK_NE(N6, 0); - CHECK_NE(N7, 0); - CHECK_NE(N8, 0); - CHECK_NE(N9, 0); - internal::FixedArray<const JetT*> jets(10); - jets[0] = x0; - jets[1] = x1; - jets[2] = x2; - jets[3] = x3; - jets[4] = x4; - jets[5] = x5; - jets[6] = x6; - jets[7] = x7; - jets[8] = x8; - jets[9] = x9; - return cost_functor_(jets.get(), residuals); - } - - private: - DynamicCostFunctionToFunctor cost_functor_; -}; - -} // namespace ceres - -#endif // CERES_PUBLIC_COST_FUNCTION_TO_FUNCTOR_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/covariance.h b/extern/libmv/third_party/ceres/include/ceres/covariance.h deleted file mode 100644 index dd20dc36ba1..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/covariance.h +++ /dev/null @@ -1,405 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_PUBLIC_COVARIANCE_H_ -#define CERES_PUBLIC_COVARIANCE_H_ - -#include <utility> -#include <vector> -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/types.h" -#include "ceres/internal/disable_warnings.h" - -namespace ceres { - -class Problem; - -namespace internal { -class CovarianceImpl; -} // namespace internal - -// WARNING -// ======= -// It is very easy to use this class incorrectly without understanding -// the underlying mathematics. Please read and understand the -// documentation completely before attempting to use this class. -// -// -// This class allows the user to evaluate the covariance for a -// non-linear least squares problem and provides random access to its -// blocks -// -// Background -// ========== -// One way to assess the quality of the solution returned by a -// non-linear least squares solve is to analyze the covariance of the -// solution. -// -// Let us consider the non-linear regression problem -// -// y = f(x) + N(0, I) -// -// i.e., the observation y is a random non-linear function of the -// independent variable x with mean f(x) and identity covariance. Then -// the maximum likelihood estimate of x given observations y is the -// solution to the non-linear least squares problem: -// -// x* = arg min_x |f(x)|^2 -// -// And the covariance of x* is given by -// -// C(x*) = inverse[J'(x*)J(x*)] -// -// Here J(x*) is the Jacobian of f at x*. The above formula assumes -// that J(x*) has full column rank. -// -// If J(x*) is rank deficient, then the covariance matrix C(x*) is -// also rank deficient and is given by -// -// C(x*) = pseudoinverse[J'(x*)J(x*)] -// -// Note that in the above, we assumed that the covariance -// matrix for y was identity. This is an important assumption. If this -// is not the case and we have -// -// y = f(x) + N(0, S) -// -// Where S is a positive semi-definite matrix denoting the covariance -// of y, then the maximum likelihood problem to be solved is -// -// x* = arg min_x f'(x) inverse[S] f(x) -// -// and the corresponding covariance estimate of x* is given by -// -// C(x*) = inverse[J'(x*) inverse[S] J(x*)] -// -// So, if it is the case that the observations being fitted to have a -// covariance matrix not equal to identity, then it is the user's -// responsibility that the corresponding cost functions are correctly -// scaled, e.g. in the above case the cost function for this problem -// should evaluate S^{-1/2} f(x) instead of just f(x), where S^{-1/2} -// is the inverse square root of the covariance matrix S. -// -// This class allows the user to evaluate the covariance for a -// non-linear least squares problem and provides random access to its -// blocks. The computation assumes that the CostFunctions compute -// residuals such that their covariance is identity. -// -// Since the computation of the covariance matrix requires computing -// the inverse of a potentially large matrix, this can involve a -// rather large amount of time and memory. However, it is usually the -// case that the user is only interested in a small part of the -// covariance matrix. Quite often just the block diagonal. This class -// allows the user to specify the parts of the covariance matrix that -// she is interested in and then uses this information to only compute -// and store those parts of the covariance matrix. -// -// Rank of the Jacobian -// -------------------- -// As we noted above, if the jacobian is rank deficient, then the -// inverse of J'J is not defined and instead a pseudo inverse needs to -// be computed. -// -// The rank deficiency in J can be structural -- columns which are -// always known to be zero or numerical -- depending on the exact -// values in the Jacobian. -// -// Structural rank deficiency occurs when the problem contains -// parameter blocks that are constant. This class correctly handles -// structural rank deficiency like that. -// -// Numerical rank deficiency, where the rank of the matrix cannot be -// predicted by its sparsity structure and requires looking at its -// numerical values is more complicated. Here again there are two -// cases. -// -// a. The rank deficiency arises from overparameterization. e.g., a -// four dimensional quaternion used to parameterize SO(3), which is -// a three dimensional manifold. In cases like this, the user should -// use an appropriate LocalParameterization. Not only will this lead -// to better numerical behaviour of the Solver, it will also expose -// the rank deficiency to the Covariance object so that it can -// handle it correctly. -// -// b. More general numerical rank deficiency in the Jacobian -// requires the computation of the so called Singular Value -// Decomposition (SVD) of J'J. We do not know how to do this for -// large sparse matrices efficiently. For small and moderate sized -// problems this is done using dense linear algebra. -// -// Gauge Invariance -// ---------------- -// In structure from motion (3D reconstruction) problems, the -// reconstruction is ambiguous upto a similarity transform. This is -// known as a Gauge Ambiguity. Handling Gauges correctly requires the -// use of SVD or custom inversion algorithms. For small problems the -// user can use the dense algorithm. For more details see -// -// Ken-ichi Kanatani, Daniel D. Morris: Gauges and gauge -// transformations for uncertainty description of geometric structure -// with indeterminacy. IEEE Transactions on Information Theory 47(5): -// 2017-2028 (2001) -// -// Example Usage -// ============= -// -// double x[3]; -// double y[2]; -// -// Problem problem; -// problem.AddParameterBlock(x, 3); -// problem.AddParameterBlock(y, 2); -// <Build Problem> -// <Solve Problem> -// -// Covariance::Options options; -// Covariance covariance(options); -// -// std::vector<std::pair<const double*, const double*> > covariance_blocks; -// covariance_blocks.push_back(make_pair(x, x)); -// covariance_blocks.push_back(make_pair(y, y)); -// covariance_blocks.push_back(make_pair(x, y)); -// -// CHECK(covariance.Compute(covariance_blocks, &problem)); -// -// double covariance_xx[3 * 3]; -// double covariance_yy[2 * 2]; -// double covariance_xy[3 * 2]; -// covariance.GetCovarianceBlock(x, x, covariance_xx) -// covariance.GetCovarianceBlock(y, y, covariance_yy) -// covariance.GetCovarianceBlock(x, y, covariance_xy) -// -class CERES_EXPORT Covariance { - public: - struct CERES_EXPORT Options { - Options() -#ifndef CERES_NO_SUITESPARSE - : algorithm_type(SUITE_SPARSE_QR), -#else - : algorithm_type(EIGEN_SPARSE_QR), -#endif - min_reciprocal_condition_number(1e-14), - null_space_rank(0), - num_threads(1), - apply_loss_function(true) { - } - - // Ceres supports three different algorithms for covariance - // estimation, which represent different tradeoffs in speed, - // accuracy and reliability. - // - // 1. DENSE_SVD uses Eigen's JacobiSVD to perform the - // computations. It computes the singular value decomposition - // - // U * S * V' = J - // - // and then uses it to compute the pseudo inverse of J'J as - // - // pseudoinverse[J'J]^ = V * pseudoinverse[S] * V' - // - // It is an accurate but slow method and should only be used - // for small to moderate sized problems. It can handle - // full-rank as well as rank deficient Jacobians. - // - // 2. EIGEN_SPARSE_QR uses the sparse QR factorization algorithm - // in Eigen to compute the decomposition - // - // Q * R = J - // - // [J'J]^-1 = [R*R']^-1 - // - // It is a moderately fast algorithm for sparse matrices. - // - // 3. SUITE_SPARSE_QR uses the SuiteSparseQR sparse QR - // factorization algorithm. It uses dense linear algebra and is - // multi threaded, so for large sparse sparse matrices it is - // significantly faster than EIGEN_SPARSE_QR. - // - // Neither EIGEN_SPARSE_QR not SUITE_SPARSE_QR are capable of - // computing the covariance if the Jacobian is rank deficient. - CovarianceAlgorithmType algorithm_type; - - // If the Jacobian matrix is near singular, then inverting J'J - // will result in unreliable results, e.g, if - // - // J = [1.0 1.0 ] - // [1.0 1.0000001 ] - // - // which is essentially a rank deficient matrix, we have - // - // inv(J'J) = [ 2.0471e+14 -2.0471e+14] - // [-2.0471e+14 2.0471e+14] - // - // This is not a useful result. Therefore, by default - // Covariance::Compute will return false if a rank deficient - // Jacobian is encountered. How rank deficiency is detected - // depends on the algorithm being used. - // - // 1. DENSE_SVD - // - // min_sigma / max_sigma < sqrt(min_reciprocal_condition_number) - // - // where min_sigma and max_sigma are the minimum and maxiumum - // singular values of J respectively. - // - // 2. SUITE_SPARSE_QR and EIGEN_SPARSE_QR - // - // rank(J) < num_col(J) - // - // Here rank(J) is the estimate of the rank of J returned by the - // sparse QR factorization algorithm. It is a fairly reliable - // indication of rank deficiency. - // - double min_reciprocal_condition_number; - - // When using DENSE_SVD, the user has more control in dealing with - // singular and near singular covariance matrices. - // - // As mentioned above, when the covariance matrix is near - // singular, instead of computing the inverse of J'J, the - // Moore-Penrose pseudoinverse of J'J should be computed. - // - // If J'J has the eigen decomposition (lambda_i, e_i), where - // lambda_i is the i^th eigenvalue and e_i is the corresponding - // eigenvector, then the inverse of J'J is - // - // inverse[J'J] = sum_i e_i e_i' / lambda_i - // - // and computing the pseudo inverse involves dropping terms from - // this sum that correspond to small eigenvalues. - // - // How terms are dropped is controlled by - // min_reciprocal_condition_number and null_space_rank. - // - // If null_space_rank is non-negative, then the smallest - // null_space_rank eigenvalue/eigenvectors are dropped - // irrespective of the magnitude of lambda_i. If the ratio of the - // smallest non-zero eigenvalue to the largest eigenvalue in the - // truncated matrix is still below - // min_reciprocal_condition_number, then the Covariance::Compute() - // will fail and return false. - // - // Setting null_space_rank = -1 drops all terms for which - // - // lambda_i / lambda_max < min_reciprocal_condition_number. - // - // This option has no effect on the SUITE_SPARSE_QR and - // EIGEN_SPARSE_QR algorithms. - int null_space_rank; - - int num_threads; - - // Even though the residual blocks in the problem may contain loss - // functions, setting apply_loss_function to false will turn off - // the application of the loss function to the output of the cost - // function and in turn its effect on the covariance. - // - // TODO(sameergaarwal): Expand this based on Jim's experiments. - bool apply_loss_function; - }; - - explicit Covariance(const Options& options); - ~Covariance(); - - // Compute a part of the covariance matrix. - // - // The vector covariance_blocks, indexes into the covariance matrix - // block-wise using pairs of parameter blocks. This allows the - // covariance estimation algorithm to only compute and store these - // blocks. - // - // Since the covariance matrix is symmetric, if the user passes - // (block1, block2), then GetCovarianceBlock can be called with - // block1, block2 as well as block2, block1. - // - // covariance_blocks cannot contain duplicates. Bad things will - // happen if they do. - // - // Note that the list of covariance_blocks is only used to determine - // what parts of the covariance matrix are computed. The full - // Jacobian is used to do the computation, i.e. they do not have an - // impact on what part of the Jacobian is used for computation. - // - // The return value indicates the success or failure of the - // covariance computation. Please see the documentation for - // Covariance::Options for more on the conditions under which this - // function returns false. - bool Compute( - const std::vector<std::pair<const double*, - const double*> >& covariance_blocks, - Problem* problem); - - // Return the block of the cross-covariance matrix corresponding to - // parameter_block1 and parameter_block2. - // - // Compute must be called before the first call to - // GetCovarianceBlock and the pair <parameter_block1, - // parameter_block2> OR the pair <parameter_block2, - // parameter_block1> must have been present in the vector - // covariance_blocks when Compute was called. Otherwise - // GetCovarianceBlock will return false. - // - // covariance_block must point to a memory location that can store a - // parameter_block1_size x parameter_block2_size matrix. The - // returned covariance will be a row-major matrix. - bool GetCovarianceBlock(const double* parameter_block1, - const double* parameter_block2, - double* covariance_block) const; - - // Return the block of the cross-covariance matrix corresponding to - // parameter_block1 and parameter_block2. - // Returns cross-covariance in the tangent space if a local - // parameterization is associated with either parameter block; - // else returns cross-covariance in the ambient space. - // - // Compute must be called before the first call to - // GetCovarianceBlock and the pair <parameter_block1, - // parameter_block2> OR the pair <parameter_block2, - // parameter_block1> must have been present in the vector - // covariance_blocks when Compute was called. Otherwise - // GetCovarianceBlock will return false. - // - // covariance_block must point to a memory location that can store a - // parameter_block1_local_size x parameter_block2_local_size matrix. The - // returned covariance will be a row-major matrix. - bool GetCovarianceBlockInTangentSpace(const double* parameter_block1, - const double* parameter_block2, - double* covariance_block) const; - - private: - internal::scoped_ptr<internal::CovarianceImpl> impl_; -}; - -} // namespace ceres - -#include "ceres/internal/reenable_warnings.h" - -#endif // CERES_PUBLIC_COVARIANCE_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/crs_matrix.h b/extern/libmv/third_party/ceres/include/ceres/crs_matrix.h deleted file mode 100644 index 23687c4670e..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/crs_matrix.h +++ /dev/null @@ -1,86 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_PUBLIC_CRS_MATRIX_H_ -#define CERES_PUBLIC_CRS_MATRIX_H_ - -#include <vector> -#include "ceres/internal/port.h" -#include "ceres/internal/disable_warnings.h" - -namespace ceres { - -// A compressed row sparse matrix used primarily for communicating the -// Jacobian matrix to the user. -struct CERES_EXPORT CRSMatrix { - CRSMatrix() : num_rows(0), num_cols(0) {} - - int num_rows; - int num_cols; - - // A compressed row matrix stores its contents in three arrays, - // rows, cols and values. - // - // rows is a num_rows + 1 sized array that points into the cols and - // values array. For each row i: - // - // cols[rows[i]] ... cols[rows[i + 1] - 1] are the indices of the - // non-zero columns of row i. - // - // values[rows[i]] .. values[rows[i + 1] - 1] are the values of the - // corresponding entries. - // - // cols and values contain as many entries as there are non-zeros in - // the matrix. - // - // e.g, consider the 3x4 sparse matrix - // - // [ 0 10 0 4 ] - // [ 0 2 -3 2 ] - // [ 1 2 0 0 ] - // - // The three arrays will be: - // - // - // -row0- ---row1--- -row2- - // rows = [ 0, 2, 5, 7] - // cols = [ 1, 3, 1, 2, 3, 0, 1] - // values = [10, 4, 2, -3, 2, 1, 2] - - std::vector<int> cols; - std::vector<int> rows; - std::vector<double> values; -}; - -} // namespace ceres - -#include "ceres/internal/reenable_warnings.h" - -#endif // CERES_PUBLIC_CRS_MATRIX_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/dynamic_autodiff_cost_function.h b/extern/libmv/third_party/ceres/include/ceres/dynamic_autodiff_cost_function.h deleted file mode 100644 index e6d26111f18..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/dynamic_autodiff_cost_function.h +++ /dev/null @@ -1,260 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// mierle@gmail.com (Keir Mierle) -// -// This autodiff implementation differs from the one found in -// autodiff_cost_function.h by supporting autodiff on cost functions -// with variable numbers of parameters with variable sizes. With the -// other implementation, all the sizes (both the number of parameter -// blocks and the size of each block) must be fixed at compile time. -// -// The functor API differs slightly from the API for fixed size -// autodiff; the expected interface for the cost functors is: -// -// struct MyCostFunctor { -// template<typename T> -// bool operator()(T const* const* parameters, T* residuals) const { -// // Use parameters[i] to access the i'th parameter block. -// } -// } -// -// Since the sizing of the parameters is done at runtime, you must -// also specify the sizes after creating the dynamic autodiff cost -// function. For example: -// -// DynamicAutoDiffCostFunction<MyCostFunctor, 3> cost_function( -// new MyCostFunctor()); -// cost_function.AddParameterBlock(5); -// cost_function.AddParameterBlock(10); -// cost_function.SetNumResiduals(21); -// -// Under the hood, the implementation evaluates the cost function -// multiple times, computing a small set of the derivatives (four by -// default, controlled by the Stride template parameter) with each -// pass. There is a tradeoff with the size of the passes; you may want -// to experiment with the stride. - -#ifndef CERES_PUBLIC_DYNAMIC_AUTODIFF_COST_FUNCTION_H_ -#define CERES_PUBLIC_DYNAMIC_AUTODIFF_COST_FUNCTION_H_ - -#include <cmath> -#include <numeric> -#include <vector> - -#include "ceres/cost_function.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/jet.h" -#include "glog/logging.h" - -namespace ceres { - -template <typename CostFunctor, int Stride = 4> -class DynamicAutoDiffCostFunction : public CostFunction { - public: - explicit DynamicAutoDiffCostFunction(CostFunctor* functor) - : functor_(functor) {} - - virtual ~DynamicAutoDiffCostFunction() {} - - void AddParameterBlock(int size) { - mutable_parameter_block_sizes()->push_back(size); - } - - void SetNumResiduals(int num_residuals) { - set_num_residuals(num_residuals); - } - - virtual bool Evaluate(double const* const* parameters, - double* residuals, - double** jacobians) const { - CHECK_GT(num_residuals(), 0) - << "You must call DynamicAutoDiffCostFunction::SetNumResiduals() " - << "before DynamicAutoDiffCostFunction::Evaluate()."; - - if (jacobians == NULL) { - return (*functor_)(parameters, residuals); - } - - // The difficulty with Jets, as implemented in Ceres, is that they were - // originally designed for strictly compile-sized use. At this point, there - // is a large body of code that assumes inside a cost functor it is - // acceptable to do e.g. T(1.5) and get an appropriately sized jet back. - // - // Unfortunately, it is impossible to communicate the expected size of a - // dynamically sized jet to the static instantiations that existing code - // depends on. - // - // To work around this issue, the solution here is to evaluate the - // jacobians in a series of passes, each one computing Stripe * - // num_residuals() derivatives. This is done with small, fixed-size jets. - const int num_parameter_blocks = parameter_block_sizes().size(); - const int num_parameters = std::accumulate(parameter_block_sizes().begin(), - parameter_block_sizes().end(), - 0); - - // Allocate scratch space for the strided evaluation. - std::vector<Jet<double, Stride> > input_jets(num_parameters); - std::vector<Jet<double, Stride> > output_jets(num_residuals()); - - // Make the parameter pack that is sent to the functor (reused). - std::vector<Jet<double, Stride>* > jet_parameters(num_parameter_blocks, - static_cast<Jet<double, Stride>* >(NULL)); - int num_active_parameters = 0; - - // To handle constant parameters between non-constant parameter blocks, the - // start position --- a raw parameter index --- of each contiguous block of - // non-constant parameters is recorded in start_derivative_section. - std::vector<int> start_derivative_section; - bool in_derivative_section = false; - int parameter_cursor = 0; - - // Discover the derivative sections and set the parameter values. - for (int i = 0; i < num_parameter_blocks; ++i) { - jet_parameters[i] = &input_jets[parameter_cursor]; - - const int parameter_block_size = parameter_block_sizes()[i]; - if (jacobians[i] != NULL) { - if (!in_derivative_section) { - start_derivative_section.push_back(parameter_cursor); - in_derivative_section = true; - } - - num_active_parameters += parameter_block_size; - } else { - in_derivative_section = false; - } - - for (int j = 0; j < parameter_block_size; ++j, parameter_cursor++) { - input_jets[parameter_cursor].a = parameters[i][j]; - } - } - - // When `num_active_parameters % Stride != 0` then it can be the case - // that `active_parameter_count < Stride` while parameter_cursor is less - // than the total number of parameters and with no remaining non-constant - // parameter blocks. Pushing parameter_cursor (the total number of - // parameters) as a final entry to start_derivative_section is required - // because if a constant parameter block is encountered after the - // last non-constant block then current_derivative_section is incremented - // and would otherwise index an invalid position in - // start_derivative_section. Setting the final element to the total number - // of parameters means that this can only happen at most once in the loop - // below. - start_derivative_section.push_back(parameter_cursor); - - // Evaluate all of the strides. Each stride is a chunk of the derivative to - // evaluate, typically some size proportional to the size of the SIMD - // registers of the CPU. - int num_strides = static_cast<int>(ceil(num_active_parameters / - static_cast<float>(Stride))); - - int current_derivative_section = 0; - int current_derivative_section_cursor = 0; - - for (int pass = 0; pass < num_strides; ++pass) { - // Set most of the jet components to zero, except for - // non-constant #Stride parameters. - const int initial_derivative_section = current_derivative_section; - const int initial_derivative_section_cursor = - current_derivative_section_cursor; - - int active_parameter_count = 0; - parameter_cursor = 0; - - for (int i = 0; i < num_parameter_blocks; ++i) { - for (int j = 0; j < parameter_block_sizes()[i]; - ++j, parameter_cursor++) { - input_jets[parameter_cursor].v.setZero(); - if (active_parameter_count < Stride && - parameter_cursor >= ( - start_derivative_section[current_derivative_section] + - current_derivative_section_cursor)) { - if (jacobians[i] != NULL) { - input_jets[parameter_cursor].v[active_parameter_count] = 1.0; - ++active_parameter_count; - ++current_derivative_section_cursor; - } else { - ++current_derivative_section; - current_derivative_section_cursor = 0; - } - } - } - } - - if (!(*functor_)(&jet_parameters[0], &output_jets[0])) { - return false; - } - - // Copy the pieces of the jacobians into their final place. - active_parameter_count = 0; - - current_derivative_section = initial_derivative_section; - current_derivative_section_cursor = initial_derivative_section_cursor; - - for (int i = 0, parameter_cursor = 0; i < num_parameter_blocks; ++i) { - for (int j = 0; j < parameter_block_sizes()[i]; - ++j, parameter_cursor++) { - if (active_parameter_count < Stride && - parameter_cursor >= ( - start_derivative_section[current_derivative_section] + - current_derivative_section_cursor)) { - if (jacobians[i] != NULL) { - for (int k = 0; k < num_residuals(); ++k) { - jacobians[i][k * parameter_block_sizes()[i] + j] = - output_jets[k].v[active_parameter_count]; - } - ++active_parameter_count; - ++current_derivative_section_cursor; - } else { - ++current_derivative_section; - current_derivative_section_cursor = 0; - } - } - } - } - - // Only copy the residuals over once (even though we compute them on - // every loop). - if (pass == num_strides - 1) { - for (int k = 0; k < num_residuals(); ++k) { - residuals[k] = output_jets[k].a; - } - } - } - return true; - } - - private: - internal::scoped_ptr<CostFunctor> functor_; -}; - -} // namespace ceres - -#endif // CERES_PUBLIC_DYNAMIC_AUTODIFF_COST_FUNCTION_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/dynamic_cost_function_to_functor.h b/extern/libmv/third_party/ceres/include/ceres/dynamic_cost_function_to_functor.h deleted file mode 100644 index 9339a503ea0..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/dynamic_cost_function_to_functor.h +++ /dev/null @@ -1,190 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// dgossow@google.com (David Gossow) -// -// DynamicCostFunctionToFunctor allows users to use CostFunction -// objects in templated functors which are to be used for automatic -// differentiation. It works similar to CostFunctionToFunctor, with the -// difference that it allows you to wrap a cost function with dynamic numbers -// of parameters and residuals. -// -// For example, let us assume that -// -// class IntrinsicProjection : public CostFunction { -// public: -// IntrinsicProjection(const double* observation); -// virtual bool Evaluate(double const* const* parameters, -// double* residuals, -// double** jacobians) const; -// }; -// -// is a cost function that implements the projection of a point in its -// local coordinate system onto its image plane and subtracts it from -// the observed point projection. It can compute its residual and -// either via analytic or numerical differentiation can compute its -// jacobians. The intrinsics are passed in as parameters[0] and the point as -// parameters[1]. -// -// Now we would like to compose the action of this CostFunction with -// the action of camera extrinsics, i.e., rotation and -// translation. Say we have a templated function -// -// template<typename T> -// void RotateAndTranslatePoint(double const* const* parameters, -// double* residuals); -// -// Then we can now do the following, -// -// struct CameraProjection { -// CameraProjection(const double* observation) -// : intrinsic_projection_.(new IntrinsicProjection(observation)) { -// } -// template <typename T> -// bool operator()(T const* const* parameters, -// T* residual) const { -// const T* rotation = parameters[0]; -// const T* translation = parameters[1]; -// const T* intrinsics = parameters[2]; -// const T* point = parameters[3]; -// T transformed_point[3]; -// RotateAndTranslatePoint(rotation, translation, point, transformed_point); -// -// // Note that we call intrinsic_projection_, just like it was -// // any other templated functor. -// const T* projection_parameters[2]; -// projection_parameters[0] = intrinsics; -// projection_parameters[1] = transformed_point; -// return intrinsic_projection_(projection_parameters, residual); -// } -// -// private: -// DynamicCostFunctionToFunctor intrinsic_projection_; -// }; - -#ifndef CERES_PUBLIC_DYNAMIC_COST_FUNCTION_TO_FUNCTOR_H_ -#define CERES_PUBLIC_DYNAMIC_COST_FUNCTION_TO_FUNCTOR_H_ - -#include <numeric> -#include <vector> - -#include "ceres/cost_function.h" -#include "ceres/internal/fixed_array.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" - -namespace ceres { - -class DynamicCostFunctionToFunctor { - public: - // Takes ownership of cost_function. - explicit DynamicCostFunctionToFunctor(CostFunction* cost_function) - : cost_function_(cost_function) { - CHECK_NOTNULL(cost_function); - } - - bool operator()(double const* const* parameters, double* residuals) const { - return cost_function_->Evaluate(parameters, residuals, NULL); - } - - template <typename JetT> - bool operator()(JetT const* const* inputs, JetT* output) const { - const std::vector<int32>& parameter_block_sizes = - cost_function_->parameter_block_sizes(); - const int num_parameter_blocks = parameter_block_sizes.size(); - const int num_residuals = cost_function_->num_residuals(); - const int num_parameters = std::accumulate(parameter_block_sizes.begin(), - parameter_block_sizes.end(), 0); - - internal::FixedArray<double> parameters(num_parameters); - internal::FixedArray<double*> parameter_blocks(num_parameter_blocks); - internal::FixedArray<double> jacobians(num_residuals * num_parameters); - internal::FixedArray<double*> jacobian_blocks(num_parameter_blocks); - internal::FixedArray<double> residuals(num_residuals); - - // Build a set of arrays to get the residuals and jacobians from - // the CostFunction wrapped by this functor. - double* parameter_ptr = parameters.get(); - double* jacobian_ptr = jacobians.get(); - for (int i = 0; i < num_parameter_blocks; ++i) { - parameter_blocks[i] = parameter_ptr; - jacobian_blocks[i] = jacobian_ptr; - for (int j = 0; j < parameter_block_sizes[i]; ++j) { - *parameter_ptr++ = inputs[i][j].a; - } - jacobian_ptr += num_residuals * parameter_block_sizes[i]; - } - - if (!cost_function_->Evaluate(parameter_blocks.get(), - residuals.get(), - jacobian_blocks.get())) { - return false; - } - - // Now that we have the incoming Jets, which are carrying the - // partial derivatives of each of the inputs w.r.t to some other - // underlying parameters. The derivative of the outputs of the - // cost function w.r.t to the same underlying parameters can now - // be computed by applying the chain rule. - // - // d output[i] d output[i] d input[j] - // -------------- = sum_j ----------- * ------------ - // d parameter[k] d input[j] d parameter[k] - // - // d input[j] - // -------------- = inputs[j], so - // d parameter[k] - // - // outputJet[i] = sum_k jacobian[i][k] * inputJet[k] - // - // The following loop, iterates over the residuals, computing one - // output jet at a time. - for (int i = 0; i < num_residuals; ++i) { - output[i].a = residuals[i]; - output[i].v.setZero(); - - for (int j = 0; j < num_parameter_blocks; ++j) { - const int32 block_size = parameter_block_sizes[j]; - for (int k = 0; k < parameter_block_sizes[j]; ++k) { - output[i].v += - jacobian_blocks[j][i * block_size + k] * inputs[j][k].v; - } - } - } - - return true; - } - - private: - internal::scoped_ptr<CostFunction> cost_function_; -}; - -} // namespace ceres - -#endif // CERES_PUBLIC_DYNAMIC_COST_FUNCTION_TO_FUNCTOR_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/dynamic_numeric_diff_cost_function.h b/extern/libmv/third_party/ceres/include/ceres/dynamic_numeric_diff_cost_function.h deleted file mode 100644 index c852d57a3fc..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/dynamic_numeric_diff_cost_function.h +++ /dev/null @@ -1,205 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: mierle@gmail.com (Keir Mierle) -// sameeragarwal@google.com (Sameer Agarwal) -// thadh@gmail.com (Thad Hughes) -// tbennun@gmail.com (Tal Ben-Nun) -// -// This numeric diff implementation differs from the one found in -// numeric_diff_cost_function.h by supporting numericdiff on cost -// functions with variable numbers of parameters with variable -// sizes. With the other implementation, all the sizes (both the -// number of parameter blocks and the size of each block) must be -// fixed at compile time. -// -// The functor API differs slightly from the API for fixed size -// numeric diff; the expected interface for the cost functors is: -// -// struct MyCostFunctor { -// bool operator()(double const* const* parameters, double* residuals) const { -// // Use parameters[i] to access the i'th parameter block. -// } -// } -// -// Since the sizing of the parameters is done at runtime, you must -// also specify the sizes after creating the -// DynamicNumericDiffCostFunction. For example: -// -// DynamicAutoDiffCostFunction<MyCostFunctor, CENTRAL> cost_function( -// new MyCostFunctor()); -// cost_function.AddParameterBlock(5); -// cost_function.AddParameterBlock(10); -// cost_function.SetNumResiduals(21); - -#ifndef CERES_PUBLIC_DYNAMIC_NUMERIC_DIFF_COST_FUNCTION_H_ -#define CERES_PUBLIC_DYNAMIC_NUMERIC_DIFF_COST_FUNCTION_H_ - -#include <cmath> -#include <numeric> -#include <vector> - -#include "ceres/cost_function.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/numeric_diff.h" -#include "ceres/numeric_diff_options.h" -#include "glog/logging.h" - -namespace ceres { - -template <typename CostFunctor, NumericDiffMethodType method = CENTRAL> -class DynamicNumericDiffCostFunction : public CostFunction { - public: - explicit DynamicNumericDiffCostFunction( - const CostFunctor* functor, - Ownership ownership = TAKE_OWNERSHIP, - const NumericDiffOptions& options = NumericDiffOptions()) - : functor_(functor), - ownership_(ownership), - options_(options) { - } - - // Deprecated. New users should avoid using this constructor. Instead, use the - // constructor with NumericDiffOptions. - DynamicNumericDiffCostFunction( - const CostFunctor* functor, - Ownership ownership, - double relative_step_size) - : functor_(functor), - ownership_(ownership), - options_() { - LOG(WARNING) << "This constructor is deprecated and will be removed in " - "a future version. Please use the NumericDiffOptions " - "constructor instead."; - - options_.relative_step_size = relative_step_size; - } - - virtual ~DynamicNumericDiffCostFunction() { - if (ownership_ != TAKE_OWNERSHIP) { - functor_.release(); - } - } - - void AddParameterBlock(int size) { - mutable_parameter_block_sizes()->push_back(size); - } - - void SetNumResiduals(int num_residuals) { - set_num_residuals(num_residuals); - } - - virtual bool Evaluate(double const* const* parameters, - double* residuals, - double** jacobians) const { - using internal::NumericDiff; - CHECK_GT(num_residuals(), 0) - << "You must call DynamicNumericDiffCostFunction::SetNumResiduals() " - << "before DynamicNumericDiffCostFunction::Evaluate()."; - - const std::vector<int32>& block_sizes = parameter_block_sizes(); - CHECK(!block_sizes.empty()) - << "You must call DynamicNumericDiffCostFunction::AddParameterBlock() " - << "before DynamicNumericDiffCostFunction::Evaluate()."; - - const bool status = EvaluateCostFunctor(parameters, residuals); - if (jacobians == NULL || !status) { - return status; - } - - // Create local space for a copy of the parameters which will get mutated. - int parameters_size = accumulate(block_sizes.begin(), block_sizes.end(), 0); - std::vector<double> parameters_copy(parameters_size); - std::vector<double*> parameters_references_copy(block_sizes.size()); - parameters_references_copy[0] = ¶meters_copy[0]; - for (int block = 1; block < block_sizes.size(); ++block) { - parameters_references_copy[block] = parameters_references_copy[block - 1] - + block_sizes[block - 1]; - } - - // Copy the parameters into the local temp space. - for (int block = 0; block < block_sizes.size(); ++block) { - memcpy(parameters_references_copy[block], - parameters[block], - block_sizes[block] * sizeof(*parameters[block])); - } - - for (int block = 0; block < block_sizes.size(); ++block) { - if (jacobians[block] != NULL && - !NumericDiff<CostFunctor, method, DYNAMIC, - DYNAMIC, DYNAMIC, DYNAMIC, DYNAMIC, DYNAMIC, - DYNAMIC, DYNAMIC, DYNAMIC, DYNAMIC, DYNAMIC, - DYNAMIC, DYNAMIC>::EvaluateJacobianForParameterBlock( - functor_.get(), - residuals, - options_, - this->num_residuals(), - block, - block_sizes[block], - ¶meters_references_copy[0], - jacobians[block])) { - return false; - } - } - return true; - } - - private: - bool EvaluateCostFunctor(double const* const* parameters, - double* residuals) const { - return EvaluateCostFunctorImpl(functor_.get(), - parameters, - residuals, - functor_.get()); - } - - // Helper templates to allow evaluation of a functor or a - // CostFunction. - bool EvaluateCostFunctorImpl(const CostFunctor* functor, - double const* const* parameters, - double* residuals, - const void* /* NOT USED */) const { - return (*functor)(parameters, residuals); - } - - bool EvaluateCostFunctorImpl(const CostFunctor* functor, - double const* const* parameters, - double* residuals, - const CostFunction* /* NOT USED */) const { - return functor->Evaluate(parameters, residuals, NULL); - } - - internal::scoped_ptr<const CostFunctor> functor_; - Ownership ownership_; - NumericDiffOptions options_; -}; - -} // namespace ceres - -#endif // CERES_PUBLIC_DYNAMIC_AUTODIFF_COST_FUNCTION_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/fpclassify.h b/extern/libmv/third_party/ceres/include/ceres/fpclassify.h deleted file mode 100644 index bc2dc90026c..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/fpclassify.h +++ /dev/null @@ -1,70 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// Portable floating point classification. The names are picked such that they -// do not collide with macros. For example, "isnan" in C99 is a macro and hence -// does not respect namespaces. -// -// TODO(keir): Finish porting! - -#ifndef CERES_PUBLIC_FPCLASSIFY_H_ -#define CERES_PUBLIC_FPCLASSIFY_H_ - -#if defined(_MSC_VER) -#include <float.h> -#endif - -#include <limits> - -namespace ceres { - -#if defined(_MSC_VER) - -inline bool IsFinite (double x) { return _finite(x) != 0; } -inline bool IsInfinite(double x) { return _finite(x) == 0 && _isnan(x) == 0; } -inline bool IsNaN (double x) { return _isnan(x) != 0; } -inline bool IsNormal (double x) { // NOLINT - const int classification = _fpclass(x); - return (classification == _FPCLASS_NN || classification == _FPCLASS_PN); -} - -# else - -// These definitions are for the normal Unix suspects. -inline bool IsFinite (double x) { return std::isfinite(x); } -inline bool IsInfinite(double x) { return std::isinf(x); } -inline bool IsNaN (double x) { return std::isnan(x); } -inline bool IsNormal (double x) { return std::isnormal(x); } - -#endif - -} // namespace ceres - -#endif // CERES_PUBLIC_FPCLASSIFY_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/gradient_checker.h b/extern/libmv/third_party/ceres/include/ceres/gradient_checker.h deleted file mode 100644 index 28304159b44..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/gradient_checker.h +++ /dev/null @@ -1,222 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// Copyright 2007 Google Inc. All Rights Reserved. -// -// Author: wjr@google.com (William Rucklidge) -// -// This file contains a class that exercises a cost function, to make sure -// that it is computing reasonable derivatives. It compares the Jacobians -// computed by the cost function with those obtained by finite -// differences. - -#ifndef CERES_PUBLIC_GRADIENT_CHECKER_H_ -#define CERES_PUBLIC_GRADIENT_CHECKER_H_ - -#include <cstddef> -#include <algorithm> -#include <vector> - -#include "ceres/internal/eigen.h" -#include "ceres/internal/fixed_array.h" -#include "ceres/internal/macros.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/numeric_diff_cost_function.h" -#include "glog/logging.h" - -namespace ceres { - -// An object that exercises a cost function, to compare the answers that it -// gives with derivatives estimated using finite differencing. -// -// The only likely usage of this is for testing. -// -// How to use: Fill in an array of pointers to parameter blocks for your -// CostFunction, and then call Probe(). Check that the return value is -// 'true'. See prober_test.cc for an example. -// -// This is templated similarly to NumericDiffCostFunction, as it internally -// uses that. -template <typename CostFunctionToProbe, - int M = 0, int N0 = 0, int N1 = 0, int N2 = 0, int N3 = 0, int N4 = 0> -class GradientChecker { - public: - // Here we stash some results from the probe, for later - // inspection. - struct GradientCheckResults { - // Computed cost. - Vector cost; - - // The sizes of these matrices are dictated by the cost function's - // parameter and residual block sizes. Each vector's length will - // term->parameter_block_sizes().size(), and each matrix is the - // Jacobian of the residual with respect to the corresponding parameter - // block. - - // Derivatives as computed by the cost function. - std::vector<Matrix> term_jacobians; - - // Derivatives as computed by finite differencing. - std::vector<Matrix> finite_difference_jacobians; - - // Infinity-norm of term_jacobians - finite_difference_jacobians. - double error_jacobians; - }; - - // Checks the Jacobian computed by a cost function. - // - // probe_point: The parameter values at which to probe. - // error_tolerance: A threshold for the infinity-norm difference - // between the Jacobians. If the Jacobians differ by more than - // this amount, then the probe fails. - // - // term: The cost function to test. Not retained after this call returns. - // - // results: On return, the two Jacobians (and other information) - // will be stored here. May be NULL. - // - // Returns true if no problems are detected and the difference between the - // Jacobians is less than error_tolerance. - static bool Probe(double const* const* probe_point, - double error_tolerance, - CostFunctionToProbe *term, - GradientCheckResults* results) { - CHECK_NOTNULL(probe_point); - CHECK_NOTNULL(term); - LOG(INFO) << "-------------------- Starting Probe() --------------------"; - - // We need a GradientCheckeresults, whether or not they supplied one. - internal::scoped_ptr<GradientCheckResults> owned_results; - if (results == NULL) { - owned_results.reset(new GradientCheckResults); - results = owned_results.get(); - } - - // Do a consistency check between the term and the template parameters. - CHECK_EQ(M, term->num_residuals()); - const int num_residuals = M; - const std::vector<int32>& block_sizes = term->parameter_block_sizes(); - const int num_blocks = block_sizes.size(); - - CHECK_LE(num_blocks, 5) << "Unable to test functions that take more " - << "than 5 parameter blocks"; - if (N0) { - CHECK_EQ(N0, block_sizes[0]); - CHECK_GE(num_blocks, 1); - } else { - CHECK_LT(num_blocks, 1); - } - if (N1) { - CHECK_EQ(N1, block_sizes[1]); - CHECK_GE(num_blocks, 2); - } else { - CHECK_LT(num_blocks, 2); - } - if (N2) { - CHECK_EQ(N2, block_sizes[2]); - CHECK_GE(num_blocks, 3); - } else { - CHECK_LT(num_blocks, 3); - } - if (N3) { - CHECK_EQ(N3, block_sizes[3]); - CHECK_GE(num_blocks, 4); - } else { - CHECK_LT(num_blocks, 4); - } - if (N4) { - CHECK_EQ(N4, block_sizes[4]); - CHECK_GE(num_blocks, 5); - } else { - CHECK_LT(num_blocks, 5); - } - - results->term_jacobians.clear(); - results->term_jacobians.resize(num_blocks); - results->finite_difference_jacobians.clear(); - results->finite_difference_jacobians.resize(num_blocks); - - internal::FixedArray<double*> term_jacobian_pointers(num_blocks); - internal::FixedArray<double*> - finite_difference_jacobian_pointers(num_blocks); - for (int i = 0; i < num_blocks; i++) { - results->term_jacobians[i].resize(num_residuals, block_sizes[i]); - term_jacobian_pointers[i] = results->term_jacobians[i].data(); - results->finite_difference_jacobians[i].resize( - num_residuals, block_sizes[i]); - finite_difference_jacobian_pointers[i] = - results->finite_difference_jacobians[i].data(); - } - results->cost.resize(num_residuals, 1); - - CHECK(term->Evaluate(probe_point, results->cost.data(), - term_jacobian_pointers.get())); - NumericDiffCostFunction<CostFunctionToProbe, CENTRAL, M, N0, N1, N2, N3, N4> - numeric_term(term, DO_NOT_TAKE_OWNERSHIP); - CHECK(numeric_term.Evaluate(probe_point, results->cost.data(), - finite_difference_jacobian_pointers.get())); - - results->error_jacobians = 0; - for (int i = 0; i < num_blocks; i++) { - Matrix jacobian_difference = results->term_jacobians[i] - - results->finite_difference_jacobians[i]; - results->error_jacobians = - std::max(results->error_jacobians, - jacobian_difference.lpNorm<Eigen::Infinity>()); - } - - LOG(INFO) << "========== term-computed derivatives =========="; - for (int i = 0; i < num_blocks; i++) { - LOG(INFO) << "term_computed block " << i; - LOG(INFO) << "\n" << results->term_jacobians[i]; - } - - LOG(INFO) << "========== finite-difference derivatives =========="; - for (int i = 0; i < num_blocks; i++) { - LOG(INFO) << "finite_difference block " << i; - LOG(INFO) << "\n" << results->finite_difference_jacobians[i]; - } - - LOG(INFO) << "========== difference =========="; - for (int i = 0; i < num_blocks; i++) { - LOG(INFO) << "difference block " << i; - LOG(INFO) << (results->term_jacobians[i] - - results->finite_difference_jacobians[i]); - } - - LOG(INFO) << "||difference|| = " << results->error_jacobians; - - return results->error_jacobians < error_tolerance; - } - - private: - CERES_DISALLOW_IMPLICIT_CONSTRUCTORS(GradientChecker); -}; - -} // namespace ceres - -#endif // CERES_PUBLIC_GRADIENT_CHECKER_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/gradient_problem.h b/extern/libmv/third_party/ceres/include/ceres/gradient_problem.h deleted file mode 100644 index 1226a4cd895..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/gradient_problem.h +++ /dev/null @@ -1,127 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_PUBLIC_GRADIENT_PROBLEM_H_ -#define CERES_PUBLIC_GRADIENT_PROBLEM_H_ - -#include "ceres/internal/macros.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/local_parameterization.h" - -namespace ceres { - -class FirstOrderFunction; - -// Instances of GradientProblem represent general non-linear -// optimization problems that must be solved using just the value of -// the objective function and its gradient. Unlike the Problem class, -// which can only be used to model non-linear least squares problems, -// instances of GradientProblem not restricted in the form of the -// objective function. -// -// Structurally GradientProblem is a composition of a -// FirstOrderFunction and optionally a LocalParameterization. -// -// The FirstOrderFunction is responsible for evaluating the cost and -// gradient of the objective function. -// -// The LocalParameterization is responsible for going back and forth -// between the ambient space and the local tangent space. (See -// local_parameterization.h for more details). When a -// LocalParameterization is not provided, then the tangent space is -// assumed to coincide with the ambient Euclidean space that the -// gradient vector lives in. -// -// Example usage: -// -// The following demonstrate the problem construction for Rosenbrock's function -// -// f(x,y) = (1-x)^2 + 100(y - x^2)^2; -// -// class Rosenbrock : public ceres::FirstOrderFunction { -// public: -// virtual ~Rosenbrock() {} -// -// virtual bool Evaluate(const double* parameters, -// double* cost, -// double* gradient) const { -// const double x = parameters[0]; -// const double y = parameters[1]; -// -// cost[0] = (1.0 - x) * (1.0 - x) + 100.0 * (y - x * x) * (y - x * x); -// if (gradient != NULL) { -// gradient[0] = -2.0 * (1.0 - x) - 200.0 * (y - x * x) * 2.0 * x; -// gradient[1] = 200.0 * (y - x * x); -// } -// return true; -// }; -// -// virtual int NumParameters() const { return 2; }; -// }; -// -// ceres::GradientProblem problem(new Rosenbrock()); -class CERES_EXPORT GradientProblem { - public: - // Takes ownership of the function. - explicit GradientProblem(FirstOrderFunction* function); - - // Takes ownership of the function and the parameterization. - GradientProblem(FirstOrderFunction* function, - LocalParameterization* parameterization); - - int NumParameters() const; - int NumLocalParameters() const; - - // This call is not thread safe. - bool Evaluate(const double* parameters, double* cost, double* gradient) const; - bool Plus(const double* x, const double* delta, double* x_plus_delta) const; - - private: - internal::scoped_ptr<FirstOrderFunction> function_; - internal::scoped_ptr<LocalParameterization> parameterization_; - internal::scoped_array<double> scratch_; -}; - -// A FirstOrderFunction object implements the evaluation of a function -// and its gradient. -class CERES_EXPORT FirstOrderFunction { - public: - virtual ~FirstOrderFunction() {} - // cost is never NULL. gradient may be null. - virtual bool Evaluate(const double* const parameters, - double* cost, - double* gradient) const = 0; - virtual int NumParameters() const = 0; -}; - -} // namespace ceres - -#endif // CERES_PUBLIC_GRADIENT_PROBLEM_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/gradient_problem_solver.h b/extern/libmv/third_party/ceres/include/ceres/gradient_problem_solver.h deleted file mode 100644 index a7d0121ea0c..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/gradient_problem_solver.h +++ /dev/null @@ -1,357 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_PUBLIC_GRADIENT_PROBLEM_SOLVER_H_ -#define CERES_PUBLIC_GRADIENT_PROBLEM_SOLVER_H_ - -#include <cmath> -#include <string> -#include <vector> -#include "ceres/internal/macros.h" -#include "ceres/internal/port.h" -#include "ceres/iteration_callback.h" -#include "ceres/types.h" -#include "ceres/internal/disable_warnings.h" - -namespace ceres { - -class GradientProblem; - -class CERES_EXPORT GradientProblemSolver { - public: - virtual ~GradientProblemSolver(); - - // The options structure contains, not surprisingly, options that control how - // the solver operates. The defaults should be suitable for a wide range of - // problems; however, better performance is often obtainable with tweaking. - // - // The constants are defined inside types.h - struct CERES_EXPORT Options { - // Default constructor that sets up a generic sparse problem. - Options() { - line_search_direction_type = LBFGS; - line_search_type = WOLFE; - nonlinear_conjugate_gradient_type = FLETCHER_REEVES; - max_lbfgs_rank = 20; - use_approximate_eigenvalue_bfgs_scaling = false; - line_search_interpolation_type = CUBIC; - min_line_search_step_size = 1e-9; - line_search_sufficient_function_decrease = 1e-4; - max_line_search_step_contraction = 1e-3; - min_line_search_step_contraction = 0.6; - max_num_line_search_step_size_iterations = 20; - max_num_line_search_direction_restarts = 5; - line_search_sufficient_curvature_decrease = 0.9; - max_line_search_step_expansion = 10.0; - max_num_iterations = 50; - max_solver_time_in_seconds = 1e9; - function_tolerance = 1e-6; - gradient_tolerance = 1e-10; - logging_type = PER_MINIMIZER_ITERATION; - minimizer_progress_to_stdout = false; - } - - // Returns true if the options struct has a valid - // configuration. Returns false otherwise, and fills in *error - // with a message describing the problem. - bool IsValid(std::string* error) const; - - // Minimizer options ---------------------------------------- - LineSearchDirectionType line_search_direction_type; - LineSearchType line_search_type; - NonlinearConjugateGradientType nonlinear_conjugate_gradient_type; - - // The LBFGS hessian approximation is a low rank approximation to - // the inverse of the Hessian matrix. The rank of the - // approximation determines (linearly) the space and time - // complexity of using the approximation. Higher the rank, the - // better is the quality of the approximation. The increase in - // quality is however is bounded for a number of reasons. - // - // 1. The method only uses secant information and not actual - // derivatives. - // - // 2. The Hessian approximation is constrained to be positive - // definite. - // - // So increasing this rank to a large number will cost time and - // space complexity without the corresponding increase in solution - // quality. There are no hard and fast rules for choosing the - // maximum rank. The best choice usually requires some problem - // specific experimentation. - // - // For more theoretical and implementation details of the LBFGS - // method, please see: - // - // Nocedal, J. (1980). "Updating Quasi-Newton Matrices with - // Limited Storage". Mathematics of Computation 35 (151): 773–782. - int max_lbfgs_rank; - - // As part of the (L)BFGS update step (BFGS) / right-multiply step (L-BFGS), - // the initial inverse Hessian approximation is taken to be the Identity. - // However, Oren showed that using instead I * \gamma, where \gamma is - // chosen to approximate an eigenvalue of the true inverse Hessian can - // result in improved convergence in a wide variety of cases. Setting - // use_approximate_eigenvalue_bfgs_scaling to true enables this scaling. - // - // It is important to note that approximate eigenvalue scaling does not - // always improve convergence, and that it can in fact significantly degrade - // performance for certain classes of problem, which is why it is disabled - // by default. In particular it can degrade performance when the - // sensitivity of the problem to different parameters varies significantly, - // as in this case a single scalar factor fails to capture this variation - // and detrimentally downscales parts of the jacobian approximation which - // correspond to low-sensitivity parameters. It can also reduce the - // robustness of the solution to errors in the jacobians. - // - // Oren S.S., Self-scaling variable metric (SSVM) algorithms - // Part II: Implementation and experiments, Management Science, - // 20(5), 863-874, 1974. - bool use_approximate_eigenvalue_bfgs_scaling; - - // Degree of the polynomial used to approximate the objective - // function. Valid values are BISECTION, QUADRATIC and CUBIC. - // - // BISECTION corresponds to pure backtracking search with no - // interpolation. - LineSearchInterpolationType line_search_interpolation_type; - - // If during the line search, the step_size falls below this - // value, it is truncated to zero. - double min_line_search_step_size; - - // Line search parameters. - - // Solving the line search problem exactly is computationally - // prohibitive. Fortunately, line search based optimization - // algorithms can still guarantee convergence if instead of an - // exact solution, the line search algorithm returns a solution - // which decreases the value of the objective function - // sufficiently. More precisely, we are looking for a step_size - // s.t. - // - // f(step_size) <= f(0) + sufficient_decrease * f'(0) * step_size - // - double line_search_sufficient_function_decrease; - - // In each iteration of the line search, - // - // new_step_size >= max_line_search_step_contraction * step_size - // - // Note that by definition, for contraction: - // - // 0 < max_step_contraction < min_step_contraction < 1 - // - double max_line_search_step_contraction; - - // In each iteration of the line search, - // - // new_step_size <= min_line_search_step_contraction * step_size - // - // Note that by definition, for contraction: - // - // 0 < max_step_contraction < min_step_contraction < 1 - // - double min_line_search_step_contraction; - - // Maximum number of trial step size iterations during each line search, - // if a step size satisfying the search conditions cannot be found within - // this number of trials, the line search will terminate. - int max_num_line_search_step_size_iterations; - - // Maximum number of restarts of the line search direction algorithm before - // terminating the optimization. Restarts of the line search direction - // algorithm occur when the current algorithm fails to produce a new descent - // direction. This typically indicates a numerical failure, or a breakdown - // in the validity of the approximations used. - int max_num_line_search_direction_restarts; - - // The strong Wolfe conditions consist of the Armijo sufficient - // decrease condition, and an additional requirement that the - // step-size be chosen s.t. the _magnitude_ ('strong' Wolfe - // conditions) of the gradient along the search direction - // decreases sufficiently. Precisely, this second condition - // is that we seek a step_size s.t. - // - // |f'(step_size)| <= sufficient_curvature_decrease * |f'(0)| - // - // Where f() is the line search objective and f'() is the derivative - // of f w.r.t step_size (d f / d step_size). - double line_search_sufficient_curvature_decrease; - - // During the bracketing phase of the Wolfe search, the step size is - // increased until either a point satisfying the Wolfe conditions is - // found, or an upper bound for a bracket containing a point satisfying - // the conditions is found. Precisely, at each iteration of the - // expansion: - // - // new_step_size <= max_step_expansion * step_size. - // - // By definition for expansion, max_step_expansion > 1.0. - double max_line_search_step_expansion; - - // Maximum number of iterations for the minimizer to run for. - int max_num_iterations; - - // Maximum time for which the minimizer should run for. - double max_solver_time_in_seconds; - - // Minimizer terminates when - // - // (new_cost - old_cost) < function_tolerance * old_cost; - // - double function_tolerance; - - // Minimizer terminates when - // - // max_i |x - Project(Plus(x, -g(x))| < gradient_tolerance - // - // This value should typically be 1e-4 * function_tolerance. - double gradient_tolerance; - - // Logging options --------------------------------------------------------- - - LoggingType logging_type; - - // By default the Minimizer progress is logged to VLOG(1), which - // is sent to STDERR depending on the vlog level. If this flag is - // set to true, and logging_type is not SILENT, the logging output - // is sent to STDOUT. - bool minimizer_progress_to_stdout; - - // Callbacks that are executed at the end of each iteration of the - // Minimizer. An iteration may terminate midway, either due to - // numerical failures or because one of the convergence tests has - // been satisfied. In this case none of the callbacks are - // executed. - - // Callbacks are executed in the order that they are specified in - // this vector. By default, parameter blocks are updated only at - // the end of the optimization, i.e when the Minimizer - // terminates. This behaviour is controlled by - // update_state_every_variable. If the user wishes to have access - // to the update parameter blocks when his/her callbacks are - // executed, then set update_state_every_iteration to true. - // - // The solver does NOT take ownership of these pointers. - std::vector<IterationCallback*> callbacks; - }; - - struct CERES_EXPORT Summary { - Summary(); - - // A brief one line description of the state of the solver after - // termination. - std::string BriefReport() const; - - // A full multiline description of the state of the solver after - // termination. - std::string FullReport() const; - - bool IsSolutionUsable() const; - - // Minimizer summary ------------------------------------------------- - TerminationType termination_type; - - // Reason why the solver terminated. - std::string message; - - // Cost of the problem (value of the objective function) before - // the optimization. - double initial_cost; - - // Cost of the problem (value of the objective function) after the - // optimization. - double final_cost; - - // IterationSummary for each minimizer iteration in order. - std::vector<IterationSummary> iterations; - - // Sum total of all time spent inside Ceres when Solve is called. - double total_time_in_seconds; - - // Time (in seconds) spent evaluating the cost. - double cost_evaluation_time_in_seconds; - - // Time (in seconds) spent evaluating the gradient. - double gradient_evaluation_time_in_seconds; - - // Time (in seconds) spent minimizing the interpolating polynomial - // to compute the next candidate step size as part of a line search. - double line_search_polynomial_minimization_time_in_seconds; - - // Number of parameters in the probem. - int num_parameters; - - // Dimension of the tangent space of the problem. - int num_local_parameters; - - // Type of line search direction used. - LineSearchDirectionType line_search_direction_type; - - // Type of the line search algorithm used. - LineSearchType line_search_type; - - // When performing line search, the degree of the polynomial used - // to approximate the objective function. - LineSearchInterpolationType line_search_interpolation_type; - - // If the line search direction is NONLINEAR_CONJUGATE_GRADIENT, - // then this indicates the particular variant of non-linear - // conjugate gradient used. - NonlinearConjugateGradientType nonlinear_conjugate_gradient_type; - - // If the type of the line search direction is LBFGS, then this - // indicates the rank of the Hessian approximation. - int max_lbfgs_rank; - }; - - // Once a least squares problem has been built, this function takes - // the problem and optimizes it based on the values of the options - // parameters. Upon return, a detailed summary of the work performed - // by the preprocessor, the non-linear minmizer and the linear - // solver are reported in the summary object. - virtual void Solve(const GradientProblemSolver::Options& options, - const GradientProblem& problem, - double* parameters, - GradientProblemSolver::Summary* summary); -}; - -// Helper function which avoids going through the interface. -CERES_EXPORT void Solve(const GradientProblemSolver::Options& options, - const GradientProblem& problem, - double* parameters, - GradientProblemSolver::Summary* summary); - -} // namespace ceres - -#include "ceres/internal/reenable_warnings.h" - -#endif // CERES_PUBLIC_GRADIENT_PROBLEM_SOLVER_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/autodiff.h b/extern/libmv/third_party/ceres/include/ceres/internal/autodiff.h deleted file mode 100644 index 136152a36cd..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/internal/autodiff.h +++ /dev/null @@ -1,317 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// Computation of the Jacobian matrix for vector-valued functions of multiple -// variables, using automatic differentiation based on the implementation of -// dual numbers in jet.h. Before reading the rest of this file, it is adivsable -// to read jet.h's header comment in detail. -// -// The helper wrapper AutoDiff::Differentiate() computes the jacobian of -// functors with templated operator() taking this form: -// -// struct F { -// template<typename T> -// bool operator()(const T *x, const T *y, ..., T *z) { -// // Compute z[] based on x[], y[], ... -// // return true if computation succeeded, false otherwise. -// } -// }; -// -// All inputs and outputs may be vector-valued. -// -// To understand how jets are used to compute the jacobian, a -// picture may help. Consider a vector-valued function, F, returning 3 -// dimensions and taking a vector-valued parameter of 4 dimensions: -// -// y x -// [ * ] F [ * ] -// [ * ] <--- [ * ] -// [ * ] [ * ] -// [ * ] -// -// Similar to the 2-parameter example for f described in jet.h, computing the -// jacobian dy/dx is done by substutiting a suitable jet object for x and all -// intermediate steps of the computation of F. Since x is has 4 dimensions, use -// a Jet<double, 4>. -// -// Before substituting a jet object for x, the dual components are set -// appropriately for each dimension of x: -// -// y x -// [ * | * * * * ] f [ * | 1 0 0 0 ] x0 -// [ * | * * * * ] <--- [ * | 0 1 0 0 ] x1 -// [ * | * * * * ] [ * | 0 0 1 0 ] x2 -// ---+--- [ * | 0 0 0 1 ] x3 -// | ^ ^ ^ ^ -// dy/dx | | | +----- infinitesimal for x3 -// | | +------- infinitesimal for x2 -// | +--------- infinitesimal for x1 -// +----------- infinitesimal for x0 -// -// The reason to set the internal 4x4 submatrix to the identity is that we wish -// to take the derivative of y separately with respect to each dimension of x. -// Each column of the 4x4 identity is therefore for a single component of the -// independent variable x. -// -// Then the jacobian of the mapping, dy/dx, is the 3x4 sub-matrix of the -// extended y vector, indicated in the above diagram. -// -// Functors with multiple parameters -// --------------------------------- -// In practice, it is often convenient to use a function f of two or more -// vector-valued parameters, for example, x[3] and z[6]. Unfortunately, the jet -// framework is designed for a single-parameter vector-valued input. The wrapper -// in this file addresses this issue adding support for functions with one or -// more parameter vectors. -// -// To support multiple parameters, all the parameter vectors are concatenated -// into one and treated as a single parameter vector, except that since the -// functor expects different inputs, we need to construct the jets as if they -// were part of a single parameter vector. The extended jets are passed -// separately for each parameter. -// -// For example, consider a functor F taking two vector parameters, p[2] and -// q[3], and producing an output y[4]: -// -// struct F { -// template<typename T> -// bool operator()(const T *p, const T *q, T *z) { -// // ... -// } -// }; -// -// In this case, the necessary jet type is Jet<double, 5>. Here is a -// visualization of the jet objects in this case: -// -// Dual components for p ----+ -// | -// -+- -// y [ * | 1 0 | 0 0 0 ] --- p[0] -// [ * | 0 1 | 0 0 0 ] --- p[1] -// [ * | . . | + + + ] | -// [ * | . . | + + + ] v -// [ * | . . | + + + ] <--- F(p, q) -// [ * | . . | + + + ] ^ -// ^^^ ^^^^^ | -// dy/dp dy/dq [ * | 0 0 | 1 0 0 ] --- q[0] -// [ * | 0 0 | 0 1 0 ] --- q[1] -// [ * | 0 0 | 0 0 1 ] --- q[2] -// --+-- -// | -// Dual components for q --------------+ -// -// where the 4x2 submatrix (marked with ".") and 4x3 submatrix (marked with "+" -// of y in the above diagram are the derivatives of y with respect to p and q -// respectively. This is how autodiff works for functors taking multiple vector -// valued arguments (up to 6). -// -// Jacobian NULL pointers -// ---------------------- -// In general, the functions below will accept NULL pointers for all or some of -// the Jacobian parameters, meaning that those Jacobians will not be computed. - -#ifndef CERES_PUBLIC_INTERNAL_AUTODIFF_H_ -#define CERES_PUBLIC_INTERNAL_AUTODIFF_H_ - -#include <stddef.h> - -#include "ceres/jet.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/fixed_array.h" -#include "ceres/internal/variadic_evaluate.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -// Extends src by a 1st order pertubation for every dimension and puts it in -// dst. The size of src is N. Since this is also used for perturbations in -// blocked arrays, offset is used to shift which part of the jet the -// perturbation occurs. This is used to set up the extended x augmented by an -// identity matrix. The JetT type should be a Jet type, and T should be a -// numeric type (e.g. double). For example, -// -// 0 1 2 3 4 5 6 7 8 -// dst[0] [ * | . . | 1 0 0 | . . . ] -// dst[1] [ * | . . | 0 1 0 | . . . ] -// dst[2] [ * | . . | 0 0 1 | . . . ] -// -// is what would get put in dst if N was 3, offset was 3, and the jet type JetT -// was 8-dimensional. -template <typename JetT, typename T, int N> -inline void Make1stOrderPerturbation(int offset, const T* src, JetT* dst) { - DCHECK(src); - DCHECK(dst); - for (int j = 0; j < N; ++j) { - dst[j].a = src[j]; - dst[j].v.setZero(); - dst[j].v[offset + j] = T(1.0); - } -} - -// Takes the 0th order part of src, assumed to be a Jet type, and puts it in -// dst. This is used to pick out the "vector" part of the extended y. -template <typename JetT, typename T> -inline void Take0thOrderPart(int M, const JetT *src, T dst) { - DCHECK(src); - for (int i = 0; i < M; ++i) { - dst[i] = src[i].a; - } -} - -// Takes N 1st order parts, starting at index N0, and puts them in the M x N -// matrix 'dst'. This is used to pick out the "matrix" parts of the extended y. -template <typename JetT, typename T, int N0, int N> -inline void Take1stOrderPart(const int M, const JetT *src, T *dst) { - DCHECK(src); - DCHECK(dst); - for (int i = 0; i < M; ++i) { - Eigen::Map<Eigen::Matrix<T, N, 1> >(dst + N * i, N) = - src[i].v.template segment<N>(N0); - } -} - -// This is in a struct because default template parameters on a -// function are not supported in C++03 (though it is available in -// C++0x). N0 through N5 are the dimension of the input arguments to -// the user supplied functor. -template <typename Functor, typename T, - int N0 = 0, int N1 = 0, int N2 = 0, int N3 = 0, int N4 = 0, - int N5 = 0, int N6 = 0, int N7 = 0, int N8 = 0, int N9 = 0> -struct AutoDiff { - static bool Differentiate(const Functor& functor, - T const *const *parameters, - int num_outputs, - T *function_value, - T **jacobians) { - // This block breaks the 80 column rule to keep it somewhat readable. - DCHECK_GT(num_outputs, 0); - DCHECK((!N1 && !N2 && !N3 && !N4 && !N5 && !N6 && !N7 && !N8 && !N9) || - ((N1 > 0) && !N2 && !N3 && !N4 && !N5 && !N6 && !N7 && !N8 && !N9) || - ((N1 > 0) && (N2 > 0) && !N3 && !N4 && !N5 && !N6 && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && !N4 && !N5 && !N6 && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && !N5 && !N6 && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && !N6 && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && (N6 > 0) && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && (N6 > 0) && (N7 > 0) && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && (N6 > 0) && (N7 > 0) && (N8 > 0) && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && (N6 > 0) && (N7 > 0) && (N8 > 0) && (N9 > 0))) // NOLINT - << "Zero block cannot precede a non-zero block. Block sizes are " - << "(ignore trailing 0s): " << N0 << ", " << N1 << ", " << N2 << ", " - << N3 << ", " << N4 << ", " << N5 << ", " << N6 << ", " << N7 << ", " - << N8 << ", " << N9; - - typedef Jet<T, N0 + N1 + N2 + N3 + N4 + N5 + N6 + N7 + N8 + N9> JetT; - FixedArray<JetT, (256 * 7) / sizeof(JetT)> x( - N0 + N1 + N2 + N3 + N4 + N5 + N6 + N7 + N8 + N9 + num_outputs); - - // These are the positions of the respective jets in the fixed array x. - const int jet0 = 0; - const int jet1 = N0; - const int jet2 = N0 + N1; - const int jet3 = N0 + N1 + N2; - const int jet4 = N0 + N1 + N2 + N3; - const int jet5 = N0 + N1 + N2 + N3 + N4; - const int jet6 = N0 + N1 + N2 + N3 + N4 + N5; - const int jet7 = N0 + N1 + N2 + N3 + N4 + N5 + N6; - const int jet8 = N0 + N1 + N2 + N3 + N4 + N5 + N6 + N7; - const int jet9 = N0 + N1 + N2 + N3 + N4 + N5 + N6 + N7 + N8; - - const JetT *unpacked_parameters[10] = { - x.get() + jet0, - x.get() + jet1, - x.get() + jet2, - x.get() + jet3, - x.get() + jet4, - x.get() + jet5, - x.get() + jet6, - x.get() + jet7, - x.get() + jet8, - x.get() + jet9, - }; - - JetT* output = x.get() + N0 + N1 + N2 + N3 + N4 + N5 + N6 + N7 + N8 + N9; - -#define CERES_MAKE_1ST_ORDER_PERTURBATION(i) \ - if (N ## i) { \ - internal::Make1stOrderPerturbation<JetT, T, N ## i>( \ - jet ## i, \ - parameters[i], \ - x.get() + jet ## i); \ - } - CERES_MAKE_1ST_ORDER_PERTURBATION(0); - CERES_MAKE_1ST_ORDER_PERTURBATION(1); - CERES_MAKE_1ST_ORDER_PERTURBATION(2); - CERES_MAKE_1ST_ORDER_PERTURBATION(3); - CERES_MAKE_1ST_ORDER_PERTURBATION(4); - CERES_MAKE_1ST_ORDER_PERTURBATION(5); - CERES_MAKE_1ST_ORDER_PERTURBATION(6); - CERES_MAKE_1ST_ORDER_PERTURBATION(7); - CERES_MAKE_1ST_ORDER_PERTURBATION(8); - CERES_MAKE_1ST_ORDER_PERTURBATION(9); -#undef CERES_MAKE_1ST_ORDER_PERTURBATION - - if (!VariadicEvaluate<Functor, JetT, - N0, N1, N2, N3, N4, N5, N6, N7, N8, N9>::Call( - functor, unpacked_parameters, output)) { - return false; - } - - internal::Take0thOrderPart(num_outputs, output, function_value); - -#define CERES_TAKE_1ST_ORDER_PERTURBATION(i) \ - if (N ## i) { \ - if (jacobians[i]) { \ - internal::Take1stOrderPart<JetT, T, \ - jet ## i, \ - N ## i>(num_outputs, \ - output, \ - jacobians[i]); \ - } \ - } - CERES_TAKE_1ST_ORDER_PERTURBATION(0); - CERES_TAKE_1ST_ORDER_PERTURBATION(1); - CERES_TAKE_1ST_ORDER_PERTURBATION(2); - CERES_TAKE_1ST_ORDER_PERTURBATION(3); - CERES_TAKE_1ST_ORDER_PERTURBATION(4); - CERES_TAKE_1ST_ORDER_PERTURBATION(5); - CERES_TAKE_1ST_ORDER_PERTURBATION(6); - CERES_TAKE_1ST_ORDER_PERTURBATION(7); - CERES_TAKE_1ST_ORDER_PERTURBATION(8); - CERES_TAKE_1ST_ORDER_PERTURBATION(9); -#undef CERES_TAKE_1ST_ORDER_PERTURBATION - return true; - } -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_PUBLIC_INTERNAL_AUTODIFF_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/disable_warnings.h b/extern/libmv/third_party/ceres/include/ceres/internal/disable_warnings.h deleted file mode 100644 index 094124f7159..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/internal/disable_warnings.h +++ /dev/null @@ -1,44 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// This file has the sole purpose to silence warnings when including Ceres. - -// This is not your usual header guard. The macro CERES_WARNINGS_DISABLED -// shows up again in reenable_warnings.h. -#ifndef CERES_WARNINGS_DISABLED -#define CERES_WARNINGS_DISABLED - -#ifdef _MSC_VER -#pragma warning( push ) -// Disable the warning C4251 which is trigerred by stl classes in -// Ceres' public interface. To quote MSDN: "C4251 can be ignored " -// "if you are deriving from a type in the Standard C++ Library" -#pragma warning( disable : 4251 ) -#endif - -#endif // CERES_WARNINGS_DISABLED diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/eigen.h b/extern/libmv/third_party/ceres/include/ceres/internal/eigen.h deleted file mode 100644 index 7138804ace4..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/internal/eigen.h +++ /dev/null @@ -1,93 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_EIGEN_H_ -#define CERES_INTERNAL_EIGEN_H_ - -#include "Eigen/Core" - -namespace ceres { - -typedef Eigen::Matrix<double, Eigen::Dynamic, 1> Vector; -typedef Eigen::Matrix<double, - Eigen::Dynamic, - Eigen::Dynamic, - Eigen::RowMajor> Matrix; -typedef Eigen::Map<Vector> VectorRef; -typedef Eigen::Map<Matrix> MatrixRef; -typedef Eigen::Map<const Vector> ConstVectorRef; -typedef Eigen::Map<const Matrix> ConstMatrixRef; - -// Column major matrices for DenseSparseMatrix/DenseQRSolver -typedef Eigen::Matrix<double, - Eigen::Dynamic, - Eigen::Dynamic, - Eigen::ColMajor> ColMajorMatrix; - -typedef Eigen::Map<ColMajorMatrix, 0, - Eigen::Stride<Eigen::Dynamic, 1> > ColMajorMatrixRef; - -typedef Eigen::Map<const ColMajorMatrix, - 0, - Eigen::Stride<Eigen::Dynamic, 1> > ConstColMajorMatrixRef; - - - -// C++ does not support templated typdefs, thus the need for this -// struct so that we can support statically sized Matrix and Maps. -template <int num_rows = Eigen::Dynamic, int num_cols = Eigen::Dynamic> -struct EigenTypes { - typedef Eigen::Matrix <double, num_rows, num_cols, Eigen::RowMajor> - Matrix; - - typedef Eigen::Map< - Eigen::Matrix<double, num_rows, num_cols, Eigen::RowMajor> > - MatrixRef; - - typedef Eigen::Matrix <double, num_rows, 1> - Vector; - - typedef Eigen::Map < - Eigen::Matrix<double, num_rows, 1> > - VectorRef; - - - typedef Eigen::Map< - const Eigen::Matrix<double, num_rows, num_cols, Eigen::RowMajor> > - ConstMatrixRef; - - typedef Eigen::Map < - const Eigen::Matrix<double, num_rows, 1> > - ConstVectorRef; -}; - -} // namespace ceres - -#endif // CERES_INTERNAL_EIGEN_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/fixed_array.h b/extern/libmv/third_party/ceres/include/ceres/internal/fixed_array.h deleted file mode 100644 index 387298c58d0..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/internal/fixed_array.h +++ /dev/null @@ -1,191 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: rennie@google.com (Jeffrey Rennie) -// Author: sanjay@google.com (Sanjay Ghemawat) -- renamed to FixedArray - -#ifndef CERES_PUBLIC_INTERNAL_FIXED_ARRAY_H_ -#define CERES_PUBLIC_INTERNAL_FIXED_ARRAY_H_ - -#include <cstddef> -#include "Eigen/Core" -#include "ceres/internal/macros.h" -#include "ceres/internal/manual_constructor.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -// A FixedArray<T> represents a non-resizable array of T where the -// length of the array does not need to be a compile time constant. -// -// FixedArray allocates small arrays inline, and large arrays on -// the heap. It is a good replacement for non-standard and deprecated -// uses of alloca() and variable length arrays (a GCC extension). -// -// FixedArray keeps performance fast for small arrays, because it -// avoids heap operations. It also helps reduce the chances of -// accidentally overflowing your stack if large input is passed to -// your function. -// -// Also, FixedArray is useful for writing portable code. Not all -// compilers support arrays of dynamic size. - -// Most users should not specify an inline_elements argument and let -// FixedArray<> automatically determine the number of elements -// to store inline based on sizeof(T). -// -// If inline_elements is specified, the FixedArray<> implementation -// will store arrays of length <= inline_elements inline. -// -// Finally note that unlike vector<T> FixedArray<T> will not zero-initialize -// simple types like int, double, bool, etc. -// -// Non-POD types will be default-initialized just like regular vectors or -// arrays. - -#if defined(_WIN64) - typedef __int64 ssize_t; -#elif defined(_WIN32) - typedef __int32 ssize_t; -#endif - -template <typename T, ssize_t inline_elements = -1> -class FixedArray { - public: - // For playing nicely with stl: - typedef T value_type; - typedef T* iterator; - typedef T const* const_iterator; - typedef T& reference; - typedef T const& const_reference; - typedef T* pointer; - typedef std::ptrdiff_t difference_type; - typedef size_t size_type; - - // REQUIRES: n >= 0 - // Creates an array object that can store "n" elements. - // - // FixedArray<T> will not zero-initialiaze POD (simple) types like int, - // double, bool, etc. - // Non-POD types will be default-initialized just like regular vectors or - // arrays. - explicit FixedArray(size_type n); - - // Releases any resources. - ~FixedArray(); - - // Returns the length of the array. - inline size_type size() const { return size_; } - - // Returns the memory size of the array in bytes. - inline size_t memsize() const { return size_ * sizeof(T); } - - // Returns a pointer to the underlying element array. - inline const T* get() const { return &array_[0].element; } - inline T* get() { return &array_[0].element; } - - // REQUIRES: 0 <= i < size() - // Returns a reference to the "i"th element. - inline T& operator[](size_type i) { - DCHECK_LT(i, size_); - return array_[i].element; - } - - // REQUIRES: 0 <= i < size() - // Returns a reference to the "i"th element. - inline const T& operator[](size_type i) const { - DCHECK_LT(i, size_); - return array_[i].element; - } - - inline iterator begin() { return &array_[0].element; } - inline iterator end() { return &array_[size_].element; } - - inline const_iterator begin() const { return &array_[0].element; } - inline const_iterator end() const { return &array_[size_].element; } - - private: - // Container to hold elements of type T. This is necessary to handle - // the case where T is a a (C-style) array. The size of InnerContainer - // and T must be the same, otherwise callers' assumptions about use - // of this code will be broken. - struct InnerContainer { - T element; - }; - - // How many elements should we store inline? - // a. If not specified, use a default of 256 bytes (256 bytes - // seems small enough to not cause stack overflow or unnecessary - // stack pollution, while still allowing stack allocation for - // reasonably long character arrays. - // b. Never use 0 length arrays (not ISO C++) - static const size_type S1 = ((inline_elements < 0) - ? (256/sizeof(T)) : inline_elements); - static const size_type S2 = (S1 <= 0) ? 1 : S1; - static const size_type kInlineElements = S2; - - size_type const size_; - InnerContainer* const array_; - - // Allocate some space, not an array of elements of type T, so that we can - // skip calling the T constructors and destructors for space we never use. - ManualConstructor<InnerContainer> inline_space_[kInlineElements]; -}; - -// Implementation details follow - -template <class T, ssize_t S> -inline FixedArray<T, S>::FixedArray(typename FixedArray<T, S>::size_type n) - : size_(n), - array_((n <= kInlineElements - ? reinterpret_cast<InnerContainer*>(inline_space_) - : new InnerContainer[n])) { - // Construct only the elements actually used. - if (array_ == reinterpret_cast<InnerContainer*>(inline_space_)) { - for (size_t i = 0; i != size_; ++i) { - inline_space_[i].Init(); - } - } -} - -template <class T, ssize_t S> -inline FixedArray<T, S>::~FixedArray() { - if (array_ != reinterpret_cast<InnerContainer*>(inline_space_)) { - delete[] array_; - } else { - for (size_t i = 0; i != size_; ++i) { - inline_space_[i].Destroy(); - } - } -} - -} // namespace internal -} // namespace ceres - -#endif // CERES_PUBLIC_INTERNAL_FIXED_ARRAY_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/macros.h b/extern/libmv/third_party/ceres/include/ceres/internal/macros.h deleted file mode 100644 index bebb965e25b..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/internal/macros.h +++ /dev/null @@ -1,170 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// -// Various Google-specific macros. -// -// This code is compiled directly on many platforms, including client -// platforms like Windows, Mac, and embedded systems. Before making -// any changes here, make sure that you're not breaking any platforms. - -#ifndef CERES_PUBLIC_INTERNAL_MACROS_H_ -#define CERES_PUBLIC_INTERNAL_MACROS_H_ - -#include <cstddef> // For size_t. - -// A macro to disallow the copy constructor and operator= functions -// This should be used in the private: declarations for a class -// -// For disallowing only assign or copy, write the code directly, but declare -// the intend in a comment, for example: -// -// void operator=(const TypeName&); // _DISALLOW_ASSIGN - -// Note, that most uses of CERES_DISALLOW_ASSIGN and CERES_DISALLOW_COPY -// are broken semantically, one should either use disallow both or -// neither. Try to avoid these in new code. -#define CERES_DISALLOW_COPY_AND_ASSIGN(TypeName) \ - TypeName(const TypeName&); \ - void operator=(const TypeName&) - -// A macro to disallow all the implicit constructors, namely the -// default constructor, copy constructor and operator= functions. -// -// This should be used in the private: declarations for a class -// that wants to prevent anyone from instantiating it. This is -// especially useful for classes containing only static methods. -#define CERES_DISALLOW_IMPLICIT_CONSTRUCTORS(TypeName) \ - TypeName(); \ - CERES_DISALLOW_COPY_AND_ASSIGN(TypeName) - -// The arraysize(arr) macro returns the # of elements in an array arr. -// The expression is a compile-time constant, and therefore can be -// used in defining new arrays, for example. If you use arraysize on -// a pointer by mistake, you will get a compile-time error. -// -// One caveat is that arraysize() doesn't accept any array of an -// anonymous type or a type defined inside a function. In these rare -// cases, you have to use the unsafe ARRAYSIZE() macro below. This is -// due to a limitation in C++'s template system. The limitation might -// eventually be removed, but it hasn't happened yet. - -// This template function declaration is used in defining arraysize. -// Note that the function doesn't need an implementation, as we only -// use its type. -template <typename T, size_t N> -char (&ArraySizeHelper(T (&array)[N]))[N]; - -// That gcc wants both of these prototypes seems mysterious. VC, for -// its part, can't decide which to use (another mystery). Matching of -// template overloads: the final frontier. -#ifndef _WIN32 -template <typename T, size_t N> -char (&ArraySizeHelper(const T (&array)[N]))[N]; -#endif - -#define arraysize(array) (sizeof(ArraySizeHelper(array))) - -// ARRAYSIZE performs essentially the same calculation as arraysize, -// but can be used on anonymous types or types defined inside -// functions. It's less safe than arraysize as it accepts some -// (although not all) pointers. Therefore, you should use arraysize -// whenever possible. -// -// The expression ARRAYSIZE(a) is a compile-time constant of type -// size_t. -// -// ARRAYSIZE catches a few type errors. If you see a compiler error -// -// "warning: division by zero in ..." -// -// when using ARRAYSIZE, you are (wrongfully) giving it a pointer. -// You should only use ARRAYSIZE on statically allocated arrays. -// -// The following comments are on the implementation details, and can -// be ignored by the users. -// -// ARRAYSIZE(arr) works by inspecting sizeof(arr) (the # of bytes in -// the array) and sizeof(*(arr)) (the # of bytes in one array -// element). If the former is divisible by the latter, perhaps arr is -// indeed an array, in which case the division result is the # of -// elements in the array. Otherwise, arr cannot possibly be an array, -// and we generate a compiler error to prevent the code from -// compiling. -// -// Since the size of bool is implementation-defined, we need to cast -// !(sizeof(a) & sizeof(*(a))) to size_t in order to ensure the final -// result has type size_t. -// -// This macro is not perfect as it wrongfully accepts certain -// pointers, namely where the pointer size is divisible by the pointee -// size. Since all our code has to go through a 32-bit compiler, -// where a pointer is 4 bytes, this means all pointers to a type whose -// size is 3 or greater than 4 will be (righteously) rejected. -// -// Kudos to Jorg Brown for this simple and elegant implementation. -// -// - wan 2005-11-16 -// -// Starting with Visual C++ 2005, WinNT.h includes ARRAYSIZE. However, -// the definition comes from the over-broad windows.h header that -// introduces a macro, ERROR, that conflicts with the logging framework -// that Ceres uses. Instead, rename ARRAYSIZE to CERES_ARRAYSIZE. -#define CERES_ARRAYSIZE(a) \ - ((sizeof(a) / sizeof(*(a))) / \ - static_cast<size_t>(!(sizeof(a) % sizeof(*(a))))) - -// Tell the compiler to warn about unused return values for functions -// declared with this macro. The macro should be used on function -// declarations following the argument list: -// -// Sprocket* AllocateSprocket() MUST_USE_RESULT; -// -#if (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)) \ - && !defined(COMPILER_ICC) -#define CERES_MUST_USE_RESULT __attribute__ ((warn_unused_result)) -#else -#define CERES_MUST_USE_RESULT -#endif - -// Platform independent macros to get aligned memory allocations. -// For example -// -// MyFoo my_foo CERES_ALIGN_ATTRIBUTE(16); -// -// Gives us an instance of MyFoo which is aligned at a 16 byte -// boundary. -#if defined(_MSC_VER) -#define CERES_ALIGN_ATTRIBUTE(n) __declspec(align(n)) -#define CERES_ALIGN_OF(T) __alignof(T) -#elif defined(__GNUC__) -#define CERES_ALIGN_ATTRIBUTE(n) __attribute__((aligned(n))) -#define CERES_ALIGN_OF(T) __alignof(T) -#endif - -#endif // CERES_PUBLIC_INTERNAL_MACROS_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/manual_constructor.h b/extern/libmv/third_party/ceres/include/ceres/internal/manual_constructor.h deleted file mode 100644 index 0d7633cef83..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/internal/manual_constructor.h +++ /dev/null @@ -1,208 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: kenton@google.com (Kenton Varda) -// -// ManualConstructor statically-allocates space in which to store some -// object, but does not initialize it. You can then call the constructor -// and destructor for the object yourself as you see fit. This is useful -// for memory management optimizations, where you want to initialize and -// destroy an object multiple times but only allocate it once. -// -// (When I say ManualConstructor statically allocates space, I mean that -// the ManualConstructor object itself is forced to be the right size.) - -#ifndef CERES_PUBLIC_INTERNAL_MANUAL_CONSTRUCTOR_H_ -#define CERES_PUBLIC_INTERNAL_MANUAL_CONSTRUCTOR_H_ - -#include <new> - -namespace ceres { -namespace internal { - -// ------- Define CERES_ALIGNED_CHAR_ARRAY -------------------------------- - -#ifndef CERES_ALIGNED_CHAR_ARRAY - -// Because MSVC and older GCCs require that the argument to their alignment -// construct to be a literal constant integer, we use a template instantiated -// at all the possible powers of two. -template<int alignment, int size> struct AlignType { }; -template<int size> struct AlignType<0, size> { typedef char result[size]; }; - -#if !defined(CERES_ALIGN_ATTRIBUTE) -#define CERES_ALIGNED_CHAR_ARRAY you_must_define_CERES_ALIGNED_CHAR_ARRAY_for_your_compiler -#else // !defined(CERES_ALIGN_ATTRIBUTE) - -#define CERES_ALIGN_TYPE_TEMPLATE(X) \ - template<int size> struct AlignType<X, size> { \ - typedef CERES_ALIGN_ATTRIBUTE(X) char result[size]; \ - } - -CERES_ALIGN_TYPE_TEMPLATE(1); -CERES_ALIGN_TYPE_TEMPLATE(2); -CERES_ALIGN_TYPE_TEMPLATE(4); -CERES_ALIGN_TYPE_TEMPLATE(8); -CERES_ALIGN_TYPE_TEMPLATE(16); -CERES_ALIGN_TYPE_TEMPLATE(32); -CERES_ALIGN_TYPE_TEMPLATE(64); -CERES_ALIGN_TYPE_TEMPLATE(128); -CERES_ALIGN_TYPE_TEMPLATE(256); -CERES_ALIGN_TYPE_TEMPLATE(512); -CERES_ALIGN_TYPE_TEMPLATE(1024); -CERES_ALIGN_TYPE_TEMPLATE(2048); -CERES_ALIGN_TYPE_TEMPLATE(4096); -CERES_ALIGN_TYPE_TEMPLATE(8192); -// Any larger and MSVC++ will complain. - -#undef CERES_ALIGN_TYPE_TEMPLATE - -#define CERES_ALIGNED_CHAR_ARRAY(T, Size) \ - typename AlignType<CERES_ALIGN_OF(T), sizeof(T) * Size>::result - -#endif // !defined(CERES_ALIGN_ATTRIBUTE) - -#endif // CERES_ALIGNED_CHAR_ARRAY - -template <typename Type> -class ManualConstructor { - public: - // No constructor or destructor because one of the most useful uses of - // this class is as part of a union, and members of a union cannot have - // constructors or destructors. And, anyway, the whole point of this - // class is to bypass these. - - inline Type* get() { - return reinterpret_cast<Type*>(space_); - } - inline const Type* get() const { - return reinterpret_cast<const Type*>(space_); - } - - inline Type* operator->() { return get(); } - inline const Type* operator->() const { return get(); } - - inline Type& operator*() { return *get(); } - inline const Type& operator*() const { return *get(); } - - // This is needed to get around the strict aliasing warning GCC generates. - inline void* space() { - return reinterpret_cast<void*>(space_); - } - - // You can pass up to four constructor arguments as arguments of Init(). - inline void Init() { - new(space()) Type; - } - - template <typename T1> - inline void Init(const T1& p1) { - new(space()) Type(p1); - } - - template <typename T1, typename T2> - inline void Init(const T1& p1, const T2& p2) { - new(space()) Type(p1, p2); - } - - template <typename T1, typename T2, typename T3> - inline void Init(const T1& p1, const T2& p2, const T3& p3) { - new(space()) Type(p1, p2, p3); - } - - template <typename T1, typename T2, typename T3, typename T4> - inline void Init(const T1& p1, const T2& p2, const T3& p3, const T4& p4) { - new(space()) Type(p1, p2, p3, p4); - } - - template <typename T1, typename T2, typename T3, typename T4, typename T5> - inline void Init(const T1& p1, const T2& p2, const T3& p3, const T4& p4, - const T5& p5) { - new(space()) Type(p1, p2, p3, p4, p5); - } - - template <typename T1, typename T2, typename T3, typename T4, typename T5, - typename T6> - inline void Init(const T1& p1, const T2& p2, const T3& p3, const T4& p4, - const T5& p5, const T6& p6) { - new(space()) Type(p1, p2, p3, p4, p5, p6); - } - - template <typename T1, typename T2, typename T3, typename T4, typename T5, - typename T6, typename T7> - inline void Init(const T1& p1, const T2& p2, const T3& p3, const T4& p4, - const T5& p5, const T6& p6, const T7& p7) { - new(space()) Type(p1, p2, p3, p4, p5, p6, p7); - } - - template <typename T1, typename T2, typename T3, typename T4, typename T5, - typename T6, typename T7, typename T8> - inline void Init(const T1& p1, const T2& p2, const T3& p3, const T4& p4, - const T5& p5, const T6& p6, const T7& p7, const T8& p8) { - new(space()) Type(p1, p2, p3, p4, p5, p6, p7, p8); - } - - template <typename T1, typename T2, typename T3, typename T4, typename T5, - typename T6, typename T7, typename T8, typename T9> - inline void Init(const T1& p1, const T2& p2, const T3& p3, const T4& p4, - const T5& p5, const T6& p6, const T7& p7, const T8& p8, - const T9& p9) { - new(space()) Type(p1, p2, p3, p4, p5, p6, p7, p8, p9); - } - - template <typename T1, typename T2, typename T3, typename T4, typename T5, - typename T6, typename T7, typename T8, typename T9, typename T10> - inline void Init(const T1& p1, const T2& p2, const T3& p3, const T4& p4, - const T5& p5, const T6& p6, const T7& p7, const T8& p8, - const T9& p9, const T10& p10) { - new(space()) Type(p1, p2, p3, p4, p5, p6, p7, p8, p9, p10); - } - - template <typename T1, typename T2, typename T3, typename T4, typename T5, - typename T6, typename T7, typename T8, typename T9, typename T10, - typename T11> - inline void Init(const T1& p1, const T2& p2, const T3& p3, const T4& p4, - const T5& p5, const T6& p6, const T7& p7, const T8& p8, - const T9& p9, const T10& p10, const T11& p11) { - new(space()) Type(p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11); - } - - inline void Destroy() { - get()->~Type(); - } - - private: - CERES_ALIGNED_CHAR_ARRAY(Type, 1) space_; -}; - -#undef CERES_ALIGNED_CHAR_ARRAY - -} // namespace internal -} // namespace ceres - -#endif // CERES_PUBLIC_INTERNAL_MANUAL_CONSTRUCTOR_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/numeric_diff.h b/extern/libmv/third_party/ceres/include/ceres/internal/numeric_diff.h deleted file mode 100644 index 11e8275b1d3..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/internal/numeric_diff.h +++ /dev/null @@ -1,446 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// mierle@gmail.com (Keir Mierle) -// tbennun@gmail.com (Tal Ben-Nun) -// -// Finite differencing routines used by NumericDiffCostFunction. - -#ifndef CERES_PUBLIC_INTERNAL_NUMERIC_DIFF_H_ -#define CERES_PUBLIC_INTERNAL_NUMERIC_DIFF_H_ - -#include <cstring> - -#include "Eigen/Dense" -#include "Eigen/StdVector" -#include "ceres/cost_function.h" -#include "ceres/internal/fixed_array.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/internal/variadic_evaluate.h" -#include "ceres/numeric_diff_options.h" -#include "ceres/types.h" -#include "glog/logging.h" - - -namespace ceres { -namespace internal { - -// Helper templates that allow evaluation of a variadic functor or a -// CostFunction object. -template <typename CostFunctor, - int N0, int N1, int N2, int N3, int N4, - int N5, int N6, int N7, int N8, int N9 > -bool EvaluateImpl(const CostFunctor* functor, - double const* const* parameters, - double* residuals, - const void* /* NOT USED */) { - return VariadicEvaluate<CostFunctor, - double, - N0, N1, N2, N3, N4, N5, N6, N7, N8, N9>::Call( - *functor, - parameters, - residuals); -} - -template <typename CostFunctor, - int N0, int N1, int N2, int N3, int N4, - int N5, int N6, int N7, int N8, int N9 > -bool EvaluateImpl(const CostFunctor* functor, - double const* const* parameters, - double* residuals, - const CostFunction* /* NOT USED */) { - return functor->Evaluate(parameters, residuals, NULL); -} - -// This is split from the main class because C++ doesn't allow partial template -// specializations for member functions. The alternative is to repeat the main -// class for differing numbers of parameters, which is also unfortunate. -template <typename CostFunctor, - NumericDiffMethodType kMethod, - int kNumResiduals, - int N0, int N1, int N2, int N3, int N4, - int N5, int N6, int N7, int N8, int N9, - int kParameterBlock, - int kParameterBlockSize> -struct NumericDiff { - // Mutates parameters but must restore them before return. - static bool EvaluateJacobianForParameterBlock( - const CostFunctor* functor, - const double* residuals_at_eval_point, - const NumericDiffOptions& options, - int num_residuals, - int parameter_block_index, - int parameter_block_size, - double **parameters, - double *jacobian) { - using Eigen::Map; - using Eigen::Matrix; - using Eigen::RowMajor; - using Eigen::ColMajor; - - const int num_residuals_internal = - (kNumResiduals != ceres::DYNAMIC ? kNumResiduals : num_residuals); - const int parameter_block_index_internal = - (kParameterBlock != ceres::DYNAMIC ? kParameterBlock : - parameter_block_index); - const int parameter_block_size_internal = - (kParameterBlockSize != ceres::DYNAMIC ? kParameterBlockSize : - parameter_block_size); - - typedef Matrix<double, kNumResiduals, 1> ResidualVector; - typedef Matrix<double, kParameterBlockSize, 1> ParameterVector; - - // The convoluted reasoning for choosing the Row/Column major - // ordering of the matrix is an artifact of the restrictions in - // Eigen that prevent it from creating RowMajor matrices with a - // single column. In these cases, we ask for a ColMajor matrix. - typedef Matrix<double, - kNumResiduals, - kParameterBlockSize, - (kParameterBlockSize == 1) ? ColMajor : RowMajor> - JacobianMatrix; - - Map<JacobianMatrix> parameter_jacobian(jacobian, - num_residuals_internal, - parameter_block_size_internal); - - Map<ParameterVector> x_plus_delta( - parameters[parameter_block_index_internal], - parameter_block_size_internal); - ParameterVector x(x_plus_delta); - ParameterVector step_size = x.array().abs() * - ((kMethod == RIDDERS) ? options.ridders_relative_initial_step_size : - options.relative_step_size); - - // It is not a good idea to make the step size arbitrarily - // small. This will lead to problems with round off and numerical - // instability when dividing by the step size. The general - // recommendation is to not go down below sqrt(epsilon). - double min_step_size = std::sqrt(std::numeric_limits<double>::epsilon()); - - // For Ridders' method, the initial step size is required to be large, - // thus ridders_relative_initial_step_size is used. - if (kMethod == RIDDERS) { - min_step_size = std::max(min_step_size, - options.ridders_relative_initial_step_size); - } - - // For each parameter in the parameter block, use finite differences to - // compute the derivative for that parameter. - FixedArray<double> temp_residual_array(num_residuals_internal); - FixedArray<double> residual_array(num_residuals_internal); - Map<ResidualVector> residuals(residual_array.get(), - num_residuals_internal); - - for (int j = 0; j < parameter_block_size_internal; ++j) { - const double delta = std::max(min_step_size, step_size(j)); - - if (kMethod == RIDDERS) { - if (!EvaluateRiddersJacobianColumn(functor, j, delta, - options, - num_residuals_internal, - parameter_block_size_internal, - x.data(), - residuals_at_eval_point, - parameters, - x_plus_delta.data(), - temp_residual_array.get(), - residual_array.get())) { - return false; - } - } else { - if (!EvaluateJacobianColumn(functor, j, delta, - num_residuals_internal, - parameter_block_size_internal, - x.data(), - residuals_at_eval_point, - parameters, - x_plus_delta.data(), - temp_residual_array.get(), - residual_array.get())) { - return false; - } - } - - parameter_jacobian.col(j).matrix() = residuals; - } - return true; - } - - static bool EvaluateJacobianColumn(const CostFunctor* functor, - int parameter_index, - double delta, - int num_residuals, - int parameter_block_size, - const double* x_ptr, - const double* residuals_at_eval_point, - double** parameters, - double* x_plus_delta_ptr, - double* temp_residuals_ptr, - double* residuals_ptr) { - using Eigen::Map; - using Eigen::Matrix; - - typedef Matrix<double, kNumResiduals, 1> ResidualVector; - typedef Matrix<double, kParameterBlockSize, 1> ParameterVector; - - Map<const ParameterVector> x(x_ptr, parameter_block_size); - Map<ParameterVector> x_plus_delta(x_plus_delta_ptr, - parameter_block_size); - - Map<ResidualVector> residuals(residuals_ptr, num_residuals); - Map<ResidualVector> temp_residuals(temp_residuals_ptr, num_residuals); - - // Mutate 1 element at a time and then restore. - x_plus_delta(parameter_index) = x(parameter_index) + delta; - - if (!EvaluateImpl<CostFunctor, N0, N1, N2, N3, N4, N5, N6, N7, N8, N9>( - functor, parameters, residuals.data(), functor)) { - return false; - } - - // Compute this column of the jacobian in 3 steps: - // 1. Store residuals for the forward part. - // 2. Subtract residuals for the backward (or 0) part. - // 3. Divide out the run. - double one_over_delta = 1.0 / delta; - if (kMethod == CENTRAL || kMethod == RIDDERS) { - // Compute the function on the other side of x(parameter_index). - x_plus_delta(parameter_index) = x(parameter_index) - delta; - - if (!EvaluateImpl<CostFunctor, N0, N1, N2, N3, N4, N5, N6, N7, N8, N9>( - functor, parameters, temp_residuals.data(), functor)) { - return false; - } - - residuals -= temp_residuals; - one_over_delta /= 2; - } else { - // Forward difference only; reuse existing residuals evaluation. - residuals -= - Map<const ResidualVector>(residuals_at_eval_point, - num_residuals); - } - - // Restore x_plus_delta. - x_plus_delta(parameter_index) = x(parameter_index); - - // Divide out the run to get slope. - residuals *= one_over_delta; - - return true; - } - - // This numeric difference implementation uses adaptive differentiation - // on the parameters to obtain the Jacobian matrix. The adaptive algorithm - // is based on Ridders' method for adaptive differentiation, which creates - // a Romberg tableau from varying step sizes and extrapolates the - // intermediate results to obtain the current computational error. - // - // References: - // C.J.F. Ridders, Accurate computation of F'(x) and F'(x) F"(x), Advances - // in Engineering Software (1978), Volume 4, Issue 2, April 1982, - // Pages 75-76, ISSN 0141-1195, - // http://dx.doi.org/10.1016/S0141-1195(82)80057-0. - static bool EvaluateRiddersJacobianColumn( - const CostFunctor* functor, - int parameter_index, - double delta, - const NumericDiffOptions& options, - int num_residuals, - int parameter_block_size, - const double* x_ptr, - const double* residuals_at_eval_point, - double** parameters, - double* x_plus_delta_ptr, - double* temp_residuals_ptr, - double* residuals_ptr) { - using Eigen::Map; - using Eigen::Matrix; - using Eigen::aligned_allocator; - - typedef Matrix<double, kNumResiduals, 1> ResidualVector; - typedef Matrix<double, kNumResiduals, Eigen::Dynamic> ResidualCandidateMatrix; - typedef Matrix<double, kParameterBlockSize, 1> ParameterVector; - - Map<const ParameterVector> x(x_ptr, parameter_block_size); - Map<ParameterVector> x_plus_delta(x_plus_delta_ptr, - parameter_block_size); - - Map<ResidualVector> residuals(residuals_ptr, num_residuals); - Map<ResidualVector> temp_residuals(temp_residuals_ptr, num_residuals); - - // In order for the algorithm to converge, the step size should be - // initialized to a value that is large enough to produce a significant - // change in the function. - // As the derivative is estimated, the step size decreases. - // By default, the step sizes are chosen so that the middle column - // of the Romberg tableau uses the input delta. - double current_step_size = delta * - pow(options.ridders_step_shrink_factor, - options.max_num_ridders_extrapolations / 2); - - // Double-buffering temporary differential candidate vectors - // from previous step size. - ResidualCandidateMatrix stepsize_candidates_a( - num_residuals, - options.max_num_ridders_extrapolations); - ResidualCandidateMatrix stepsize_candidates_b( - num_residuals, - options.max_num_ridders_extrapolations); - ResidualCandidateMatrix* current_candidates = &stepsize_candidates_a; - ResidualCandidateMatrix* previous_candidates = &stepsize_candidates_b; - - // Represents the computational error of the derivative. This variable is - // initially set to a large value, and is set to the difference between - // current and previous finite difference extrapolations. - // norm_error is supposed to decrease as the finite difference tableau - // generation progresses, serving both as an estimate for differentiation - // error and as a measure of differentiation numerical stability. - double norm_error = std::numeric_limits<double>::max(); - - // Loop over decreasing step sizes until: - // 1. Error is smaller than a given value (ridders_epsilon), - // 2. Maximal order of extrapolation reached, or - // 3. Extrapolation becomes numerically unstable. - for (int i = 0; i < options.max_num_ridders_extrapolations; ++i) { - // Compute the numerical derivative at this step size. - if (!EvaluateJacobianColumn(functor, parameter_index, current_step_size, - num_residuals, - parameter_block_size, - x.data(), - residuals_at_eval_point, - parameters, - x_plus_delta.data(), - temp_residuals.data(), - current_candidates->col(0).data())) { - // Something went wrong; bail. - return false; - } - - // Store initial results. - if (i == 0) { - residuals = current_candidates->col(0); - } - - // Shrink differentiation step size. - current_step_size /= options.ridders_step_shrink_factor; - - // Extrapolation factor for Richardson acceleration method (see below). - double richardson_factor = options.ridders_step_shrink_factor * - options.ridders_step_shrink_factor; - for (int k = 1; k <= i; ++k) { - // Extrapolate the various orders of finite differences using - // the Richardson acceleration method. - current_candidates->col(k) = - (richardson_factor * current_candidates->col(k - 1) - - previous_candidates->col(k - 1)) / (richardson_factor - 1.0); - - richardson_factor *= options.ridders_step_shrink_factor * - options.ridders_step_shrink_factor; - - // Compute the difference between the previous value and the current. - double candidate_error = std::max( - (current_candidates->col(k) - - current_candidates->col(k - 1)).norm(), - (current_candidates->col(k) - - previous_candidates->col(k - 1)).norm()); - - // If the error has decreased, update results. - if (candidate_error <= norm_error) { - norm_error = candidate_error; - residuals = current_candidates->col(k); - - // If the error is small enough, stop. - if (norm_error < options.ridders_epsilon) { - break; - } - } - } - - // After breaking out of the inner loop, declare convergence. - if (norm_error < options.ridders_epsilon) { - break; - } - - // Check to see if the current gradient estimate is numerically unstable. - // If so, bail out and return the last stable result. - if (i > 0) { - double tableau_error = (current_candidates->col(i) - - previous_candidates->col(i - 1)).norm(); - - // Compare current error to the chosen candidate's error. - if (tableau_error >= 2 * norm_error) { - break; - } - } - - std::swap(current_candidates, previous_candidates); - } - return true; - } -}; - -template <typename CostFunctor, - NumericDiffMethodType kMethod, - int kNumResiduals, - int N0, int N1, int N2, int N3, int N4, - int N5, int N6, int N7, int N8, int N9, - int kParameterBlock> -struct NumericDiff<CostFunctor, kMethod, kNumResiduals, - N0, N1, N2, N3, N4, N5, N6, N7, N8, N9, - kParameterBlock, 0> { - // Mutates parameters but must restore them before return. - static bool EvaluateJacobianForParameterBlock( - const CostFunctor* functor, - const double* residuals_at_eval_point, - const NumericDiffOptions& options, - const int num_residuals, - const int parameter_block_index, - const int parameter_block_size, - double **parameters, - double *jacobian) { - // Silence unused parameter compiler warnings. - (void)functor; - (void)residuals_at_eval_point; - (void)options; - (void)num_residuals; - (void)parameter_block_index; - (void)parameter_block_size; - (void)parameters; - (void)jacobian; - LOG(FATAL) << "Control should never reach here."; - return true; - } -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_PUBLIC_INTERNAL_NUMERIC_DIFF_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/port.h b/extern/libmv/third_party/ceres/include/ceres/internal/port.h deleted file mode 100644 index e57049dde4b..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/internal/port.h +++ /dev/null @@ -1,76 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#ifndef CERES_PUBLIC_INTERNAL_PORT_H_ -#define CERES_PUBLIC_INTERNAL_PORT_H_ - -// This file needs to compile as c code. -#ifdef __cplusplus - -#include "ceres/internal/config.h" - -#if defined(CERES_TR1_MEMORY_HEADER) -#include <tr1/memory> -#else -#include <memory> -#endif - -namespace ceres { - -#if defined(CERES_TR1_SHARED_PTR) -using std::tr1::shared_ptr; -#else -using std::shared_ptr; -#endif - -} // namespace ceres - -#endif // __cplusplus - -// A macro to signal which functions and classes are exported when -// building a DLL with MSVC. -// -// Note that the ordering here is important, CERES_BUILDING_SHARED_LIBRARY -// is only defined locally when Ceres is compiled, it is never exported to -// users. However, in order that we do not have to configure config.h -// separately for building vs installing, if we are using MSVC and building -// a shared library, then both CERES_BUILDING_SHARED_LIBRARY and -// CERES_USING_SHARED_LIBRARY will be defined when Ceres is compiled. -// Hence it is important that the check for CERES_BUILDING_SHARED_LIBRARY -// happens first. -#if defined(_MSC_VER) && defined(CERES_BUILDING_SHARED_LIBRARY) -# define CERES_EXPORT __declspec(dllexport) -#elif defined(_MSC_VER) && defined(CERES_USING_SHARED_LIBRARY) -# define CERES_EXPORT __declspec(dllimport) -#else -# define CERES_EXPORT -#endif - -#endif // CERES_PUBLIC_INTERNAL_PORT_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/reenable_warnings.h b/extern/libmv/third_party/ceres/include/ceres/internal/reenable_warnings.h deleted file mode 100644 index 7e410259d64..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/internal/reenable_warnings.h +++ /dev/null @@ -1,38 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// - -// This is not your usual header guard. See disable_warnings.h -#ifdef CERES_WARNINGS_DISABLED -#undef CERES_WARNINGS_DISABLED - -#ifdef _MSC_VER -#pragma warning( pop ) -#endif - -#endif // CERES_WARNINGS_DISABLED diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/scoped_ptr.h b/extern/libmv/third_party/ceres/include/ceres/internal/scoped_ptr.h deleted file mode 100644 index fa0ac25a031..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/internal/scoped_ptr.h +++ /dev/null @@ -1,310 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: jorg@google.com (Jorg Brown) -// -// This is an implementation designed to match the anticipated future TR2 -// implementation of the scoped_ptr class, and its closely-related brethren, -// scoped_array, scoped_ptr_malloc, and make_scoped_ptr. - -#ifndef CERES_PUBLIC_INTERNAL_SCOPED_PTR_H_ -#define CERES_PUBLIC_INTERNAL_SCOPED_PTR_H_ - -#include <assert.h> -#include <stdlib.h> -#include <cstddef> -#include <algorithm> - -namespace ceres { -namespace internal { - -template <class C> class scoped_ptr; -template <class C, class Free> class scoped_ptr_malloc; -template <class C> class scoped_array; - -template <class C> -scoped_ptr<C> make_scoped_ptr(C *); - -// A scoped_ptr<T> is like a T*, except that the destructor of -// scoped_ptr<T> automatically deletes the pointer it holds (if -// any). That is, scoped_ptr<T> owns the T object that it points -// to. Like a T*, a scoped_ptr<T> may hold either NULL or a pointer to -// a T object. Also like T*, scoped_ptr<T> is thread-compatible, and -// once you dereference it, you get the threadsafety guarantees of T. -// -// The size of a scoped_ptr is small: sizeof(scoped_ptr<C>) == sizeof(C*) -template <class C> -class scoped_ptr { - public: - // The element type - typedef C element_type; - - // Constructor. Defaults to intializing with NULL. - // There is no way to create an uninitialized scoped_ptr. - // The input parameter must be allocated with new. - explicit scoped_ptr(C* p = NULL) : ptr_(p) { } - - // Destructor. If there is a C object, delete it. - // We don't need to test ptr_ == NULL because C++ does that for us. - ~scoped_ptr() { - enum { type_must_be_complete = sizeof(C) }; - delete ptr_; - } - - // Reset. Deletes the current owned object, if any. - // Then takes ownership of a new object, if given. - // this->reset(this->get()) works. - void reset(C* p = NULL) { - if (p != ptr_) { - enum { type_must_be_complete = sizeof(C) }; - delete ptr_; - ptr_ = p; - } - } - - // Accessors to get the owned object. - // operator* and operator-> will assert() if there is no current object. - C& operator*() const { - assert(ptr_ != NULL); - return *ptr_; - } - C* operator->() const { - assert(ptr_ != NULL); - return ptr_; - } - C* get() const { return ptr_; } - - // Comparison operators. - // These return whether a scoped_ptr and a raw pointer refer to - // the same object, not just to two different but equal objects. - bool operator==(const C* p) const { return ptr_ == p; } - bool operator!=(const C* p) const { return ptr_ != p; } - - // Swap two scoped pointers. - void swap(scoped_ptr& p2) { - C* tmp = ptr_; - ptr_ = p2.ptr_; - p2.ptr_ = tmp; - } - - // Release a pointer. - // The return value is the current pointer held by this object. - // If this object holds a NULL pointer, the return value is NULL. - // After this operation, this object will hold a NULL pointer, - // and will not own the object any more. - C* release() { - C* retVal = ptr_; - ptr_ = NULL; - return retVal; - } - - private: - C* ptr_; - - // google3 friend class that can access copy ctor (although if it actually - // calls a copy ctor, there will be a problem) see below - friend scoped_ptr<C> make_scoped_ptr<C>(C *p); - - // Forbid comparison of scoped_ptr types. If C2 != C, it totally doesn't - // make sense, and if C2 == C, it still doesn't make sense because you should - // never have the same object owned by two different scoped_ptrs. - template <class C2> bool operator==(scoped_ptr<C2> const& p2) const; - template <class C2> bool operator!=(scoped_ptr<C2> const& p2) const; - - // Disallow evil constructors - scoped_ptr(const scoped_ptr&); - void operator=(const scoped_ptr&); -}; - -// Free functions -template <class C> -inline void swap(scoped_ptr<C>& p1, scoped_ptr<C>& p2) { - p1.swap(p2); -} - -template <class C> -inline bool operator==(const C* p1, const scoped_ptr<C>& p2) { - return p1 == p2.get(); -} - -template <class C> -inline bool operator==(const C* p1, const scoped_ptr<const C>& p2) { - return p1 == p2.get(); -} - -template <class C> -inline bool operator!=(const C* p1, const scoped_ptr<C>& p2) { - return p1 != p2.get(); -} - -template <class C> -inline bool operator!=(const C* p1, const scoped_ptr<const C>& p2) { - return p1 != p2.get(); -} - -template <class C> -scoped_ptr<C> make_scoped_ptr(C *p) { - // This does nothing but to return a scoped_ptr of the type that the passed - // pointer is of. (This eliminates the need to specify the name of T when - // making a scoped_ptr that is used anonymously/temporarily.) From an - // access control point of view, we construct an unnamed scoped_ptr here - // which we return and thus copy-construct. Hence, we need to have access - // to scoped_ptr::scoped_ptr(scoped_ptr const &). However, it is guaranteed - // that we never actually call the copy constructor, which is a good thing - // as we would call the temporary's object destructor (and thus delete p) - // if we actually did copy some object, here. - return scoped_ptr<C>(p); -} - -// scoped_array<C> is like scoped_ptr<C>, except that the caller must allocate -// with new [] and the destructor deletes objects with delete []. -// -// As with scoped_ptr<C>, a scoped_array<C> either points to an object -// or is NULL. A scoped_array<C> owns the object that it points to. -// scoped_array<T> is thread-compatible, and once you index into it, -// the returned objects have only the threadsafety guarantees of T. -// -// Size: sizeof(scoped_array<C>) == sizeof(C*) -template <class C> -class scoped_array { - public: - // The element type - typedef C element_type; - - // Constructor. Defaults to intializing with NULL. - // There is no way to create an uninitialized scoped_array. - // The input parameter must be allocated with new []. - explicit scoped_array(C* p = NULL) : array_(p) { } - - // Destructor. If there is a C object, delete it. - // We don't need to test ptr_ == NULL because C++ does that for us. - ~scoped_array() { - enum { type_must_be_complete = sizeof(C) }; - delete[] array_; - } - - // Reset. Deletes the current owned object, if any. - // Then takes ownership of a new object, if given. - // this->reset(this->get()) works. - void reset(C* p = NULL) { - if (p != array_) { - enum { type_must_be_complete = sizeof(C) }; - delete[] array_; - array_ = p; - } - } - - // Get one element of the current object. - // Will assert() if there is no current object, or index i is negative. - C& operator[](std::ptrdiff_t i) const { - assert(i >= 0); - assert(array_ != NULL); - return array_[i]; - } - - // Get a pointer to the zeroth element of the current object. - // If there is no current object, return NULL. - C* get() const { - return array_; - } - - // Comparison operators. - // These return whether a scoped_array and a raw pointer refer to - // the same array, not just to two different but equal arrays. - bool operator==(const C* p) const { return array_ == p; } - bool operator!=(const C* p) const { return array_ != p; } - - // Swap two scoped arrays. - void swap(scoped_array& p2) { - C* tmp = array_; - array_ = p2.array_; - p2.array_ = tmp; - } - - // Release an array. - // The return value is the current pointer held by this object. - // If this object holds a NULL pointer, the return value is NULL. - // After this operation, this object will hold a NULL pointer, - // and will not own the object any more. - C* release() { - C* retVal = array_; - array_ = NULL; - return retVal; - } - - private: - C* array_; - - // Forbid comparison of different scoped_array types. - template <class C2> bool operator==(scoped_array<C2> const& p2) const; - template <class C2> bool operator!=(scoped_array<C2> const& p2) const; - - // Disallow evil constructors - scoped_array(const scoped_array&); - void operator=(const scoped_array&); -}; - -// Free functions -template <class C> -inline void swap(scoped_array<C>& p1, scoped_array<C>& p2) { - p1.swap(p2); -} - -template <class C> -inline bool operator==(const C* p1, const scoped_array<C>& p2) { - return p1 == p2.get(); -} - -template <class C> -inline bool operator==(const C* p1, const scoped_array<const C>& p2) { - return p1 == p2.get(); -} - -template <class C> -inline bool operator!=(const C* p1, const scoped_array<C>& p2) { - return p1 != p2.get(); -} - -template <class C> -inline bool operator!=(const C* p1, const scoped_array<const C>& p2) { - return p1 != p2.get(); -} - -// This class wraps the c library function free() in a class that can be -// passed as a template argument to scoped_ptr_malloc below. -class ScopedPtrMallocFree { - public: - inline void operator()(void* x) const { - free(x); - } -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_PUBLIC_INTERNAL_SCOPED_PTR_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/variadic_evaluate.h b/extern/libmv/third_party/ceres/include/ceres/internal/variadic_evaluate.h deleted file mode 100644 index b3515b96d18..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/internal/variadic_evaluate.h +++ /dev/null @@ -1,194 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// mierle@gmail.com (Keir Mierle) - -#ifndef CERES_PUBLIC_INTERNAL_VARIADIC_EVALUATE_H_ -#define CERES_PUBLIC_INTERNAL_VARIADIC_EVALUATE_H_ - -#include <stddef.h> - -#include "ceres/jet.h" -#include "ceres/types.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/fixed_array.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -// This block of quasi-repeated code calls the user-supplied functor, which may -// take a variable number of arguments. This is accomplished by specializing the -// struct based on the size of the trailing parameters; parameters with 0 size -// are assumed missing. -template<typename Functor, typename T, int N0, int N1, int N2, int N3, int N4, - int N5, int N6, int N7, int N8, int N9> -struct VariadicEvaluate { - static bool Call(const Functor& functor, T const *const *input, T* output) { - return functor(input[0], - input[1], - input[2], - input[3], - input[4], - input[5], - input[6], - input[7], - input[8], - input[9], - output); - } -}; - -template<typename Functor, typename T, int N0, int N1, int N2, int N3, int N4, - int N5, int N6, int N7, int N8> -struct VariadicEvaluate<Functor, T, N0, N1, N2, N3, N4, N5, N6, N7, N8, 0> { - static bool Call(const Functor& functor, T const *const *input, T* output) { - return functor(input[0], - input[1], - input[2], - input[3], - input[4], - input[5], - input[6], - input[7], - input[8], - output); - } -}; - -template<typename Functor, typename T, int N0, int N1, int N2, int N3, int N4, - int N5, int N6, int N7> -struct VariadicEvaluate<Functor, T, N0, N1, N2, N3, N4, N5, N6, N7, 0, 0> { - static bool Call(const Functor& functor, T const *const *input, T* output) { - return functor(input[0], - input[1], - input[2], - input[3], - input[4], - input[5], - input[6], - input[7], - output); - } -}; - -template<typename Functor, typename T, int N0, int N1, int N2, int N3, int N4, - int N5, int N6> -struct VariadicEvaluate<Functor, T, N0, N1, N2, N3, N4, N5, N6, 0, 0, 0> { - static bool Call(const Functor& functor, T const *const *input, T* output) { - return functor(input[0], - input[1], - input[2], - input[3], - input[4], - input[5], - input[6], - output); - } -}; - -template<typename Functor, typename T, int N0, int N1, int N2, int N3, int N4, - int N5> -struct VariadicEvaluate<Functor, T, N0, N1, N2, N3, N4, N5, 0, 0, 0, 0> { - static bool Call(const Functor& functor, T const *const *input, T* output) { - return functor(input[0], - input[1], - input[2], - input[3], - input[4], - input[5], - output); - } -}; - -template<typename Functor, typename T, int N0, int N1, int N2, int N3, int N4> -struct VariadicEvaluate<Functor, T, N0, N1, N2, N3, N4, 0, 0, 0, 0, 0> { - static bool Call(const Functor& functor, T const *const *input, T* output) { - return functor(input[0], - input[1], - input[2], - input[3], - input[4], - output); - } -}; - -template<typename Functor, typename T, int N0, int N1, int N2, int N3> -struct VariadicEvaluate<Functor, T, N0, N1, N2, N3, 0, 0, 0, 0, 0, 0> { - static bool Call(const Functor& functor, T const *const *input, T* output) { - return functor(input[0], - input[1], - input[2], - input[3], - output); - } -}; - -template<typename Functor, typename T, int N0, int N1, int N2> -struct VariadicEvaluate<Functor, T, N0, N1, N2, 0, 0, 0, 0, 0, 0, 0> { - static bool Call(const Functor& functor, T const *const *input, T* output) { - return functor(input[0], - input[1], - input[2], - output); - } -}; - -template<typename Functor, typename T, int N0, int N1> -struct VariadicEvaluate<Functor, T, N0, N1, 0, 0, 0, 0, 0, 0, 0, 0> { - static bool Call(const Functor& functor, T const *const *input, T* output) { - return functor(input[0], - input[1], - output); - } -}; - -template<typename Functor, typename T, int N0> -struct VariadicEvaluate<Functor, T, N0, 0, 0, 0, 0, 0, 0, 0, 0, 0> { - static bool Call(const Functor& functor, T const *const *input, T* output) { - return functor(input[0], - output); - } -}; - -// Template instantiation for dynamically-sized functors. -template<typename Functor, typename T> -struct VariadicEvaluate<Functor, T, ceres::DYNAMIC, ceres::DYNAMIC, - ceres::DYNAMIC, ceres::DYNAMIC, ceres::DYNAMIC, - ceres::DYNAMIC, ceres::DYNAMIC, ceres::DYNAMIC, - ceres::DYNAMIC, ceres::DYNAMIC> { - static bool Call(const Functor& functor, T const *const *input, T* output) { - return functor(input, output); - } -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_PUBLIC_INTERNAL_VARIADIC_EVALUATE_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/iteration_callback.h b/extern/libmv/third_party/ceres/include/ceres/iteration_callback.h deleted file mode 100644 index 6bab00439c5..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/iteration_callback.h +++ /dev/null @@ -1,225 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// When an iteration callback is specified, Ceres calls the callback -// after each minimizer step (if the minimizer has not converged) and -// passes it an IterationSummary object, defined below. - -#ifndef CERES_PUBLIC_ITERATION_CALLBACK_H_ -#define CERES_PUBLIC_ITERATION_CALLBACK_H_ - -#include "ceres/types.h" -#include "ceres/internal/disable_warnings.h" - -namespace ceres { - -// This struct describes the state of the optimizer after each -// iteration of the minimization. -struct CERES_EXPORT IterationSummary { - IterationSummary() - : iteration(0), - step_is_valid(false), - step_is_nonmonotonic(false), - step_is_successful(false), - cost(0.0), - cost_change(0.0), - gradient_max_norm(0.0), - gradient_norm(0.0), - step_norm(0.0), - eta(0.0), - step_size(0.0), - line_search_function_evaluations(0), - line_search_gradient_evaluations(0), - line_search_iterations(0), - linear_solver_iterations(0), - iteration_time_in_seconds(0.0), - step_solver_time_in_seconds(0.0), - cumulative_time_in_seconds(0.0) {} - - // Current iteration number. - int32 iteration; - - // Step was numerically valid, i.e., all values are finite and the - // step reduces the value of the linearized model. - // - // Note: step_is_valid is false when iteration = 0. - bool step_is_valid; - - // Step did not reduce the value of the objective function - // sufficiently, but it was accepted because of the relaxed - // acceptance criterion used by the non-monotonic trust region - // algorithm. - // - // Note: step_is_nonmonotonic is false when iteration = 0; - bool step_is_nonmonotonic; - - // Whether or not the minimizer accepted this step or not. If the - // ordinary trust region algorithm is used, this means that the - // relative reduction in the objective function value was greater - // than Solver::Options::min_relative_decrease. However, if the - // non-monotonic trust region algorithm is used - // (Solver::Options:use_nonmonotonic_steps = true), then even if the - // relative decrease is not sufficient, the algorithm may accept the - // step and the step is declared successful. - // - // Note: step_is_successful is false when iteration = 0. - bool step_is_successful; - - // Value of the objective function. - double cost; - - // Change in the value of the objective function in this - // iteration. This can be positive or negative. - double cost_change; - - // Infinity norm of the gradient vector. - double gradient_max_norm; - - // 2-norm of the gradient vector. - double gradient_norm; - - // 2-norm of the size of the step computed by the optimization - // algorithm. - double step_norm; - - // For trust region algorithms, the ratio of the actual change in - // cost and the change in the cost of the linearized approximation. - double relative_decrease; - - // Size of the trust region at the end of the current iteration. For - // the Levenberg-Marquardt algorithm, the regularization parameter - // mu = 1.0 / trust_region_radius. - double trust_region_radius; - - // For the inexact step Levenberg-Marquardt algorithm, this is the - // relative accuracy with which the Newton(LM) step is solved. This - // number affects only the iterative solvers capable of solving - // linear systems inexactly. Factorization-based exact solvers - // ignore it. - double eta; - - // Step sized computed by the line search algorithm. - double step_size; - - // Number of function value evaluations used by the line search algorithm. - int line_search_function_evaluations; - - // Number of function gradient evaluations used by the line search algorithm. - int line_search_gradient_evaluations; - - // Number of iterations taken by the line search algorithm. - int line_search_iterations; - - // Number of iterations taken by the linear solver to solve for the - // Newton step. - int linear_solver_iterations; - - // All times reported below are wall times. - - // Time (in seconds) spent inside the minimizer loop in the current - // iteration. - double iteration_time_in_seconds; - - // Time (in seconds) spent inside the trust region step solver. - double step_solver_time_in_seconds; - - // Time (in seconds) since the user called Solve(). - double cumulative_time_in_seconds; -}; - -// Interface for specifying callbacks that are executed at the end of -// each iteration of the Minimizer. The solver uses the return value -// of operator() to decide whether to continue solving or to -// terminate. The user can return three values. -// -// SOLVER_ABORT indicates that the callback detected an abnormal -// situation. The solver returns without updating the parameter blocks -// (unless Solver::Options::update_state_every_iteration is set -// true). Solver returns with Solver::Summary::termination_type set to -// USER_ABORT. -// -// SOLVER_TERMINATE_SUCCESSFULLY indicates that there is no need to -// optimize anymore (some user specified termination criterion has -// been met). Solver returns with Solver::Summary::termination_type -// set to USER_SUCCESS. -// -// SOLVER_CONTINUE indicates that the solver should continue -// optimizing. -// -// For example, the following Callback is used internally by Ceres to -// log the progress of the optimization. -// -// Callback for logging the state of the minimizer to STDERR or STDOUT -// depending on the user's preferences and logging level. -// -// class LoggingCallback : public IterationCallback { -// public: -// explicit LoggingCallback(bool log_to_stdout) -// : log_to_stdout_(log_to_stdout) {} -// -// ~LoggingCallback() {} -// -// CallbackReturnType operator()(const IterationSummary& summary) { -// const char* kReportRowFormat = -// "% 4d: f:% 8e d:% 3.2e g:% 3.2e h:% 3.2e " -// "rho:% 3.2e mu:% 3.2e eta:% 3.2e li:% 3d"; -// string output = StringPrintf(kReportRowFormat, -// summary.iteration, -// summary.cost, -// summary.cost_change, -// summary.gradient_max_norm, -// summary.step_norm, -// summary.relative_decrease, -// summary.trust_region_radius, -// summary.eta, -// summary.linear_solver_iterations); -// if (log_to_stdout_) { -// cout << output << endl; -// } else { -// VLOG(1) << output; -// } -// return SOLVER_CONTINUE; -// } -// -// private: -// const bool log_to_stdout_; -// }; -// -class CERES_EXPORT IterationCallback { - public: - virtual ~IterationCallback() {} - virtual CallbackReturnType operator()(const IterationSummary& summary) = 0; -}; - -} // namespace ceres - -#include "ceres/internal/reenable_warnings.h" - -#endif // CERES_PUBLIC_ITERATION_CALLBACK_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/jet.h b/extern/libmv/third_party/ceres/include/ceres/jet.h deleted file mode 100644 index a21fd7adb90..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/jet.h +++ /dev/null @@ -1,784 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// A simple implementation of N-dimensional dual numbers, for automatically -// computing exact derivatives of functions. -// -// While a complete treatment of the mechanics of automatic differentation is -// beyond the scope of this header (see -// http://en.wikipedia.org/wiki/Automatic_differentiation for details), the -// basic idea is to extend normal arithmetic with an extra element, "e," often -// denoted with the greek symbol epsilon, such that e != 0 but e^2 = 0. Dual -// numbers are extensions of the real numbers analogous to complex numbers: -// whereas complex numbers augment the reals by introducing an imaginary unit i -// such that i^2 = -1, dual numbers introduce an "infinitesimal" unit e such -// that e^2 = 0. Dual numbers have two components: the "real" component and the -// "infinitesimal" component, generally written as x + y*e. Surprisingly, this -// leads to a convenient method for computing exact derivatives without needing -// to manipulate complicated symbolic expressions. -// -// For example, consider the function -// -// f(x) = x^2 , -// -// evaluated at 10. Using normal arithmetic, f(10) = 100, and df/dx(10) = 20. -// Next, augument 10 with an infinitesimal to get: -// -// f(10 + e) = (10 + e)^2 -// = 100 + 2 * 10 * e + e^2 -// = 100 + 20 * e -+- -// -- | -// | +--- This is zero, since e^2 = 0 -// | -// +----------------- This is df/dx! -// -// Note that the derivative of f with respect to x is simply the infinitesimal -// component of the value of f(x + e). So, in order to take the derivative of -// any function, it is only necessary to replace the numeric "object" used in -// the function with one extended with infinitesimals. The class Jet, defined in -// this header, is one such example of this, where substitution is done with -// templates. -// -// To handle derivatives of functions taking multiple arguments, different -// infinitesimals are used, one for each variable to take the derivative of. For -// example, consider a scalar function of two scalar parameters x and y: -// -// f(x, y) = x^2 + x * y -// -// Following the technique above, to compute the derivatives df/dx and df/dy for -// f(1, 3) involves doing two evaluations of f, the first time replacing x with -// x + e, the second time replacing y with y + e. -// -// For df/dx: -// -// f(1 + e, y) = (1 + e)^2 + (1 + e) * 3 -// = 1 + 2 * e + 3 + 3 * e -// = 4 + 5 * e -// -// --> df/dx = 5 -// -// For df/dy: -// -// f(1, 3 + e) = 1^2 + 1 * (3 + e) -// = 1 + 3 + e -// = 4 + e -// -// --> df/dy = 1 -// -// To take the gradient of f with the implementation of dual numbers ("jets") in -// this file, it is necessary to create a single jet type which has components -// for the derivative in x and y, and passing them to a templated version of f: -// -// template<typename T> -// T f(const T &x, const T &y) { -// return x * x + x * y; -// } -// -// // The "2" means there should be 2 dual number components. -// Jet<double, 2> x(0); // Pick the 0th dual number for x. -// Jet<double, 2> y(1); // Pick the 1st dual number for y. -// Jet<double, 2> z = f(x, y); -// -// LOG(INFO) << "df/dx = " << z.v[0] -// << "df/dy = " << z.v[1]; -// -// Most users should not use Jet objects directly; a wrapper around Jet objects, -// which makes computing the derivative, gradient, or jacobian of templated -// functors simple, is in autodiff.h. Even autodiff.h should not be used -// directly; instead autodiff_cost_function.h is typically the file of interest. -// -// For the more mathematically inclined, this file implements first-order -// "jets". A 1st order jet is an element of the ring -// -// T[N] = T[t_1, ..., t_N] / (t_1, ..., t_N)^2 -// -// which essentially means that each jet consists of a "scalar" value 'a' from T -// and a 1st order perturbation vector 'v' of length N: -// -// x = a + \sum_i v[i] t_i -// -// A shorthand is to write an element as x = a + u, where u is the pertubation. -// Then, the main point about the arithmetic of jets is that the product of -// perturbations is zero: -// -// (a + u) * (b + v) = ab + av + bu + uv -// = ab + (av + bu) + 0 -// -// which is what operator* implements below. Addition is simpler: -// -// (a + u) + (b + v) = (a + b) + (u + v). -// -// The only remaining question is how to evaluate the function of a jet, for -// which we use the chain rule: -// -// f(a + u) = f(a) + f'(a) u -// -// where f'(a) is the (scalar) derivative of f at a. -// -// By pushing these things through sufficiently and suitably templated -// functions, we can do automatic differentiation. Just be sure to turn on -// function inlining and common-subexpression elimination, or it will be very -// slow! -// -// WARNING: Most Ceres users should not directly include this file or know the -// details of how jets work. Instead the suggested method for automatic -// derivatives is to use autodiff_cost_function.h, which is a wrapper around -// both jets.h and autodiff.h to make taking derivatives of cost functions for -// use in Ceres easier. - -#ifndef CERES_PUBLIC_JET_H_ -#define CERES_PUBLIC_JET_H_ - -#include <cmath> -#include <iosfwd> -#include <iostream> // NOLINT -#include <limits> -#include <string> - -#include "Eigen/Core" -#include "ceres/fpclassify.h" - -namespace ceres { - -template <typename T, int N> -struct Jet { - enum { DIMENSION = N }; - - // Default-construct "a" because otherwise this can lead to false errors about - // uninitialized uses when other classes relying on default constructed T - // (where T is a Jet<T, N>). This usually only happens in opt mode. Note that - // the C++ standard mandates that e.g. default constructed doubles are - // initialized to 0.0; see sections 8.5 of the C++03 standard. - Jet() : a() { - v.setZero(); - } - - // Constructor from scalar: a + 0. - explicit Jet(const T& value) { - a = value; - v.setZero(); - } - - // Constructor from scalar plus variable: a + t_i. - Jet(const T& value, int k) { - a = value; - v.setZero(); - v[k] = T(1.0); - } - - // Constructor from scalar and vector part - // The use of Eigen::DenseBase allows Eigen expressions - // to be passed in without being fully evaluated until - // they are assigned to v - template<typename Derived> - EIGEN_STRONG_INLINE Jet(const T& a, const Eigen::DenseBase<Derived> &v) - : a(a), v(v) { - } - - // Compound operators - Jet<T, N>& operator+=(const Jet<T, N> &y) { - *this = *this + y; - return *this; - } - - Jet<T, N>& operator-=(const Jet<T, N> &y) { - *this = *this - y; - return *this; - } - - Jet<T, N>& operator*=(const Jet<T, N> &y) { - *this = *this * y; - return *this; - } - - Jet<T, N>& operator/=(const Jet<T, N> &y) { - *this = *this / y; - return *this; - } - - // The scalar part. - T a; - - // The infinitesimal part. - // - // Note the Eigen::DontAlign bit is needed here because this object - // gets allocated on the stack and as part of other arrays and - // structs. Forcing the right alignment there is the source of much - // pain and suffering. Even if that works, passing Jets around to - // functions by value has problems because the C++ ABI does not - // guarantee alignment for function arguments. - // - // Setting the DontAlign bit prevents Eigen from using SSE for the - // various operations on Jets. This is a small performance penalty - // since the AutoDiff code will still expose much of the code as - // statically sized loops to the compiler. But given the subtle - // issues that arise due to alignment, especially when dealing with - // multiple platforms, it seems to be a trade off worth making. - Eigen::Matrix<T, N, 1, Eigen::DontAlign> v; -}; - -// Unary + -template<typename T, int N> inline -Jet<T, N> const& operator+(const Jet<T, N>& f) { - return f; -} - -// TODO(keir): Try adding __attribute__((always_inline)) to these functions to -// see if it causes a performance increase. - -// Unary - -template<typename T, int N> inline -Jet<T, N> operator-(const Jet<T, N>&f) { - return Jet<T, N>(-f.a, -f.v); -} - -// Binary + -template<typename T, int N> inline -Jet<T, N> operator+(const Jet<T, N>& f, - const Jet<T, N>& g) { - return Jet<T, N>(f.a + g.a, f.v + g.v); -} - -// Binary + with a scalar: x + s -template<typename T, int N> inline -Jet<T, N> operator+(const Jet<T, N>& f, T s) { - return Jet<T, N>(f.a + s, f.v); -} - -// Binary + with a scalar: s + x -template<typename T, int N> inline -Jet<T, N> operator+(T s, const Jet<T, N>& f) { - return Jet<T, N>(f.a + s, f.v); -} - -// Binary - -template<typename T, int N> inline -Jet<T, N> operator-(const Jet<T, N>& f, - const Jet<T, N>& g) { - return Jet<T, N>(f.a - g.a, f.v - g.v); -} - -// Binary - with a scalar: x - s -template<typename T, int N> inline -Jet<T, N> operator-(const Jet<T, N>& f, T s) { - return Jet<T, N>(f.a - s, f.v); -} - -// Binary - with a scalar: s - x -template<typename T, int N> inline -Jet<T, N> operator-(T s, const Jet<T, N>& f) { - return Jet<T, N>(s - f.a, -f.v); -} - -// Binary * -template<typename T, int N> inline -Jet<T, N> operator*(const Jet<T, N>& f, - const Jet<T, N>& g) { - return Jet<T, N>(f.a * g.a, f.a * g.v + f.v * g.a); -} - -// Binary * with a scalar: x * s -template<typename T, int N> inline -Jet<T, N> operator*(const Jet<T, N>& f, T s) { - return Jet<T, N>(f.a * s, f.v * s); -} - -// Binary * with a scalar: s * x -template<typename T, int N> inline -Jet<T, N> operator*(T s, const Jet<T, N>& f) { - return Jet<T, N>(f.a * s, f.v * s); -} - -// Binary / -template<typename T, int N> inline -Jet<T, N> operator/(const Jet<T, N>& f, - const Jet<T, N>& g) { - // This uses: - // - // a + u (a + u)(b - v) (a + u)(b - v) - // ----- = -------------- = -------------- - // b + v (b + v)(b - v) b^2 - // - // which holds because v*v = 0. - const T g_a_inverse = T(1.0) / g.a; - const T f_a_by_g_a = f.a * g_a_inverse; - return Jet<T, N>(f.a * g_a_inverse, (f.v - f_a_by_g_a * g.v) * g_a_inverse); -} - -// Binary / with a scalar: s / x -template<typename T, int N> inline -Jet<T, N> operator/(T s, const Jet<T, N>& g) { - const T minus_s_g_a_inverse2 = -s / (g.a * g.a); - return Jet<T, N>(s / g.a, g.v * minus_s_g_a_inverse2); -} - -// Binary / with a scalar: x / s -template<typename T, int N> inline -Jet<T, N> operator/(const Jet<T, N>& f, T s) { - const T s_inverse = 1.0 / s; - return Jet<T, N>(f.a * s_inverse, f.v * s_inverse); -} - -// Binary comparison operators for both scalars and jets. -#define CERES_DEFINE_JET_COMPARISON_OPERATOR(op) \ -template<typename T, int N> inline \ -bool operator op(const Jet<T, N>& f, const Jet<T, N>& g) { \ - return f.a op g.a; \ -} \ -template<typename T, int N> inline \ -bool operator op(const T& s, const Jet<T, N>& g) { \ - return s op g.a; \ -} \ -template<typename T, int N> inline \ -bool operator op(const Jet<T, N>& f, const T& s) { \ - return f.a op s; \ -} -CERES_DEFINE_JET_COMPARISON_OPERATOR( < ) // NOLINT -CERES_DEFINE_JET_COMPARISON_OPERATOR( <= ) // NOLINT -CERES_DEFINE_JET_COMPARISON_OPERATOR( > ) // NOLINT -CERES_DEFINE_JET_COMPARISON_OPERATOR( >= ) // NOLINT -CERES_DEFINE_JET_COMPARISON_OPERATOR( == ) // NOLINT -CERES_DEFINE_JET_COMPARISON_OPERATOR( != ) // NOLINT -#undef CERES_DEFINE_JET_COMPARISON_OPERATOR - -// Pull some functions from namespace std. -// -// This is necessary because we want to use the same name (e.g. 'sqrt') for -// double-valued and Jet-valued functions, but we are not allowed to put -// Jet-valued functions inside namespace std. -// -// TODO(keir): Switch to "using". -inline double abs (double x) { return std::abs(x); } -inline double log (double x) { return std::log(x); } -inline double exp (double x) { return std::exp(x); } -inline double sqrt (double x) { return std::sqrt(x); } -inline double cos (double x) { return std::cos(x); } -inline double acos (double x) { return std::acos(x); } -inline double sin (double x) { return std::sin(x); } -inline double asin (double x) { return std::asin(x); } -inline double tan (double x) { return std::tan(x); } -inline double atan (double x) { return std::atan(x); } -inline double sinh (double x) { return std::sinh(x); } -inline double cosh (double x) { return std::cosh(x); } -inline double tanh (double x) { return std::tanh(x); } -inline double pow (double x, double y) { return std::pow(x, y); } -inline double atan2(double y, double x) { return std::atan2(y, x); } - -// In general, f(a + h) ~= f(a) + f'(a) h, via the chain rule. - -// abs(x + h) ~= x + h or -(x + h) -template <typename T, int N> inline -Jet<T, N> abs(const Jet<T, N>& f) { - return f.a < T(0.0) ? -f : f; -} - -// log(a + h) ~= log(a) + h / a -template <typename T, int N> inline -Jet<T, N> log(const Jet<T, N>& f) { - const T a_inverse = T(1.0) / f.a; - return Jet<T, N>(log(f.a), f.v * a_inverse); -} - -// exp(a + h) ~= exp(a) + exp(a) h -template <typename T, int N> inline -Jet<T, N> exp(const Jet<T, N>& f) { - const T tmp = exp(f.a); - return Jet<T, N>(tmp, tmp * f.v); -} - -// sqrt(a + h) ~= sqrt(a) + h / (2 sqrt(a)) -template <typename T, int N> inline -Jet<T, N> sqrt(const Jet<T, N>& f) { - const T tmp = sqrt(f.a); - const T two_a_inverse = T(1.0) / (T(2.0) * tmp); - return Jet<T, N>(tmp, f.v * two_a_inverse); -} - -// cos(a + h) ~= cos(a) - sin(a) h -template <typename T, int N> inline -Jet<T, N> cos(const Jet<T, N>& f) { - return Jet<T, N>(cos(f.a), - sin(f.a) * f.v); -} - -// acos(a + h) ~= acos(a) - 1 / sqrt(1 - a^2) h -template <typename T, int N> inline -Jet<T, N> acos(const Jet<T, N>& f) { - const T tmp = - T(1.0) / sqrt(T(1.0) - f.a * f.a); - return Jet<T, N>(acos(f.a), tmp * f.v); -} - -// sin(a + h) ~= sin(a) + cos(a) h -template <typename T, int N> inline -Jet<T, N> sin(const Jet<T, N>& f) { - return Jet<T, N>(sin(f.a), cos(f.a) * f.v); -} - -// asin(a + h) ~= asin(a) + 1 / sqrt(1 - a^2) h -template <typename T, int N> inline -Jet<T, N> asin(const Jet<T, N>& f) { - const T tmp = T(1.0) / sqrt(T(1.0) - f.a * f.a); - return Jet<T, N>(asin(f.a), tmp * f.v); -} - -// tan(a + h) ~= tan(a) + (1 + tan(a)^2) h -template <typename T, int N> inline -Jet<T, N> tan(const Jet<T, N>& f) { - const T tan_a = tan(f.a); - const T tmp = T(1.0) + tan_a * tan_a; - return Jet<T, N>(tan_a, tmp * f.v); -} - -// atan(a + h) ~= atan(a) + 1 / (1 + a^2) h -template <typename T, int N> inline -Jet<T, N> atan(const Jet<T, N>& f) { - const T tmp = T(1.0) / (T(1.0) + f.a * f.a); - return Jet<T, N>(atan(f.a), tmp * f.v); -} - -// sinh(a + h) ~= sinh(a) + cosh(a) h -template <typename T, int N> inline -Jet<T, N> sinh(const Jet<T, N>& f) { - return Jet<T, N>(sinh(f.a), cosh(f.a) * f.v); -} - -// cosh(a + h) ~= cosh(a) + sinh(a) h -template <typename T, int N> inline -Jet<T, N> cosh(const Jet<T, N>& f) { - return Jet<T, N>(cosh(f.a), sinh(f.a) * f.v); -} - -// tanh(a + h) ~= tanh(a) + (1 - tanh(a)^2) h -template <typename T, int N> inline -Jet<T, N> tanh(const Jet<T, N>& f) { - const T tanh_a = tanh(f.a); - const T tmp = T(1.0) - tanh_a * tanh_a; - return Jet<T, N>(tanh_a, tmp * f.v); -} - -// Bessel functions of the first kind with integer order equal to 0, 1, n. -inline double BesselJ0(double x) { return j0(x); } -inline double BesselJ1(double x) { return j1(x); } -inline double BesselJn(int n, double x) { return jn(n, x); } - -// For the formulae of the derivatives of the Bessel functions see the book: -// Olver, Lozier, Boisvert, Clark, NIST Handbook of Mathematical Functions, -// Cambridge University Press 2010. -// -// Formulae are also available at http://dlmf.nist.gov - -// See formula http://dlmf.nist.gov/10.6#E3 -// j0(a + h) ~= j0(a) - j1(a) h -template <typename T, int N> inline -Jet<T, N> BesselJ0(const Jet<T, N>& f) { - return Jet<T, N>(BesselJ0(f.a), - -BesselJ1(f.a) * f.v); -} - -// See formula http://dlmf.nist.gov/10.6#E1 -// j1(a + h) ~= j1(a) + 0.5 ( j0(a) - j2(a) ) h -template <typename T, int N> inline -Jet<T, N> BesselJ1(const Jet<T, N>& f) { - return Jet<T, N>(BesselJ1(f.a), - T(0.5) * (BesselJ0(f.a) - BesselJn(2, f.a)) * f.v); -} - -// See formula http://dlmf.nist.gov/10.6#E1 -// j_n(a + h) ~= j_n(a) + 0.5 ( j_{n-1}(a) - j_{n+1}(a) ) h -template <typename T, int N> inline -Jet<T, N> BesselJn(int n, const Jet<T, N>& f) { - return Jet<T, N>(BesselJn(n, f.a), - T(0.5) * (BesselJn(n - 1, f.a) - BesselJn(n + 1, f.a)) * f.v); -} - -// Jet Classification. It is not clear what the appropriate semantics are for -// these classifications. This picks that IsFinite and isnormal are "all" -// operations, i.e. all elements of the jet must be finite for the jet itself -// to be finite (or normal). For IsNaN and IsInfinite, the answer is less -// clear. This takes a "any" approach for IsNaN and IsInfinite such that if any -// part of a jet is nan or inf, then the entire jet is nan or inf. This leads -// to strange situations like a jet can be both IsInfinite and IsNaN, but in -// practice the "any" semantics are the most useful for e.g. checking that -// derivatives are sane. - -// The jet is finite if all parts of the jet are finite. -template <typename T, int N> inline -bool IsFinite(const Jet<T, N>& f) { - if (!IsFinite(f.a)) { - return false; - } - for (int i = 0; i < N; ++i) { - if (!IsFinite(f.v[i])) { - return false; - } - } - return true; -} - -// The jet is infinite if any part of the jet is infinite. -template <typename T, int N> inline -bool IsInfinite(const Jet<T, N>& f) { - if (IsInfinite(f.a)) { - return true; - } - for (int i = 0; i < N; i++) { - if (IsInfinite(f.v[i])) { - return true; - } - } - return false; -} - -// The jet is NaN if any part of the jet is NaN. -template <typename T, int N> inline -bool IsNaN(const Jet<T, N>& f) { - if (IsNaN(f.a)) { - return true; - } - for (int i = 0; i < N; ++i) { - if (IsNaN(f.v[i])) { - return true; - } - } - return false; -} - -// The jet is normal if all parts of the jet are normal. -template <typename T, int N> inline -bool IsNormal(const Jet<T, N>& f) { - if (!IsNormal(f.a)) { - return false; - } - for (int i = 0; i < N; ++i) { - if (!IsNormal(f.v[i])) { - return false; - } - } - return true; -} - -// atan2(b + db, a + da) ~= atan2(b, a) + (- b da + a db) / (a^2 + b^2) -// -// In words: the rate of change of theta is 1/r times the rate of -// change of (x, y) in the positive angular direction. -template <typename T, int N> inline -Jet<T, N> atan2(const Jet<T, N>& g, const Jet<T, N>& f) { - // Note order of arguments: - // - // f = a + da - // g = b + db - - T const tmp = T(1.0) / (f.a * f.a + g.a * g.a); - return Jet<T, N>(atan2(g.a, f.a), tmp * (- g.a * f.v + f.a * g.v)); -} - - -// pow -- base is a differentiable function, exponent is a constant. -// (a+da)^p ~= a^p + p*a^(p-1) da -template <typename T, int N> inline -Jet<T, N> pow(const Jet<T, N>& f, double g) { - T const tmp = g * pow(f.a, g - T(1.0)); - return Jet<T, N>(pow(f.a, g), tmp * f.v); -} - -// pow -- base is a constant, exponent is a differentiable function. -// We have various special cases, see the comment for pow(Jet, Jet) for -// analysis: -// -// 1. For f > 0 we have: (f)^(g + dg) ~= f^g + f^g log(f) dg -// -// 2. For f == 0 and g > 0 we have: (f)^(g + dg) ~= f^g -// -// 3. For f < 0 and integer g we have: (f)^(g + dg) ~= f^g but if dg -// != 0, the derivatives are not defined and we return NaN. - -template <typename T, int N> inline -Jet<T, N> pow(double f, const Jet<T, N>& g) { - if (f == 0 && g.a > 0) { - // Handle case 2. - return Jet<T, N>(T(0.0)); - } - if (f < 0 && g.a == floor(g.a)) { - // Handle case 3. - Jet<T, N> ret(pow(f, g.a)); - for (int i = 0; i < N; i++) { - if (g.v[i] != T(0.0)) { - // Return a NaN when g.v != 0. - ret.v[i] = std::numeric_limits<T>::quiet_NaN(); - } - } - return ret; - } - // Handle case 1. - T const tmp = pow(f, g.a); - return Jet<T, N>(tmp, log(f) * tmp * g.v); -} - -// pow -- both base and exponent are differentiable functions. This has a -// variety of special cases that require careful handling. -// -// 1. For f > 0: -// (f + df)^(g + dg) ~= f^g + f^(g - 1) * (g * df + f * log(f) * dg) -// The numerical evaluation of f * log(f) for f > 0 is well behaved, even for -// extremely small values (e.g. 1e-99). -// -// 2. For f == 0 and g > 1: (f + df)^(g + dg) ~= 0 -// This cases is needed because log(0) can not be evaluated in the f > 0 -// expression. However the function f*log(f) is well behaved around f == 0 -// and its limit as f-->0 is zero. -// -// 3. For f == 0 and g == 1: (f + df)^(g + dg) ~= 0 + df -// -// 4. For f == 0 and 0 < g < 1: The value is finite but the derivatives are not. -// -// 5. For f == 0 and g < 0: The value and derivatives of f^g are not finite. -// -// 6. For f == 0 and g == 0: The C standard incorrectly defines 0^0 to be 1 -// "because there are applications that can exploit this definition". We -// (arbitrarily) decree that derivatives here will be nonfinite, since that -// is consistent with the behavior for f == 0, g < 0 and 0 < g < 1. -// Practically any definition could have been justified because mathematical -// consistency has been lost at this point. -// -// 7. For f < 0, g integer, dg == 0: (f + df)^(g + dg) ~= f^g + g * f^(g - 1) df -// This is equivalent to the case where f is a differentiable function and g -// is a constant (to first order). -// -// 8. For f < 0, g integer, dg != 0: The value is finite but the derivatives are -// not, because any change in the value of g moves us away from the point -// with a real-valued answer into the region with complex-valued answers. -// -// 9. For f < 0, g noninteger: The value and derivatives of f^g are not finite. - -template <typename T, int N> inline -Jet<T, N> pow(const Jet<T, N>& f, const Jet<T, N>& g) { - if (f.a == 0 && g.a >= 1) { - // Handle cases 2 and 3. - if (g.a > 1) { - return Jet<T, N>(T(0.0)); - } - return f; - } - if (f.a < 0 && g.a == floor(g.a)) { - // Handle cases 7 and 8. - T const tmp = g.a * pow(f.a, g.a - T(1.0)); - Jet<T, N> ret(pow(f.a, g.a), tmp * f.v); - for (int i = 0; i < N; i++) { - if (g.v[i] != T(0.0)) { - // Return a NaN when g.v != 0. - ret.v[i] = std::numeric_limits<T>::quiet_NaN(); - } - } - return ret; - } - // Handle the remaining cases. For cases 4,5,6,9 we allow the log() function - // to generate -HUGE_VAL or NaN, since those cases result in a nonfinite - // derivative. - T const tmp1 = pow(f.a, g.a); - T const tmp2 = g.a * pow(f.a, g.a - T(1.0)); - T const tmp3 = tmp1 * log(f.a); - return Jet<T, N>(tmp1, tmp2 * f.v + tmp3 * g.v); -} - -// Define the helper functions Eigen needs to embed Jet types. -// -// NOTE(keir): machine_epsilon() and precision() are missing, because they don't -// work with nested template types (e.g. where the scalar is itself templated). -// Among other things, this means that decompositions of Jet's does not work, -// for example -// -// Matrix<Jet<T, N> ... > A, x, b; -// ... -// A.solve(b, &x) -// -// does not work and will fail with a strange compiler error. -// -// TODO(keir): This is an Eigen 2.0 limitation that is lifted in 3.0. When we -// switch to 3.0, also add the rest of the specialization functionality. -template<typename T, int N> inline const Jet<T, N>& ei_conj(const Jet<T, N>& x) { return x; } // NOLINT -template<typename T, int N> inline const Jet<T, N>& ei_real(const Jet<T, N>& x) { return x; } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_imag(const Jet<T, N>& ) { return Jet<T, N>(0.0); } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_abs (const Jet<T, N>& x) { return fabs(x); } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_abs2(const Jet<T, N>& x) { return x * x; } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_sqrt(const Jet<T, N>& x) { return sqrt(x); } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_exp (const Jet<T, N>& x) { return exp(x); } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_log (const Jet<T, N>& x) { return log(x); } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_sin (const Jet<T, N>& x) { return sin(x); } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_cos (const Jet<T, N>& x) { return cos(x); } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_tan (const Jet<T, N>& x) { return tan(x); } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_atan(const Jet<T, N>& x) { return atan(x); } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_sinh(const Jet<T, N>& x) { return sinh(x); } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_cosh(const Jet<T, N>& x) { return cosh(x); } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_tanh(const Jet<T, N>& x) { return tanh(x); } // NOLINT -template<typename T, int N> inline Jet<T, N> ei_pow (const Jet<T, N>& x, Jet<T, N> y) { return pow(x, y); } // NOLINT - -// Note: This has to be in the ceres namespace for argument dependent lookup to -// function correctly. Otherwise statements like CHECK_LE(x, 2.0) fail with -// strange compile errors. -template <typename T, int N> -inline std::ostream &operator<<(std::ostream &s, const Jet<T, N>& z) { - return s << "[" << z.a << " ; " << z.v.transpose() << "]"; -} - -} // namespace ceres - -namespace Eigen { - -// Creating a specialization of NumTraits enables placing Jet objects inside -// Eigen arrays, getting all the goodness of Eigen combined with autodiff. -template<typename T, int N> -struct NumTraits<ceres::Jet<T, N> > { - typedef ceres::Jet<T, N> Real; - typedef ceres::Jet<T, N> NonInteger; - typedef ceres::Jet<T, N> Nested; - - static typename ceres::Jet<T, N> dummy_precision() { - return ceres::Jet<T, N>(1e-12); - } - - static inline Real epsilon() { - return Real(std::numeric_limits<T>::epsilon()); - } - - enum { - IsComplex = 0, - IsInteger = 0, - IsSigned, - ReadCost = 1, - AddCost = 1, - // For Jet types, multiplication is more expensive than addition. - MulCost = 3, - HasFloatingPoint = 1, - RequireInitialization = 1 - }; -}; - -} // namespace Eigen - -#endif // CERES_PUBLIC_JET_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/local_parameterization.h b/extern/libmv/third_party/ceres/include/ceres/local_parameterization.h deleted file mode 100644 index 67633de309f..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/local_parameterization.h +++ /dev/null @@ -1,301 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_PUBLIC_LOCAL_PARAMETERIZATION_H_ -#define CERES_PUBLIC_LOCAL_PARAMETERIZATION_H_ - -#include <vector> -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/internal/disable_warnings.h" - -namespace ceres { - -// Purpose: Sometimes parameter blocks x can overparameterize a problem -// -// min f(x) -// x -// -// In that case it is desirable to choose a parameterization for the -// block itself to remove the null directions of the cost. More -// generally, if x lies on a manifold of a smaller dimension than the -// ambient space that it is embedded in, then it is numerically and -// computationally more effective to optimize it using a -// parameterization that lives in the tangent space of that manifold -// at each point. -// -// For example, a sphere in three dimensions is a 2 dimensional -// manifold, embedded in a three dimensional space. At each point on -// the sphere, the plane tangent to it defines a two dimensional -// tangent space. For a cost function defined on this sphere, given a -// point x, moving in the direction normal to the sphere at that point -// is not useful. Thus a better way to do a local optimization is to -// optimize over two dimensional vector delta in the tangent space at -// that point and then "move" to the point x + delta, where the move -// operation involves projecting back onto the sphere. Doing so -// removes a redundent dimension from the optimization, making it -// numerically more robust and efficient. -// -// More generally we can define a function -// -// x_plus_delta = Plus(x, delta), -// -// where x_plus_delta has the same size as x, and delta is of size -// less than or equal to x. The function Plus, generalizes the -// definition of vector addition. Thus it satisfies the identify -// -// Plus(x, 0) = x, for all x. -// -// A trivial version of Plus is when delta is of the same size as x -// and -// -// Plus(x, delta) = x + delta -// -// A more interesting case if x is two dimensional vector, and the -// user wishes to hold the first coordinate constant. Then, delta is a -// scalar and Plus is defined as -// -// Plus(x, delta) = x + [0] * delta -// [1] -// -// An example that occurs commonly in Structure from Motion problems -// is when camera rotations are parameterized using Quaternion. There, -// it is useful only make updates orthogonal to that 4-vector defining -// the quaternion. One way to do this is to let delta be a 3 -// dimensional vector and define Plus to be -// -// Plus(x, delta) = [cos(|delta|), sin(|delta|) delta / |delta|] * x -// -// The multiplication between the two 4-vectors on the RHS is the -// standard quaternion product. -// -// Given g and a point x, optimizing f can now be restated as -// -// min f(Plus(x, delta)) -// delta -// -// Given a solution delta to this problem, the optimal value is then -// given by -// -// x* = Plus(x, delta) -// -// The class LocalParameterization defines the function Plus and its -// Jacobian which is needed to compute the Jacobian of f w.r.t delta. -class CERES_EXPORT LocalParameterization { - public: - virtual ~LocalParameterization(); - - // Generalization of the addition operation, - // - // x_plus_delta = Plus(x, delta) - // - // with the condition that Plus(x, 0) = x. - virtual bool Plus(const double* x, - const double* delta, - double* x_plus_delta) const = 0; - - // The jacobian of Plus(x, delta) w.r.t delta at delta = 0. - // - // jacobian is a row-major GlobalSize() x LocalSize() matrix. - virtual bool ComputeJacobian(const double* x, double* jacobian) const = 0; - - // local_matrix = global_matrix * jacobian - // - // global_matrix is a num_rows x GlobalSize row major matrix. - // local_matrix is a num_rows x LocalSize row major matrix. - // jacobian(x) is the matrix returned by ComputeJacobian at x. - // - // This is only used by GradientProblem. For most normal uses, it is - // okay to use the default implementation. - virtual bool MultiplyByJacobian(const double* x, - const int num_rows, - const double* global_matrix, - double* local_matrix) const; - - // Size of x. - virtual int GlobalSize() const = 0; - - // Size of delta. - virtual int LocalSize() const = 0; -}; - -// Some basic parameterizations - -// Identity Parameterization: Plus(x, delta) = x + delta -class CERES_EXPORT IdentityParameterization : public LocalParameterization { - public: - explicit IdentityParameterization(int size); - virtual ~IdentityParameterization() {} - virtual bool Plus(const double* x, - const double* delta, - double* x_plus_delta) const; - virtual bool ComputeJacobian(const double* x, - double* jacobian) const; - virtual bool MultiplyByJacobian(const double* x, - const int num_cols, - const double* global_matrix, - double* local_matrix) const; - virtual int GlobalSize() const { return size_; } - virtual int LocalSize() const { return size_; } - - private: - const int size_; -}; - -// Hold a subset of the parameters inside a parameter block constant. -class CERES_EXPORT SubsetParameterization : public LocalParameterization { - public: - explicit SubsetParameterization(int size, - const std::vector<int>& constant_parameters); - virtual ~SubsetParameterization() {} - virtual bool Plus(const double* x, - const double* delta, - double* x_plus_delta) const; - virtual bool ComputeJacobian(const double* x, - double* jacobian) const; - virtual bool MultiplyByJacobian(const double* x, - const int num_cols, - const double* global_matrix, - double* local_matrix) const; - virtual int GlobalSize() const { - return static_cast<int>(constancy_mask_.size()); - } - virtual int LocalSize() const { return local_size_; } - - private: - const int local_size_; - std::vector<char> constancy_mask_; -}; - -// Plus(x, delta) = [cos(|delta|), sin(|delta|) delta / |delta|] * x -// with * being the quaternion multiplication operator. Here we assume -// that the first element of the quaternion vector is the real (cos -// theta) part. -class CERES_EXPORT QuaternionParameterization : public LocalParameterization { - public: - virtual ~QuaternionParameterization() {} - virtual bool Plus(const double* x, - const double* delta, - double* x_plus_delta) const; - virtual bool ComputeJacobian(const double* x, - double* jacobian) const; - virtual int GlobalSize() const { return 4; } - virtual int LocalSize() const { return 3; } -}; - - -// This provides a parameterization for homogeneous vectors which are commonly -// used in Structure for Motion problems. One example where they are used is -// in representing points whose triangulation is ill-conditioned. Here -// it is advantageous to use an over-parameterization since homogeneous vectors -// can represent points at infinity. -// -// The plus operator is defined as -// Plus(x, delta) = -// [sin(0.5 * |delta|) * delta / |delta|, cos(0.5 * |delta|)] * x -// with * defined as an operator which applies the update orthogonal to x to -// remain on the sphere. We assume that the last element of x is the scalar -// component. The size of the homogeneous vector is required to be greater than -// 1. -class CERES_EXPORT HomogeneousVectorParameterization : - public LocalParameterization { - public: - explicit HomogeneousVectorParameterization(int size); - virtual ~HomogeneousVectorParameterization() {} - virtual bool Plus(const double* x, - const double* delta, - double* x_plus_delta) const; - virtual bool ComputeJacobian(const double* x, - double* jacobian) const; - virtual int GlobalSize() const { return size_; } - virtual int LocalSize() const { return size_ - 1; } - - private: - const int size_; -}; - -// Construct a local parameterization by taking the Cartesian product -// of a number of other local parameterizations. This is useful, when -// a parameter block is the cartesian product of two or more -// manifolds. For example the parameters of a camera consist of a -// rotation and a translation, i.e., SO(3) x R^3. -// -// Currently this class supports taking the cartesian product of up to -// four local parameterizations. -// -// Example usage: -// -// ProductParameterization product_param(new QuaterionionParameterization(), -// new IdentityParameterization(3)); -// -// is the local parameterization for a rigid transformation, where the -// rotation is represented using a quaternion. -class CERES_EXPORT ProductParameterization : public LocalParameterization { - public: - // - // NOTE: All the constructors take ownership of the input local - // parameterizations. - // - ProductParameterization(LocalParameterization* local_param1, - LocalParameterization* local_param2); - - ProductParameterization(LocalParameterization* local_param1, - LocalParameterization* local_param2, - LocalParameterization* local_param3); - - ProductParameterization(LocalParameterization* local_param1, - LocalParameterization* local_param2, - LocalParameterization* local_param3, - LocalParameterization* local_param4); - - virtual ~ProductParameterization(); - virtual bool Plus(const double* x, - const double* delta, - double* x_plus_delta) const; - virtual bool ComputeJacobian(const double* x, - double* jacobian) const; - virtual int GlobalSize() const { return global_size_; } - virtual int LocalSize() const { return local_size_; } - - private: - void Init(); - - std::vector<LocalParameterization*> local_params_; - int local_size_; - int global_size_; - int buffer_size_; -}; - -} // namespace ceres - -#include "ceres/internal/reenable_warnings.h" - -#endif // CERES_PUBLIC_LOCAL_PARAMETERIZATION_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/loss_function.h b/extern/libmv/third_party/ceres/include/ceres/loss_function.h deleted file mode 100644 index 0512c135143..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/loss_function.h +++ /dev/null @@ -1,428 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// The LossFunction interface is the way users describe how residuals -// are converted to cost terms for the overall problem cost function. -// For the exact manner in which loss functions are converted to the -// overall cost for a problem, see problem.h. -// -// For least squares problem where there are no outliers and standard -// squared loss is expected, it is not necessary to create a loss -// function; instead passing a NULL to the problem when adding -// residuals implies a standard squared loss. -// -// For least squares problems where the minimization may encounter -// input terms that contain outliers, that is, completely bogus -// measurements, it is important to use a loss function that reduces -// their associated penalty. -// -// Consider a structure from motion problem. The unknowns are 3D -// points and camera parameters, and the measurements are image -// coordinates describing the expected reprojected position for a -// point in a camera. For example, we want to model the geometry of a -// street scene with fire hydrants and cars, observed by a moving -// camera with unknown parameters, and the only 3D points we care -// about are the pointy tippy-tops of the fire hydrants. Our magic -// image processing algorithm, which is responsible for producing the -// measurements that are input to Ceres, has found and matched all -// such tippy-tops in all image frames, except that in one of the -// frame it mistook a car's headlight for a hydrant. If we didn't do -// anything special (i.e. if we used a basic quadratic loss), the -// residual for the erroneous measurement will result in extreme error -// due to the quadratic nature of squared loss. This results in the -// entire solution getting pulled away from the optimimum to reduce -// the large error that would otherwise be attributed to the wrong -// measurement. -// -// Using a robust loss function, the cost for large residuals is -// reduced. In the example above, this leads to outlier terms getting -// downweighted so they do not overly influence the final solution. -// -// What cost function is best? -// -// In general, there isn't a principled way to select a robust loss -// function. The authors suggest starting with a non-robust cost, then -// only experimenting with robust loss functions if standard squared -// loss doesn't work. - -#ifndef CERES_PUBLIC_LOSS_FUNCTION_H_ -#define CERES_PUBLIC_LOSS_FUNCTION_H_ - -#include "glog/logging.h" -#include "ceres/internal/macros.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/types.h" -#include "ceres/internal/disable_warnings.h" - -namespace ceres { - -class CERES_EXPORT LossFunction { - public: - virtual ~LossFunction() {} - - // For a residual vector with squared 2-norm 'sq_norm', this method - // is required to fill in the value and derivatives of the loss - // function (rho in this example): - // - // out[0] = rho(sq_norm), - // out[1] = rho'(sq_norm), - // out[2] = rho''(sq_norm), - // - // Here the convention is that the contribution of a term to the - // cost function is given by 1/2 rho(s), where - // - // s = ||residuals||^2. - // - // Calling the method with a negative value of 's' is an error and - // the implementations are not required to handle that case. - // - // Most sane choices of rho() satisfy: - // - // rho(0) = 0, - // rho'(0) = 1, - // rho'(s) < 1 in outlier region, - // rho''(s) < 0 in outlier region, - // - // so that they mimic the least squares cost for small residuals. - virtual void Evaluate(double sq_norm, double out[3]) const = 0; -}; - -// Some common implementations follow below. -// -// Note: in the region of interest (i.e. s < 3) we have: -// TrivialLoss >= HuberLoss >= SoftLOneLoss >= CauchyLoss - - -// This corresponds to no robustification. -// -// rho(s) = s -// -// At s = 0: rho = [0, 1, 0]. -// -// It is not normally necessary to use this, as passing NULL for the -// loss function when building the problem accomplishes the same -// thing. -class CERES_EXPORT TrivialLoss : public LossFunction { - public: - virtual void Evaluate(double, double*) const; -}; - -// Scaling -// ------- -// Given one robustifier -// s -> rho(s) -// one can change the length scale at which robustification takes -// place, by adding a scale factor 'a' as follows: -// -// s -> a^2 rho(s / a^2). -// -// The first and second derivatives are: -// -// s -> rho'(s / a^2), -// s -> (1 / a^2) rho''(s / a^2), -// -// but the behaviour near s = 0 is the same as the original function, -// i.e. -// -// rho(s) = s + higher order terms, -// a^2 rho(s / a^2) = s + higher order terms. -// -// The scalar 'a' should be positive. -// -// The reason for the appearance of squaring is that 'a' is in the -// units of the residual vector norm whereas 's' is a squared -// norm. For applications it is more convenient to specify 'a' than -// its square. The commonly used robustifiers below are described in -// un-scaled format (a = 1) but their implementations work for any -// non-zero value of 'a'. - -// Huber. -// -// rho(s) = s for s <= 1, -// rho(s) = 2 sqrt(s) - 1 for s >= 1. -// -// At s = 0: rho = [0, 1, 0]. -// -// The scaling parameter 'a' corresponds to 'delta' on this page: -// http://en.wikipedia.org/wiki/Huber_Loss_Function -class CERES_EXPORT HuberLoss : public LossFunction { - public: - explicit HuberLoss(double a) : a_(a), b_(a * a) { } - virtual void Evaluate(double, double*) const; - - private: - const double a_; - // b = a^2. - const double b_; -}; - -// Soft L1, similar to Huber but smooth. -// -// rho(s) = 2 (sqrt(1 + s) - 1). -// -// At s = 0: rho = [0, 1, -1/2]. -class CERES_EXPORT SoftLOneLoss : public LossFunction { - public: - explicit SoftLOneLoss(double a) : b_(a * a), c_(1 / b_) { } - virtual void Evaluate(double, double*) const; - - private: - // b = a^2. - const double b_; - // c = 1 / a^2. - const double c_; -}; - -// Inspired by the Cauchy distribution -// -// rho(s) = log(1 + s). -// -// At s = 0: rho = [0, 1, -1]. -class CERES_EXPORT CauchyLoss : public LossFunction { - public: - explicit CauchyLoss(double a) : b_(a * a), c_(1 / b_) { } - virtual void Evaluate(double, double*) const; - - private: - // b = a^2. - const double b_; - // c = 1 / a^2. - const double c_; -}; - -// Loss that is capped beyond a certain level using the arc-tangent function. -// The scaling parameter 'a' determines the level where falloff occurs. -// For costs much smaller than 'a', the loss function is linear and behaves like -// TrivialLoss, and for values much larger than 'a' the value asymptotically -// approaches the constant value of a * PI / 2. -// -// rho(s) = a atan(s / a). -// -// At s = 0: rho = [0, 1, 0]. -class CERES_EXPORT ArctanLoss : public LossFunction { - public: - explicit ArctanLoss(double a) : a_(a), b_(1 / (a * a)) { } - virtual void Evaluate(double, double*) const; - - private: - const double a_; - // b = 1 / a^2. - const double b_; -}; - -// Loss function that maps to approximately zero cost in a range around the -// origin, and reverts to linear in error (quadratic in cost) beyond this range. -// The tolerance parameter 'a' sets the nominal point at which the -// transition occurs, and the transition size parameter 'b' sets the nominal -// distance over which most of the transition occurs. Both a and b must be -// greater than zero, and typically b will be set to a fraction of a. -// The slope rho'[s] varies smoothly from about 0 at s <= a - b to -// about 1 at s >= a + b. -// -// The term is computed as: -// -// rho(s) = b log(1 + exp((s - a) / b)) - c0. -// -// where c0 is chosen so that rho(0) == 0 -// -// c0 = b log(1 + exp(-a / b) -// -// This has the following useful properties: -// -// rho(s) == 0 for s = 0 -// rho'(s) ~= 0 for s << a - b -// rho'(s) ~= 1 for s >> a + b -// rho''(s) > 0 for all s -// -// In addition, all derivatives are continuous, and the curvature is -// concentrated in the range a - b to a + b. -// -// At s = 0: rho = [0, ~0, ~0]. -class CERES_EXPORT TolerantLoss : public LossFunction { - public: - explicit TolerantLoss(double a, double b); - virtual void Evaluate(double, double*) const; - - private: - const double a_, b_, c_; -}; - -// This is the Tukey biweight loss function which aggressively -// attempts to suppress large errors. -// -// The term is computed as: -// -// rho(s) = a^2 / 6 * (1 - (1 - s / a^2)^3 ) for s <= a^2, -// rho(s) = a^2 / 6 for s > a^2. -// -// At s = 0: rho = [0, 0.5, -1 / a^2] -class CERES_EXPORT TukeyLoss : public ceres::LossFunction { - public: - explicit TukeyLoss(double a) : a_squared_(a * a) { } - virtual void Evaluate(double, double*) const; - - private: - const double a_squared_; -}; - -// Composition of two loss functions. The error is the result of first -// evaluating g followed by f to yield the composition f(g(s)). -// The loss functions must not be NULL. -class CERES_EXPORT ComposedLoss : public LossFunction { - public: - explicit ComposedLoss(const LossFunction* f, Ownership ownership_f, - const LossFunction* g, Ownership ownership_g); - virtual ~ComposedLoss(); - virtual void Evaluate(double, double*) const; - - private: - internal::scoped_ptr<const LossFunction> f_, g_; - const Ownership ownership_f_, ownership_g_; -}; - -// The discussion above has to do with length scaling: it affects the space -// in which s is measured. Sometimes you want to simply scale the output -// value of the robustifier. For example, you might want to weight -// different error terms differently (e.g., weight pixel reprojection -// errors differently from terrain errors). -// -// If rho is the wrapped robustifier, then this simply outputs -// s -> a * rho(s) -// -// The first and second derivatives are, not surprisingly -// s -> a * rho'(s) -// s -> a * rho''(s) -// -// Since we treat the a NULL Loss function as the Identity loss -// function, rho = NULL is a valid input and will result in the input -// being scaled by a. This provides a simple way of implementing a -// scaled ResidualBlock. -class CERES_EXPORT ScaledLoss : public LossFunction { - public: - // Constructs a ScaledLoss wrapping another loss function. Takes - // ownership of the wrapped loss function or not depending on the - // ownership parameter. - ScaledLoss(const LossFunction* rho, double a, Ownership ownership) : - rho_(rho), a_(a), ownership_(ownership) { } - - virtual ~ScaledLoss() { - if (ownership_ == DO_NOT_TAKE_OWNERSHIP) { - rho_.release(); - } - } - virtual void Evaluate(double, double*) const; - - private: - internal::scoped_ptr<const LossFunction> rho_; - const double a_; - const Ownership ownership_; - CERES_DISALLOW_COPY_AND_ASSIGN(ScaledLoss); -}; - -// Sometimes after the optimization problem has been constructed, we -// wish to mutate the scale of the loss function. For example, when -// performing estimation from data which has substantial outliers, -// convergence can be improved by starting out with a large scale, -// optimizing the problem and then reducing the scale. This can have -// better convergence behaviour than just using a loss function with a -// small scale. -// -// This templated class allows the user to implement a loss function -// whose scale can be mutated after an optimization problem has been -// constructed. -// -// Since we treat the a NULL Loss function as the Identity loss -// function, rho = NULL is a valid input. -// -// Example usage -// -// Problem problem; -// -// // Add parameter blocks -// -// CostFunction* cost_function = -// new AutoDiffCostFunction < UW_Camera_Mapper, 2, 9, 3>( -// new UW_Camera_Mapper(feature_x, feature_y)); -// -// LossFunctionWrapper* loss_function(new HuberLoss(1.0), TAKE_OWNERSHIP); -// -// problem.AddResidualBlock(cost_function, loss_function, parameters); -// -// Solver::Options options; -// Solger::Summary summary; -// -// Solve(options, &problem, &summary) -// -// loss_function->Reset(new HuberLoss(1.0), TAKE_OWNERSHIP); -// -// Solve(options, &problem, &summary) -// -class CERES_EXPORT LossFunctionWrapper : public LossFunction { - public: - LossFunctionWrapper(LossFunction* rho, Ownership ownership) - : rho_(rho), ownership_(ownership) { - } - - virtual ~LossFunctionWrapper() { - if (ownership_ == DO_NOT_TAKE_OWNERSHIP) { - rho_.release(); - } - } - - virtual void Evaluate(double sq_norm, double out[3]) const { - if (rho_.get() == NULL) { - out[0] = sq_norm; - out[1] = 1.0; - out[2] = 0.0; - } - else { - rho_->Evaluate(sq_norm, out); - } - } - - void Reset(LossFunction* rho, Ownership ownership) { - if (ownership_ == DO_NOT_TAKE_OWNERSHIP) { - rho_.release(); - } - rho_.reset(rho); - ownership_ = ownership; - } - - private: - internal::scoped_ptr<const LossFunction> rho_; - Ownership ownership_; - CERES_DISALLOW_COPY_AND_ASSIGN(LossFunctionWrapper); -}; - -} // namespace ceres - -#include "ceres/internal/reenable_warnings.h" - -#endif // CERES_PUBLIC_LOSS_FUNCTION_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/normal_prior.h b/extern/libmv/third_party/ceres/include/ceres/normal_prior.h deleted file mode 100644 index cd98b4c846b..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/normal_prior.h +++ /dev/null @@ -1,78 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Cost term that implements a prior on a parameter block using a -// normal distribution. - -#ifndef CERES_PUBLIC_NORMAL_PRIOR_H_ -#define CERES_PUBLIC_NORMAL_PRIOR_H_ - -#include "ceres/cost_function.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/disable_warnings.h" - -namespace ceres { - -// Implements a cost function of the form -// -// cost(x) = ||A(x - b)||^2 -// -// where, the matrix A and the vector b are fixed and x is the -// variable. In case the user is interested in implementing a cost -// function of the form -// -// cost(x) = (x - mu)^T S^{-1} (x - mu) -// -// where, mu is a vector and S is a covariance matrix, then, A = -// S^{-1/2}, i.e the matrix A is the square root of the inverse of the -// covariance, also known as the stiffness matrix. There are however -// no restrictions on the shape of A. It is free to be rectangular, -// which would be the case if the covariance matrix S is rank -// deficient. - -class CERES_EXPORT NormalPrior: public CostFunction { - public: - // Check that the number of rows in the vector b are the same as the - // number of columns in the matrix A, crash otherwise. - NormalPrior(const Matrix& A, const Vector& b); - - virtual bool Evaluate(double const* const* parameters, - double* residuals, - double** jacobians) const; - private: - Matrix A_; - Vector b_; -}; - -} // namespace ceres - -#include "ceres/internal/reenable_warnings.h" - -#endif // CERES_PUBLIC_NORMAL_PRIOR_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/numeric_diff_cost_function.h b/extern/libmv/third_party/ceres/include/ceres/numeric_diff_cost_function.h deleted file mode 100644 index fa96078df02..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/numeric_diff_cost_function.h +++ /dev/null @@ -1,342 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// sameeragarwal@google.com (Sameer Agarwal) -// -// Create CostFunctions as needed by the least squares framework with jacobians -// computed via numeric (a.k.a. finite) differentiation. For more details see -// http://en.wikipedia.org/wiki/Numerical_differentiation. -// -// To get an numerically differentiated cost function, you must define -// a class with a operator() (a functor) that computes the residuals. -// -// The function must write the computed value in the last argument -// (the only non-const one) and return true to indicate success. -// Please see cost_function.h for details on how the return value -// maybe used to impose simple constraints on the parameter block. -// -// For example, consider a scalar error e = k - x'y, where both x and y are -// two-dimensional column vector parameters, the prime sign indicates -// transposition, and k is a constant. The form of this error, which is the -// difference between a constant and an expression, is a common pattern in least -// squares problems. For example, the value x'y might be the model expectation -// for a series of measurements, where there is an instance of the cost function -// for each measurement k. -// -// The actual cost added to the total problem is e^2, or (k - x'k)^2; however, -// the squaring is implicitly done by the optimization framework. -// -// To write an numerically-differentiable cost function for the above model, first -// define the object -// -// class MyScalarCostFunctor { -// MyScalarCostFunctor(double k): k_(k) {} -// -// bool operator()(const double* const x, -// const double* const y, -// double* residuals) const { -// residuals[0] = k_ - x[0] * y[0] + x[1] * y[1]; -// return true; -// } -// -// private: -// double k_; -// }; -// -// Note that in the declaration of operator() the input parameters x -// and y come first, and are passed as const pointers to arrays of -// doubles. If there were three input parameters, then the third input -// parameter would come after y. The output is always the last -// parameter, and is also a pointer to an array. In the example above, -// the residual is a scalar, so only residuals[0] is set. -// -// Then given this class definition, the numerically differentiated -// cost function with central differences used for computing the -// derivative can be constructed as follows. -// -// CostFunction* cost_function -// = new NumericDiffCostFunction<MyScalarCostFunctor, CENTRAL, 1, 2, 2>( -// new MyScalarCostFunctor(1.0)); ^ ^ ^ ^ -// | | | | -// Finite Differencing Scheme -+ | | | -// Dimension of residual ------------+ | | -// Dimension of x ----------------------+ | -// Dimension of y -------------------------+ -// -// In this example, there is usually an instance for each measurement of k. -// -// In the instantiation above, the template parameters following -// "MyScalarCostFunctor", "1, 2, 2", describe the functor as computing -// a 1-dimensional output from two arguments, both 2-dimensional. -// -// NumericDiffCostFunction also supports cost functions with a -// runtime-determined number of residuals. For example: -// -// CostFunction* cost_function -// = new NumericDiffCostFunction<MyScalarCostFunctor, CENTRAL, DYNAMIC, 2, 2>( -// new CostFunctorWithDynamicNumResiduals(1.0), ^ ^ ^ -// TAKE_OWNERSHIP, | | | -// runtime_number_of_residuals); <----+ | | | -// | | | | -// | | | | -// Actual number of residuals ------+ | | | -// Indicate dynamic number of residuals --------------------+ | | -// Dimension of x ------------------------------------------------+ | -// Dimension of y ---------------------------------------------------+ -// -// The framework can currently accommodate cost functions of up to 10 -// independent variables, and there is no limit on the dimensionality -// of each of them. -// -// The central difference method is considerably more accurate at the cost of -// twice as many function evaluations than forward difference. Consider using -// central differences begin with, and only after that works, trying forward -// difference to improve performance. -// -// WARNING #1: A common beginner's error when first using -// NumericDiffCostFunction is to get the sizing wrong. In particular, -// there is a tendency to set the template parameters to (dimension of -// residual, number of parameters) instead of passing a dimension -// parameter for *every parameter*. In the example above, that would -// be <MyScalarCostFunctor, 1, 2>, which is missing the last '2' -// argument. Please be careful when setting the size parameters. -// -//////////////////////////////////////////////////////////////////////////// -//////////////////////////////////////////////////////////////////////////// -// -// ALTERNATE INTERFACE -// -// For a variety of reasons, including compatibility with legacy code, -// NumericDiffCostFunction can also take CostFunction objects as -// input. The following describes how. -// -// To get a numerically differentiated cost function, define a -// subclass of CostFunction such that the Evaluate() function ignores -// the jacobian parameter. The numeric differentiation wrapper will -// fill in the jacobian parameter if necessary by repeatedly calling -// the Evaluate() function with small changes to the appropriate -// parameters, and computing the slope. For performance, the numeric -// differentiation wrapper class is templated on the concrete cost -// function, even though it could be implemented only in terms of the -// virtual CostFunction interface. -// -// The numerically differentiated version of a cost function for a cost function -// can be constructed as follows: -// -// CostFunction* cost_function -// = new NumericDiffCostFunction<MyCostFunction, CENTRAL, 1, 4, 8>( -// new MyCostFunction(...), TAKE_OWNERSHIP); -// -// where MyCostFunction has 1 residual and 2 parameter blocks with sizes 4 and 8 -// respectively. Look at the tests for a more detailed example. -// -// TODO(keir): Characterize accuracy; mention pitfalls; provide alternatives. - -#ifndef CERES_PUBLIC_NUMERIC_DIFF_COST_FUNCTION_H_ -#define CERES_PUBLIC_NUMERIC_DIFF_COST_FUNCTION_H_ - -#include "Eigen/Dense" -#include "ceres/cost_function.h" -#include "ceres/internal/numeric_diff.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/numeric_diff_options.h" -#include "ceres/sized_cost_function.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { - -template <typename CostFunctor, - NumericDiffMethodType method = CENTRAL, - int kNumResiduals = 0, // Number of residuals, or ceres::DYNAMIC - int N0 = 0, // Number of parameters in block 0. - int N1 = 0, // Number of parameters in block 1. - int N2 = 0, // Number of parameters in block 2. - int N3 = 0, // Number of parameters in block 3. - int N4 = 0, // Number of parameters in block 4. - int N5 = 0, // Number of parameters in block 5. - int N6 = 0, // Number of parameters in block 6. - int N7 = 0, // Number of parameters in block 7. - int N8 = 0, // Number of parameters in block 8. - int N9 = 0> // Number of parameters in block 9. -class NumericDiffCostFunction - : public SizedCostFunction<kNumResiduals, - N0, N1, N2, N3, N4, - N5, N6, N7, N8, N9> { - public: - NumericDiffCostFunction( - CostFunctor* functor, - Ownership ownership = TAKE_OWNERSHIP, - int num_residuals = kNumResiduals, - const NumericDiffOptions& options = NumericDiffOptions()) - : functor_(functor), - ownership_(ownership), - options_(options) { - if (kNumResiduals == DYNAMIC) { - SizedCostFunction<kNumResiduals, - N0, N1, N2, N3, N4, - N5, N6, N7, N8, N9> - ::set_num_residuals(num_residuals); - } - } - - // Deprecated. New users should avoid using this constructor. Instead, use the - // constructor with NumericDiffOptions. - NumericDiffCostFunction(CostFunctor* functor, - Ownership ownership, - int num_residuals, - const double relative_step_size) - :functor_(functor), - ownership_(ownership), - options_() { - LOG(WARNING) << "This constructor is deprecated and will be removed in " - "a future version. Please use the NumericDiffOptions " - "constructor instead."; - - if (kNumResiduals == DYNAMIC) { - SizedCostFunction<kNumResiduals, - N0, N1, N2, N3, N4, - N5, N6, N7, N8, N9> - ::set_num_residuals(num_residuals); - } - - options_.relative_step_size = relative_step_size; - } - - ~NumericDiffCostFunction() { - if (ownership_ != TAKE_OWNERSHIP) { - functor_.release(); - } - } - - virtual bool Evaluate(double const* const* parameters, - double* residuals, - double** jacobians) const { - using internal::FixedArray; - using internal::NumericDiff; - - const int kNumParameters = N0 + N1 + N2 + N3 + N4 + N5 + N6 + N7 + N8 + N9; - const int kNumParameterBlocks = - (N0 > 0) + (N1 > 0) + (N2 > 0) + (N3 > 0) + (N4 > 0) + - (N5 > 0) + (N6 > 0) + (N7 > 0) + (N8 > 0) + (N9 > 0); - - // Get the function value (residuals) at the the point to evaluate. - if (!internal::EvaluateImpl<CostFunctor, - N0, N1, N2, N3, N4, N5, N6, N7, N8, N9>( - functor_.get(), - parameters, - residuals, - functor_.get())) { - return false; - } - - if (jacobians == NULL) { - return true; - } - - // Create a copy of the parameters which will get mutated. - FixedArray<double> parameters_copy(kNumParameters); - FixedArray<double*> parameters_reference_copy(kNumParameterBlocks); - - parameters_reference_copy[0] = parameters_copy.get(); - if (N1) parameters_reference_copy[1] = parameters_reference_copy[0] + N0; - if (N2) parameters_reference_copy[2] = parameters_reference_copy[1] + N1; - if (N3) parameters_reference_copy[3] = parameters_reference_copy[2] + N2; - if (N4) parameters_reference_copy[4] = parameters_reference_copy[3] + N3; - if (N5) parameters_reference_copy[5] = parameters_reference_copy[4] + N4; - if (N6) parameters_reference_copy[6] = parameters_reference_copy[5] + N5; - if (N7) parameters_reference_copy[7] = parameters_reference_copy[6] + N6; - if (N8) parameters_reference_copy[8] = parameters_reference_copy[7] + N7; - if (N9) parameters_reference_copy[9] = parameters_reference_copy[8] + N8; - -#define CERES_COPY_PARAMETER_BLOCK(block) \ - if (N ## block) memcpy(parameters_reference_copy[block], \ - parameters[block], \ - sizeof(double) * N ## block); // NOLINT - - CERES_COPY_PARAMETER_BLOCK(0); - CERES_COPY_PARAMETER_BLOCK(1); - CERES_COPY_PARAMETER_BLOCK(2); - CERES_COPY_PARAMETER_BLOCK(3); - CERES_COPY_PARAMETER_BLOCK(4); - CERES_COPY_PARAMETER_BLOCK(5); - CERES_COPY_PARAMETER_BLOCK(6); - CERES_COPY_PARAMETER_BLOCK(7); - CERES_COPY_PARAMETER_BLOCK(8); - CERES_COPY_PARAMETER_BLOCK(9); - -#undef CERES_COPY_PARAMETER_BLOCK - -#define CERES_EVALUATE_JACOBIAN_FOR_BLOCK(block) \ - if (N ## block && jacobians[block] != NULL) { \ - if (!NumericDiff<CostFunctor, \ - method, \ - kNumResiduals, \ - N0, N1, N2, N3, N4, N5, N6, N7, N8, N9, \ - block, \ - N ## block >::EvaluateJacobianForParameterBlock( \ - functor_.get(), \ - residuals, \ - options_, \ - SizedCostFunction<kNumResiduals, \ - N0, N1, N2, N3, N4, \ - N5, N6, N7, N8, N9>::num_residuals(), \ - block, \ - N ## block, \ - parameters_reference_copy.get(), \ - jacobians[block])) { \ - return false; \ - } \ - } - - CERES_EVALUATE_JACOBIAN_FOR_BLOCK(0); - CERES_EVALUATE_JACOBIAN_FOR_BLOCK(1); - CERES_EVALUATE_JACOBIAN_FOR_BLOCK(2); - CERES_EVALUATE_JACOBIAN_FOR_BLOCK(3); - CERES_EVALUATE_JACOBIAN_FOR_BLOCK(4); - CERES_EVALUATE_JACOBIAN_FOR_BLOCK(5); - CERES_EVALUATE_JACOBIAN_FOR_BLOCK(6); - CERES_EVALUATE_JACOBIAN_FOR_BLOCK(7); - CERES_EVALUATE_JACOBIAN_FOR_BLOCK(8); - CERES_EVALUATE_JACOBIAN_FOR_BLOCK(9); - -#undef CERES_EVALUATE_JACOBIAN_FOR_BLOCK - - return true; - } - - private: - internal::scoped_ptr<CostFunctor> functor_; - Ownership ownership_; - NumericDiffOptions options_; -}; - -} // namespace ceres - -#endif // CERES_PUBLIC_NUMERIC_DIFF_COST_FUNCTION_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/numeric_diff_options.h b/extern/libmv/third_party/ceres/include/ceres/numeric_diff_options.h deleted file mode 100644 index 119c8a86596..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/numeric_diff_options.h +++ /dev/null @@ -1,79 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: tbennun@gmail.com (Tal Ben-Nun) -// - -#ifndef CERES_PUBLIC_NUMERIC_DIFF_OPTIONS_H_ -#define CERES_PUBLIC_NUMERIC_DIFF_OPTIONS_H_ - -namespace ceres { - -// Options pertaining to numeric differentiation (e.g., convergence criteria, -// step sizes). -struct CERES_EXPORT NumericDiffOptions { - NumericDiffOptions() { - relative_step_size = 1e-6; - ridders_relative_initial_step_size = 1e-2; - max_num_ridders_extrapolations = 10; - ridders_epsilon = 1e-12; - ridders_step_shrink_factor = 2.0; - } - - // Numeric differentiation step size (multiplied by parameter block's - // order of magnitude). If parameters are close to zero, the step size - // is set to sqrt(machine_epsilon). - double relative_step_size; - - // Initial step size for Ridders adaptive numeric differentiation (multiplied - // by parameter block's order of magnitude). - // If parameters are close to zero, Ridders' method sets the step size - // directly to this value. This parameter is separate from - // "relative_step_size" in order to set a different default value. - // - // Note: For Ridders' method to converge, the step size should be initialized - // to a value that is large enough to produce a significant change in the - // function. As the derivative is estimated, the step size decreases. - double ridders_relative_initial_step_size; - - // Maximal number of adaptive extrapolations (sampling) in Ridders' method. - int max_num_ridders_extrapolations; - - // Convergence criterion on extrapolation error for Ridders adaptive - // differentiation. The available error estimation methods are defined in - // NumericDiffErrorType and set in the "ridders_error_method" field. - double ridders_epsilon; - - // The factor in which to shrink the step size with each extrapolation in - // Ridders' method. - double ridders_step_shrink_factor; -}; - -} // namespace ceres - -#endif // CERES_PUBLIC_NUMERIC_DIFF_OPTIONS_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/ordered_groups.h b/extern/libmv/third_party/ceres/include/ceres/ordered_groups.h deleted file mode 100644 index aa1bd3a7da1..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/ordered_groups.h +++ /dev/null @@ -1,208 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_PUBLIC_ORDERED_GROUPS_H_ -#define CERES_PUBLIC_ORDERED_GROUPS_H_ - -#include <map> -#include <set> -#include <vector> -#include "ceres/internal/port.h" -#include "glog/logging.h" - -namespace ceres { - -// A class for storing and manipulating an ordered collection of -// groups/sets with the following semantics: -// -// Group ids are non-negative integer values. Elements are any type -// that can serve as a key in a map or an element of a set. -// -// An element can only belong to one group at a time. A group may -// contain an arbitrary number of elements. -// -// Groups are ordered by their group id. -template <typename T> -class OrderedGroups { - public: - // Add an element to a group. If a group with this id does not - // exist, one is created. This method can be called any number of - // times for the same element. Group ids should be non-negative - // numbers. - // - // Return value indicates if adding the element was a success. - bool AddElementToGroup(const T element, const int group) { - if (group < 0) { - return false; - } - - typename std::map<T, int>::const_iterator it = - element_to_group_.find(element); - if (it != element_to_group_.end()) { - if (it->second == group) { - // Element is already in the right group, nothing to do. - return true; - } - - group_to_elements_[it->second].erase(element); - if (group_to_elements_[it->second].size() == 0) { - group_to_elements_.erase(it->second); - } - } - - element_to_group_[element] = group; - group_to_elements_[group].insert(element); - return true; - } - - void Clear() { - group_to_elements_.clear(); - element_to_group_.clear(); - } - - // Remove the element, no matter what group it is in. Return value - // indicates if the element was actually removed. - bool Remove(const T element) { - const int current_group = GroupId(element); - if (current_group < 0) { - return false; - } - - group_to_elements_[current_group].erase(element); - - if (group_to_elements_[current_group].size() == 0) { - // If the group is empty, then get rid of it. - group_to_elements_.erase(current_group); - } - - element_to_group_.erase(element); - return true; - } - - // Bulk remove elements. The return value indicates the number of - // elements successfully removed. - int Remove(const std::vector<T>& elements) { - if (NumElements() == 0 || elements.size() == 0) { - return 0; - } - - int num_removed = 0; - for (int i = 0; i < elements.size(); ++i) { - num_removed += Remove(elements[i]); - } - return num_removed; - } - - // Reverse the order of the groups in place. - void Reverse() { - if (NumGroups() == 0) { - return; - } - - typename std::map<int, std::set<T> >::reverse_iterator it = - group_to_elements_.rbegin(); - std::map<int, std::set<T> > new_group_to_elements; - new_group_to_elements[it->first] = it->second; - - int new_group_id = it->first + 1; - for (++it; it != group_to_elements_.rend(); ++it) { - for (typename std::set<T>::const_iterator element_it = it->second.begin(); - element_it != it->second.end(); - ++element_it) { - element_to_group_[*element_it] = new_group_id; - } - new_group_to_elements[new_group_id] = it->second; - new_group_id++; - } - - group_to_elements_.swap(new_group_to_elements); - } - - // Return the group id for the element. If the element is not a - // member of any group, return -1. - int GroupId(const T element) const { - typename std::map<T, int>::const_iterator it = - element_to_group_.find(element); - if (it == element_to_group_.end()) { - return -1; - } - return it->second; - } - - bool IsMember(const T element) const { - typename std::map<T, int>::const_iterator it = - element_to_group_.find(element); - return (it != element_to_group_.end()); - } - - // This function always succeeds, i.e., implicitly there exists a - // group for every integer. - int GroupSize(const int group) const { - typename std::map<int, std::set<T> >::const_iterator it = - group_to_elements_.find(group); - return (it == group_to_elements_.end()) ? 0 : it->second.size(); - } - - int NumElements() const { - return element_to_group_.size(); - } - - // Number of groups with one or more elements. - int NumGroups() const { - return group_to_elements_.size(); - } - - // The first group with one or more elements. Calling this when - // there are no groups with non-zero elements will result in a - // crash. - int MinNonZeroGroup() const { - CHECK_NE(NumGroups(), 0); - return group_to_elements_.begin()->first; - } - - const std::map<int, std::set<T> >& group_to_elements() const { - return group_to_elements_; - } - - const std::map<T, int>& element_to_group() const { - return element_to_group_; - } - - private: - std::map<int, std::set<T> > group_to_elements_; - std::map<T, int> element_to_group_; -}; - -// Typedef for the most commonly used version of OrderedGroups. -typedef OrderedGroups<double*> ParameterBlockOrdering; - -} // namespace ceres - -#endif // CERES_PUBLIC_ORDERED_GROUP_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/problem.h b/extern/libmv/third_party/ceres/include/ceres/problem.h deleted file mode 100644 index 409274c62c2..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/problem.h +++ /dev/null @@ -1,481 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// keir@google.com (Keir Mierle) -// -// The Problem object is used to build and hold least squares problems. - -#ifndef CERES_PUBLIC_PROBLEM_H_ -#define CERES_PUBLIC_PROBLEM_H_ - -#include <cstddef> -#include <map> -#include <set> -#include <vector> - -#include "glog/logging.h" -#include "ceres/internal/macros.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/types.h" -#include "ceres/internal/disable_warnings.h" - - -namespace ceres { - -class CostFunction; -class LossFunction; -class LocalParameterization; -class Solver; -struct CRSMatrix; - -namespace internal { -class Preprocessor; -class ProblemImpl; -class ParameterBlock; -class ResidualBlock; -} // namespace internal - -// A ResidualBlockId is an opaque handle clients can use to remove residual -// blocks from a Problem after adding them. -typedef internal::ResidualBlock* ResidualBlockId; - -// A class to represent non-linear least squares problems. Such -// problems have a cost function that is a sum of error terms (known -// as "residuals"), where each residual is a function of some subset -// of the parameters. The cost function takes the form -// -// N 1 -// SUM --- loss( || r_i1, r_i2,..., r_ik ||^2 ), -// i=1 2 -// -// where -// -// r_ij is residual number i, component j; the residual is a -// function of some subset of the parameters x1...xk. For -// example, in a structure from motion problem a residual -// might be the difference between a measured point in an -// image and the reprojected position for the matching -// camera, point pair. The residual would have two -// components, error in x and error in y. -// -// loss(y) is the loss function; for example, squared error or -// Huber L1 loss. If loss(y) = y, then the cost function is -// non-robustified least squares. -// -// This class is specifically designed to address the important subset -// of "sparse" least squares problems, where each component of the -// residual depends only on a small number number of parameters, even -// though the total number of residuals and parameters may be very -// large. This property affords tremendous gains in scale, allowing -// efficient solving of large problems that are otherwise -// inaccessible. -// -// The canonical example of a sparse least squares problem is -// "structure-from-motion" (SFM), where the parameters are points and -// cameras, and residuals are reprojection errors. Typically a single -// residual will depend only on 9 parameters (3 for the point, 6 for -// the camera). -// -// To create a least squares problem, use the AddResidualBlock() and -// AddParameterBlock() methods, documented below. Here is an example least -// squares problem containing 3 parameter blocks of sizes 3, 4 and 5 -// respectively and two residual terms of size 2 and 6: -// -// double x1[] = { 1.0, 2.0, 3.0 }; -// double x2[] = { 1.0, 2.0, 3.0, 5.0 }; -// double x3[] = { 1.0, 2.0, 3.0, 6.0, 7.0 }; -// -// Problem problem; -// -// problem.AddResidualBlock(new MyUnaryCostFunction(...), x1); -// problem.AddResidualBlock(new MyBinaryCostFunction(...), x2, x3); -// -// Please see cost_function.h for details of the CostFunction object. -class CERES_EXPORT Problem { - public: - struct CERES_EXPORT Options { - Options() - : cost_function_ownership(TAKE_OWNERSHIP), - loss_function_ownership(TAKE_OWNERSHIP), - local_parameterization_ownership(TAKE_OWNERSHIP), - enable_fast_removal(false), - disable_all_safety_checks(false) {} - - // These flags control whether the Problem object owns the cost - // functions, loss functions, and parameterizations passed into - // the Problem. If set to TAKE_OWNERSHIP, then the problem object - // will delete the corresponding cost or loss functions on - // destruction. The destructor is careful to delete the pointers - // only once, since sharing cost/loss/parameterizations is - // allowed. - Ownership cost_function_ownership; - Ownership loss_function_ownership; - Ownership local_parameterization_ownership; - - // If true, trades memory for faster RemoveResidualBlock() and - // RemoveParameterBlock() operations. - // - // By default, RemoveParameterBlock() and RemoveResidualBlock() take time - // proportional to the size of the entire problem. If you only ever remove - // parameters or residuals from the problem occassionally, this might be - // acceptable. However, if you have memory to spare, enable this option to - // make RemoveParameterBlock() take time proportional to the number of - // residual blocks that depend on it, and RemoveResidualBlock() take (on - // average) constant time. - // - // The increase in memory usage is twofold: an additonal hash set per - // parameter block containing all the residuals that depend on the parameter - // block; and a hash set in the problem containing all residuals. - bool enable_fast_removal; - - // By default, Ceres performs a variety of safety checks when constructing - // the problem. There is a small but measurable performance penalty to - // these checks, typically around 5% of construction time. If you are sure - // your problem construction is correct, and 5% of the problem construction - // time is truly an overhead you want to avoid, then you can set - // disable_all_safety_checks to true. - // - // WARNING: Do not set this to true, unless you are absolutely sure of what - // you are doing. - bool disable_all_safety_checks; - }; - - // The default constructor is equivalent to the - // invocation Problem(Problem::Options()). - Problem(); - explicit Problem(const Options& options); - - ~Problem(); - - // Add a residual block to the overall cost function. The cost - // function carries with it information about the sizes of the - // parameter blocks it expects. The function checks that these match - // the sizes of the parameter blocks listed in parameter_blocks. The - // program aborts if a mismatch is detected. loss_function can be - // NULL, in which case the cost of the term is just the squared norm - // of the residuals. - // - // The user has the option of explicitly adding the parameter blocks - // using AddParameterBlock. This causes additional correctness - // checking; however, AddResidualBlock implicitly adds the parameter - // blocks if they are not present, so calling AddParameterBlock - // explicitly is not required. - // - // The Problem object by default takes ownership of the - // cost_function and loss_function pointers. These objects remain - // live for the life of the Problem object. If the user wishes to - // keep control over the destruction of these objects, then they can - // do this by setting the corresponding enums in the Options struct. - // - // Note: Even though the Problem takes ownership of cost_function - // and loss_function, it does not preclude the user from re-using - // them in another residual block. The destructor takes care to call - // delete on each cost_function or loss_function pointer only once, - // regardless of how many residual blocks refer to them. - // - // Example usage: - // - // double x1[] = {1.0, 2.0, 3.0}; - // double x2[] = {1.0, 2.0, 5.0, 6.0}; - // double x3[] = {3.0, 6.0, 2.0, 5.0, 1.0}; - // - // Problem problem; - // - // problem.AddResidualBlock(new MyUnaryCostFunction(...), NULL, x1); - // problem.AddResidualBlock(new MyBinaryCostFunction(...), NULL, x2, x1); - // - ResidualBlockId AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - const std::vector<double*>& parameter_blocks); - - // Convenience methods for adding residuals with a small number of - // parameters. This is the common case. Instead of specifying the - // parameter block arguments as a vector, list them as pointers. - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3, double* x4); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3, double* x4, double* x5); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3, double* x4, double* x5, - double* x6); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3, double* x4, double* x5, - double* x6, double* x7); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3, double* x4, double* x5, - double* x6, double* x7, double* x8); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3, double* x4, double* x5, - double* x6, double* x7, double* x8, - double* x9); - - // Add a parameter block with appropriate size to the problem. - // Repeated calls with the same arguments are ignored. Repeated - // calls with the same double pointer but a different size results - // in undefined behaviour. - void AddParameterBlock(double* values, int size); - - // Add a parameter block with appropriate size and parameterization - // to the problem. Repeated calls with the same arguments are - // ignored. Repeated calls with the same double pointer but a - // different size results in undefined behaviour. - void AddParameterBlock(double* values, - int size, - LocalParameterization* local_parameterization); - - // Remove a parameter block from the problem. The parameterization of the - // parameter block, if it exists, will persist until the deletion of the - // problem (similar to cost/loss functions in residual block removal). Any - // residual blocks that depend on the parameter are also removed, as - // described above in RemoveResidualBlock(). - // - // If Problem::Options::enable_fast_removal is true, then the - // removal is fast (almost constant time). Otherwise, removing a parameter - // block will incur a scan of the entire Problem object. - // - // WARNING: Removing a residual or parameter block will destroy the implicit - // ordering, rendering the jacobian or residuals returned from the solver - // uninterpretable. If you depend on the evaluated jacobian, do not use - // remove! This may change in a future release. - void RemoveParameterBlock(double* values); - - // Remove a residual block from the problem. Any parameters that the residual - // block depends on are not removed. The cost and loss functions for the - // residual block will not get deleted immediately; won't happen until the - // problem itself is deleted. - // - // WARNING: Removing a residual or parameter block will destroy the implicit - // ordering, rendering the jacobian or residuals returned from the solver - // uninterpretable. If you depend on the evaluated jacobian, do not use - // remove! This may change in a future release. - void RemoveResidualBlock(ResidualBlockId residual_block); - - // Hold the indicated parameter block constant during optimization. - void SetParameterBlockConstant(double* values); - - // Allow the indicated parameter block to vary during optimization. - void SetParameterBlockVariable(double* values); - - // Set the local parameterization for one of the parameter blocks. - // The local_parameterization is owned by the Problem by default. It - // is acceptable to set the same parameterization for multiple - // parameters; the destructor is careful to delete local - // parameterizations only once. The local parameterization can only - // be set once per parameter, and cannot be changed once set. - void SetParameterization(double* values, - LocalParameterization* local_parameterization); - - // Get the local parameterization object associated with this - // parameter block. If there is no parameterization object - // associated then NULL is returned. - const LocalParameterization* GetParameterization(double* values) const; - - // Set the lower/upper bound for the parameter with position "index". - void SetParameterLowerBound(double* values, int index, double lower_bound); - void SetParameterUpperBound(double* values, int index, double upper_bound); - - // Number of parameter blocks in the problem. Always equals - // parameter_blocks().size() and parameter_block_sizes().size(). - int NumParameterBlocks() const; - - // The size of the parameter vector obtained by summing over the - // sizes of all the parameter blocks. - int NumParameters() const; - - // Number of residual blocks in the problem. Always equals - // residual_blocks().size(). - int NumResidualBlocks() const; - - // The size of the residual vector obtained by summing over the - // sizes of all of the residual blocks. - int NumResiduals() const; - - // The size of the parameter block. - int ParameterBlockSize(const double* values) const; - - // The size of local parameterization for the parameter block. If - // there is no local parameterization associated with this parameter - // block, then ParameterBlockLocalSize = ParameterBlockSize. - int ParameterBlockLocalSize(const double* values) const; - - // Is the given parameter block present in this problem or not? - bool HasParameterBlock(const double* values) const; - - // Fills the passed parameter_blocks vector with pointers to the - // parameter blocks currently in the problem. After this call, - // parameter_block.size() == NumParameterBlocks. - void GetParameterBlocks(std::vector<double*>* parameter_blocks) const; - - // Fills the passed residual_blocks vector with pointers to the - // residual blocks currently in the problem. After this call, - // residual_blocks.size() == NumResidualBlocks. - void GetResidualBlocks(std::vector<ResidualBlockId>* residual_blocks) const; - - // Get all the parameter blocks that depend on the given residual block. - void GetParameterBlocksForResidualBlock( - const ResidualBlockId residual_block, - std::vector<double*>* parameter_blocks) const; - - // Get the CostFunction for the given residual block. - const CostFunction* GetCostFunctionForResidualBlock( - const ResidualBlockId residual_block) const; - - // Get the LossFunction for the given residual block. Returns NULL - // if no loss function is associated with this residual block. - const LossFunction* GetLossFunctionForResidualBlock( - const ResidualBlockId residual_block) const; - - // Get all the residual blocks that depend on the given parameter block. - // - // If Problem::Options::enable_fast_removal is true, then - // getting the residual blocks is fast and depends only on the number of - // residual blocks. Otherwise, getting the residual blocks for a parameter - // block will incur a scan of the entire Problem object. - void GetResidualBlocksForParameterBlock( - const double* values, - std::vector<ResidualBlockId>* residual_blocks) const; - - // Options struct to control Problem::Evaluate. - struct EvaluateOptions { - EvaluateOptions() - : apply_loss_function(true), - num_threads(1) { - } - - // The set of parameter blocks for which evaluation should be - // performed. This vector determines the order that parameter - // blocks occur in the gradient vector and in the columns of the - // jacobian matrix. If parameter_blocks is empty, then it is - // assumed to be equal to vector containing ALL the parameter - // blocks. Generally speaking the parameter blocks will occur in - // the order in which they were added to the problem. But, this - // may change if the user removes any parameter blocks from the - // problem. - // - // NOTE: This vector should contain the same pointers as the ones - // used to add parameter blocks to the Problem. These parameter - // block should NOT point to new memory locations. Bad things will - // happen otherwise. - std::vector<double*> parameter_blocks; - - // The set of residual blocks to evaluate. This vector determines - // the order in which the residuals occur, and how the rows of the - // jacobian are ordered. If residual_blocks is empty, then it is - // assumed to be equal to the vector containing ALL the residual - // blocks. Generally speaking the residual blocks will occur in - // the order in which they were added to the problem. But, this - // may change if the user removes any residual blocks from the - // problem. - std::vector<ResidualBlockId> residual_blocks; - - // Even though the residual blocks in the problem may contain loss - // functions, setting apply_loss_function to false will turn off - // the application of the loss function to the output of the cost - // function. This is of use for example if the user wishes to - // analyse the solution quality by studying the distribution of - // residuals before and after the solve. - bool apply_loss_function; - - int num_threads; - }; - - // Evaluate Problem. Any of the output pointers can be NULL. Which - // residual blocks and parameter blocks are used is controlled by - // the EvaluateOptions struct above. - // - // Note 1: The evaluation will use the values stored in the memory - // locations pointed to by the parameter block pointers used at the - // time of the construction of the problem. i.e., - // - // Problem problem; - // double x = 1; - // problem.AddResidualBlock(new MyCostFunction, NULL, &x); - // - // double cost = 0.0; - // problem.Evaluate(Problem::EvaluateOptions(), &cost, NULL, NULL, NULL); - // - // The cost is evaluated at x = 1. If you wish to evaluate the - // problem at x = 2, then - // - // x = 2; - // problem.Evaluate(Problem::EvaluateOptions(), &cost, NULL, NULL, NULL); - // - // is the way to do so. - // - // Note 2: If no local parameterizations are used, then the size of - // the gradient vector (and the number of columns in the jacobian) - // is the sum of the sizes of all the parameter blocks. If a - // parameter block has a local parameterization, then it contributes - // "LocalSize" entries to the gradient vector (and the number of - // columns in the jacobian). - bool Evaluate(const EvaluateOptions& options, - double* cost, - std::vector<double>* residuals, - std::vector<double>* gradient, - CRSMatrix* jacobian); - - private: - friend class Solver; - friend class Covariance; - internal::scoped_ptr<internal::ProblemImpl> problem_impl_; - CERES_DISALLOW_COPY_AND_ASSIGN(Problem); -}; - -} // namespace ceres - -#include "ceres/internal/reenable_warnings.h" - -#endif // CERES_PUBLIC_PROBLEM_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/rotation.h b/extern/libmv/third_party/ceres/include/ceres/rotation.h deleted file mode 100644 index e9496d772e4..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/rotation.h +++ /dev/null @@ -1,629 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// sameeragarwal@google.com (Sameer Agarwal) -// -// Templated functions for manipulating rotations. The templated -// functions are useful when implementing functors for automatic -// differentiation. -// -// In the following, the Quaternions are laid out as 4-vectors, thus: -// -// q[0] scalar part. -// q[1] coefficient of i. -// q[2] coefficient of j. -// q[3] coefficient of k. -// -// where: i*i = j*j = k*k = -1 and i*j = k, j*k = i, k*i = j. - -#ifndef CERES_PUBLIC_ROTATION_H_ -#define CERES_PUBLIC_ROTATION_H_ - -#include <algorithm> -#include <cmath> -#include <limits> -#include "glog/logging.h" - -namespace ceres { - -// Trivial wrapper to index linear arrays as matrices, given a fixed -// column and row stride. When an array "T* array" is wrapped by a -// -// (const) MatrixAdapter<T, row_stride, col_stride> M" -// -// the expression M(i, j) is equivalent to -// -// arrary[i * row_stride + j * col_stride] -// -// Conversion functions to and from rotation matrices accept -// MatrixAdapters to permit using row-major and column-major layouts, -// and rotation matrices embedded in larger matrices (such as a 3x4 -// projection matrix). -template <typename T, int row_stride, int col_stride> -struct MatrixAdapter; - -// Convenience functions to create a MatrixAdapter that treats the -// array pointed to by "pointer" as a 3x3 (contiguous) column-major or -// row-major matrix. -template <typename T> -MatrixAdapter<T, 1, 3> ColumnMajorAdapter3x3(T* pointer); - -template <typename T> -MatrixAdapter<T, 3, 1> RowMajorAdapter3x3(T* pointer); - -// Convert a value in combined axis-angle representation to a quaternion. -// The value angle_axis is a triple whose norm is an angle in radians, -// and whose direction is aligned with the axis of rotation, -// and quaternion is a 4-tuple that will contain the resulting quaternion. -// The implementation may be used with auto-differentiation up to the first -// derivative, higher derivatives may have unexpected results near the origin. -template<typename T> -void AngleAxisToQuaternion(const T* angle_axis, T* quaternion); - -// Convert a quaternion to the equivalent combined axis-angle representation. -// The value quaternion must be a unit quaternion - it is not normalized first, -// and angle_axis will be filled with a value whose norm is the angle of -// rotation in radians, and whose direction is the axis of rotation. -// The implemention may be used with auto-differentiation up to the first -// derivative, higher derivatives may have unexpected results near the origin. -template<typename T> -void QuaternionToAngleAxis(const T* quaternion, T* angle_axis); - -// Conversions between 3x3 rotation matrix (in column major order) and -// quaternion rotation representations. Templated for use with -// autodifferentiation. -template <typename T> -void RotationMatrixToQuaternion(const T* R, T* quaternion); - -template <typename T, int row_stride, int col_stride> -void RotationMatrixToQuaternion( - const MatrixAdapter<const T, row_stride, col_stride>& R, - T* quaternion); - -// Conversions between 3x3 rotation matrix (in column major order) and -// axis-angle rotation representations. Templated for use with -// autodifferentiation. -template <typename T> -void RotationMatrixToAngleAxis(const T* R, T* angle_axis); - -template <typename T, int row_stride, int col_stride> -void RotationMatrixToAngleAxis( - const MatrixAdapter<const T, row_stride, col_stride>& R, - T* angle_axis); - -template <typename T> -void AngleAxisToRotationMatrix(const T* angle_axis, T* R); - -template <typename T, int row_stride, int col_stride> -void AngleAxisToRotationMatrix( - const T* angle_axis, - const MatrixAdapter<T, row_stride, col_stride>& R); - -// Conversions between 3x3 rotation matrix (in row major order) and -// Euler angle (in degrees) rotation representations. -// -// The {pitch,roll,yaw} Euler angles are rotations around the {x,y,z} -// axes, respectively. They are applied in that same order, so the -// total rotation R is Rz * Ry * Rx. -template <typename T> -void EulerAnglesToRotationMatrix(const T* euler, int row_stride, T* R); - -template <typename T, int row_stride, int col_stride> -void EulerAnglesToRotationMatrix( - const T* euler, - const MatrixAdapter<T, row_stride, col_stride>& R); - -// Convert a 4-vector to a 3x3 scaled rotation matrix. -// -// The choice of rotation is such that the quaternion [1 0 0 0] goes to an -// identity matrix and for small a, b, c the quaternion [1 a b c] goes to -// the matrix -// -// [ 0 -c b ] -// I + 2 [ c 0 -a ] + higher order terms -// [ -b a 0 ] -// -// which corresponds to a Rodrigues approximation, the last matrix being -// the cross-product matrix of [a b c]. Together with the property that -// R(q1 * q2) = R(q1) * R(q2) this uniquely defines the mapping from q to R. -// -// No normalization of the quaternion is performed, i.e. -// R = ||q||^2 * Q, where Q is an orthonormal matrix -// such that det(Q) = 1 and Q*Q' = I -// -// WARNING: The rotation matrix is ROW MAJOR -template <typename T> inline -void QuaternionToScaledRotation(const T q[4], T R[3 * 3]); - -template <typename T, int row_stride, int col_stride> inline -void QuaternionToScaledRotation( - const T q[4], - const MatrixAdapter<T, row_stride, col_stride>& R); - -// Same as above except that the rotation matrix is normalized by the -// Frobenius norm, so that R * R' = I (and det(R) = 1). -// -// WARNING: The rotation matrix is ROW MAJOR -template <typename T> inline -void QuaternionToRotation(const T q[4], T R[3 * 3]); - -template <typename T, int row_stride, int col_stride> inline -void QuaternionToRotation( - const T q[4], - const MatrixAdapter<T, row_stride, col_stride>& R); - -// Rotates a point pt by a quaternion q: -// -// result = R(q) * pt -// -// Assumes the quaternion is unit norm. This assumption allows us to -// write the transform as (something)*pt + pt, as is clear from the -// formula below. If you pass in a quaternion with |q|^2 = 2 then you -// WILL NOT get back 2 times the result you get for a unit quaternion. -template <typename T> inline -void UnitQuaternionRotatePoint(const T q[4], const T pt[3], T result[3]); - -// With this function you do not need to assume that q has unit norm. -// It does assume that the norm is non-zero. -template <typename T> inline -void QuaternionRotatePoint(const T q[4], const T pt[3], T result[3]); - -// zw = z * w, where * is the Quaternion product between 4 vectors. -template<typename T> inline -void QuaternionProduct(const T z[4], const T w[4], T zw[4]); - -// xy = x cross y; -template<typename T> inline -void CrossProduct(const T x[3], const T y[3], T x_cross_y[3]); - -template<typename T> inline -T DotProduct(const T x[3], const T y[3]); - -// y = R(angle_axis) * x; -template<typename T> inline -void AngleAxisRotatePoint(const T angle_axis[3], const T pt[3], T result[3]); - -// --- IMPLEMENTATION - -template<typename T, int row_stride, int col_stride> -struct MatrixAdapter { - T* pointer_; - explicit MatrixAdapter(T* pointer) - : pointer_(pointer) - {} - - T& operator()(int r, int c) const { - return pointer_[r * row_stride + c * col_stride]; - } -}; - -template <typename T> -MatrixAdapter<T, 1, 3> ColumnMajorAdapter3x3(T* pointer) { - return MatrixAdapter<T, 1, 3>(pointer); -} - -template <typename T> -MatrixAdapter<T, 3, 1> RowMajorAdapter3x3(T* pointer) { - return MatrixAdapter<T, 3, 1>(pointer); -} - -template<typename T> -inline void AngleAxisToQuaternion(const T* angle_axis, T* quaternion) { - const T& a0 = angle_axis[0]; - const T& a1 = angle_axis[1]; - const T& a2 = angle_axis[2]; - const T theta_squared = a0 * a0 + a1 * a1 + a2 * a2; - - // For points not at the origin, the full conversion is numerically stable. - if (theta_squared > T(0.0)) { - const T theta = sqrt(theta_squared); - const T half_theta = theta * T(0.5); - const T k = sin(half_theta) / theta; - quaternion[0] = cos(half_theta); - quaternion[1] = a0 * k; - quaternion[2] = a1 * k; - quaternion[3] = a2 * k; - } else { - // At the origin, sqrt() will produce NaN in the derivative since - // the argument is zero. By approximating with a Taylor series, - // and truncating at one term, the value and first derivatives will be - // computed correctly when Jets are used. - const T k(0.5); - quaternion[0] = T(1.0); - quaternion[1] = a0 * k; - quaternion[2] = a1 * k; - quaternion[3] = a2 * k; - } -} - -template<typename T> -inline void QuaternionToAngleAxis(const T* quaternion, T* angle_axis) { - const T& q1 = quaternion[1]; - const T& q2 = quaternion[2]; - const T& q3 = quaternion[3]; - const T sin_squared_theta = q1 * q1 + q2 * q2 + q3 * q3; - - // For quaternions representing non-zero rotation, the conversion - // is numerically stable. - if (sin_squared_theta > T(0.0)) { - const T sin_theta = sqrt(sin_squared_theta); - const T& cos_theta = quaternion[0]; - - // If cos_theta is negative, theta is greater than pi/2, which - // means that angle for the angle_axis vector which is 2 * theta - // would be greater than pi. - // - // While this will result in the correct rotation, it does not - // result in a normalized angle-axis vector. - // - // In that case we observe that 2 * theta ~ 2 * theta - 2 * pi, - // which is equivalent saying - // - // theta - pi = atan(sin(theta - pi), cos(theta - pi)) - // = atan(-sin(theta), -cos(theta)) - // - const T two_theta = - T(2.0) * ((cos_theta < 0.0) - ? atan2(-sin_theta, -cos_theta) - : atan2(sin_theta, cos_theta)); - const T k = two_theta / sin_theta; - angle_axis[0] = q1 * k; - angle_axis[1] = q2 * k; - angle_axis[2] = q3 * k; - } else { - // For zero rotation, sqrt() will produce NaN in the derivative since - // the argument is zero. By approximating with a Taylor series, - // and truncating at one term, the value and first derivatives will be - // computed correctly when Jets are used. - const T k(2.0); - angle_axis[0] = q1 * k; - angle_axis[1] = q2 * k; - angle_axis[2] = q3 * k; - } -} - -template <typename T> -void RotationMatrixToQuaternion(const T* R, T* angle_axis) { - RotationMatrixToQuaternion(ColumnMajorAdapter3x3(R), angle_axis); -} - -// This algorithm comes from "Quaternion Calculus and Fast Animation", -// Ken Shoemake, 1987 SIGGRAPH course notes -template <typename T, int row_stride, int col_stride> -void RotationMatrixToQuaternion( - const MatrixAdapter<const T, row_stride, col_stride>& R, - T* quaternion) { - const T trace = R(0, 0) + R(1, 1) + R(2, 2); - if (trace >= 0.0) { - T t = sqrt(trace + T(1.0)); - quaternion[0] = T(0.5) * t; - t = T(0.5) / t; - quaternion[1] = (R(2, 1) - R(1, 2)) * t; - quaternion[2] = (R(0, 2) - R(2, 0)) * t; - quaternion[3] = (R(1, 0) - R(0, 1)) * t; - } else { - int i = 0; - if (R(1, 1) > R(0, 0)) { - i = 1; - } - - if (R(2, 2) > R(i, i)) { - i = 2; - } - - const int j = (i + 1) % 3; - const int k = (j + 1) % 3; - T t = sqrt(R(i, i) - R(j, j) - R(k, k) + T(1.0)); - quaternion[i + 1] = T(0.5) * t; - t = T(0.5) / t; - quaternion[0] = (R(k, j) - R(j, k)) * t; - quaternion[j + 1] = (R(j, i) + R(i, j)) * t; - quaternion[k + 1] = (R(k, i) + R(i, k)) * t; - } -} - -// The conversion of a rotation matrix to the angle-axis form is -// numerically problematic when then rotation angle is close to zero -// or to Pi. The following implementation detects when these two cases -// occurs and deals with them by taking code paths that are guaranteed -// to not perform division by a small number. -template <typename T> -inline void RotationMatrixToAngleAxis(const T* R, T* angle_axis) { - RotationMatrixToAngleAxis(ColumnMajorAdapter3x3(R), angle_axis); -} - -template <typename T, int row_stride, int col_stride> -void RotationMatrixToAngleAxis( - const MatrixAdapter<const T, row_stride, col_stride>& R, - T* angle_axis) { - T quaternion[4]; - RotationMatrixToQuaternion(R, quaternion); - QuaternionToAngleAxis(quaternion, angle_axis); - return; -} - -template <typename T> -inline void AngleAxisToRotationMatrix(const T* angle_axis, T* R) { - AngleAxisToRotationMatrix(angle_axis, ColumnMajorAdapter3x3(R)); -} - -template <typename T, int row_stride, int col_stride> -void AngleAxisToRotationMatrix( - const T* angle_axis, - const MatrixAdapter<T, row_stride, col_stride>& R) { - static const T kOne = T(1.0); - const T theta2 = DotProduct(angle_axis, angle_axis); - if (theta2 > T(std::numeric_limits<double>::epsilon())) { - // We want to be careful to only evaluate the square root if the - // norm of the angle_axis vector is greater than zero. Otherwise - // we get a division by zero. - const T theta = sqrt(theta2); - const T wx = angle_axis[0] / theta; - const T wy = angle_axis[1] / theta; - const T wz = angle_axis[2] / theta; - - const T costheta = cos(theta); - const T sintheta = sin(theta); - - R(0, 0) = costheta + wx*wx*(kOne - costheta); - R(1, 0) = wz*sintheta + wx*wy*(kOne - costheta); - R(2, 0) = -wy*sintheta + wx*wz*(kOne - costheta); - R(0, 1) = wx*wy*(kOne - costheta) - wz*sintheta; - R(1, 1) = costheta + wy*wy*(kOne - costheta); - R(2, 1) = wx*sintheta + wy*wz*(kOne - costheta); - R(0, 2) = wy*sintheta + wx*wz*(kOne - costheta); - R(1, 2) = -wx*sintheta + wy*wz*(kOne - costheta); - R(2, 2) = costheta + wz*wz*(kOne - costheta); - } else { - // Near zero, we switch to using the first order Taylor expansion. - R(0, 0) = kOne; - R(1, 0) = angle_axis[2]; - R(2, 0) = -angle_axis[1]; - R(0, 1) = -angle_axis[2]; - R(1, 1) = kOne; - R(2, 1) = angle_axis[0]; - R(0, 2) = angle_axis[1]; - R(1, 2) = -angle_axis[0]; - R(2, 2) = kOne; - } -} - -template <typename T> -inline void EulerAnglesToRotationMatrix(const T* euler, - const int row_stride_parameter, - T* R) { - CHECK_EQ(row_stride_parameter, 3); - EulerAnglesToRotationMatrix(euler, RowMajorAdapter3x3(R)); -} - -template <typename T, int row_stride, int col_stride> -void EulerAnglesToRotationMatrix( - const T* euler, - const MatrixAdapter<T, row_stride, col_stride>& R) { - const double kPi = 3.14159265358979323846; - const T degrees_to_radians(kPi / 180.0); - - const T pitch(euler[0] * degrees_to_radians); - const T roll(euler[1] * degrees_to_radians); - const T yaw(euler[2] * degrees_to_radians); - - const T c1 = cos(yaw); - const T s1 = sin(yaw); - const T c2 = cos(roll); - const T s2 = sin(roll); - const T c3 = cos(pitch); - const T s3 = sin(pitch); - - R(0, 0) = c1*c2; - R(0, 1) = -s1*c3 + c1*s2*s3; - R(0, 2) = s1*s3 + c1*s2*c3; - - R(1, 0) = s1*c2; - R(1, 1) = c1*c3 + s1*s2*s3; - R(1, 2) = -c1*s3 + s1*s2*c3; - - R(2, 0) = -s2; - R(2, 1) = c2*s3; - R(2, 2) = c2*c3; -} - -template <typename T> inline -void QuaternionToScaledRotation(const T q[4], T R[3 * 3]) { - QuaternionToScaledRotation(q, RowMajorAdapter3x3(R)); -} - -template <typename T, int row_stride, int col_stride> inline -void QuaternionToScaledRotation( - const T q[4], - const MatrixAdapter<T, row_stride, col_stride>& R) { - // Make convenient names for elements of q. - T a = q[0]; - T b = q[1]; - T c = q[2]; - T d = q[3]; - // This is not to eliminate common sub-expression, but to - // make the lines shorter so that they fit in 80 columns! - T aa = a * a; - T ab = a * b; - T ac = a * c; - T ad = a * d; - T bb = b * b; - T bc = b * c; - T bd = b * d; - T cc = c * c; - T cd = c * d; - T dd = d * d; - - R(0, 0) = aa + bb - cc - dd; R(0, 1) = T(2) * (bc - ad); R(0, 2) = T(2) * (ac + bd); // NOLINT - R(1, 0) = T(2) * (ad + bc); R(1, 1) = aa - bb + cc - dd; R(1, 2) = T(2) * (cd - ab); // NOLINT - R(2, 0) = T(2) * (bd - ac); R(2, 1) = T(2) * (ab + cd); R(2, 2) = aa - bb - cc + dd; // NOLINT -} - -template <typename T> inline -void QuaternionToRotation(const T q[4], T R[3 * 3]) { - QuaternionToRotation(q, RowMajorAdapter3x3(R)); -} - -template <typename T, int row_stride, int col_stride> inline -void QuaternionToRotation(const T q[4], - const MatrixAdapter<T, row_stride, col_stride>& R) { - QuaternionToScaledRotation(q, R); - - T normalizer = q[0]*q[0] + q[1]*q[1] + q[2]*q[2] + q[3]*q[3]; - CHECK_NE(normalizer, T(0)); - normalizer = T(1) / normalizer; - - for (int i = 0; i < 3; ++i) { - for (int j = 0; j < 3; ++j) { - R(i, j) *= normalizer; - } - } -} - -template <typename T> inline -void UnitQuaternionRotatePoint(const T q[4], const T pt[3], T result[3]) { - const T t2 = q[0] * q[1]; - const T t3 = q[0] * q[2]; - const T t4 = q[0] * q[3]; - const T t5 = -q[1] * q[1]; - const T t6 = q[1] * q[2]; - const T t7 = q[1] * q[3]; - const T t8 = -q[2] * q[2]; - const T t9 = q[2] * q[3]; - const T t1 = -q[3] * q[3]; - result[0] = T(2) * ((t8 + t1) * pt[0] + (t6 - t4) * pt[1] + (t3 + t7) * pt[2]) + pt[0]; // NOLINT - result[1] = T(2) * ((t4 + t6) * pt[0] + (t5 + t1) * pt[1] + (t9 - t2) * pt[2]) + pt[1]; // NOLINT - result[2] = T(2) * ((t7 - t3) * pt[0] + (t2 + t9) * pt[1] + (t5 + t8) * pt[2]) + pt[2]; // NOLINT -} - -template <typename T> inline -void QuaternionRotatePoint(const T q[4], const T pt[3], T result[3]) { - // 'scale' is 1 / norm(q). - const T scale = T(1) / sqrt(q[0] * q[0] + - q[1] * q[1] + - q[2] * q[2] + - q[3] * q[3]); - - // Make unit-norm version of q. - const T unit[4] = { - scale * q[0], - scale * q[1], - scale * q[2], - scale * q[3], - }; - - UnitQuaternionRotatePoint(unit, pt, result); -} - -template<typename T> inline -void QuaternionProduct(const T z[4], const T w[4], T zw[4]) { - zw[0] = z[0] * w[0] - z[1] * w[1] - z[2] * w[2] - z[3] * w[3]; - zw[1] = z[0] * w[1] + z[1] * w[0] + z[2] * w[3] - z[3] * w[2]; - zw[2] = z[0] * w[2] - z[1] * w[3] + z[2] * w[0] + z[3] * w[1]; - zw[3] = z[0] * w[3] + z[1] * w[2] - z[2] * w[1] + z[3] * w[0]; -} - -// xy = x cross y; -template<typename T> inline -void CrossProduct(const T x[3], const T y[3], T x_cross_y[3]) { - x_cross_y[0] = x[1] * y[2] - x[2] * y[1]; - x_cross_y[1] = x[2] * y[0] - x[0] * y[2]; - x_cross_y[2] = x[0] * y[1] - x[1] * y[0]; -} - -template<typename T> inline -T DotProduct(const T x[3], const T y[3]) { - return (x[0] * y[0] + x[1] * y[1] + x[2] * y[2]); -} - -template<typename T> inline -void AngleAxisRotatePoint(const T angle_axis[3], const T pt[3], T result[3]) { - const T theta2 = DotProduct(angle_axis, angle_axis); - if (theta2 > T(std::numeric_limits<double>::epsilon())) { - // Away from zero, use the rodriguez formula - // - // result = pt costheta + - // (w x pt) * sintheta + - // w (w . pt) (1 - costheta) - // - // We want to be careful to only evaluate the square root if the - // norm of the angle_axis vector is greater than zero. Otherwise - // we get a division by zero. - // - const T theta = sqrt(theta2); - const T costheta = cos(theta); - const T sintheta = sin(theta); - const T theta_inverse = 1.0 / theta; - - const T w[3] = { angle_axis[0] * theta_inverse, - angle_axis[1] * theta_inverse, - angle_axis[2] * theta_inverse }; - - // Explicitly inlined evaluation of the cross product for - // performance reasons. - const T w_cross_pt[3] = { w[1] * pt[2] - w[2] * pt[1], - w[2] * pt[0] - w[0] * pt[2], - w[0] * pt[1] - w[1] * pt[0] }; - const T tmp = - (w[0] * pt[0] + w[1] * pt[1] + w[2] * pt[2]) * (T(1.0) - costheta); - - result[0] = pt[0] * costheta + w_cross_pt[0] * sintheta + w[0] * tmp; - result[1] = pt[1] * costheta + w_cross_pt[1] * sintheta + w[1] * tmp; - result[2] = pt[2] * costheta + w_cross_pt[2] * sintheta + w[2] * tmp; - } else { - // Near zero, the first order Taylor approximation of the rotation - // matrix R corresponding to a vector w and angle w is - // - // R = I + hat(w) * sin(theta) - // - // But sintheta ~ theta and theta * w = angle_axis, which gives us - // - // R = I + hat(w) - // - // and actually performing multiplication with the point pt, gives us - // R * pt = pt + w x pt. - // - // Switching to the Taylor expansion near zero provides meaningful - // derivatives when evaluated using Jets. - // - // Explicitly inlined evaluation of the cross product for - // performance reasons. - const T w_cross_pt[3] = { angle_axis[1] * pt[2] - angle_axis[2] * pt[1], - angle_axis[2] * pt[0] - angle_axis[0] * pt[2], - angle_axis[0] * pt[1] - angle_axis[1] * pt[0] }; - - result[0] = pt[0] + w_cross_pt[0]; - result[1] = pt[1] + w_cross_pt[1]; - result[2] = pt[2] + w_cross_pt[2]; - } -} - -} // namespace ceres - -#endif // CERES_PUBLIC_ROTATION_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/sized_cost_function.h b/extern/libmv/third_party/ceres/include/ceres/sized_cost_function.h deleted file mode 100644 index b10421e81be..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/sized_cost_function.h +++ /dev/null @@ -1,96 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// A convenience class for cost functions which are statically sized. -// Compared to the dynamically-sized base class, this reduces boilerplate. -// -// The kNumResiduals template parameter can be a constant such as 2 or 5, or it -// can be ceres::DYNAMIC. If kNumResiduals is ceres::DYNAMIC, then subclasses -// are responsible for calling set_num_residuals() at runtime. - -#ifndef CERES_PUBLIC_SIZED_COST_FUNCTION_H_ -#define CERES_PUBLIC_SIZED_COST_FUNCTION_H_ - -#include "ceres/types.h" -#include "ceres/cost_function.h" -#include "glog/logging.h" - -namespace ceres { - -template<int kNumResiduals, - int N0 = 0, int N1 = 0, int N2 = 0, int N3 = 0, int N4 = 0, - int N5 = 0, int N6 = 0, int N7 = 0, int N8 = 0, int N9 = 0> -class SizedCostFunction : public CostFunction { - public: - SizedCostFunction() { - CHECK(kNumResiduals > 0 || kNumResiduals == DYNAMIC) - << "Cost functions must have at least one residual block."; - - // This block breaks the 80 column rule to keep it somewhat readable. - CHECK((!N1 && !N2 && !N3 && !N4 && !N5 && !N6 && !N7 && !N8 && !N9) || - ((N1 > 0) && !N2 && !N3 && !N4 && !N5 && !N6 && !N7 && !N8 && !N9) || - ((N1 > 0) && (N2 > 0) && !N3 && !N4 && !N5 && !N6 && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && !N4 && !N5 && !N6 && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && !N5 && !N6 && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && !N6 && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && (N6 > 0) && !N7 && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && (N6 > 0) && (N7 > 0) && !N8 && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && (N6 > 0) && (N7 > 0) && (N8 > 0) && !N9) || // NOLINT - ((N1 > 0) && (N2 > 0) && (N3 > 0) && (N4 > 0) && (N5 > 0) && (N6 > 0) && (N7 > 0) && (N8 > 0) && (N9 > 0))) // NOLINT - << "Zero block cannot precede a non-zero block. Block sizes are " - << "(ignore trailing 0s): " << N0 << ", " << N1 << ", " << N2 << ", " - << N3 << ", " << N4 << ", " << N5 << ", " << N6 << ", " << N7 << ", " - << N8 << ", " << N9; - - set_num_residuals(kNumResiduals); - -#define CERES_ADD_PARAMETER_BLOCK(N) \ - if (N) mutable_parameter_block_sizes()->push_back(N); - CERES_ADD_PARAMETER_BLOCK(N0); - CERES_ADD_PARAMETER_BLOCK(N1); - CERES_ADD_PARAMETER_BLOCK(N2); - CERES_ADD_PARAMETER_BLOCK(N3); - CERES_ADD_PARAMETER_BLOCK(N4); - CERES_ADD_PARAMETER_BLOCK(N5); - CERES_ADD_PARAMETER_BLOCK(N6); - CERES_ADD_PARAMETER_BLOCK(N7); - CERES_ADD_PARAMETER_BLOCK(N8); - CERES_ADD_PARAMETER_BLOCK(N9); -#undef CERES_ADD_PARAMETER_BLOCK - } - - virtual ~SizedCostFunction() { } - - // Subclasses must implement Evaluate(). -}; - -} // namespace ceres - -#endif // CERES_PUBLIC_SIZED_COST_FUNCTION_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/solver.h b/extern/libmv/third_party/ceres/include/ceres/solver.h deleted file mode 100644 index 318cf48cb83..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/solver.h +++ /dev/null @@ -1,1028 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_PUBLIC_SOLVER_H_ -#define CERES_PUBLIC_SOLVER_H_ - -#include <cmath> -#include <string> -#include <vector> -#include "ceres/crs_matrix.h" -#include "ceres/internal/macros.h" -#include "ceres/internal/port.h" -#include "ceres/iteration_callback.h" -#include "ceres/ordered_groups.h" -#include "ceres/types.h" -#include "ceres/internal/disable_warnings.h" - -namespace ceres { - -class Problem; - -// Interface for non-linear least squares solvers. -class CERES_EXPORT Solver { - public: - virtual ~Solver(); - - // The options structure contains, not surprisingly, options that control how - // the solver operates. The defaults should be suitable for a wide range of - // problems; however, better performance is often obtainable with tweaking. - // - // The constants are defined inside types.h - struct CERES_EXPORT Options { - // Default constructor that sets up a generic sparse problem. - Options() { - minimizer_type = TRUST_REGION; - line_search_direction_type = LBFGS; - line_search_type = WOLFE; - nonlinear_conjugate_gradient_type = FLETCHER_REEVES; - max_lbfgs_rank = 20; - use_approximate_eigenvalue_bfgs_scaling = false; - line_search_interpolation_type = CUBIC; - min_line_search_step_size = 1e-9; - line_search_sufficient_function_decrease = 1e-4; - max_line_search_step_contraction = 1e-3; - min_line_search_step_contraction = 0.6; - max_num_line_search_step_size_iterations = 20; - max_num_line_search_direction_restarts = 5; - line_search_sufficient_curvature_decrease = 0.9; - max_line_search_step_expansion = 10.0; - trust_region_strategy_type = LEVENBERG_MARQUARDT; - dogleg_type = TRADITIONAL_DOGLEG; - use_nonmonotonic_steps = false; - max_consecutive_nonmonotonic_steps = 5; - max_num_iterations = 50; - max_solver_time_in_seconds = 1e9; - num_threads = 1; - initial_trust_region_radius = 1e4; - max_trust_region_radius = 1e16; - min_trust_region_radius = 1e-32; - min_relative_decrease = 1e-3; - min_lm_diagonal = 1e-6; - max_lm_diagonal = 1e32; - max_num_consecutive_invalid_steps = 5; - function_tolerance = 1e-6; - gradient_tolerance = 1e-10; - parameter_tolerance = 1e-8; - -#if defined(CERES_NO_SUITESPARSE) && defined(CERES_NO_CXSPARSE) && !defined(CERES_ENABLE_LGPL_CODE) // NOLINT - linear_solver_type = DENSE_QR; -#else - linear_solver_type = SPARSE_NORMAL_CHOLESKY; -#endif - - preconditioner_type = JACOBI; - visibility_clustering_type = CANONICAL_VIEWS; - dense_linear_algebra_library_type = EIGEN; - - // Choose a default sparse linear algebra library in the order: - // - // SUITE_SPARSE > CX_SPARSE > EIGEN_SPARSE > NO_SPARSE - sparse_linear_algebra_library_type = NO_SPARSE; -#if !defined(CERES_NO_SUITESPARSE) - sparse_linear_algebra_library_type = SUITE_SPARSE; -#else - #if !defined(CERES_NO_CXSPARSE) - sparse_linear_algebra_library_type = CX_SPARSE; - #else - #if defined(CERES_USE_EIGEN_SPARSE) - sparse_linear_algebra_library_type = EIGEN_SPARSE; - #endif - #endif -#endif - - num_linear_solver_threads = 1; - use_explicit_schur_complement = false; - use_postordering = false; - dynamic_sparsity = false; - min_linear_solver_iterations = 0; - max_linear_solver_iterations = 500; - eta = 1e-1; - jacobi_scaling = true; - use_inner_iterations = false; - inner_iteration_tolerance = 1e-3; - logging_type = PER_MINIMIZER_ITERATION; - minimizer_progress_to_stdout = false; - trust_region_problem_dump_directory = "/tmp"; - trust_region_problem_dump_format_type = TEXTFILE; - check_gradients = false; - gradient_check_relative_precision = 1e-8; - numeric_derivative_relative_step_size = 1e-6; - update_state_every_iteration = false; - } - - // Returns true if the options struct has a valid - // configuration. Returns false otherwise, and fills in *error - // with a message describing the problem. - bool IsValid(std::string* error) const; - - // Minimizer options ---------------------------------------- - - // Ceres supports the two major families of optimization strategies - - // Trust Region and Line Search. - // - // 1. The line search approach first finds a descent direction - // along which the objective function will be reduced and then - // computes a step size that decides how far should move along - // that direction. The descent direction can be computed by - // various methods, such as gradient descent, Newton's method and - // Quasi-Newton method. The step size can be determined either - // exactly or inexactly. - // - // 2. The trust region approach approximates the objective - // function using using a model function (often a quadratic) over - // a subset of the search space known as the trust region. If the - // model function succeeds in minimizing the true objective - // function the trust region is expanded; conversely, otherwise it - // is contracted and the model optimization problem is solved - // again. - // - // Trust region methods are in some sense dual to line search methods: - // trust region methods first choose a step size (the size of the - // trust region) and then a step direction while line search methods - // first choose a step direction and then a step size. - MinimizerType minimizer_type; - - LineSearchDirectionType line_search_direction_type; - LineSearchType line_search_type; - NonlinearConjugateGradientType nonlinear_conjugate_gradient_type; - - // The LBFGS hessian approximation is a low rank approximation to - // the inverse of the Hessian matrix. The rank of the - // approximation determines (linearly) the space and time - // complexity of using the approximation. Higher the rank, the - // better is the quality of the approximation. The increase in - // quality is however is bounded for a number of reasons. - // - // 1. The method only uses secant information and not actual - // derivatives. - // - // 2. The Hessian approximation is constrained to be positive - // definite. - // - // So increasing this rank to a large number will cost time and - // space complexity without the corresponding increase in solution - // quality. There are no hard and fast rules for choosing the - // maximum rank. The best choice usually requires some problem - // specific experimentation. - // - // For more theoretical and implementation details of the LBFGS - // method, please see: - // - // Nocedal, J. (1980). "Updating Quasi-Newton Matrices with - // Limited Storage". Mathematics of Computation 35 (151): 773–782. - int max_lbfgs_rank; - - // As part of the (L)BFGS update step (BFGS) / right-multiply step (L-BFGS), - // the initial inverse Hessian approximation is taken to be the Identity. - // However, Oren showed that using instead I * \gamma, where \gamma is - // chosen to approximate an eigenvalue of the true inverse Hessian can - // result in improved convergence in a wide variety of cases. Setting - // use_approximate_eigenvalue_bfgs_scaling to true enables this scaling. - // - // It is important to note that approximate eigenvalue scaling does not - // always improve convergence, and that it can in fact significantly degrade - // performance for certain classes of problem, which is why it is disabled - // by default. In particular it can degrade performance when the - // sensitivity of the problem to different parameters varies significantly, - // as in this case a single scalar factor fails to capture this variation - // and detrimentally downscales parts of the jacobian approximation which - // correspond to low-sensitivity parameters. It can also reduce the - // robustness of the solution to errors in the jacobians. - // - // Oren S.S., Self-scaling variable metric (SSVM) algorithms - // Part II: Implementation and experiments, Management Science, - // 20(5), 863-874, 1974. - bool use_approximate_eigenvalue_bfgs_scaling; - - // Degree of the polynomial used to approximate the objective - // function. Valid values are BISECTION, QUADRATIC and CUBIC. - // - // BISECTION corresponds to pure backtracking search with no - // interpolation. - LineSearchInterpolationType line_search_interpolation_type; - - // If during the line search, the step_size falls below this - // value, it is truncated to zero. - double min_line_search_step_size; - - // Line search parameters. - - // Solving the line search problem exactly is computationally - // prohibitive. Fortunately, line search based optimization - // algorithms can still guarantee convergence if instead of an - // exact solution, the line search algorithm returns a solution - // which decreases the value of the objective function - // sufficiently. More precisely, we are looking for a step_size - // s.t. - // - // f(step_size) <= f(0) + sufficient_decrease * f'(0) * step_size - // - double line_search_sufficient_function_decrease; - - // In each iteration of the line search, - // - // new_step_size >= max_line_search_step_contraction * step_size - // - // Note that by definition, for contraction: - // - // 0 < max_step_contraction < min_step_contraction < 1 - // - double max_line_search_step_contraction; - - // In each iteration of the line search, - // - // new_step_size <= min_line_search_step_contraction * step_size - // - // Note that by definition, for contraction: - // - // 0 < max_step_contraction < min_step_contraction < 1 - // - double min_line_search_step_contraction; - - // Maximum number of trial step size iterations during each line search, - // if a step size satisfying the search conditions cannot be found within - // this number of trials, the line search will terminate. - int max_num_line_search_step_size_iterations; - - // Maximum number of restarts of the line search direction algorithm before - // terminating the optimization. Restarts of the line search direction - // algorithm occur when the current algorithm fails to produce a new descent - // direction. This typically indicates a numerical failure, or a breakdown - // in the validity of the approximations used. - int max_num_line_search_direction_restarts; - - // The strong Wolfe conditions consist of the Armijo sufficient - // decrease condition, and an additional requirement that the - // step-size be chosen s.t. the _magnitude_ ('strong' Wolfe - // conditions) of the gradient along the search direction - // decreases sufficiently. Precisely, this second condition - // is that we seek a step_size s.t. - // - // |f'(step_size)| <= sufficient_curvature_decrease * |f'(0)| - // - // Where f() is the line search objective and f'() is the derivative - // of f w.r.t step_size (d f / d step_size). - double line_search_sufficient_curvature_decrease; - - // During the bracketing phase of the Wolfe search, the step size is - // increased until either a point satisfying the Wolfe conditions is - // found, or an upper bound for a bracket containing a point satisfying - // the conditions is found. Precisely, at each iteration of the - // expansion: - // - // new_step_size <= max_step_expansion * step_size. - // - // By definition for expansion, max_step_expansion > 1.0. - double max_line_search_step_expansion; - - TrustRegionStrategyType trust_region_strategy_type; - - // Type of dogleg strategy to use. - DoglegType dogleg_type; - - // The classical trust region methods are descent methods, in that - // they only accept a point if it strictly reduces the value of - // the objective function. - // - // Relaxing this requirement allows the algorithm to be more - // efficient in the long term at the cost of some local increase - // in the value of the objective function. - // - // This is because allowing for non-decreasing objective function - // values in a princpled manner allows the algorithm to "jump over - // boulders" as the method is not restricted to move into narrow - // valleys while preserving its convergence properties. - // - // Setting use_nonmonotonic_steps to true enables the - // non-monotonic trust region algorithm as described by Conn, - // Gould & Toint in "Trust Region Methods", Section 10.1. - // - // The parameter max_consecutive_nonmonotonic_steps controls the - // window size used by the step selection algorithm to accept - // non-monotonic steps. - // - // Even though the value of the objective function may be larger - // than the minimum value encountered over the course of the - // optimization, the final parameters returned to the user are the - // ones corresponding to the minimum cost over all iterations. - bool use_nonmonotonic_steps; - int max_consecutive_nonmonotonic_steps; - - // Maximum number of iterations for the minimizer to run for. - int max_num_iterations; - - // Maximum time for which the minimizer should run for. - double max_solver_time_in_seconds; - - // Number of threads used by Ceres for evaluating the cost and - // jacobians. - int num_threads; - - // Trust region minimizer settings. - double initial_trust_region_radius; - double max_trust_region_radius; - - // Minimizer terminates when the trust region radius becomes - // smaller than this value. - double min_trust_region_radius; - - // Lower bound for the relative decrease before a step is - // accepted. - double min_relative_decrease; - - // For the Levenberg-Marquadt algorithm, the scaled diagonal of - // the normal equations J'J is used to control the size of the - // trust region. Extremely small and large values along the - // diagonal can make this regularization scheme - // fail. max_lm_diagonal and min_lm_diagonal, clamp the values of - // diag(J'J) from above and below. In the normal course of - // operation, the user should not have to modify these parameters. - double min_lm_diagonal; - double max_lm_diagonal; - - // Sometimes due to numerical conditioning problems or linear - // solver flakiness, the trust region strategy may return a - // numerically invalid step that can be fixed by reducing the - // trust region size. So the TrustRegionMinimizer allows for a few - // successive invalid steps before it declares NUMERICAL_FAILURE. - int max_num_consecutive_invalid_steps; - - // Minimizer terminates when - // - // (new_cost - old_cost) < function_tolerance * old_cost; - // - double function_tolerance; - - // Minimizer terminates when - // - // max_i |x - Project(Plus(x, -g(x))| < gradient_tolerance - // - // This value should typically be 1e-4 * function_tolerance. - double gradient_tolerance; - - // Minimizer terminates when - // - // |step|_2 <= parameter_tolerance * ( |x|_2 + parameter_tolerance) - // - double parameter_tolerance; - - // Linear least squares solver options ------------------------------------- - - LinearSolverType linear_solver_type; - - // Type of preconditioner to use with the iterative linear solvers. - PreconditionerType preconditioner_type; - - // Type of clustering algorithm to use for visibility based - // preconditioning. This option is used only when the - // preconditioner_type is CLUSTER_JACOBI or CLUSTER_TRIDIAGONAL. - VisibilityClusteringType visibility_clustering_type; - - // Ceres supports using multiple dense linear algebra libraries - // for dense matrix factorizations. Currently EIGEN and LAPACK are - // the valid choices. EIGEN is always available, LAPACK refers to - // the system BLAS + LAPACK library which may or may not be - // available. - // - // This setting affects the DENSE_QR, DENSE_NORMAL_CHOLESKY and - // DENSE_SCHUR solvers. For small to moderate sized probem EIGEN - // is a fine choice but for large problems, an optimized LAPACK + - // BLAS implementation can make a substantial difference in - // performance. - DenseLinearAlgebraLibraryType dense_linear_algebra_library_type; - - // Ceres supports using multiple sparse linear algebra libraries - // for sparse matrix ordering and factorizations. Currently, - // SUITE_SPARSE and CX_SPARSE are the valid choices, depending on - // whether they are linked into Ceres at build time. - SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type; - - // Number of threads used by Ceres to solve the Newton - // step. Currently only the SPARSE_SCHUR solver is capable of - // using this setting. - int num_linear_solver_threads; - - // The order in which variables are eliminated in a linear solver - // can have a significant of impact on the efficiency and accuracy - // of the method. e.g., when doing sparse Cholesky factorization, - // there are matrices for which a good ordering will give a - // Cholesky factor with O(n) storage, where as a bad ordering will - // result in an completely dense factor. - // - // Ceres allows the user to provide varying amounts of hints to - // the solver about the variable elimination ordering to use. This - // can range from no hints, where the solver is free to decide the - // best possible ordering based on the user's choices like the - // linear solver being used, to an exact order in which the - // variables should be eliminated, and a variety of possibilities - // in between. - // - // Instances of the ParameterBlockOrdering class are used to - // communicate this information to Ceres. - // - // Formally an ordering is an ordered partitioning of the - // parameter blocks, i.e, each parameter block belongs to exactly - // one group, and each group has a unique non-negative integer - // associated with it, that determines its order in the set of - // groups. - // - // Given such an ordering, Ceres ensures that the parameter blocks in - // the lowest numbered group are eliminated first, and then the - // parmeter blocks in the next lowest numbered group and so on. Within - // each group, Ceres is free to order the parameter blocks as it - // chooses. - // - // If NULL, then all parameter blocks are assumed to be in the - // same group and the solver is free to decide the best - // ordering. - // - // e.g. Consider the linear system - // - // x + y = 3 - // 2x + 3y = 7 - // - // There are two ways in which it can be solved. First eliminating x - // from the two equations, solving for y and then back substituting - // for x, or first eliminating y, solving for x and back substituting - // for y. The user can construct three orderings here. - // - // {0: x}, {1: y} - eliminate x first. - // {0: y}, {1: x} - eliminate y first. - // {0: x, y} - Solver gets to decide the elimination order. - // - // Thus, to have Ceres determine the ordering automatically using - // heuristics, put all the variables in group 0 and to control the - // ordering for every variable, create groups 0..N-1, one per - // variable, in the desired order. - // - // Bundle Adjustment - // ----------------- - // - // A particular case of interest is bundle adjustment, where the user - // has two options. The default is to not specify an ordering at all, - // the solver will see that the user wants to use a Schur type solver - // and figure out the right elimination ordering. - // - // But if the user already knows what parameter blocks are points and - // what are cameras, they can save preprocessing time by partitioning - // the parameter blocks into two groups, one for the points and one - // for the cameras, where the group containing the points has an id - // smaller than the group containing cameras. - shared_ptr<ParameterBlockOrdering> linear_solver_ordering; - - // Use an explicitly computed Schur complement matrix with - // ITERATIVE_SCHUR. - // - // By default this option is disabled and ITERATIVE_SCHUR - // evaluates evaluates matrix-vector products between the Schur - // complement and a vector implicitly by exploiting the algebraic - // expression for the Schur complement. - // - // The cost of this evaluation scales with the number of non-zeros - // in the Jacobian. - // - // For small to medium sized problems there is a sweet spot where - // computing the Schur complement is cheap enough that it is much - // more efficient to explicitly compute it and use it for evaluating - // the matrix-vector products. - // - // Enabling this option tells ITERATIVE_SCHUR to use an explicitly - // computed Schur complement. - // - // NOTE: This option can only be used with the SCHUR_JACOBI - // preconditioner. - bool use_explicit_schur_complement; - - // Sparse Cholesky factorization algorithms use a fill-reducing - // ordering to permute the columns of the Jacobian matrix. There - // are two ways of doing this. - - // 1. Compute the Jacobian matrix in some order and then have the - // factorization algorithm permute the columns of the Jacobian. - - // 2. Compute the Jacobian with its columns already permuted. - - // The first option incurs a significant memory penalty. The - // factorization algorithm has to make a copy of the permuted - // Jacobian matrix, thus Ceres pre-permutes the columns of the - // Jacobian matrix and generally speaking, there is no performance - // penalty for doing so. - - // In some rare cases, it is worth using a more complicated - // reordering algorithm which has slightly better runtime - // performance at the expense of an extra copy of the Jacobian - // matrix. Setting use_postordering to true enables this tradeoff. - bool use_postordering; - - // Some non-linear least squares problems are symbolically dense but - // numerically sparse. i.e. at any given state only a small number - // of jacobian entries are non-zero, but the position and number of - // non-zeros is different depending on the state. For these problems - // it can be useful to factorize the sparse jacobian at each solver - // iteration instead of including all of the zero entries in a single - // general factorization. - // - // If your problem does not have this property (or you do not know), - // then it is probably best to keep this false, otherwise it will - // likely lead to worse performance. - - // This settings affects the SPARSE_NORMAL_CHOLESKY solver. - bool dynamic_sparsity; - - // Some non-linear least squares problems have additional - // structure in the way the parameter blocks interact that it is - // beneficial to modify the way the trust region step is computed. - // - // e.g., consider the following regression problem - // - // y = a_1 exp(b_1 x) + a_2 exp(b_3 x^2 + c_1) - // - // Given a set of pairs{(x_i, y_i)}, the user wishes to estimate - // a_1, a_2, b_1, b_2, and c_1. - // - // Notice here that the expression on the left is linear in a_1 - // and a_2, and given any value for b_1, b_2 and c_1, it is - // possible to use linear regression to estimate the optimal - // values of a_1 and a_2. Indeed, its possible to analytically - // eliminate the variables a_1 and a_2 from the problem all - // together. Problems like these are known as separable least - // squares problem and the most famous algorithm for solving them - // is the Variable Projection algorithm invented by Golub & - // Pereyra. - // - // Similar structure can be found in the matrix factorization with - // missing data problem. There the corresponding algorithm is - // known as Wiberg's algorithm. - // - // Ruhe & Wedin (Algorithms for Separable Nonlinear Least Squares - // Problems, SIAM Reviews, 22(3), 1980) present an analyis of - // various algorithms for solving separable non-linear least - // squares problems and refer to "Variable Projection" as - // Algorithm I in their paper. - // - // Implementing Variable Projection is tedious and expensive, and - // they present a simpler algorithm, which they refer to as - // Algorithm II, where once the Newton/Trust Region step has been - // computed for the whole problem (a_1, a_2, b_1, b_2, c_1) and - // additional optimization step is performed to estimate a_1 and - // a_2 exactly. - // - // This idea can be generalized to cases where the residual is not - // linear in a_1 and a_2, i.e., Solve for the trust region step - // for the full problem, and then use it as the starting point to - // further optimize just a_1 and a_2. For the linear case, this - // amounts to doing a single linear least squares solve. For - // non-linear problems, any method for solving the a_1 and a_2 - // optimization problems will do. The only constraint on a_1 and - // a_2 is that they do not co-occur in any residual block. - // - // This idea can be further generalized, by not just optimizing - // (a_1, a_2), but decomposing the graph corresponding to the - // Hessian matrix's sparsity structure in a collection of - // non-overlapping independent sets and optimizing each of them. - // - // Setting "use_inner_iterations" to true enables the use of this - // non-linear generalization of Ruhe & Wedin's Algorithm II. This - // version of Ceres has a higher iteration complexity, but also - // displays better convergence behaviour per iteration. Setting - // Solver::Options::num_threads to the maximum number possible is - // highly recommended. - bool use_inner_iterations; - - // If inner_iterations is true, then the user has two choices. - // - // 1. Let the solver heuristically decide which parameter blocks - // to optimize in each inner iteration. To do this leave - // Solver::Options::inner_iteration_ordering untouched. - // - // 2. Specify a collection of of ordered independent sets. Where - // the lower numbered groups are optimized before the higher - // number groups. Each group must be an independent set. Not - // all parameter blocks need to be present in the ordering. - shared_ptr<ParameterBlockOrdering> inner_iteration_ordering; - - // Generally speaking, inner iterations make significant progress - // in the early stages of the solve and then their contribution - // drops down sharply, at which point the time spent doing inner - // iterations is not worth it. - // - // Once the relative decrease in the objective function due to - // inner iterations drops below inner_iteration_tolerance, the use - // of inner iterations in subsequent trust region minimizer - // iterations is disabled. - double inner_iteration_tolerance; - - // Minimum number of iterations for which the linear solver should - // run, even if the convergence criterion is satisfied. - int min_linear_solver_iterations; - - // Maximum number of iterations for which the linear solver should - // run. If the solver does not converge in less than - // max_linear_solver_iterations, then it returns MAX_ITERATIONS, - // as its termination type. - int max_linear_solver_iterations; - - // Forcing sequence parameter. The truncated Newton solver uses - // this number to control the relative accuracy with which the - // Newton step is computed. - // - // This constant is passed to ConjugateGradientsSolver which uses - // it to terminate the iterations when - // - // (Q_i - Q_{i-1})/Q_i < eta/i - double eta; - - // Normalize the jacobian using Jacobi scaling before calling - // the linear least squares solver. - bool jacobi_scaling; - - // Logging options --------------------------------------------------------- - - LoggingType logging_type; - - // By default the Minimizer progress is logged to VLOG(1), which - // is sent to STDERR depending on the vlog level. If this flag is - // set to true, and logging_type is not SILENT, the logging output - // is sent to STDOUT. - bool minimizer_progress_to_stdout; - - // List of iterations at which the minimizer should dump the trust - // region problem. Useful for testing and benchmarking. If empty - // (default), no problems are dumped. - std::vector<int> trust_region_minimizer_iterations_to_dump; - - // Directory to which the problems should be written to. Should be - // non-empty if trust_region_minimizer_iterations_to_dump is - // non-empty and trust_region_problem_dump_format_type is not - // CONSOLE. - std::string trust_region_problem_dump_directory; - DumpFormatType trust_region_problem_dump_format_type; - - // Finite differences options ---------------------------------------------- - - // Check all jacobians computed by each residual block with finite - // differences. This is expensive since it involves computing the - // derivative by normal means (e.g. user specified, autodiff, - // etc), then also computing it using finite differences. The - // results are compared, and if they differ substantially, details - // are printed to the log. - bool check_gradients; - - // Relative precision to check for in the gradient checker. If the - // relative difference between an element in a jacobian exceeds - // this number, then the jacobian for that cost term is dumped. - double gradient_check_relative_precision; - - // Relative shift used for taking numeric derivatives. For finite - // differencing, each dimension is evaluated at slightly shifted - // values; for the case of central difference, this is what gets - // evaluated: - // - // delta = numeric_derivative_relative_step_size; - // f_initial = f(x) - // f_forward = f((1 + delta) * x) - // f_backward = f((1 - delta) * x) - // - // The finite differencing is done along each dimension. The - // reason to use a relative (rather than absolute) step size is - // that this way, numeric differentation works for functions where - // the arguments are typically large (e.g. 1e9) and when the - // values are small (e.g. 1e-5). It is possible to construct - // "torture cases" which break this finite difference heuristic, - // but they do not come up often in practice. - // - // TODO(keir): Pick a smarter number than the default above! In - // theory a good choice is sqrt(eps) * x, which for doubles means - // about 1e-8 * x. However, I have found this number too - // optimistic. This number should be exposed for users to change. - double numeric_derivative_relative_step_size; - - // If true, the user's parameter blocks are updated at the end of - // every Minimizer iteration, otherwise they are updated when the - // Minimizer terminates. This is useful if, for example, the user - // wishes to visualize the state of the optimization every - // iteration. - bool update_state_every_iteration; - - // Callbacks that are executed at the end of each iteration of the - // Minimizer. An iteration may terminate midway, either due to - // numerical failures or because one of the convergence tests has - // been satisfied. In this case none of the callbacks are - // executed. - - // Callbacks are executed in the order that they are specified in - // this vector. By default, parameter blocks are updated only at - // the end of the optimization, i.e when the Minimizer - // terminates. This behaviour is controlled by - // update_state_every_variable. If the user wishes to have access - // to the update parameter blocks when his/her callbacks are - // executed, then set update_state_every_iteration to true. - // - // The solver does NOT take ownership of these pointers. - std::vector<IterationCallback*> callbacks; - }; - - struct CERES_EXPORT Summary { - Summary(); - - // A brief one line description of the state of the solver after - // termination. - std::string BriefReport() const; - - // A full multiline description of the state of the solver after - // termination. - std::string FullReport() const; - - bool IsSolutionUsable() const; - - // Minimizer summary ------------------------------------------------- - MinimizerType minimizer_type; - - TerminationType termination_type; - - // Reason why the solver terminated. - std::string message; - - // Cost of the problem (value of the objective function) before - // the optimization. - double initial_cost; - - // Cost of the problem (value of the objective function) after the - // optimization. - double final_cost; - - // The part of the total cost that comes from residual blocks that - // were held fixed by the preprocessor because all the parameter - // blocks that they depend on were fixed. - double fixed_cost; - - // IterationSummary for each minimizer iteration in order. - std::vector<IterationSummary> iterations; - - // Number of minimizer iterations in which the step was - // accepted. Unless use_non_monotonic_steps is true this is also - // the number of steps in which the objective function value/cost - // went down. - int num_successful_steps; - - // Number of minimizer iterations in which the step was rejected - // either because it did not reduce the cost enough or the step - // was not numerically valid. - int num_unsuccessful_steps; - - // Number of times inner iterations were performed. - int num_inner_iteration_steps; - - // All times reported below are wall times. - - // When the user calls Solve, before the actual optimization - // occurs, Ceres performs a number of preprocessing steps. These - // include error checks, memory allocations, and reorderings. This - // time is accounted for as preprocessing time. - double preprocessor_time_in_seconds; - - // Time spent in the TrustRegionMinimizer. - double minimizer_time_in_seconds; - - // After the Minimizer is finished, some time is spent in - // re-evaluating residuals etc. This time is accounted for in the - // postprocessor time. - double postprocessor_time_in_seconds; - - // Some total of all time spent inside Ceres when Solve is called. - double total_time_in_seconds; - - // Time (in seconds) spent in the linear solver computing the - // trust region step. - double linear_solver_time_in_seconds; - - // Time (in seconds) spent evaluating the residual vector. - double residual_evaluation_time_in_seconds; - - // Time (in seconds) spent evaluating the jacobian matrix. - double jacobian_evaluation_time_in_seconds; - - // Time (in seconds) spent doing inner iterations. - double inner_iteration_time_in_seconds; - - // Cumulative timing information for line searches performed as part of the - // solve. Note that in addition to the case when the Line Search minimizer - // is used, the Trust Region minimizer also uses a line search when - // solving a constrained problem. - - // Time (in seconds) spent evaluating the univariate cost function as part - // of a line search. - double line_search_cost_evaluation_time_in_seconds; - - // Time (in seconds) spent evaluating the gradient of the univariate cost - // function as part of a line search. - double line_search_gradient_evaluation_time_in_seconds; - - // Time (in seconds) spent minimizing the interpolating polynomial - // to compute the next candidate step size as part of a line search. - double line_search_polynomial_minimization_time_in_seconds; - - // Total time (in seconds) spent performing line searches. - double line_search_total_time_in_seconds; - - // Number of parameter blocks in the problem. - int num_parameter_blocks; - - // Number of parameters in the probem. - int num_parameters; - - // Dimension of the tangent space of the problem (or the number of - // columns in the Jacobian for the problem). This is different - // from num_parameters if a parameter block is associated with a - // LocalParameterization - int num_effective_parameters; - - // Number of residual blocks in the problem. - int num_residual_blocks; - - // Number of residuals in the problem. - int num_residuals; - - // Number of parameter blocks in the problem after the inactive - // and constant parameter blocks have been removed. A parameter - // block is inactive if no residual block refers to it. - int num_parameter_blocks_reduced; - - // Number of parameters in the reduced problem. - int num_parameters_reduced; - - // Dimension of the tangent space of the reduced problem (or the - // number of columns in the Jacobian for the reduced - // problem). This is different from num_parameters_reduced if a - // parameter block in the reduced problem is associated with a - // LocalParameterization. - int num_effective_parameters_reduced; - - // Number of residual blocks in the reduced problem. - int num_residual_blocks_reduced; - - // Number of residuals in the reduced problem. - int num_residuals_reduced; - - // Is the reduced problem bounds constrained. - bool is_constrained; - - // Number of threads specified by the user for Jacobian and - // residual evaluation. - int num_threads_given; - - // Number of threads actually used by the solver for Jacobian and - // residual evaluation. This number is not equal to - // num_threads_given if OpenMP is not available. - int num_threads_used; - - // Number of threads specified by the user for solving the trust - // region problem. - int num_linear_solver_threads_given; - - // Number of threads actually used by the solver for solving the - // trust region problem. This number is not equal to - // num_threads_given if OpenMP is not available. - int num_linear_solver_threads_used; - - // Type of the linear solver requested by the user. - LinearSolverType linear_solver_type_given; - - // Type of the linear solver actually used. This may be different - // from linear_solver_type_given if Ceres determines that the - // problem structure is not compatible with the linear solver - // requested or if the linear solver requested by the user is not - // available, e.g. The user requested SPARSE_NORMAL_CHOLESKY but - // no sparse linear algebra library was available. - LinearSolverType linear_solver_type_used; - - // Size of the elimination groups given by the user as hints to - // the linear solver. - std::vector<int> linear_solver_ordering_given; - - // Size of the parameter groups used by the solver when ordering - // the columns of the Jacobian. This maybe different from - // linear_solver_ordering_given if the user left - // linear_solver_ordering_given blank and asked for an automatic - // ordering, or if the problem contains some constant or inactive - // parameter blocks. - std::vector<int> linear_solver_ordering_used; - - // True if the user asked for inner iterations to be used as part - // of the optimization. - bool inner_iterations_given; - - // True if the user asked for inner iterations to be used as part - // of the optimization and the problem structure was such that - // they were actually performed. e.g., in a problem with just one - // parameter block, inner iterations are not performed. - bool inner_iterations_used; - - // Size of the parameter groups given by the user for performing - // inner iterations. - std::vector<int> inner_iteration_ordering_given; - - // Size of the parameter groups given used by the solver for - // performing inner iterations. This maybe different from - // inner_iteration_ordering_given if the user left - // inner_iteration_ordering_given blank and asked for an automatic - // ordering, or if the problem contains some constant or inactive - // parameter blocks. - std::vector<int> inner_iteration_ordering_used; - - // Type of the preconditioner requested by the user. - PreconditionerType preconditioner_type_given; - - // Type of the preconditioner actually used. This may be different - // from linear_solver_type_given if Ceres determines that the - // problem structure is not compatible with the linear solver - // requested or if the linear solver requested by the user is not - // available. - PreconditionerType preconditioner_type_used; - - // Type of clustering algorithm used for visibility based - // preconditioning. Only meaningful when the preconditioner_type - // is CLUSTER_JACOBI or CLUSTER_TRIDIAGONAL. - VisibilityClusteringType visibility_clustering_type; - - // Type of trust region strategy. - TrustRegionStrategyType trust_region_strategy_type; - - // Type of dogleg strategy used for solving the trust region - // problem. - DoglegType dogleg_type; - - // Type of the dense linear algebra library used. - DenseLinearAlgebraLibraryType dense_linear_algebra_library_type; - - // Type of the sparse linear algebra library used. - SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type; - - // Type of line search direction used. - LineSearchDirectionType line_search_direction_type; - - // Type of the line search algorithm used. - LineSearchType line_search_type; - - // When performing line search, the degree of the polynomial used - // to approximate the objective function. - LineSearchInterpolationType line_search_interpolation_type; - - // If the line search direction is NONLINEAR_CONJUGATE_GRADIENT, - // then this indicates the particular variant of non-linear - // conjugate gradient used. - NonlinearConjugateGradientType nonlinear_conjugate_gradient_type; - - // If the type of the line search direction is LBFGS, then this - // indicates the rank of the Hessian approximation. - int max_lbfgs_rank; - }; - - // Once a least squares problem has been built, this function takes - // the problem and optimizes it based on the values of the options - // parameters. Upon return, a detailed summary of the work performed - // by the preprocessor, the non-linear minmizer and the linear - // solver are reported in the summary object. - virtual void Solve(const Options& options, - Problem* problem, - Solver::Summary* summary); -}; - -// Helper function which avoids going through the interface. -CERES_EXPORT void Solve(const Solver::Options& options, - Problem* problem, - Solver::Summary* summary); - -} // namespace ceres - -#include "ceres/internal/reenable_warnings.h" - -#endif // CERES_PUBLIC_SOLVER_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/types.h b/extern/libmv/third_party/ceres/include/ceres/types.h deleted file mode 100644 index 2ea41803629..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/types.h +++ /dev/null @@ -1,508 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Enums and other top level class definitions. -// -// Note: internal/types.cc defines stringification routines for some -// of these enums. Please update those routines if you extend or -// remove enums from here. - -#ifndef CERES_PUBLIC_TYPES_H_ -#define CERES_PUBLIC_TYPES_H_ - -#include <string> - -#include "ceres/internal/port.h" -#include "ceres/internal/disable_warnings.h" - -namespace ceres { - -// Basic integer types. These typedefs are in the Ceres namespace to avoid -// conflicts with other packages having similar typedefs. -typedef int int32; - -// Argument type used in interfaces that can optionally take ownership -// of a passed in argument. If TAKE_OWNERSHIP is passed, the called -// object takes ownership of the pointer argument, and will call -// delete on it upon completion. -enum Ownership { - DO_NOT_TAKE_OWNERSHIP, - TAKE_OWNERSHIP -}; - -// TODO(keir): Considerably expand the explanations of each solver type. -enum LinearSolverType { - // These solvers are for general rectangular systems formed from the - // normal equations A'A x = A'b. They are direct solvers and do not - // assume any special problem structure. - - // Solve the normal equations using a dense Cholesky solver; based - // on Eigen. - DENSE_NORMAL_CHOLESKY, - - // Solve the normal equations using a dense QR solver; based on - // Eigen. - DENSE_QR, - - // Solve the normal equations using a sparse cholesky solver; requires - // SuiteSparse or CXSparse. - SPARSE_NORMAL_CHOLESKY, - - // Specialized solvers, specific to problems with a generalized - // bi-partitite structure. - - // Solves the reduced linear system using a dense Cholesky solver; - // based on Eigen. - DENSE_SCHUR, - - // Solves the reduced linear system using a sparse Cholesky solver; - // based on CHOLMOD. - SPARSE_SCHUR, - - // Solves the reduced linear system using Conjugate Gradients, based - // on a new Ceres implementation. Suitable for large scale - // problems. - ITERATIVE_SCHUR, - - // Conjugate gradients on the normal equations. - CGNR -}; - -enum PreconditionerType { - // Trivial preconditioner - the identity matrix. - IDENTITY, - - // Block diagonal of the Gauss-Newton Hessian. - JACOBI, - - // Note: The following three preconditioners can only be used with - // the ITERATIVE_SCHUR solver. They are well suited for Structure - // from Motion problems. - - // Block diagonal of the Schur complement. This preconditioner may - // only be used with the ITERATIVE_SCHUR solver. - SCHUR_JACOBI, - - // Visibility clustering based preconditioners. - // - // The following two preconditioners use the visibility structure of - // the scene to determine the sparsity structure of the - // preconditioner. This is done using a clustering algorithm. The - // available visibility clustering algorithms are described below. - // - // Note: Requires SuiteSparse. - CLUSTER_JACOBI, - CLUSTER_TRIDIAGONAL -}; - -enum VisibilityClusteringType { - // Canonical views algorithm as described in - // - // "Scene Summarization for Online Image Collections", Ian Simon, Noah - // Snavely, Steven M. Seitz, ICCV 2007. - // - // This clustering algorithm can be quite slow, but gives high - // quality clusters. The original visibility based clustering paper - // used this algorithm. - CANONICAL_VIEWS, - - // The classic single linkage algorithm. It is extremely fast as - // compared to CANONICAL_VIEWS, but can give slightly poorer - // results. For problems with large number of cameras though, this - // is generally a pretty good option. - // - // If you are using SCHUR_JACOBI preconditioner and have SuiteSparse - // available, CLUSTER_JACOBI and CLUSTER_TRIDIAGONAL in combination - // with the SINGLE_LINKAGE algorithm will generally give better - // results. - SINGLE_LINKAGE -}; - -enum SparseLinearAlgebraLibraryType { - // High performance sparse Cholesky factorization and approximate - // minimum degree ordering. - SUITE_SPARSE, - - // A lightweight replacment for SuiteSparse, which does not require - // a LAPACK/BLAS implementation. Consequently, its performance is - // also a bit lower than SuiteSparse. - CX_SPARSE, - - // Eigen's sparse linear algebra routines. In particular Ceres uses - // the Simplicial LDLT routines. - EIGEN_SPARSE, - - // No sparse linear solver should be used. This does not necessarily - // imply that Ceres was built without any sparse library, although that - // is the likely use case, merely that one should not be used. - NO_SPARSE -}; - -enum DenseLinearAlgebraLibraryType { - EIGEN, - LAPACK -}; - -// Logging options -// The options get progressively noisier. -enum LoggingType { - SILENT, - PER_MINIMIZER_ITERATION -}; - -enum MinimizerType { - LINE_SEARCH, - TRUST_REGION -}; - -enum LineSearchDirectionType { - // Negative of the gradient. - STEEPEST_DESCENT, - - // A generalization of the Conjugate Gradient method to non-linear - // functions. The generalization can be performed in a number of - // different ways, resulting in a variety of search directions. The - // precise choice of the non-linear conjugate gradient algorithm - // used is determined by NonlinerConjuateGradientType. - NONLINEAR_CONJUGATE_GRADIENT, - - // BFGS, and it's limited memory approximation L-BFGS, are quasi-Newton - // algorithms that approximate the Hessian matrix by iteratively refining - // an initial estimate with rank-one updates using the gradient at each - // iteration. They are a generalisation of the Secant method and satisfy - // the Secant equation. The Secant equation has an infinium of solutions - // in multiple dimensions, as there are N*(N+1)/2 degrees of freedom in a - // symmetric matrix but only N conditions are specified by the Secant - // equation. The requirement that the Hessian approximation be positive - // definite imposes another N additional constraints, but that still leaves - // remaining degrees-of-freedom. (L)BFGS methods uniquely deteremine the - // approximate Hessian by imposing the additional constraints that the - // approximation at the next iteration must be the 'closest' to the current - // approximation (the nature of how this proximity is measured is actually - // the defining difference between a family of quasi-Newton methods including - // (L)BFGS & DFP). (L)BFGS is currently regarded as being the best known - // general quasi-Newton method. - // - // The principal difference between BFGS and L-BFGS is that whilst BFGS - // maintains a full, dense approximation to the (inverse) Hessian, L-BFGS - // maintains only a window of the last M observations of the parameters and - // gradients. Using this observation history, the calculation of the next - // search direction can be computed without requiring the construction of the - // full dense inverse Hessian approximation. This is particularly important - // for problems with a large number of parameters, where storage of an N-by-N - // matrix in memory would be prohibitive. - // - // For more details on BFGS see: - // - // Broyden, C.G., "The Convergence of a Class of Double-rank Minimization - // Algorithms,"; J. Inst. Maths. Applics., Vol. 6, pp 76–90, 1970. - // - // Fletcher, R., "A New Approach to Variable Metric Algorithms," - // Computer Journal, Vol. 13, pp 317–322, 1970. - // - // Goldfarb, D., "A Family of Variable Metric Updates Derived by Variational - // Means," Mathematics of Computing, Vol. 24, pp 23–26, 1970. - // - // Shanno, D.F., "Conditioning of Quasi-Newton Methods for Function - // Minimization," Mathematics of Computing, Vol. 24, pp 647–656, 1970. - // - // For more details on L-BFGS see: - // - // Nocedal, J. (1980). "Updating Quasi-Newton Matrices with Limited - // Storage". Mathematics of Computation 35 (151): 773–782. - // - // Byrd, R. H.; Nocedal, J.; Schnabel, R. B. (1994). - // "Representations of Quasi-Newton Matrices and their use in - // Limited Memory Methods". Mathematical Programming 63 (4): - // 129–156. - // - // A general reference for both methods: - // - // Nocedal J., Wright S., Numerical Optimization, 2nd Ed. Springer, 1999. - LBFGS, - BFGS, -}; - -// Nonliner conjugate gradient methods are a generalization of the -// method of Conjugate Gradients for linear systems. The -// generalization can be carried out in a number of different ways -// leading to number of different rules for computing the search -// direction. Ceres provides a number of different variants. For more -// details see Numerical Optimization by Nocedal & Wright. -enum NonlinearConjugateGradientType { - FLETCHER_REEVES, - POLAK_RIBIERE, - HESTENES_STIEFEL, -}; - -enum LineSearchType { - // Backtracking line search with polynomial interpolation or - // bisection. - ARMIJO, - WOLFE, -}; - -// Ceres supports different strategies for computing the trust region -// step. -enum TrustRegionStrategyType { - // The default trust region strategy is to use the step computation - // used in the Levenberg-Marquardt algorithm. For more details see - // levenberg_marquardt_strategy.h - LEVENBERG_MARQUARDT, - - // Powell's dogleg algorithm interpolates between the Cauchy point - // and the Gauss-Newton step. It is particularly useful if the - // LEVENBERG_MARQUARDT algorithm is making a large number of - // unsuccessful steps. For more details see dogleg_strategy.h. - // - // NOTES: - // - // 1. This strategy has not been experimented with or tested as - // extensively as LEVENBERG_MARQUARDT, and therefore it should be - // considered EXPERIMENTAL for now. - // - // 2. For now this strategy should only be used with exact - // factorization based linear solvers, i.e., SPARSE_SCHUR, - // DENSE_SCHUR, DENSE_QR and SPARSE_NORMAL_CHOLESKY. - DOGLEG -}; - -// Ceres supports two different dogleg strategies. -// The "traditional" dogleg method by Powell and the -// "subspace" method described in -// R. H. Byrd, R. B. Schnabel, and G. A. Shultz, -// "Approximate solution of the trust region problem by minimization -// over two-dimensional subspaces", Mathematical Programming, -// 40 (1988), pp. 247--263 -enum DoglegType { - // The traditional approach constructs a dogleg path - // consisting of two line segments and finds the furthest - // point on that path that is still inside the trust region. - TRADITIONAL_DOGLEG, - - // The subspace approach finds the exact minimum of the model - // constrained to the subspace spanned by the dogleg path. - SUBSPACE_DOGLEG -}; - -enum TerminationType { - // Minimizer terminated because one of the convergence criterion set - // by the user was satisfied. - // - // 1. (new_cost - old_cost) < function_tolerance * old_cost; - // 2. max_i |gradient_i| < gradient_tolerance - // 3. |step|_2 <= parameter_tolerance * ( |x|_2 + parameter_tolerance) - // - // The user's parameter blocks will be updated with the solution. - CONVERGENCE, - - // The solver ran for maximum number of iterations or maximum amount - // of time specified by the user, but none of the convergence - // criterion specified by the user were met. The user's parameter - // blocks will be updated with the solution found so far. - NO_CONVERGENCE, - - // The minimizer terminated because of an error. The user's - // parameter blocks will not be updated. - FAILURE, - - // Using an IterationCallback object, user code can control the - // minimizer. The following enums indicate that the user code was - // responsible for termination. - // - // Minimizer terminated successfully because a user - // IterationCallback returned SOLVER_TERMINATE_SUCCESSFULLY. - // - // The user's parameter blocks will be updated with the solution. - USER_SUCCESS, - - // Minimizer terminated because because a user IterationCallback - // returned SOLVER_ABORT. - // - // The user's parameter blocks will not be updated. - USER_FAILURE -}; - -// Enums used by the IterationCallback instances to indicate to the -// solver whether it should continue solving, the user detected an -// error or the solution is good enough and the solver should -// terminate. -enum CallbackReturnType { - // Continue solving to next iteration. - SOLVER_CONTINUE, - - // Terminate solver, and do not update the parameter blocks upon - // return. Unless the user has set - // Solver:Options:::update_state_every_iteration, in which case the - // state would have been updated every iteration - // anyways. Solver::Summary::termination_type is set to USER_ABORT. - SOLVER_ABORT, - - // Terminate solver, update state and - // return. Solver::Summary::termination_type is set to USER_SUCCESS. - SOLVER_TERMINATE_SUCCESSFULLY -}; - -// The format in which linear least squares problems should be logged -// when Solver::Options::lsqp_iterations_to_dump is non-empty. -enum DumpFormatType { - // Print the linear least squares problem in a human readable format - // to stderr. The Jacobian is printed as a dense matrix. The vectors - // D, x and f are printed as dense vectors. This should only be used - // for small problems. - CONSOLE, - - // Write out the linear least squares problem to the directory - // pointed to by Solver::Options::lsqp_dump_directory as text files - // which can be read into MATLAB/Octave. The Jacobian is dumped as a - // text file containing (i,j,s) triplets, the vectors D, x and f are - // dumped as text files containing a list of their values. - // - // A MATLAB/octave script called lm_iteration_???.m is also output, - // which can be used to parse and load the problem into memory. - TEXTFILE -}; - -// For SizedCostFunction and AutoDiffCostFunction, DYNAMIC can be -// specified for the number of residuals. If specified, then the -// number of residuas for that cost function can vary at runtime. -enum DimensionType { - DYNAMIC = -1 -}; - -// The differentiation method used to compute numerical derivatives in -// NumericDiffCostFunction and DynamicNumericDiffCostFunction. -enum NumericDiffMethodType { - // Compute central finite difference: f'(x) ~ (f(x+h) - f(x-h)) / 2h. - CENTRAL, - - // Compute forward finite difference: f'(x) ~ (f(x+h) - f(x)) / h. - FORWARD, - - // Adaptive numerical differentiation using Ridders' method. Provides more - // accurate and robust derivatives at the expense of additional cost - // function evaluations. - RIDDERS -}; - -enum LineSearchInterpolationType { - BISECTION, - QUADRATIC, - CUBIC -}; - -enum CovarianceAlgorithmType { - DENSE_SVD, - SUITE_SPARSE_QR, - EIGEN_SPARSE_QR -}; - -CERES_EXPORT const char* LinearSolverTypeToString( - LinearSolverType type); -CERES_EXPORT bool StringToLinearSolverType(std::string value, - LinearSolverType* type); - -CERES_EXPORT const char* PreconditionerTypeToString(PreconditionerType type); -CERES_EXPORT bool StringToPreconditionerType(std::string value, - PreconditionerType* type); - -CERES_EXPORT const char* VisibilityClusteringTypeToString( - VisibilityClusteringType type); -CERES_EXPORT bool StringToVisibilityClusteringType(std::string value, - VisibilityClusteringType* type); - -CERES_EXPORT const char* SparseLinearAlgebraLibraryTypeToString( - SparseLinearAlgebraLibraryType type); -CERES_EXPORT bool StringToSparseLinearAlgebraLibraryType( - std::string value, - SparseLinearAlgebraLibraryType* type); - -CERES_EXPORT const char* DenseLinearAlgebraLibraryTypeToString( - DenseLinearAlgebraLibraryType type); -CERES_EXPORT bool StringToDenseLinearAlgebraLibraryType( - std::string value, - DenseLinearAlgebraLibraryType* type); - -CERES_EXPORT const char* TrustRegionStrategyTypeToString( - TrustRegionStrategyType type); -CERES_EXPORT bool StringToTrustRegionStrategyType(std::string value, - TrustRegionStrategyType* type); - -CERES_EXPORT const char* DoglegTypeToString(DoglegType type); -CERES_EXPORT bool StringToDoglegType(std::string value, DoglegType* type); - -CERES_EXPORT const char* MinimizerTypeToString(MinimizerType type); -CERES_EXPORT bool StringToMinimizerType(std::string value, MinimizerType* type); - -CERES_EXPORT const char* LineSearchDirectionTypeToString( - LineSearchDirectionType type); -CERES_EXPORT bool StringToLineSearchDirectionType(std::string value, - LineSearchDirectionType* type); - -CERES_EXPORT const char* LineSearchTypeToString(LineSearchType type); -CERES_EXPORT bool StringToLineSearchType(std::string value, LineSearchType* type); - -CERES_EXPORT const char* NonlinearConjugateGradientTypeToString( - NonlinearConjugateGradientType type); -CERES_EXPORT bool StringToNonlinearConjugateGradientType( - std::string value, - NonlinearConjugateGradientType* type); - -CERES_EXPORT const char* LineSearchInterpolationTypeToString( - LineSearchInterpolationType type); -CERES_EXPORT bool StringToLineSearchInterpolationType( - std::string value, - LineSearchInterpolationType* type); - -CERES_EXPORT const char* CovarianceAlgorithmTypeToString( - CovarianceAlgorithmType type); -CERES_EXPORT bool StringToCovarianceAlgorithmType( - std::string value, - CovarianceAlgorithmType* type); - -CERES_EXPORT const char* NumericDiffMethodTypeToString( - NumericDiffMethodType type); -CERES_EXPORT bool StringToNumericDiffMethodType( - std::string value, - NumericDiffMethodType* type); - -CERES_EXPORT const char* TerminationTypeToString(TerminationType type); - -CERES_EXPORT bool IsSchurType(LinearSolverType type); -CERES_EXPORT bool IsSparseLinearAlgebraLibraryTypeAvailable( - SparseLinearAlgebraLibraryType type); -CERES_EXPORT bool IsDenseLinearAlgebraLibraryTypeAvailable( - DenseLinearAlgebraLibraryType type); - -} // namespace ceres - -#include "ceres/internal/reenable_warnings.h" - -#endif // CERES_PUBLIC_TYPES_H_ diff --git a/extern/libmv/third_party/ceres/include/ceres/version.h b/extern/libmv/third_party/ceres/include/ceres/version.h deleted file mode 100644 index 66505a515c9..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/version.h +++ /dev/null @@ -1,48 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: mierle@gmail.com (Keir Mierle) - -#ifndef CERES_PUBLIC_VERSION_H_ -#define CERES_PUBLIC_VERSION_H_ - -#define CERES_VERSION_MAJOR 1 -#define CERES_VERSION_MINOR 11 -#define CERES_VERSION_REVISION 0 - -// Classic CPP stringifcation; the extra level of indirection allows the -// preprocessor to expand the macro before being converted to a string. -#define CERES_TO_STRING_HELPER(x) #x -#define CERES_TO_STRING(x) CERES_TO_STRING_HELPER(x) - -// The Ceres version as a string; for example "1.9.0". -#define CERES_VERSION_STRING CERES_TO_STRING(CERES_VERSION_MAJOR) "." \ - CERES_TO_STRING(CERES_VERSION_MINOR) "." \ - CERES_TO_STRING(CERES_VERSION_REVISION) - -#endif // CERES_PUBLIC_VERSION_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/array_utils.cc b/extern/libmv/third_party/ceres/internal/ceres/array_utils.cc deleted file mode 100644 index 7be3c78ce24..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/array_utils.cc +++ /dev/null @@ -1,115 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/array_utils.h" - -#include <algorithm> -#include <cmath> -#include <cstddef> -#include <string> -#include <vector> -#include "ceres/fpclassify.h" -#include "ceres/stringprintf.h" - -namespace ceres { -namespace internal { - -using std::string; - -// It is a near impossibility that user code generates this exact -// value in normal operation, thus we will use it to fill arrays -// before passing them to user code. If on return an element of the -// array still contains this value, we will assume that the user code -// did not write to that memory location. -const double kImpossibleValue = 1e302; - -bool IsArrayValid(const int size, const double* x) { - if (x != NULL) { - for (int i = 0; i < size; ++i) { - if (!IsFinite(x[i]) || (x[i] == kImpossibleValue)) { - return false; - } - } - } - return true; -} - -int FindInvalidValue(const int size, const double* x) { - if (x == NULL) { - return size; - } - - for (int i = 0; i < size; ++i) { - if (!IsFinite(x[i]) || (x[i] == kImpossibleValue)) { - return i; - } - } - - return size; -} - -void InvalidateArray(const int size, double* x) { - if (x != NULL) { - for (int i = 0; i < size; ++i) { - x[i] = kImpossibleValue; - } - } -} - -void AppendArrayToString(const int size, const double* x, string* result) { - for (int i = 0; i < size; ++i) { - if (x == NULL) { - StringAppendF(result, "Not Computed "); - } else { - if (x[i] == kImpossibleValue) { - StringAppendF(result, "Uninitialized "); - } else { - StringAppendF(result, "%12g ", x[i]); - } - } - } -} - -void MapValuesToContiguousRange(const int size, int* array) { - std::vector<int> unique_values(array, array + size); - std::sort(unique_values.begin(), unique_values.end()); - unique_values.erase(std::unique(unique_values.begin(), - unique_values.end()), - unique_values.end()); - - for (int i = 0; i < size; ++i) { - array[i] = std::lower_bound(unique_values.begin(), - unique_values.end(), - array[i]) - unique_values.begin(); - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/array_utils.h b/extern/libmv/third_party/ceres/internal/ceres/array_utils.h deleted file mode 100644 index 2d2ffca8809..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/array_utils.h +++ /dev/null @@ -1,89 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Utility routines for validating arrays. -// -// These are useful for detecting two common class of errors. -// -// 1. Uninitialized memory - where the user for some reason did not -// compute part of an array, but the code expects it. -// -// 2. Numerical failure while computing the cost/residual/jacobian, -// e.g. NaN, infinities etc. This is particularly useful since the -// automatic differentiation code does computations that are not -// evident to the user and can silently generate hard to debug errors. - -#ifndef CERES_INTERNAL_ARRAY_UTILS_H_ -#define CERES_INTERNAL_ARRAY_UTILS_H_ - -#include <string> -#include "ceres/internal/port.h" - -namespace ceres { -namespace internal { - -// Fill the array x with an impossible value that the user code is -// never expected to compute. -void InvalidateArray(int size, double* x); - -// Check if all the entries of the array x are valid, i.e. all the -// values in the array should be finite and none of them should be -// equal to the "impossible" value used by InvalidateArray. -bool IsArrayValid(int size, const double* x); - -// If the array contains an invalid value, return the index for it, -// otherwise return size. -int FindInvalidValue(const int size, const double* x); - -// Utility routine to print an array of doubles to a string. If the -// array pointer is NULL, it is treated as an array of zeros. -void AppendArrayToString(const int size, const double* x, std::string* result); - -extern const double kImpossibleValue; - -// This routine takes an array of integer values, sorts and uniques -// them and then maps each value in the array to its position in the -// sorted+uniqued array. By doing this, if there are are k unique -// values in the array, each value is replaced by an integer in the -// range [0, k-1], while preserving their relative order. -// -// For example -// -// [1 0 3 5 0 1 5] -// -// gets mapped to -// -// [1 0 2 3 0 1 3] -void MapValuesToContiguousRange(int size, int* array); - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_ARRAY_UTILS_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/blas.cc b/extern/libmv/third_party/ceres/internal/ceres/blas.cc deleted file mode 100644 index 3ba63bbed5a..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/blas.cc +++ /dev/null @@ -1,81 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/blas.h" -#include "ceres/internal/port.h" -#include "glog/logging.h" - -#ifndef CERES_NO_LAPACK -extern "C" void dsyrk_(char* uplo, - char* trans, - int* n, - int* k, - double* alpha, - double* a, - int* lda, - double* beta, - double* c, - int* ldc); -#endif - -namespace ceres { -namespace internal { - -void BLAS::SymmetricRankKUpdate(int num_rows, - int num_cols, - const double* a, - bool transpose, - double alpha, - double beta, - double* c) { -#ifdef CERES_NO_LAPACK - LOG(FATAL) << "Ceres was built without a BLAS library."; -#else - char uplo = 'L'; - char trans = transpose ? 'T' : 'N'; - int n = transpose ? num_cols : num_rows; - int k = transpose ? num_rows : num_cols; - int lda = k; - int ldc = n; - dsyrk_(&uplo, - &trans, - &n, - &k, - &alpha, - const_cast<double*>(a), - &lda, - &beta, - c, - &ldc); -#endif -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/blas.h b/extern/libmv/third_party/ceres/internal/ceres/blas.h deleted file mode 100644 index a43301c5d18..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/blas.h +++ /dev/null @@ -1,57 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Wrapper functions around BLAS functions. - -#ifndef CERES_INTERNAL_BLAS_H_ -#define CERES_INTERNAL_BLAS_H_ - -namespace ceres { -namespace internal { - -class BLAS { - public: - // transpose = true : c = alpha * a'a + beta * c; - // transpose = false : c = alpha * aa' + beta * c; - // - // Assumes column major matrices. - static void SymmetricRankKUpdate(int num_rows, - int num_cols, - const double* a, - bool transpose, - double alpha, - double beta, - double* c); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_BLAS_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.cc b/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.cc deleted file mode 100644 index 59c0d3ecc10..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.cc +++ /dev/null @@ -1,83 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#include "ceres/block_evaluate_preparer.h" - -#include <vector> -#include "ceres/block_sparse_matrix.h" -#include "ceres/casts.h" -#include "ceres/parameter_block.h" -#include "ceres/residual_block.h" -#include "ceres/sparse_matrix.h" - -namespace ceres { -namespace internal { - -void BlockEvaluatePreparer::Init(int const* const* jacobian_layout, - int max_derivatives_per_residual_block) { - jacobian_layout_ = jacobian_layout; - scratch_evaluate_preparer_.Init(max_derivatives_per_residual_block); -} - -// Point the jacobian blocks directly into the block sparse matrix. -void BlockEvaluatePreparer::Prepare(const ResidualBlock* residual_block, - int residual_block_index, - SparseMatrix* jacobian, - double** jacobians) { - // If the overall jacobian is not available, use the scratch space. - if (jacobian == NULL) { - scratch_evaluate_preparer_.Prepare(residual_block, - residual_block_index, - jacobian, - jacobians); - return; - } - - double* jacobian_values = - down_cast<BlockSparseMatrix*>(jacobian)->mutable_values(); - - const int* jacobian_block_offset = jacobian_layout_[residual_block_index]; - const int num_parameter_blocks = residual_block->NumParameterBlocks(); - for (int j = 0; j < num_parameter_blocks; ++j) { - if (!residual_block->parameter_blocks()[j]->IsConstant()) { - jacobians[j] = jacobian_values + *jacobian_block_offset; - - // The jacobian_block_offset can't be indexed with 'j' since the code - // that creates the layout strips out any blocks for inactive - // parameters. Instead, bump the pointer for active parameters only. - jacobian_block_offset++; - } else { - jacobians[j] = NULL; - } - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.h b/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.h deleted file mode 100644 index 4378689729f..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.h +++ /dev/null @@ -1,77 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// A evaluate preparer which puts jacobian the evaluated jacobian blocks -// directly into their final resting place in an overall block sparse matrix. -// The evaluator takes care to avoid evaluating the jacobian for fixed -// parameters. - -#ifndef CERES_INTERNAL_BLOCK_EVALUATE_PREPARER_H_ -#define CERES_INTERNAL_BLOCK_EVALUATE_PREPARER_H_ - -#include "ceres/scratch_evaluate_preparer.h" - -namespace ceres { -namespace internal { - -class ResidualBlock; -class SparseMatrix; - -class BlockEvaluatePreparer { - public: - // Using Init() instead of a constructor allows for allocating this structure - // with new[]. This is because C++ doesn't allow passing arguments to objects - // constructed with new[] (as opposed to plain 'new'). - void Init(int const* const* jacobian_layout, - int max_derivatives_per_residual_block); - - // EvaluatePreparer interface - - // Point the jacobian blocks directly into the block sparse matrix, if - // jacobian is non-null. Otherwise, uses an internal per-thread buffer to - // store the jacobians temporarily. - void Prepare(const ResidualBlock* residual_block, - int residual_block_index, - SparseMatrix* jacobian, - double** jacobians); - - private: - int const* const* jacobian_layout_; - - // For the case that the overall jacobian is not available, but the - // individual jacobians are requested, use a pass-through scratch evaluate - // preparer. - ScratchEvaluatePreparer scratch_evaluate_preparer_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_BLOCK_EVALUATE_PREPARER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_jacobi_preconditioner.cc b/extern/libmv/third_party/ceres/internal/ceres/block_jacobi_preconditioner.cc deleted file mode 100644 index 22d4b351c51..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_jacobi_preconditioner.cc +++ /dev/null @@ -1,106 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#include "ceres/block_jacobi_preconditioner.h" - -#include "ceres/block_sparse_matrix.h" -#include "ceres/block_structure.h" -#include "ceres/block_random_access_diagonal_matrix.h" -#include "ceres/casts.h" -#include "ceres/integral_types.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -BlockJacobiPreconditioner::BlockJacobiPreconditioner( - const BlockSparseMatrix& A) { - const CompressedRowBlockStructure* bs = A.block_structure(); - std::vector<int> blocks(bs->cols.size()); - for (int i = 0; i < blocks.size(); ++i) { - blocks[i] = bs->cols[i].size; - } - - m_.reset(new BlockRandomAccessDiagonalMatrix(blocks)); -} - -BlockJacobiPreconditioner::~BlockJacobiPreconditioner() {} - -bool BlockJacobiPreconditioner::UpdateImpl(const BlockSparseMatrix& A, - const double* D) { - const CompressedRowBlockStructure* bs = A.block_structure(); - const double* values = A.values(); - m_->SetZero(); - for (int i = 0; i < bs->rows.size(); ++i) { - const int row_block_size = bs->rows[i].block.size; - const std::vector<Cell>& cells = bs->rows[i].cells; - for (int j = 0; j < cells.size(); ++j) { - const int block_id = cells[j].block_id; - const int col_block_size = bs->cols[block_id].size; - - int r, c, row_stride, col_stride; - CellInfo* cell_info = m_->GetCell(block_id, block_id, - &r, &c, - &row_stride, &col_stride); - MatrixRef m(cell_info->values, row_stride, col_stride); - ConstMatrixRef b(values + cells[j].position, - row_block_size, - col_block_size); - m.block(r, c, col_block_size, col_block_size) += b.transpose() * b; - } - } - - if (D != NULL) { - // Add the diagonal. - int position = 0; - for (int i = 0; i < bs->cols.size(); ++i) { - const int block_size = bs->cols[i].size; - int r, c, row_stride, col_stride; - CellInfo* cell_info = m_->GetCell(i, i, - &r, &c, - &row_stride, &col_stride); - MatrixRef m(cell_info->values, row_stride, col_stride); - m.block(r, c, block_size, block_size).diagonal() += - ConstVectorRef(D + position, block_size).array().square().matrix(); - position += block_size; - } - } - - m_->Invert(); - return true; -} - -void BlockJacobiPreconditioner::RightMultiply(const double* x, - double* y) const { - m_->RightMultiply(x, y); -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_jacobi_preconditioner.h b/extern/libmv/third_party/ceres/internal/ceres/block_jacobi_preconditioner.h deleted file mode 100644 index 14007295823..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_jacobi_preconditioner.h +++ /dev/null @@ -1,76 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#ifndef CERES_INTERNAL_BLOCK_JACOBI_PRECONDITIONER_H_ -#define CERES_INTERNAL_BLOCK_JACOBI_PRECONDITIONER_H_ - -#include <vector> -#include "ceres/block_random_access_diagonal_matrix.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/preconditioner.h" - -namespace ceres { -namespace internal { - -class BlockSparseMatrix; -struct CompressedRowBlockStructure; - -// A block Jacobi preconditioner. This is intended for use with -// conjugate gradients, or other iterative symmetric solvers. To use -// the preconditioner, create one by passing a BlockSparseMatrix "A" -// to the constructor. This fixes the sparsity pattern to the pattern -// of the matrix A^TA. -// -// Before each use of the preconditioner in a solve with conjugate gradients, -// update the matrix by running Update(A, D). The values of the matrix A are -// inspected to construct the preconditioner. The vector D is applied as the -// D^TD diagonal term. -class BlockJacobiPreconditioner : public BlockSparseMatrixPreconditioner { - public: - // A must remain valid while the BlockJacobiPreconditioner is. - explicit BlockJacobiPreconditioner(const BlockSparseMatrix& A); - virtual ~BlockJacobiPreconditioner(); - - // Preconditioner interface - virtual void RightMultiply(const double* x, double* y) const; - virtual int num_rows() const { return m_->num_rows(); } - virtual int num_cols() const { return m_->num_rows(); } - - const BlockRandomAccessDiagonalMatrix& matrix() const { return *m_; } - private: - virtual bool UpdateImpl(const BlockSparseMatrix& A, const double* D); - - scoped_ptr<BlockRandomAccessDiagonalMatrix> m_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_BLOCK_JACOBI_PRECONDITIONER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_jacobian_writer.cc b/extern/libmv/third_party/ceres/internal/ceres/block_jacobian_writer.cc deleted file mode 100644 index 7a3fee4fbdf..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_jacobian_writer.cc +++ /dev/null @@ -1,214 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#include "ceres/block_jacobian_writer.h" - -#include "ceres/block_evaluate_preparer.h" -#include "ceres/block_sparse_matrix.h" -#include "ceres/parameter_block.h" -#include "ceres/program.h" -#include "ceres/residual_block.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" - -namespace ceres { -namespace internal { - -using std::vector; - -namespace { - -// Given the residual block ordering, build a lookup table to determine which -// per-parameter jacobian goes where in the overall program jacobian. -// -// Since we expect to use a Schur type linear solver to solve the LM step, take -// extra care to place the E blocks and the F blocks contiguously. E blocks are -// the first num_eliminate_blocks parameter blocks as indicated by the parameter -// block ordering. The remaining parameter blocks are the F blocks. -// -// TODO(keir): Consider if we should use a boolean for each parameter block -// instead of num_eliminate_blocks. -void BuildJacobianLayout(const Program& program, - int num_eliminate_blocks, - vector<int*>* jacobian_layout, - vector<int>* jacobian_layout_storage) { - const vector<ResidualBlock*>& residual_blocks = program.residual_blocks(); - - // Iterate over all the active residual blocks and determine how many E blocks - // are there. This will determine where the F blocks start in the jacobian - // matrix. Also compute the number of jacobian blocks. - int f_block_pos = 0; - int num_jacobian_blocks = 0; - for (int i = 0; i < residual_blocks.size(); ++i) { - ResidualBlock* residual_block = residual_blocks[i]; - const int num_residuals = residual_block->NumResiduals(); - const int num_parameter_blocks = residual_block->NumParameterBlocks(); - - // Advance f_block_pos over each E block for this residual. - for (int j = 0; j < num_parameter_blocks; ++j) { - ParameterBlock* parameter_block = residual_block->parameter_blocks()[j]; - if (!parameter_block->IsConstant()) { - // Only count blocks for active parameters. - num_jacobian_blocks++; - if (parameter_block->index() < num_eliminate_blocks) { - f_block_pos += num_residuals * parameter_block->LocalSize(); - } - } - } - } - - // We now know that the E blocks are laid out starting at zero, and the F - // blocks are laid out starting at f_block_pos. Iterate over the residual - // blocks again, and this time fill the jacobian_layout array with the - // position information. - - jacobian_layout->resize(program.NumResidualBlocks()); - jacobian_layout_storage->resize(num_jacobian_blocks); - - int e_block_pos = 0; - int* jacobian_pos = &(*jacobian_layout_storage)[0]; - for (int i = 0; i < residual_blocks.size(); ++i) { - const ResidualBlock* residual_block = residual_blocks[i]; - const int num_residuals = residual_block->NumResiduals(); - const int num_parameter_blocks = residual_block->NumParameterBlocks(); - - (*jacobian_layout)[i] = jacobian_pos; - for (int j = 0; j < num_parameter_blocks; ++j) { - ParameterBlock* parameter_block = residual_block->parameter_blocks()[j]; - const int parameter_block_index = parameter_block->index(); - if (parameter_block->IsConstant()) { - continue; - } - const int jacobian_block_size = - num_residuals * parameter_block->LocalSize(); - if (parameter_block_index < num_eliminate_blocks) { - *jacobian_pos = e_block_pos; - e_block_pos += jacobian_block_size; - } else { - *jacobian_pos = f_block_pos; - f_block_pos += jacobian_block_size; - } - jacobian_pos++; - } - } -} - -} // namespace - -BlockJacobianWriter::BlockJacobianWriter(const Evaluator::Options& options, - Program* program) - : program_(program) { - CHECK_GE(options.num_eliminate_blocks, 0) - << "num_eliminate_blocks must be greater than 0."; - - BuildJacobianLayout(*program, - options.num_eliminate_blocks, - &jacobian_layout_, - &jacobian_layout_storage_); -} - -// Create evaluate prepareres that point directly into the final jacobian. This -// makes the final Write() a nop. -BlockEvaluatePreparer* BlockJacobianWriter::CreateEvaluatePreparers( - int num_threads) { - int max_derivatives_per_residual_block = - program_->MaxDerivativesPerResidualBlock(); - - BlockEvaluatePreparer* preparers = new BlockEvaluatePreparer[num_threads]; - for (int i = 0; i < num_threads; i++) { - preparers[i].Init(&jacobian_layout_[0], max_derivatives_per_residual_block); - } - return preparers; -} - -SparseMatrix* BlockJacobianWriter::CreateJacobian() const { - CompressedRowBlockStructure* bs = new CompressedRowBlockStructure; - - const vector<ParameterBlock*>& parameter_blocks = - program_->parameter_blocks(); - - // Construct the column blocks. - bs->cols.resize(parameter_blocks.size()); - for (int i = 0, cursor = 0; i < parameter_blocks.size(); ++i) { - CHECK_NE(parameter_blocks[i]->index(), -1); - CHECK(!parameter_blocks[i]->IsConstant()); - bs->cols[i].size = parameter_blocks[i]->LocalSize(); - bs->cols[i].position = cursor; - cursor += bs->cols[i].size; - } - - // Construct the cells in each row. - const vector<ResidualBlock*>& residual_blocks = program_->residual_blocks(); - int row_block_position = 0; - bs->rows.resize(residual_blocks.size()); - for (int i = 0; i < residual_blocks.size(); ++i) { - const ResidualBlock* residual_block = residual_blocks[i]; - CompressedRow* row = &bs->rows[i]; - - row->block.size = residual_block->NumResiduals(); - row->block.position = row_block_position; - row_block_position += row->block.size; - - // Size the row by the number of active parameters in this residual. - const int num_parameter_blocks = residual_block->NumParameterBlocks(); - int num_active_parameter_blocks = 0; - for (int j = 0; j < num_parameter_blocks; ++j) { - if (residual_block->parameter_blocks()[j]->index() != -1) { - num_active_parameter_blocks++; - } - } - row->cells.resize(num_active_parameter_blocks); - - // Add layout information for the active parameters in this row. - for (int j = 0, k = 0; j < num_parameter_blocks; ++j) { - const ParameterBlock* parameter_block = - residual_block->parameter_blocks()[j]; - if (!parameter_block->IsConstant()) { - Cell& cell = row->cells[k]; - cell.block_id = parameter_block->index(); - cell.position = jacobian_layout_[i][k]; - - // Only increment k for active parameters, since there is only layout - // information for active parameters. - k++; - } - } - - sort(row->cells.begin(), row->cells.end(), CellLessThan); - } - - BlockSparseMatrix* jacobian = new BlockSparseMatrix(bs); - CHECK_NOTNULL(jacobian); - return jacobian; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_jacobian_writer.h b/extern/libmv/third_party/ceres/internal/ceres/block_jacobian_writer.h deleted file mode 100644 index 8e6f45130a4..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_jacobian_writer.h +++ /dev/null @@ -1,127 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// A jacobian writer that writes to block sparse matrices. The "writer" name is -// misleading, since the Write() operation on the block jacobian writer does not -// write anything. Instead, the Prepare() method on the BlockEvaluatePreparers -// makes a jacobians array which has direct pointers into the block sparse -// jacobian. When the cost function is evaluated, the jacobian blocks get placed -// directly in their final location. - -#ifndef CERES_INTERNAL_BLOCK_JACOBIAN_WRITER_H_ -#define CERES_INTERNAL_BLOCK_JACOBIAN_WRITER_H_ - -#include <vector> -#include "ceres/evaluator.h" -#include "ceres/internal/port.h" - -namespace ceres { -namespace internal { - -class BlockEvaluatePreparer; -class Program; -class SparseMatrix; - -class BlockJacobianWriter { - public: - BlockJacobianWriter(const Evaluator::Options& options, - Program* program); - - // JacobianWriter interface. - - // Create evaluate prepareres that point directly into the final jacobian. - // This makes the final Write() a nop. - BlockEvaluatePreparer* CreateEvaluatePreparers(int num_threads); - - SparseMatrix* CreateJacobian() const; - - void Write(int /* residual_id */, - int /* residual_offset */, - double** /* jacobians */, - SparseMatrix* /* jacobian */) { - // This is a noop since the blocks were written directly into their final - // position by the outside evaluate call, thanks to the jacobians array - // prepared by the BlockEvaluatePreparers. - } - - private: - Program* program_; - - // Stores the position of each residual / parameter jacobian. - // - // The block sparse matrix that this writer writes to is stored as a set of - // contiguos dense blocks, one after each other; see BlockSparseMatrix. The - // "double* values_" member of the block sparse matrix contains all of these - // blocks. Given a pointer to the first element of a block and the size of - // that block, it's possible to write to it. - // - // In the case of a block sparse jacobian, the jacobian writer needs a way to - // find the offset in the values_ array of each residual/parameter jacobian - // block. - // - // That is the purpose of jacobian_layout_. - // - // In particular, jacobian_layout_[i][j] is the offset in the values_ array of - // the derivative of residual block i with respect to the parameter block at - // active argument position j. - // - // The active qualifier means that non-active parameters do not count. Care - // must be taken when indexing into jacobian_layout_ to account for this. - // Consider a single residual example: - // - // r(x, y, z) - // - // with r in R^3, x in R^4, y in R^2, and z in R^5. - // Take y as a constant (non-active) parameter. - // Take r as residual number 0. - // - // In this case, the active arguments are only (x, z), so the active argument - // position for x is 0, and the active argument position for z is 1. This is - // similar to thinking of r as taking only 2 parameters: - // - // r(x, z) - // - // There are only 2 jacobian blocks: dr/dx and dr/dz. jacobian_layout_ would - // have the following contents: - // - // jacobian_layout_[0] = { 0, 12 } - // - // which indicates that dr/dx is located at values_[0], and dr/dz is at - // values_[12]. See BlockEvaluatePreparer::Prepare()'s comments about 'j'. - std::vector<int*> jacobian_layout_; - - // The pointers in jacobian_layout_ point directly into this vector. - std::vector<int> jacobian_layout_storage_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_BLOCK_JACOBIAN_WRITER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.cc deleted file mode 100644 index 61748ef6f7f..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.cc +++ /dev/null @@ -1,88 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/block_random_access_dense_matrix.h" - -#include <vector> -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -BlockRandomAccessDenseMatrix::BlockRandomAccessDenseMatrix( - const std::vector<int>& blocks) { - const int num_blocks = blocks.size(); - block_layout_.resize(num_blocks, 0); - num_rows_ = 0; - for (int i = 0; i < num_blocks; ++i) { - block_layout_[i] = num_rows_; - num_rows_ += blocks[i]; - } - - values_.reset(new double[num_rows_ * num_rows_]); - - cell_infos_.reset(new CellInfo[num_blocks * num_blocks]); - for (int i = 0; i < num_blocks * num_blocks; ++i) { - cell_infos_[i].values = values_.get(); - } - - SetZero(); -} - -// Assume that the user does not hold any locks on any cell blocks -// when they are calling SetZero. -BlockRandomAccessDenseMatrix::~BlockRandomAccessDenseMatrix() { -} - -CellInfo* BlockRandomAccessDenseMatrix::GetCell(const int row_block_id, - const int col_block_id, - int* row, - int* col, - int* row_stride, - int* col_stride) { - *row = block_layout_[row_block_id]; - *col = block_layout_[col_block_id]; - *row_stride = num_rows_; - *col_stride = num_rows_; - return &cell_infos_[row_block_id * block_layout_.size() + col_block_id]; -} - -// Assume that the user does not hold any locks on any cell blocks -// when they are calling SetZero. -void BlockRandomAccessDenseMatrix::SetZero() { - if (num_rows_) { - VectorRef(values_.get(), num_rows_ * num_rows_).setZero(); - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.h deleted file mode 100644 index 89689082561..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.h +++ /dev/null @@ -1,98 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_BLOCK_RANDOM_ACCESS_DENSE_MATRIX_H_ -#define CERES_INTERNAL_BLOCK_RANDOM_ACCESS_DENSE_MATRIX_H_ - -#include "ceres/block_random_access_matrix.h" - -#include <vector> - -#include "ceres/internal/macros.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" - -namespace ceres { -namespace internal { - -// A square block random accessible matrix with the same row and -// column block structure. All cells are stored in the same single -// array, so that its also accessible as a dense matrix of size -// num_rows x num_cols. -// -// This class is NOT thread safe. Since all n^2 cells are stored, -// GetCell never returns NULL for any (row_block_id, col_block_id) -// pair. -// -// ReturnCell is a nop. -class BlockRandomAccessDenseMatrix : public BlockRandomAccessMatrix { - public: - // blocks is a vector of block sizes. The resulting matrix has - // blocks.size() * blocks.size() cells. - explicit BlockRandomAccessDenseMatrix(const std::vector<int>& blocks); - - // The destructor is not thread safe. It assumes that no one is - // modifying any cells when the matrix is being destroyed. - virtual ~BlockRandomAccessDenseMatrix(); - - // BlockRandomAccessMatrix interface. - virtual CellInfo* GetCell(int row_block_id, - int col_block_id, - int* row, - int* col, - int* row_stride, - int* col_stride); - - // This is not a thread safe method, it assumes that no cell is - // locked. - virtual void SetZero(); - - // Since the matrix is square with the same row and column block - // structure, num_rows() = num_cols(). - virtual int num_rows() const { return num_rows_; } - virtual int num_cols() const { return num_rows_; } - - // The underlying matrix storing the cells. - const double* values() const { return values_.get(); } - double* mutable_values() { return values_.get(); } - - private: - int num_rows_; - std::vector<int> block_layout_; - scoped_array<double> values_; - scoped_array<CellInfo> cell_infos_; - - CERES_DISALLOW_COPY_AND_ASSIGN(BlockRandomAccessDenseMatrix); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_BLOCK_RANDOM_ACCESS_DENSE_MATRIX_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_diagonal_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_diagonal_matrix.cc deleted file mode 100644 index 052690d18be..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_diagonal_matrix.cc +++ /dev/null @@ -1,154 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/block_random_access_diagonal_matrix.h" - -#include <algorithm> -#include <set> -#include <utility> -#include <vector> -#include "Eigen/Dense" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/stl_util.h" -#include "ceres/triplet_sparse_matrix.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::vector; - -// TODO(sameeragarwal): Drop the dependence on TripletSparseMatrix. - -BlockRandomAccessDiagonalMatrix::BlockRandomAccessDiagonalMatrix( - const vector<int>& blocks) - : blocks_(blocks) { - // Build the row/column layout vector and count the number of scalar - // rows/columns. - int num_cols = 0; - int num_nonzeros = 0; - vector<int> block_positions; - for (int i = 0; i < blocks_.size(); ++i) { - block_positions.push_back(num_cols); - num_cols += blocks_[i]; - num_nonzeros += blocks_[i] * blocks_[i]; - } - - VLOG(1) << "Matrix Size [" << num_cols - << "," << num_cols - << "] " << num_nonzeros; - - tsm_.reset(new TripletSparseMatrix(num_cols, num_cols, num_nonzeros)); - tsm_->set_num_nonzeros(num_nonzeros); - int* rows = tsm_->mutable_rows(); - int* cols = tsm_->mutable_cols(); - double* values = tsm_->mutable_values(); - - int pos = 0; - for (int i = 0; i < blocks_.size(); ++i) { - const int block_size = blocks_[i]; - layout_.push_back(new CellInfo(values + pos)); - const int block_begin = block_positions[i]; - for (int r = 0; r < block_size; ++r) { - for (int c = 0; c < block_size; ++c, ++pos) { - rows[pos] = block_begin + r; - cols[pos] = block_begin + c; - } - } - } -} - -// Assume that the user does not hold any locks on any cell blocks -// when they are calling SetZero. -BlockRandomAccessDiagonalMatrix::~BlockRandomAccessDiagonalMatrix() { - STLDeleteContainerPointers(layout_.begin(), layout_.end()); -} - -CellInfo* BlockRandomAccessDiagonalMatrix::GetCell(int row_block_id, - int col_block_id, - int* row, - int* col, - int* row_stride, - int* col_stride) { - if (row_block_id != col_block_id) { - return NULL; - } - const int stride = blocks_[row_block_id]; - - // Each cell is stored contiguously as its own little dense matrix. - *row = 0; - *col = 0; - *row_stride = stride; - *col_stride = stride; - return layout_[row_block_id]; -} - -// Assume that the user does not hold any locks on any cell blocks -// when they are calling SetZero. -void BlockRandomAccessDiagonalMatrix::SetZero() { - if (tsm_->num_nonzeros()) { - VectorRef(tsm_->mutable_values(), - tsm_->num_nonzeros()).setZero(); - } -} - -void BlockRandomAccessDiagonalMatrix::Invert() { - double* values = tsm_->mutable_values(); - for (int i = 0; i < blocks_.size(); ++i) { - const int block_size = blocks_[i]; - MatrixRef block(values, block_size, block_size); - block = - block - .selfadjointView<Eigen::Upper>() - .llt() - .solve(Matrix::Identity(block_size, block_size)); - values += block_size * block_size; - } -} - -void BlockRandomAccessDiagonalMatrix::RightMultiply(const double* x, - double* y) const { - CHECK_NOTNULL(x); - CHECK_NOTNULL(y); - const double* values = tsm_->values(); - for (int i = 0; i < blocks_.size(); ++i) { - const int block_size = blocks_[i]; - ConstMatrixRef block(values, block_size, block_size); - VectorRef(y, block_size).noalias() += block * ConstVectorRef(x, block_size); - x += block_size; - y += block_size; - values += block_size * block_size; - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_diagonal_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_diagonal_matrix.h deleted file mode 100644 index 07ffc9d4a0d..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_diagonal_matrix.h +++ /dev/null @@ -1,101 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_BLOCK_RANDOM_ACCESS_DIAGONAL_MATRIX_H_ -#define CERES_INTERNAL_BLOCK_RANDOM_ACCESS_DIAGONAL_MATRIX_H_ - -#include <set> -#include <vector> -#include <utility> -#include "ceres/mutex.h" -#include "ceres/block_random_access_matrix.h" -#include "ceres/collections_port.h" -#include "ceres/triplet_sparse_matrix.h" -#include "ceres/integral_types.h" -#include "ceres/internal/macros.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -// A thread safe block diagonal matrix implementation of -// BlockRandomAccessMatrix. -class BlockRandomAccessDiagonalMatrix : public BlockRandomAccessMatrix { - public: - // blocks is an array of block sizes. - explicit BlockRandomAccessDiagonalMatrix(const std::vector<int>& blocks); - - // The destructor is not thread safe. It assumes that no one is - // modifying any cells when the matrix is being destroyed. - virtual ~BlockRandomAccessDiagonalMatrix(); - - // BlockRandomAccessMatrix Interface. - virtual CellInfo* GetCell(int row_block_id, - int col_block_id, - int* row, - int* col, - int* row_stride, - int* col_stride); - - // This is not a thread safe method, it assumes that no cell is - // locked. - virtual void SetZero(); - - // Invert the matrix assuming that each block is positive definite. - void Invert(); - - // y += S * x - void RightMultiply(const double* x, double* y) const; - - // Since the matrix is square, num_rows() == num_cols(). - virtual int num_rows() const { return tsm_->num_rows(); } - virtual int num_cols() const { return tsm_->num_cols(); } - - const TripletSparseMatrix* matrix() const { return tsm_.get(); } - TripletSparseMatrix* mutable_matrix() { return tsm_.get(); } - - private: - // row/column block sizes. - const std::vector<int> blocks_; - std::vector<CellInfo*> layout_; - - // The underlying matrix object which actually stores the cells. - scoped_ptr<TripletSparseMatrix> tsm_; - - friend class BlockRandomAccessDiagonalMatrixTest; - CERES_DISALLOW_COPY_AND_ASSIGN(BlockRandomAccessDiagonalMatrix); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_BLOCK_RANDOM_ACCESS_DIAGONAL_MATRIX_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_matrix.cc deleted file mode 100644 index 347d765bbca..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_matrix.cc +++ /dev/null @@ -1,40 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/block_random_access_matrix.h" - -namespace ceres { -namespace internal { - -BlockRandomAccessMatrix::~BlockRandomAccessMatrix() { -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_matrix.h deleted file mode 100644 index 34c8bf5cd4d..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_matrix.h +++ /dev/null @@ -1,132 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Interface for matrices that allow block based random access. - -#ifndef CERES_INTERNAL_BLOCK_RANDOM_ACCESS_MATRIX_H_ -#define CERES_INTERNAL_BLOCK_RANDOM_ACCESS_MATRIX_H_ - -#include "ceres/mutex.h" - -namespace ceres { -namespace internal { - -// A matrix implementing the BlockRandomAccessMatrix interface is a -// matrix whose rows and columns are divided into blocks. For example -// the matrix A: -// -// 3 4 5 -// A = 5 [c_11 c_12 c_13] -// 4 [c_21 c_22 c_23] -// -// has row blocks of size 5 and 4, and column blocks of size 3, 4 and -// 5. It has six cells corresponding to the six row-column block -// combinations. -// -// BlockRandomAccessMatrix objects provide access to cells c_ij using -// the GetCell method. when a cell is present, GetCell will return a -// CellInfo object containing a pointer to an array which contains the -// cell as a submatrix and a mutex that guards this submatrix. If the -// user is accessing the matrix concurrently, it is his responsibility -// to use the mutex to exclude other writers from writing to the cell -// concurrently. -// -// There is no requirement that all cells be present, i.e. the matrix -// itself can be block sparse. When a cell is not present, the GetCell -// method will return a NULL pointer. -// -// There is no requirement about how the cells are stored beyond that -// form a dense submatrix of a larger dense matrix. Like everywhere -// else in Ceres, RowMajor storage assumed. -// -// Example usage: -// -// BlockRandomAccessMatrix* A = new BlockRandomAccessMatrixSubClass(...) -// -// int row, col, row_stride, col_stride; -// CellInfo* cell = A->GetCell(row_block_id, col_block_id, -// &row, &col, -// &row_stride, &col_stride); -// -// if (cell != NULL) { -// MatrixRef m(cell->values, row_stride, col_stride); -// CeresMutexLock l(&cell->m); -// m.block(row, col, row_block_size, col_block_size) = ... -// } - -// Structure to carry a pointer to the array containing a cell and the -// Mutex guarding it. -struct CellInfo { - CellInfo() - : values(NULL) { - } - - explicit CellInfo(double* ptr) - : values(ptr) { - } - - double* values; - Mutex m; -}; - -class BlockRandomAccessMatrix { - public: - virtual ~BlockRandomAccessMatrix(); - - // If the cell (row_block_id, col_block_id) is present, then return - // a CellInfo with a pointer to the dense matrix containing it, - // otherwise return NULL. The dense matrix containing this cell has - // size row_stride, col_stride and the cell is located at position - // (row, col) within this matrix. - // - // The size of the cell is row_block_size x col_block_size is - // assumed known to the caller. row_block_size less than or equal to - // row_stride and col_block_size is upper bounded by col_stride. - virtual CellInfo* GetCell(int row_block_id, - int col_block_id, - int* row, - int* col, - int* row_stride, - int* col_stride) = 0; - - // Zero out the values of the array. The structure of the matrix - // (size and sparsity) is preserved. - virtual void SetZero() = 0; - - // Number of scalar rows and columns in the matrix, i.e the sum of - // all row blocks and column block sizes respectively. - virtual int num_rows() const = 0; - virtual int num_cols() const = 0; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_BLOCK_RANDOM_ACCESS_MATRIX_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.cc deleted file mode 100644 index 5432ec1064a..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.cc +++ /dev/null @@ -1,196 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/block_random_access_sparse_matrix.h" - -#include <algorithm> -#include <set> -#include <utility> -#include <vector> -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/mutex.h" -#include "ceres/triplet_sparse_matrix.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::make_pair; -using std::pair; -using std::set; -using std::vector; - -BlockRandomAccessSparseMatrix::BlockRandomAccessSparseMatrix( - const vector<int>& blocks, - const set<pair<int, int> >& block_pairs) - : kMaxRowBlocks(10 * 1000 * 1000), - blocks_(blocks) { - CHECK_LT(blocks.size(), kMaxRowBlocks); - - // Build the row/column layout vector and count the number of scalar - // rows/columns. - int num_cols = 0; - block_positions_.reserve(blocks_.size()); - for (int i = 0; i < blocks_.size(); ++i) { - block_positions_.push_back(num_cols); - num_cols += blocks_[i]; - } - - // Count the number of scalar non-zero entries and build the layout - // object for looking into the values array of the - // TripletSparseMatrix. - int num_nonzeros = 0; - for (set<pair<int, int> >::const_iterator it = block_pairs.begin(); - it != block_pairs.end(); - ++it) { - const int row_block_size = blocks_[it->first]; - const int col_block_size = blocks_[it->second]; - num_nonzeros += row_block_size * col_block_size; - } - - VLOG(1) << "Matrix Size [" << num_cols - << "," << num_cols - << "] " << num_nonzeros; - - tsm_.reset(new TripletSparseMatrix(num_cols, num_cols, num_nonzeros)); - tsm_->set_num_nonzeros(num_nonzeros); - int* rows = tsm_->mutable_rows(); - int* cols = tsm_->mutable_cols(); - double* values = tsm_->mutable_values(); - - int pos = 0; - for (set<pair<int, int> >::const_iterator it = block_pairs.begin(); - it != block_pairs.end(); - ++it) { - const int row_block_size = blocks_[it->first]; - const int col_block_size = blocks_[it->second]; - cell_values_.push_back(make_pair(make_pair(it->first, it->second), - values + pos)); - layout_[IntPairToLong(it->first, it->second)] = - new CellInfo(values + pos); - pos += row_block_size * col_block_size; - } - - // Fill the sparsity pattern of the underlying matrix. - for (set<pair<int, int> >::const_iterator it = block_pairs.begin(); - it != block_pairs.end(); - ++it) { - const int row_block_id = it->first; - const int col_block_id = it->second; - const int row_block_size = blocks_[row_block_id]; - const int col_block_size = blocks_[col_block_id]; - int pos = - layout_[IntPairToLong(row_block_id, col_block_id)]->values - values; - for (int r = 0; r < row_block_size; ++r) { - for (int c = 0; c < col_block_size; ++c, ++pos) { - rows[pos] = block_positions_[row_block_id] + r; - cols[pos] = block_positions_[col_block_id] + c; - values[pos] = 1.0; - DCHECK_LT(rows[pos], tsm_->num_rows()); - DCHECK_LT(cols[pos], tsm_->num_rows()); - } - } - } -} - -// Assume that the user does not hold any locks on any cell blocks -// when they are calling SetZero. -BlockRandomAccessSparseMatrix::~BlockRandomAccessSparseMatrix() { - for (LayoutType::iterator it = layout_.begin(); - it != layout_.end(); - ++it) { - delete it->second; - } -} - -CellInfo* BlockRandomAccessSparseMatrix::GetCell(int row_block_id, - int col_block_id, - int* row, - int* col, - int* row_stride, - int* col_stride) { - const LayoutType::iterator it = - layout_.find(IntPairToLong(row_block_id, col_block_id)); - if (it == layout_.end()) { - return NULL; - } - - // Each cell is stored contiguously as its own little dense matrix. - *row = 0; - *col = 0; - *row_stride = blocks_[row_block_id]; - *col_stride = blocks_[col_block_id]; - return it->second; -} - -// Assume that the user does not hold any locks on any cell blocks -// when they are calling SetZero. -void BlockRandomAccessSparseMatrix::SetZero() { - if (tsm_->num_nonzeros()) { - VectorRef(tsm_->mutable_values(), - tsm_->num_nonzeros()).setZero(); - } -} - -void BlockRandomAccessSparseMatrix::SymmetricRightMultiply(const double* x, - double* y) const { - vector< pair<pair<int, int>, double*> >::const_iterator it = - cell_values_.begin(); - for (; it != cell_values_.end(); ++it) { - const int row = it->first.first; - const int row_block_size = blocks_[row]; - const int row_block_pos = block_positions_[row]; - - const int col = it->first.second; - const int col_block_size = blocks_[col]; - const int col_block_pos = block_positions_[col]; - - MatrixVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>( - it->second, row_block_size, col_block_size, - x + col_block_pos, - y + row_block_pos); - - // Since the matrix is symmetric, but only the upper triangular - // part is stored, if the block being accessed is not a diagonal - // block, then use the same block to do the corresponding lower - // triangular multiply also. - if (row != col) { - MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>( - it->second, row_block_size, col_block_size, - x + row_block_pos, - y + col_block_pos); - } - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.h deleted file mode 100644 index 2b3c7fdabae..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.h +++ /dev/null @@ -1,129 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_BLOCK_RANDOM_ACCESS_SPARSE_MATRIX_H_ -#define CERES_INTERNAL_BLOCK_RANDOM_ACCESS_SPARSE_MATRIX_H_ - -#include <set> -#include <vector> -#include <utility> -#include "ceres/mutex.h" -#include "ceres/block_random_access_matrix.h" -#include "ceres/collections_port.h" -#include "ceres/triplet_sparse_matrix.h" -#include "ceres/integral_types.h" -#include "ceres/internal/macros.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/types.h" -#include "ceres/small_blas.h" - -namespace ceres { -namespace internal { - -// A thread safe square block sparse implementation of -// BlockRandomAccessMatrix. Internally a TripletSparseMatrix is used -// for doing the actual storage. This class augments this matrix with -// an unordered_map that allows random read/write access. -class BlockRandomAccessSparseMatrix : public BlockRandomAccessMatrix { - public: - // blocks is an array of block sizes. block_pairs is a set of - // <row_block_id, col_block_id> pairs to identify the non-zero cells - // of this matrix. - BlockRandomAccessSparseMatrix( - const std::vector<int>& blocks, - const std::set<std::pair<int, int> >& block_pairs); - - // The destructor is not thread safe. It assumes that no one is - // modifying any cells when the matrix is being destroyed. - virtual ~BlockRandomAccessSparseMatrix(); - - // BlockRandomAccessMatrix Interface. - virtual CellInfo* GetCell(int row_block_id, - int col_block_id, - int* row, - int* col, - int* row_stride, - int* col_stride); - - // This is not a thread safe method, it assumes that no cell is - // locked. - virtual void SetZero(); - - // Assume that the matrix is symmetric and only one half of the - // matrix is stored. - // - // y += S * x - void SymmetricRightMultiply(const double* x, double* y) const; - - // Since the matrix is square, num_rows() == num_cols(). - virtual int num_rows() const { return tsm_->num_rows(); } - virtual int num_cols() const { return tsm_->num_cols(); } - - // Access to the underlying matrix object. - const TripletSparseMatrix* matrix() const { return tsm_.get(); } - TripletSparseMatrix* mutable_matrix() { return tsm_.get(); } - - private: - int64 IntPairToLong(int row, int col) const { - return row * kMaxRowBlocks + col; - } - - void LongToIntPair(int64 index, int* row, int* col) const { - *row = index / kMaxRowBlocks; - *col = index % kMaxRowBlocks; - } - - const int64 kMaxRowBlocks; - - // row/column block sizes. - const std::vector<int> blocks_; - std::vector<int> block_positions_; - - // A mapping from <row_block_id, col_block_id> to the position in - // the values array of tsm_ where the block is stored. - typedef HashMap<long int, CellInfo* > LayoutType; - LayoutType layout_; - - // In order traversal of contents of the matrix. This allows us to - // implement a matrix-vector which is 20% faster than using the - // iterator in the Layout object instead. - std::vector<std::pair<std::pair<int, int>, double*> > cell_values_; - // The underlying matrix object which actually stores the cells. - scoped_ptr<TripletSparseMatrix> tsm_; - - friend class BlockRandomAccessSparseMatrixTest; - CERES_DISALLOW_COPY_AND_ASSIGN(BlockRandomAccessSparseMatrix); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_BLOCK_RANDOM_ACCESS_SPARSE_MATRIX_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.cc deleted file mode 100644 index 68d0780156c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.cc +++ /dev/null @@ -1,246 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/block_sparse_matrix.h" - -#include <cstddef> -#include <algorithm> -#include <vector> -#include "ceres/block_structure.h" -#include "ceres/internal/eigen.h" -#include "ceres/small_blas.h" -#include "ceres/triplet_sparse_matrix.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::vector; - -BlockSparseMatrix::~BlockSparseMatrix() {} - -BlockSparseMatrix::BlockSparseMatrix( - CompressedRowBlockStructure* block_structure) - : num_rows_(0), - num_cols_(0), - num_nonzeros_(0), - values_(NULL), - block_structure_(block_structure) { - CHECK_NOTNULL(block_structure_.get()); - - // Count the number of columns in the matrix. - for (int i = 0; i < block_structure_->cols.size(); ++i) { - num_cols_ += block_structure_->cols[i].size; - } - - // Count the number of non-zero entries and the number of rows in - // the matrix. - for (int i = 0; i < block_structure_->rows.size(); ++i) { - int row_block_size = block_structure_->rows[i].block.size; - num_rows_ += row_block_size; - - const vector<Cell>& cells = block_structure_->rows[i].cells; - for (int j = 0; j < cells.size(); ++j) { - int col_block_id = cells[j].block_id; - int col_block_size = block_structure_->cols[col_block_id].size; - num_nonzeros_ += col_block_size * row_block_size; - } - } - - CHECK_GE(num_rows_, 0); - CHECK_GE(num_cols_, 0); - CHECK_GE(num_nonzeros_, 0); - VLOG(2) << "Allocating values array with " - << num_nonzeros_ * sizeof(double) << " bytes."; // NOLINT - values_.reset(new double[num_nonzeros_]); - CHECK_NOTNULL(values_.get()); -} - -void BlockSparseMatrix::SetZero() { - std::fill(values_.get(), values_.get() + num_nonzeros_, 0.0); -} - -void BlockSparseMatrix::RightMultiply(const double* x, double* y) const { - CHECK_NOTNULL(x); - CHECK_NOTNULL(y); - - for (int i = 0; i < block_structure_->rows.size(); ++i) { - int row_block_pos = block_structure_->rows[i].block.position; - int row_block_size = block_structure_->rows[i].block.size; - const vector<Cell>& cells = block_structure_->rows[i].cells; - for (int j = 0; j < cells.size(); ++j) { - int col_block_id = cells[j].block_id; - int col_block_size = block_structure_->cols[col_block_id].size; - int col_block_pos = block_structure_->cols[col_block_id].position; - MatrixVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>( - values_.get() + cells[j].position, row_block_size, col_block_size, - x + col_block_pos, - y + row_block_pos); - } - } -} - -void BlockSparseMatrix::LeftMultiply(const double* x, double* y) const { - CHECK_NOTNULL(x); - CHECK_NOTNULL(y); - - for (int i = 0; i < block_structure_->rows.size(); ++i) { - int row_block_pos = block_structure_->rows[i].block.position; - int row_block_size = block_structure_->rows[i].block.size; - const vector<Cell>& cells = block_structure_->rows[i].cells; - for (int j = 0; j < cells.size(); ++j) { - int col_block_id = cells[j].block_id; - int col_block_size = block_structure_->cols[col_block_id].size; - int col_block_pos = block_structure_->cols[col_block_id].position; - MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>( - values_.get() + cells[j].position, row_block_size, col_block_size, - x + row_block_pos, - y + col_block_pos); - } - } -} - -void BlockSparseMatrix::SquaredColumnNorm(double* x) const { - CHECK_NOTNULL(x); - VectorRef(x, num_cols_).setZero(); - for (int i = 0; i < block_structure_->rows.size(); ++i) { - int row_block_size = block_structure_->rows[i].block.size; - const vector<Cell>& cells = block_structure_->rows[i].cells; - for (int j = 0; j < cells.size(); ++j) { - int col_block_id = cells[j].block_id; - int col_block_size = block_structure_->cols[col_block_id].size; - int col_block_pos = block_structure_->cols[col_block_id].position; - const MatrixRef m(values_.get() + cells[j].position, - row_block_size, col_block_size); - VectorRef(x + col_block_pos, col_block_size) += m.colwise().squaredNorm(); - } - } -} - -void BlockSparseMatrix::ScaleColumns(const double* scale) { - CHECK_NOTNULL(scale); - - for (int i = 0; i < block_structure_->rows.size(); ++i) { - int row_block_size = block_structure_->rows[i].block.size; - const vector<Cell>& cells = block_structure_->rows[i].cells; - for (int j = 0; j < cells.size(); ++j) { - int col_block_id = cells[j].block_id; - int col_block_size = block_structure_->cols[col_block_id].size; - int col_block_pos = block_structure_->cols[col_block_id].position; - MatrixRef m(values_.get() + cells[j].position, - row_block_size, col_block_size); - m *= ConstVectorRef(scale + col_block_pos, col_block_size).asDiagonal(); - } - } -} - -void BlockSparseMatrix::ToDenseMatrix(Matrix* dense_matrix) const { - CHECK_NOTNULL(dense_matrix); - - dense_matrix->resize(num_rows_, num_cols_); - dense_matrix->setZero(); - Matrix& m = *dense_matrix; - - for (int i = 0; i < block_structure_->rows.size(); ++i) { - int row_block_pos = block_structure_->rows[i].block.position; - int row_block_size = block_structure_->rows[i].block.size; - const vector<Cell>& cells = block_structure_->rows[i].cells; - for (int j = 0; j < cells.size(); ++j) { - int col_block_id = cells[j].block_id; - int col_block_size = block_structure_->cols[col_block_id].size; - int col_block_pos = block_structure_->cols[col_block_id].position; - int jac_pos = cells[j].position; - m.block(row_block_pos, col_block_pos, row_block_size, col_block_size) - += MatrixRef(values_.get() + jac_pos, row_block_size, col_block_size); - } - } -} - -void BlockSparseMatrix::ToTripletSparseMatrix( - TripletSparseMatrix* matrix) const { - CHECK_NOTNULL(matrix); - - matrix->Reserve(num_nonzeros_); - matrix->Resize(num_rows_, num_cols_); - matrix->SetZero(); - - for (int i = 0; i < block_structure_->rows.size(); ++i) { - int row_block_pos = block_structure_->rows[i].block.position; - int row_block_size = block_structure_->rows[i].block.size; - const vector<Cell>& cells = block_structure_->rows[i].cells; - for (int j = 0; j < cells.size(); ++j) { - int col_block_id = cells[j].block_id; - int col_block_size = block_structure_->cols[col_block_id].size; - int col_block_pos = block_structure_->cols[col_block_id].position; - int jac_pos = cells[j].position; - for (int r = 0; r < row_block_size; ++r) { - for (int c = 0; c < col_block_size; ++c, ++jac_pos) { - matrix->mutable_rows()[jac_pos] = row_block_pos + r; - matrix->mutable_cols()[jac_pos] = col_block_pos + c; - matrix->mutable_values()[jac_pos] = values_[jac_pos]; - } - } - } - } - matrix->set_num_nonzeros(num_nonzeros_); -} - -// Return a pointer to the block structure. We continue to hold -// ownership of the object though. -const CompressedRowBlockStructure* BlockSparseMatrix::block_structure() - const { - return block_structure_.get(); -} - -void BlockSparseMatrix::ToTextFile(FILE* file) const { - CHECK_NOTNULL(file); - for (int i = 0; i < block_structure_->rows.size(); ++i) { - const int row_block_pos = block_structure_->rows[i].block.position; - const int row_block_size = block_structure_->rows[i].block.size; - const vector<Cell>& cells = block_structure_->rows[i].cells; - for (int j = 0; j < cells.size(); ++j) { - const int col_block_id = cells[j].block_id; - const int col_block_size = block_structure_->cols[col_block_id].size; - const int col_block_pos = block_structure_->cols[col_block_id].position; - int jac_pos = cells[j].position; - for (int r = 0; r < row_block_size; ++r) { - for (int c = 0; c < col_block_size; ++c) { - fprintf(file, "% 10d % 10d %17f\n", - row_block_pos + r, - col_block_pos + c, - values_[jac_pos++]); - } - } - } - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.h deleted file mode 100644 index 2f9afb738f8..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.h +++ /dev/null @@ -1,100 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Implementation of the SparseMatrix interface for block sparse -// matrices. - -#ifndef CERES_INTERNAL_BLOCK_SPARSE_MATRIX_H_ -#define CERES_INTERNAL_BLOCK_SPARSE_MATRIX_H_ - -#include "ceres/block_structure.h" -#include "ceres/sparse_matrix.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/macros.h" -#include "ceres/internal/scoped_ptr.h" - -namespace ceres { -namespace internal { - -class TripletSparseMatrix; - -// This class implements the SparseMatrix interface for storing and -// manipulating block sparse matrices. The block structure is stored -// in the CompressedRowBlockStructure object and one is needed to -// initialize the matrix. For details on how the blocks structure of -// the matrix is stored please see the documentation -// -// internal/ceres/block_structure.h -// -class BlockSparseMatrix : public SparseMatrix { - public: - // Construct a block sparse matrix with a fully initialized - // CompressedRowBlockStructure objected. The matrix takes over - // ownership of this object and destroys it upon destruction. - // - // TODO(sameeragarwal): Add a function which will validate legal - // CompressedRowBlockStructure objects. - explicit BlockSparseMatrix(CompressedRowBlockStructure* block_structure); - - BlockSparseMatrix(); - virtual ~BlockSparseMatrix(); - - // Implementation of SparseMatrix interface. - virtual void SetZero(); - virtual void RightMultiply(const double* x, double* y) const; - virtual void LeftMultiply(const double* x, double* y) const; - virtual void SquaredColumnNorm(double* x) const; - virtual void ScaleColumns(const double* scale); - virtual void ToDenseMatrix(Matrix* dense_matrix) const; - virtual void ToTextFile(FILE* file) const; - - virtual int num_rows() const { return num_rows_; } - virtual int num_cols() const { return num_cols_; } - virtual int num_nonzeros() const { return num_nonzeros_; } - virtual const double* values() const { return values_.get(); } - virtual double* mutable_values() { return values_.get(); } - - void ToTripletSparseMatrix(TripletSparseMatrix* matrix) const; - const CompressedRowBlockStructure* block_structure() const; - - private: - int num_rows_; - int num_cols_; - int max_num_nonzeros_; - int num_nonzeros_; - scoped_array<double> values_; - scoped_ptr<CompressedRowBlockStructure> block_structure_; - CERES_DISALLOW_COPY_AND_ASSIGN(BlockSparseMatrix); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_BLOCK_SPARSE_MATRIX_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_structure.cc b/extern/libmv/third_party/ceres/internal/ceres/block_structure.cc deleted file mode 100644 index 6479b60f700..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_structure.cc +++ /dev/null @@ -1,44 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/block_structure.h" - -namespace ceres { -namespace internal { - -bool CellLessThan(const Cell& lhs, const Cell& rhs) { - if (lhs.block_id == rhs.block_id) { - return (lhs.position < rhs.position); - } - return (lhs.block_id < rhs.block_id); -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_structure.h b/extern/libmv/third_party/ceres/internal/ceres/block_structure.h deleted file mode 100644 index 6e7003addb6..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/block_structure.h +++ /dev/null @@ -1,93 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Block structure objects are used to carry information about the -// dense block structure of sparse matrices. The BlockSparseMatrix -// object uses the BlockStructure objects to keep track of the matrix -// structure and operate upon it. This allows us to use more cache -// friendly block oriented linear algebra operations on the matrix -// instead of accessing it one scalar entry at a time. - -#ifndef CERES_INTERNAL_BLOCK_STRUCTURE_H_ -#define CERES_INTERNAL_BLOCK_STRUCTURE_H_ - -#include <vector> -#include "ceres/internal/port.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -typedef int32 BlockSize; - -struct Block { - Block() : size(-1), position(-1) {} - Block(int size_, int position_) : size(size_), position(position_) {} - - BlockSize size; - int position; // Position along the row/column. -}; - -struct Cell { - Cell() : block_id(-1), position(-1) {} - Cell(int block_id_, int position_) - : block_id(block_id_), position(position_) {} - - // Column or row block id as the case maybe. - int block_id; - // Where in the values array of the jacobian is this cell located. - int position; -}; - -// Order cell by their block_id; -bool CellLessThan(const Cell& lhs, const Cell& rhs); - -struct CompressedList { - Block block; - std::vector<Cell> cells; -}; - -typedef CompressedList CompressedRow; -typedef CompressedList CompressedColumn; - -struct CompressedRowBlockStructure { - std::vector<Block> cols; - std::vector<CompressedRow> rows; -}; - -struct CompressedColumnBlockStructure { - std::vector<Block> rows; - std::vector<CompressedColumn> cols; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_BLOCK_STRUCTURE_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/c_api.cc b/extern/libmv/third_party/ceres/internal/ceres/c_api.cc deleted file mode 100644 index ada8f3e0013..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/c_api.cc +++ /dev/null @@ -1,188 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: mierle@gmail.com (Keir Mierle) -// -// An incomplete C API for Ceres. -// -// TODO(keir): Figure out why logging does not seem to work. - -#include "ceres/c_api.h" - -#include <vector> -#include <iostream> -#include <string> -#include "ceres/cost_function.h" -#include "ceres/loss_function.h" -#include "ceres/problem.h" -#include "ceres/solver.h" -#include "ceres/types.h" // for std -#include "glog/logging.h" - -using ceres::Problem; - -void ceres_init() { - // This is not ideal, but it's not clear what to do if there is no gflags and - // no access to command line arguments. - char message[] = "<unknown>"; - google::InitGoogleLogging(message); -} - -ceres_problem_t* ceres_create_problem() { - return reinterpret_cast<ceres_problem_t*>(new Problem); -} - -void ceres_free_problem(ceres_problem_t* problem) { - delete reinterpret_cast<Problem*>(problem); -} - -// This cost function wraps a C-level function pointer from the user, to bridge -// between C and C++. -class CallbackCostFunction : public ceres::CostFunction { - public: - CallbackCostFunction(ceres_cost_function_t cost_function, - void* user_data, - int num_residuals, - int num_parameter_blocks, - int* parameter_block_sizes) - : cost_function_(cost_function), - user_data_(user_data) { - set_num_residuals(num_residuals); - for (int i = 0; i < num_parameter_blocks; ++i) { - mutable_parameter_block_sizes()->push_back(parameter_block_sizes[i]); - } - } - - virtual ~CallbackCostFunction() {} - - virtual bool Evaluate(double const* const* parameters, - double* residuals, - double** jacobians) const { - return (*cost_function_)(user_data_, - const_cast<double**>(parameters), - residuals, - jacobians); - } - - private: - ceres_cost_function_t cost_function_; - void* user_data_; -}; - -// This loss function wraps a C-level function pointer from the user, to bridge -// between C and C++. -class CallbackLossFunction : public ceres::LossFunction { - public: - explicit CallbackLossFunction(ceres_loss_function_t loss_function, - void* user_data) - : loss_function_(loss_function), user_data_(user_data) {} - virtual void Evaluate(double sq_norm, double* rho) const { - (*loss_function_)(user_data_, sq_norm, rho); - } - - private: - ceres_loss_function_t loss_function_; - void* user_data_; -}; - -// Wrappers for the stock loss functions. -void* ceres_create_huber_loss_function_data(double a) { - return new ceres::HuberLoss(a); -} -void* ceres_create_softl1_loss_function_data(double a) { - return new ceres::SoftLOneLoss(a); -} -void* ceres_create_cauchy_loss_function_data(double a) { - return new ceres::CauchyLoss(a); -} -void* ceres_create_arctan_loss_function_data(double a) { - return new ceres::ArctanLoss(a); -} -void* ceres_create_tolerant_loss_function_data(double a, double b) { - return new ceres::TolerantLoss(a, b); -} - -void ceres_free_stock_loss_function_data(void* loss_function_data) { - delete reinterpret_cast<ceres::LossFunction*>(loss_function_data); -} - -void ceres_stock_loss_function(void* user_data, - double squared_norm, - double out[3]) { - reinterpret_cast<ceres::LossFunction*>(user_data) - ->Evaluate(squared_norm, out); -} - -ceres_residual_block_id_t* ceres_problem_add_residual_block( - ceres_problem_t* problem, - ceres_cost_function_t cost_function, - void* cost_function_data, - ceres_loss_function_t loss_function, - void* loss_function_data, - int num_residuals, - int num_parameter_blocks, - int* parameter_block_sizes, - double** parameters) { - Problem* ceres_problem = reinterpret_cast<Problem*>(problem); - - ceres::CostFunction* callback_cost_function = - new CallbackCostFunction(cost_function, - cost_function_data, - num_residuals, - num_parameter_blocks, - parameter_block_sizes); - - ceres::LossFunction* callback_loss_function = NULL; - if (loss_function != NULL) { - callback_loss_function = new CallbackLossFunction(loss_function, - loss_function_data); - } - - std::vector<double*> parameter_blocks(parameters, - parameters + num_parameter_blocks); - return reinterpret_cast<ceres_residual_block_id_t*>( - ceres_problem->AddResidualBlock(callback_cost_function, - callback_loss_function, - parameter_blocks)); -} - -void ceres_solve(ceres_problem_t* c_problem) { - Problem* problem = reinterpret_cast<Problem*>(c_problem); - - // TODO(keir): Obviously, this way of setting options won't scale or last. - // Instead, figure out a way to specify some of the options without - // duplicating everything. - ceres::Solver::Options options; - options.max_num_iterations = 100; - options.linear_solver_type = ceres::DENSE_QR; - options.minimizer_progress_to_stdout = true; - - ceres::Solver::Summary summary; - ceres::Solve(options, problem, &summary); - std::cout << summary.FullReport() << "\n"; -} diff --git a/extern/libmv/third_party/ceres/internal/ceres/callbacks.cc b/extern/libmv/third_party/ceres/internal/ceres/callbacks.cc deleted file mode 100644 index 50a0ec19924..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/callbacks.cc +++ /dev/null @@ -1,111 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include <iostream> // NO LINT -#include "ceres/callbacks.h" -#include "ceres/program.h" -#include "ceres/stringprintf.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::string; - -StateUpdatingCallback::StateUpdatingCallback(Program* program, - double* parameters) - : program_(program), parameters_(parameters) {} - -StateUpdatingCallback::~StateUpdatingCallback() {} - -CallbackReturnType StateUpdatingCallback::operator()( - const IterationSummary& summary) { - if (summary.step_is_successful) { - program_->StateVectorToParameterBlocks(parameters_); - program_->CopyParameterBlockStateToUserState(); - } - return SOLVER_CONTINUE; -} - -LoggingCallback::LoggingCallback(const MinimizerType minimizer_type, - const bool log_to_stdout) - : minimizer_type(minimizer_type), - log_to_stdout_(log_to_stdout) {} - -LoggingCallback::~LoggingCallback() {} - -CallbackReturnType LoggingCallback::operator()( - const IterationSummary& summary) { - string output; - if (minimizer_type == LINE_SEARCH) { - const char* kReportRowFormat = - "% 4d: f:% 8e d:% 3.2e g:% 3.2e h:% 3.2e " - "s:% 3.2e e:% 3d it:% 3.2e tt:% 3.2e"; - output = StringPrintf(kReportRowFormat, - summary.iteration, - summary.cost, - summary.cost_change, - summary.gradient_max_norm, - summary.step_norm, - summary.step_size, - summary.line_search_function_evaluations, - summary.iteration_time_in_seconds, - summary.cumulative_time_in_seconds); - } else if (minimizer_type == TRUST_REGION) { - if (summary.iteration == 0) { - output = "iter cost cost_change |gradient| |step| tr_ratio tr_radius ls_iter iter_time total_time\n"; // NOLINT - } - const char* kReportRowFormat = - "% 4d % 8e % 3.2e % 3.2e % 3.2e % 3.2e % 3.2e % 4d % 3.2e % 3.2e"; // NOLINT - output += StringPrintf(kReportRowFormat, - summary.iteration, - summary.cost, - summary.cost_change, - summary.gradient_max_norm, - summary.step_norm, - summary.relative_decrease, - summary.trust_region_radius, - summary.linear_solver_iterations, - summary.iteration_time_in_seconds, - summary.cumulative_time_in_seconds); - } else { - LOG(FATAL) << "Unknown minimizer type."; - } - - if (log_to_stdout_) { - std::cout << output << std::endl; - } else { - VLOG(1) << output; - } - return SOLVER_CONTINUE; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/callbacks.h b/extern/libmv/third_party/ceres/internal/ceres/callbacks.h deleted file mode 100644 index 33c66df5c11..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/callbacks.h +++ /dev/null @@ -1,71 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_CALLBACKS_H_ -#define CERES_INTERNAL_CALLBACKS_H_ - -#include <string> -#include "ceres/iteration_callback.h" -#include "ceres/internal/port.h" - -namespace ceres { -namespace internal { - -class Program; - -// Callback for updating the externally visible state of parameter -// blocks. -class StateUpdatingCallback : public IterationCallback { - public: - StateUpdatingCallback(Program* program, double* parameters); - virtual ~StateUpdatingCallback(); - virtual CallbackReturnType operator()(const IterationSummary& summary); - private: - Program* program_; - double* parameters_; -}; - -// Callback for logging the state of the minimizer to STDERR or -// STDOUT depending on the user's preferences and logging level. -class LoggingCallback : public IterationCallback { - public: - LoggingCallback(MinimizerType minimizer_type, bool log_to_stdout); - virtual ~LoggingCallback(); - virtual CallbackReturnType operator()(const IterationSummary& summary); - - private: - const MinimizerType minimizer_type; - const bool log_to_stdout_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_CALLBACKS_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/casts.h b/extern/libmv/third_party/ceres/internal/ceres/casts.h deleted file mode 100644 index f18fdea2d86..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/casts.h +++ /dev/null @@ -1,108 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#ifndef CERES_INTERNAL_CASTS_H_ -#define CERES_INTERNAL_CASTS_H_ - -#include <cassert> -#include <cstddef> // For NULL. - -namespace ceres { - -// Identity metafunction. -template <class T> -struct identity_ { - typedef T type; -}; - -// Use implicit_cast as a safe version of static_cast or const_cast -// for implicit conversions. For example: -// - Upcasting in a type hierarchy. -// - Performing arithmetic conversions (int32 to int64, int to double, etc.). -// - Adding const or volatile qualifiers. -// -// In general, implicit_cast can be used to convert this code -// To to = from; -// DoSomething(to); -// to this -// DoSomething(implicit_cast<To>(from)); -// -// base::identity_ is used to make a non-deduced context, which -// forces all callers to explicitly specify the template argument. -template<typename To> -inline To implicit_cast(typename identity_<To>::type to) { - return to; -} - -// This version of implicit_cast is used when two template arguments -// are specified. It's obsolete and should not be used. -template<typename To, typename From> -inline To implicit_cast(typename identity_<From>::type const &f) { - return f; -} - -// When you upcast (that is, cast a pointer from type Foo to type -// SuperclassOfFoo), it's fine to use implicit_cast<>, since upcasts -// always succeed. When you downcast (that is, cast a pointer from -// type Foo to type SubclassOfFoo), static_cast<> isn't safe, because -// how do you know the pointer is really of type SubclassOfFoo? It -// could be a bare Foo, or of type DifferentSubclassOfFoo. Thus, -// when you downcast, you should use this macro. In debug mode, we -// use dynamic_cast<> to double-check the downcast is legal (we die -// if it's not). In normal mode, we do the efficient static_cast<> -// instead. Thus, it's important to test in debug mode to make sure -// the cast is legal! -// This is the only place in the code we should use dynamic_cast<>. -// In particular, you SHOULDN'T be using dynamic_cast<> in order to -// do RTTI (eg code like this: -// if (dynamic_cast<Subclass1>(foo)) HandleASubclass1Object(foo); -// if (dynamic_cast<Subclass2>(foo)) HandleASubclass2Object(foo); -// You should design the code some other way not to need this. - -template<typename To, typename From> // use like this: down_cast<T*>(foo); -inline To down_cast(From* f) { // so we only accept pointers - // Ensures that To is a sub-type of From *. This test is here only - // for compile-time type checking, and has no overhead in an - // optimized build at run-time, as it will be optimized away - // completely. - - // TODO(csilvers): This should use COMPILE_ASSERT. - if (false) { - implicit_cast<From*, To>(NULL); - } - - // uses RTTI in dbg and fastbuild. asserts are disabled in opt builds. - assert(f == NULL || dynamic_cast<To>(f) != NULL); // NOLINT - return static_cast<To>(f); -} - -} // namespace ceres - -#endif // CERES_INTERNAL_CASTS_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/cgnr_linear_operator.h b/extern/libmv/third_party/ceres/internal/ceres/cgnr_linear_operator.h deleted file mode 100644 index 44c07cabd01..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/cgnr_linear_operator.h +++ /dev/null @@ -1,120 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#ifndef CERES_INTERNAL_CGNR_LINEAR_OPERATOR_H_ -#define CERES_INTERNAL_CGNR_LINEAR_OPERATOR_H_ - -#include <algorithm> -#include "ceres/linear_operator.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -class SparseMatrix; - -// A linear operator which takes a matrix A and a diagonal vector D and -// performs products of the form -// -// (A^T A + D^T D)x -// -// This is used to implement iterative general sparse linear solving with -// conjugate gradients, where A is the Jacobian and D is a regularizing -// parameter. A brief proof that D^T D is the correct regularizer: -// -// Given a regularized least squares problem: -// -// min ||Ax - b||^2 + ||Dx||^2 -// x -// -// First expand into matrix notation: -// -// (Ax - b)^T (Ax - b) + xD^TDx -// -// Then multiply out to get: -// -// = xA^TAx - 2b^T Ax + b^Tb + xD^TDx -// -// Take the derivative: -// -// 0 = 2A^TAx - 2A^T b + 2 D^TDx -// 0 = A^TAx - A^T b + D^TDx -// 0 = (A^TA + D^TD)x - A^T b -// -// Thus, the symmetric system we need to solve for CGNR is -// -// Sx = z -// -// with S = A^TA + D^TD -// and z = A^T b -// -// Note: This class is not thread safe, since it uses some temporary storage. -class CgnrLinearOperator : public LinearOperator { - public: - CgnrLinearOperator(const LinearOperator& A, const double *D) - : A_(A), D_(D), z_(new double[A.num_rows()]) { - } - virtual ~CgnrLinearOperator() {} - - virtual void RightMultiply(const double* x, double* y) const { - std::fill(z_.get(), z_.get() + A_.num_rows(), 0.0); - - // z = Ax - A_.RightMultiply(x, z_.get()); - - // y = y + Atz - A_.LeftMultiply(z_.get(), y); - - // y = y + DtDx - if (D_ != NULL) { - int n = A_.num_cols(); - VectorRef(y, n).array() += ConstVectorRef(D_, n).array().square() * - ConstVectorRef(x, n).array(); - } - } - - virtual void LeftMultiply(const double* x, double* y) const { - RightMultiply(x, y); - } - - virtual int num_rows() const { return A_.num_cols(); } - virtual int num_cols() const { return A_.num_cols(); } - - private: - const LinearOperator& A_; - const double* D_; - scoped_array<double> z_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_CGNR_LINEAR_OPERATOR_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/cgnr_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/cgnr_solver.cc deleted file mode 100644 index 61fae758d5b..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/cgnr_solver.cc +++ /dev/null @@ -1,88 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#include "ceres/cgnr_solver.h" - -#include "ceres/block_jacobi_preconditioner.h" -#include "ceres/cgnr_linear_operator.h" -#include "ceres/conjugate_gradients_solver.h" -#include "ceres/internal/eigen.h" -#include "ceres/linear_solver.h" -#include "ceres/wall_time.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -CgnrSolver::CgnrSolver(const LinearSolver::Options& options) - : options_(options), - preconditioner_(NULL) { - if (options_.preconditioner_type != JACOBI && - options_.preconditioner_type != IDENTITY) { - LOG(FATAL) << "CGNR only supports IDENTITY and JACOBI preconditioners."; - } -} - -LinearSolver::Summary CgnrSolver::SolveImpl( - BlockSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x) { - EventLogger event_logger("CgnrSolver::Solve"); - - // Form z = Atb. - Vector z(A->num_cols()); - z.setZero(); - A->LeftMultiply(b, z.data()); - - // Precondition if necessary. - LinearSolver::PerSolveOptions cg_per_solve_options = per_solve_options; - if (options_.preconditioner_type == JACOBI) { - if (preconditioner_.get() == NULL) { - preconditioner_.reset(new BlockJacobiPreconditioner(*A)); - } - preconditioner_->Update(*A, per_solve_options.D); - cg_per_solve_options.preconditioner = preconditioner_.get(); - } - - // Solve (AtA + DtD)x = z (= Atb). - VectorRef(x, A->num_cols()).setZero(); - CgnrLinearOperator lhs(*A, per_solve_options.D); - event_logger.AddEvent("Setup"); - - ConjugateGradientsSolver conjugate_gradient_solver(options_); - LinearSolver::Summary summary = - conjugate_gradient_solver.Solve(&lhs, z.data(), cg_per_solve_options, x); - event_logger.AddEvent("Solve"); - return summary; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/cgnr_solver.h b/extern/libmv/third_party/ceres/internal/ceres/cgnr_solver.h deleted file mode 100644 index f7a15736925..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/cgnr_solver.h +++ /dev/null @@ -1,69 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#ifndef CERES_INTERNAL_CGNR_SOLVER_H_ -#define CERES_INTERNAL_CGNR_SOLVER_H_ - -#include "ceres/internal/scoped_ptr.h" -#include "ceres/linear_solver.h" - -namespace ceres { -namespace internal { - -class Preconditioner; - -class BlockJacobiPreconditioner; - -// A conjugate gradients on the normal equations solver. This directly solves -// for the solution to -// -// (A^T A + D^T D)x = A^T b -// -// as required for solving for x in the least squares sense. Currently only -// block diagonal preconditioning is supported. -class CgnrSolver : public BlockSparseMatrixSolver { - public: - explicit CgnrSolver(const LinearSolver::Options& options); - virtual Summary SolveImpl( - BlockSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x); - - private: - const LinearSolver::Options options_; - scoped_ptr<Preconditioner> preconditioner_; - CERES_DISALLOW_COPY_AND_ASSIGN(CgnrSolver); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_CGNR_SOLVER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/collections_port.h b/extern/libmv/third_party/ceres/internal/ceres/collections_port.h deleted file mode 100644 index e699a661b8b..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/collections_port.h +++ /dev/null @@ -1,196 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// Portable HashMap and HashSet, and a specialized overload for hashing pairs. - -#ifndef CERES_INTERNAL_COLLECTIONS_PORT_H_ -#define CERES_INTERNAL_COLLECTIONS_PORT_H_ - -#include "ceres/internal/port.h" - -#if defined(CERES_NO_UNORDERED_MAP) -# include <map> -# include <set> -#endif - -#if defined(CERES_TR1_UNORDERED_MAP) -# include <tr1/unordered_map> -# include <tr1/unordered_set> -# define CERES_HASH_NAMESPACE_START namespace std { namespace tr1 { -# define CERES_HASH_NAMESPACE_END } } -#endif - -#if defined(CERES_STD_UNORDERED_MAP) -# include <unordered_map> -# include <unordered_set> -# define CERES_HASH_NAMESPACE_START namespace std { -# define CERES_HASH_NAMESPACE_END } -#endif - -#if defined(CERES_STD_UNORDERED_MAP_IN_TR1_NAMESPACE) -# include <unordered_map> -# include <unordered_set> -# define CERES_HASH_NAMESPACE_START namespace std { namespace tr1 { -# define CERES_HASH_NAMESPACE_END } } -#endif - -#if !defined(CERES_NO_UNORDERED_MAP) && !defined(CERES_TR1_UNORDERED_MAP) && \ - !defined(CERES_STD_UNORDERED_MAP) && !defined(CERES_STD_UNORDERED_MAP_IN_TR1_NAMESPACE) // NOLINT -# error One of: CERES_NO_UNORDERED_MAP, CERES_TR1_UNORDERED_MAP,\ - CERES_STD_UNORDERED_MAP, CERES_STD_UNORDERED_MAP_IN_TR1_NAMESPACE must be defined! // NOLINT -#endif - -#include <utility> -#include "ceres/integral_types.h" - -// Some systems don't have access to unordered_map/unordered_set. In -// that case, substitute the hash map/set with normal map/set. The -// price to pay is slower speed for some operations. -#if defined(CERES_NO_UNORDERED_MAP) - -namespace ceres { -namespace internal { - -template<typename K, typename V> -struct HashMap : map<K, V> {}; - -template<typename K> -struct HashSet : set<K> {}; - -} // namespace internal -} // namespace ceres - -#else - -namespace ceres { -namespace internal { - -#if defined(CERES_TR1_UNORDERED_MAP) || \ - defined(CERES_STD_UNORDERED_MAP_IN_TR1_NAMESPACE) -template<typename K, typename V> -struct HashMap : std::tr1::unordered_map<K, V> {}; -template<typename K> -struct HashSet : std::tr1::unordered_set<K> {}; -#endif - -#if defined(CERES_STD_UNORDERED_MAP) -template<typename K, typename V> -struct HashMap : std::unordered_map<K, V> {}; -template<typename K> -struct HashSet : std::unordered_set<K> {}; -#endif - -#if defined(_WIN32) && !defined(__MINGW64__) && !defined(__MINGW32__) -#define GG_LONGLONG(x) x##I64 -#define GG_ULONGLONG(x) x##UI64 -#else -#define GG_LONGLONG(x) x##LL -#define GG_ULONGLONG(x) x##ULL -#endif - -// The hash function is due to Bob Jenkins (see -// http://burtleburtle.net/bob/hash/index.html). Each mix takes 36 instructions, -// in 18 cycles if you're lucky. On x86 architectures, this requires 45 -// instructions in 27 cycles, if you're lucky. -// -// 32bit version -inline void hash_mix(uint32& a, uint32& b, uint32& c) { - a -= b; a -= c; a ^= (c>>13); - b -= c; b -= a; b ^= (a<<8); - c -= a; c -= b; c ^= (b>>13); - a -= b; a -= c; a ^= (c>>12); - b -= c; b -= a; b ^= (a<<16); - c -= a; c -= b; c ^= (b>>5); - a -= b; a -= c; a ^= (c>>3); - b -= c; b -= a; b ^= (a<<10); - c -= a; c -= b; c ^= (b>>15); -} - -// 64bit version -inline void hash_mix(uint64& a, uint64& b, uint64& c) { - a -= b; a -= c; a ^= (c>>43); - b -= c; b -= a; b ^= (a<<9); - c -= a; c -= b; c ^= (b>>8); - a -= b; a -= c; a ^= (c>>38); - b -= c; b -= a; b ^= (a<<23); - c -= a; c -= b; c ^= (b>>5); - a -= b; a -= c; a ^= (c>>35); - b -= c; b -= a; b ^= (a<<49); - c -= a; c -= b; c ^= (b>>11); -} - -inline uint32 Hash32NumWithSeed(uint32 num, uint32 c) { - // The golden ratio; an arbitrary value. - uint32 b = 0x9e3779b9UL; - hash_mix(num, b, c); - return c; -} - -inline uint64 Hash64NumWithSeed(uint64 num, uint64 c) { - // More of the golden ratio. - uint64 b = GG_ULONGLONG(0xe08c1d668b756f82); - hash_mix(num, b, c); - return c; -} - -} // namespace internal -} // namespace ceres - -// Since on some platforms this is a doubly-nested namespace (std::tr1) and -// others it is not, the entire namespace line must be in a macro. -CERES_HASH_NAMESPACE_START - -// The outrageously annoying specializations below are for portability reasons. -// In short, it's not possible to have two overloads of hash<pair<T1, T2> - -// Hasher for STL pairs. Requires hashers for both members to be defined. -template<typename T> -struct hash<pair<T, T> > { - size_t operator()(const pair<T, T>& p) const { - size_t h1 = hash<T>()(p.first); - size_t h2 = hash<T>()(p.second); - // The decision below is at compile time - return (sizeof(h1) <= sizeof(ceres::internal::uint32)) ? - ceres::internal::Hash32NumWithSeed(h1, h2) : - ceres::internal::Hash64NumWithSeed(h1, h2); - } - // Less than operator for MSVC. - bool operator()(const pair<T, T>& a, - const pair<T, T>& b) const { - return a < b; - } - static const size_t bucket_size = 4; // These are required by MSVC - static const size_t min_buckets = 8; // 4 and 8 are defaults. -}; - -CERES_HASH_NAMESPACE_END - -#endif // CERES_NO_UNORDERED_MAP -#endif // CERES_INTERNAL_COLLECTIONS_PORT_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/compressed_col_sparse_matrix_utils.cc b/extern/libmv/third_party/ceres/internal/ceres/compressed_col_sparse_matrix_utils.cc deleted file mode 100644 index ebb2a62c544..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/compressed_col_sparse_matrix_utils.cc +++ /dev/null @@ -1,122 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/compressed_col_sparse_matrix_utils.h" - -#include <vector> -#include <algorithm> -#include "ceres/internal/port.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::vector; - -void CompressedColumnScalarMatrixToBlockMatrix( - const int* scalar_rows, - const int* scalar_cols, - const vector<int>& row_blocks, - const vector<int>& col_blocks, - vector<int>* block_rows, - vector<int>* block_cols) { - CHECK_NOTNULL(block_rows)->clear(); - CHECK_NOTNULL(block_cols)->clear(); - const int num_row_blocks = row_blocks.size(); - const int num_col_blocks = col_blocks.size(); - - vector<int> row_block_starts(num_row_blocks); - for (int i = 0, cursor = 0; i < num_row_blocks; ++i) { - row_block_starts[i] = cursor; - cursor += row_blocks[i]; - } - - // This loop extracts the block sparsity of the scalar sparse matrix - // It does so by iterating over the columns, but only considering - // the columns corresponding to the first element of each column - // block. Within each column, the inner loop iterates over the rows, - // and detects the presence of a row block by checking for the - // presence of a non-zero entry corresponding to its first element. - block_cols->push_back(0); - int c = 0; - for (int col_block = 0; col_block < num_col_blocks; ++col_block) { - int column_size = 0; - for (int idx = scalar_cols[c]; idx < scalar_cols[c + 1]; ++idx) { - vector<int>::const_iterator it = - std::lower_bound(row_block_starts.begin(), - row_block_starts.end(), - scalar_rows[idx]); - // Since we are using lower_bound, it will return the row id - // where the row block starts. For everything but the first row - // of the block, where these values will be the same, we can - // skip, as we only need the first row to detect the presence of - // the block. - // - // For rows all but the first row in the last row block, - // lower_bound will return row_block_starts.end(), but those can - // be skipped like the rows in other row blocks too. - if (it == row_block_starts.end() || *it != scalar_rows[idx]) { - continue; - } - - block_rows->push_back(it - row_block_starts.begin()); - ++column_size; - } - block_cols->push_back(block_cols->back() + column_size); - c += col_blocks[col_block]; - } -} - -void BlockOrderingToScalarOrdering(const vector<int>& blocks, - const vector<int>& block_ordering, - vector<int>* scalar_ordering) { - CHECK_EQ(blocks.size(), block_ordering.size()); - const int num_blocks = blocks.size(); - - // block_starts = [0, block1, block1 + block2 ..] - vector<int> block_starts(num_blocks); - for (int i = 0, cursor = 0; i < num_blocks ; ++i) { - block_starts[i] = cursor; - cursor += blocks[i]; - } - - scalar_ordering->resize(block_starts.back() + blocks.back()); - int cursor = 0; - for (int i = 0; i < num_blocks; ++i) { - const int block_id = block_ordering[i]; - const int block_size = blocks[block_id]; - int block_position = block_starts[block_id]; - for (int j = 0; j < block_size; ++j) { - (*scalar_ordering)[cursor++] = block_position++; - } - } -} -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/compressed_col_sparse_matrix_utils.h b/extern/libmv/third_party/ceres/internal/ceres/compressed_col_sparse_matrix_utils.h deleted file mode 100644 index da2109fba3e..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/compressed_col_sparse_matrix_utils.h +++ /dev/null @@ -1,144 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_COMPRESSED_COL_SPARSE_MATRIX_UTILS_H_ -#define CERES_INTERNAL_COMPRESSED_COL_SPARSE_MATRIX_UTILS_H_ - -#include <vector> -#include "ceres/internal/port.h" - -namespace ceres { -namespace internal { - -// Extract the block sparsity pattern of the scalar compressed columns -// matrix and return it in compressed column form. The compressed -// column form is stored in two vectors block_rows, and block_cols, -// which correspond to the row and column arrays in a compressed -// column sparse matrix. -// -// If c_ij is the block in the matrix A corresponding to row block i -// and column block j, then it is expected that A contains at least -// one non-zero entry corresponding to the top left entry of c_ij, -// as that entry is used to detect the presence of a non-zero c_ij. -void CompressedColumnScalarMatrixToBlockMatrix( - const int* scalar_rows, - const int* scalar_cols, - const std::vector<int>& row_blocks, - const std::vector<int>& col_blocks, - std::vector<int>* block_rows, - std::vector<int>* block_cols); - -// Given a set of blocks and a permutation of these blocks, compute -// the corresponding "scalar" ordering, where the scalar ordering of -// size sum(blocks). -void BlockOrderingToScalarOrdering( - const std::vector<int>& blocks, - const std::vector<int>& block_ordering, - std::vector<int>* scalar_ordering); - -// Solve the linear system -// -// R * solution = rhs -// -// Where R is an upper triangular compressed column sparse matrix. -template <typename IntegerType> -void SolveUpperTriangularInPlace(IntegerType num_cols, - const IntegerType* rows, - const IntegerType* cols, - const double* values, - double* rhs_and_solution) { - for (IntegerType c = num_cols - 1; c >= 0; --c) { - rhs_and_solution[c] /= values[cols[c + 1] - 1]; - for (IntegerType idx = cols[c]; idx < cols[c + 1] - 1; ++idx) { - const IntegerType r = rows[idx]; - const double v = values[idx]; - rhs_and_solution[r] -= v * rhs_and_solution[c]; - } - } -} - -// Solve the linear system -// -// R' * solution = rhs -// -// Where R is an upper triangular compressed column sparse matrix. -template <typename IntegerType> -void SolveUpperTriangularTransposeInPlace(IntegerType num_cols, - const IntegerType* rows, - const IntegerType* cols, - const double* values, - double* rhs_and_solution) { - for (IntegerType c = 0; c < num_cols; ++c) { - for (IntegerType idx = cols[c]; idx < cols[c + 1] - 1; ++idx) { - const IntegerType r = rows[idx]; - const double v = values[idx]; - rhs_and_solution[c] -= v * rhs_and_solution[r]; - } - rhs_and_solution[c] = rhs_and_solution[c] / values[cols[c + 1] - 1]; - } -} - -// Given a upper triangular matrix R in compressed column form, solve -// the linear system, -// -// R'R x = b -// -// Where b is all zeros except for rhs_nonzero_index, where it is -// equal to one. -// -// The function exploits this knowledge to reduce the number of -// floating point operations. -template <typename IntegerType> -void SolveRTRWithSparseRHS(IntegerType num_cols, - const IntegerType* rows, - const IntegerType* cols, - const double* values, - const int rhs_nonzero_index, - double* solution) { - std::fill(solution, solution + num_cols, 0.0); - solution[rhs_nonzero_index] = 1.0 / values[cols[rhs_nonzero_index + 1] - 1]; - - for (IntegerType c = rhs_nonzero_index + 1; c < num_cols; ++c) { - for (IntegerType idx = cols[c]; idx < cols[c + 1] - 1; ++idx) { - const IntegerType r = rows[idx]; - if (r < rhs_nonzero_index) continue; - const double v = values[idx]; - solution[c] -= v * solution[r]; - } - solution[c] = solution[c] / values[cols[c + 1] - 1]; - } - - SolveUpperTriangularInPlace(num_cols, rows, cols, values, solution); -} - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_COMPRESSED_COL_SPARSE_MATRIX_UTILS_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_jacobian_writer.cc b/extern/libmv/third_party/ceres/internal/ceres/compressed_row_jacobian_writer.cc deleted file mode 100644 index 64b6ac00447..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_jacobian_writer.cc +++ /dev/null @@ -1,233 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#include "ceres/compressed_row_jacobian_writer.h" - -#include <utility> -#include <vector> - -#include "ceres/casts.h" -#include "ceres/compressed_row_sparse_matrix.h" -#include "ceres/parameter_block.h" -#include "ceres/program.h" -#include "ceres/residual_block.h" -#include "ceres/scratch_evaluate_preparer.h" - -namespace ceres { -namespace internal { - -using std::make_pair; -using std::pair; -using std::vector; - -void CompressedRowJacobianWriter::PopulateJacobianRowAndColumnBlockVectors( - const Program* program, CompressedRowSparseMatrix* jacobian) { - const vector<ParameterBlock*>& parameter_blocks = - program->parameter_blocks(); - vector<int>& col_blocks = *(jacobian->mutable_col_blocks()); - col_blocks.resize(parameter_blocks.size()); - for (int i = 0; i < parameter_blocks.size(); ++i) { - col_blocks[i] = parameter_blocks[i]->LocalSize(); - } - - const vector<ResidualBlock*>& residual_blocks = - program->residual_blocks(); - vector<int>& row_blocks = *(jacobian->mutable_row_blocks()); - row_blocks.resize(residual_blocks.size()); - for (int i = 0; i < residual_blocks.size(); ++i) { - row_blocks[i] = residual_blocks[i]->NumResiduals(); - } -} - -void CompressedRowJacobianWriter::GetOrderedParameterBlocks( - const Program* program, - int residual_id, - vector<pair<int, int> >* evaluated_jacobian_blocks) { - const ResidualBlock* residual_block = - program->residual_blocks()[residual_id]; - const int num_parameter_blocks = residual_block->NumParameterBlocks(); - - for (int j = 0; j < num_parameter_blocks; ++j) { - const ParameterBlock* parameter_block = - residual_block->parameter_blocks()[j]; - if (!parameter_block->IsConstant()) { - evaluated_jacobian_blocks->push_back( - make_pair(parameter_block->index(), j)); - } - } - sort(evaluated_jacobian_blocks->begin(), evaluated_jacobian_blocks->end()); -} - -SparseMatrix* CompressedRowJacobianWriter::CreateJacobian() const { - const vector<ResidualBlock*>& residual_blocks = - program_->residual_blocks(); - - int total_num_residuals = program_->NumResiduals(); - int total_num_effective_parameters = program_->NumEffectiveParameters(); - - // Count the number of jacobian nonzeros. - int num_jacobian_nonzeros = 0; - for (int i = 0; i < residual_blocks.size(); ++i) { - ResidualBlock* residual_block = residual_blocks[i]; - const int num_residuals = residual_block->NumResiduals(); - const int num_parameter_blocks = residual_block->NumParameterBlocks(); - for (int j = 0; j < num_parameter_blocks; ++j) { - ParameterBlock* parameter_block = residual_block->parameter_blocks()[j]; - if (!parameter_block->IsConstant()) { - num_jacobian_nonzeros += num_residuals * parameter_block->LocalSize(); - } - } - } - - // Allocate storage for the jacobian with some extra space at the end. - // Allocate more space than needed to store the jacobian so that when the LM - // algorithm adds the diagonal, no reallocation is necessary. This reduces - // peak memory usage significantly. - CompressedRowSparseMatrix* jacobian = - new CompressedRowSparseMatrix( - total_num_residuals, - total_num_effective_parameters, - num_jacobian_nonzeros + total_num_effective_parameters); - - // At this stage, the CompressedRowSparseMatrix is an invalid state. But this - // seems to be the only way to construct it without doing a memory copy. - int* rows = jacobian->mutable_rows(); - int* cols = jacobian->mutable_cols(); - int row_pos = 0; - rows[0] = 0; - for (int i = 0; i < residual_blocks.size(); ++i) { - const ResidualBlock* residual_block = residual_blocks[i]; - const int num_parameter_blocks = residual_block->NumParameterBlocks(); - - // Count the number of derivatives for a row of this residual block and - // build a list of active parameter block indices. - int num_derivatives = 0; - vector<int> parameter_indices; - for (int j = 0; j < num_parameter_blocks; ++j) { - ParameterBlock* parameter_block = residual_block->parameter_blocks()[j]; - if (!parameter_block->IsConstant()) { - parameter_indices.push_back(parameter_block->index()); - num_derivatives += parameter_block->LocalSize(); - } - } - - // Sort the parameters by their position in the state vector. - sort(parameter_indices.begin(), parameter_indices.end()); - CHECK(unique(parameter_indices.begin(), parameter_indices.end()) == - parameter_indices.end()) - << "Ceres internal error: " - << "Duplicate parameter blocks detected in a cost function. " - << "This should never happen. Please report this to " - << "the Ceres developers."; - - // Update the row indices. - const int num_residuals = residual_block->NumResiduals(); - for (int j = 0; j < num_residuals; ++j) { - rows[row_pos + j + 1] = rows[row_pos + j] + num_derivatives; - } - - // Iterate over parameter blocks in the order which they occur in the - // parameter vector. This code mirrors that in Write(), where jacobian - // values are updated. - int col_pos = 0; - for (int j = 0; j < parameter_indices.size(); ++j) { - ParameterBlock* parameter_block = - program_->parameter_blocks()[parameter_indices[j]]; - const int parameter_block_size = parameter_block->LocalSize(); - - for (int r = 0; r < num_residuals; ++r) { - // This is the position in the values array of the jacobian where this - // row of the jacobian block should go. - const int column_block_begin = rows[row_pos + r] + col_pos; - - for (int c = 0; c < parameter_block_size; ++c) { - cols[column_block_begin + c] = parameter_block->delta_offset() + c; - } - } - col_pos += parameter_block_size; - } - row_pos += num_residuals; - } - CHECK_EQ(num_jacobian_nonzeros, rows[total_num_residuals]); - - PopulateJacobianRowAndColumnBlockVectors(program_, jacobian); - - return jacobian; -} - -void CompressedRowJacobianWriter::Write(int residual_id, - int residual_offset, - double **jacobians, - SparseMatrix* base_jacobian) { - CompressedRowSparseMatrix* jacobian = - down_cast<CompressedRowSparseMatrix*>(base_jacobian); - - double* jacobian_values = jacobian->mutable_values(); - const int* jacobian_rows = jacobian->rows(); - - const ResidualBlock* residual_block = - program_->residual_blocks()[residual_id]; - const int num_residuals = residual_block->NumResiduals(); - - vector<pair<int, int> > evaluated_jacobian_blocks; - GetOrderedParameterBlocks(program_, residual_id, &evaluated_jacobian_blocks); - - // Where in the current row does the jacobian for a parameter block begin. - int col_pos = 0; - - // Iterate over the jacobian blocks in increasing order of their - // positions in the reduced parameter vector. - for (int i = 0; i < evaluated_jacobian_blocks.size(); ++i) { - const ParameterBlock* parameter_block = - program_->parameter_blocks()[evaluated_jacobian_blocks[i].first]; - const int argument = evaluated_jacobian_blocks[i].second; - const int parameter_block_size = parameter_block->LocalSize(); - - // Copy one row of the jacobian block at a time. - for (int r = 0; r < num_residuals; ++r) { - // Position of the r^th row of the current jacobian block. - const double* block_row_begin = - jacobians[argument] + r * parameter_block_size; - - // Position in the values array of the jacobian where this - // row of the jacobian block should go. - double* column_block_begin = - jacobian_values + jacobian_rows[residual_offset + r] + col_pos; - - std::copy(block_row_begin, - block_row_begin + parameter_block_size, - column_block_begin); - } - col_pos += parameter_block_size; - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_jacobian_writer.h b/extern/libmv/third_party/ceres/internal/ceres/compressed_row_jacobian_writer.h deleted file mode 100644 index 1cd01235ccf..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_jacobian_writer.h +++ /dev/null @@ -1,112 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// A jacobian writer that directly writes to compressed row sparse matrices. - -#ifndef CERES_INTERNAL_COMPRESSED_ROW_JACOBIAN_WRITER_H_ -#define CERES_INTERNAL_COMPRESSED_ROW_JACOBIAN_WRITER_H_ - -#include <utility> -#include <vector> - -#include "ceres/evaluator.h" -#include "ceres/scratch_evaluate_preparer.h" - -namespace ceres { -namespace internal { - -class CompressedRowSparseMatrix; -class Program; -class SparseMatrix; - -class CompressedRowJacobianWriter { - public: - CompressedRowJacobianWriter(Evaluator::Options /* ignored */, - Program* program) - : program_(program) { - } - - // PopulateJacobianRowAndColumnBlockVectors sets col_blocks and - // row_blocks for a CompressedRowSparseMatrix, based on the - // parameter block sizes and residual sizes respectively from the - // program. This is useful when Solver::Options::use_block_amd = - // true; - // - // This function is static so that it is available to other jacobian - // writers which use CompressedRowSparseMatrix (or derived types). - // (Jacobian writers do not fall under any type hierarchy; they only - // have to provide an interface as specified in program_evaluator.h). - static void PopulateJacobianRowAndColumnBlockVectors( - const Program* program, - CompressedRowSparseMatrix* jacobian); - - // It is necessary to determine the order of the jacobian blocks - // before copying them into a CompressedRowSparseMatrix (or derived - // type). Just because a cost function uses parameter blocks 1 - // after 2 in its arguments does not mean that the block 1 occurs - // before block 2 in the column layout of the jacobian. Thus, - // GetOrderedParameterBlocks determines the order by sorting the - // jacobian blocks by their position in the state vector. - // - // This function is static so that it is available to other jacobian - // writers which use CompressedRowSparseMatrix (or derived types). - // (Jacobian writers do not fall under any type hierarchy; they only - // have to provide an interface as specified in - // program_evaluator.h). - static void GetOrderedParameterBlocks( - const Program* program, - int residual_id, - std::vector<std::pair<int, int> >* evaluated_jacobian_blocks); - - // JacobianWriter interface. - - // Since the compressed row matrix has different layout than that - // assumed by the cost functions, use scratch space to store the - // jacobians temporarily then copy them over to the larger jacobian - // in the Write() function. - ScratchEvaluatePreparer* CreateEvaluatePreparers(int num_threads) { - return ScratchEvaluatePreparer::Create(*program_, num_threads); - } - - SparseMatrix* CreateJacobian() const; - - void Write(int residual_id, - int residual_offset, - double **jacobians, - SparseMatrix* base_jacobian); - - private: - Program* program_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_COMPRESSED_ROW_JACOBIAN_WRITER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.cc deleted file mode 100644 index 91d18bbd604..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.cc +++ /dev/null @@ -1,562 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/compressed_row_sparse_matrix.h" - -#include <algorithm> -#include <numeric> -#include <vector> -#include "ceres/crs_matrix.h" -#include "ceres/internal/port.h" -#include "ceres/triplet_sparse_matrix.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::vector; - -namespace { - -// Helper functor used by the constructor for reordering the contents -// of a TripletSparseMatrix. This comparator assumes thay there are no -// duplicates in the pair of arrays rows and cols, i.e., there is no -// indices i and j (not equal to each other) s.t. -// -// rows[i] == rows[j] && cols[i] == cols[j] -// -// If this is the case, this functor will not be a StrictWeakOrdering. -struct RowColLessThan { - RowColLessThan(const int* rows, const int* cols) - : rows(rows), cols(cols) { - } - - bool operator()(const int x, const int y) const { - if (rows[x] == rows[y]) { - return (cols[x] < cols[y]); - } - return (rows[x] < rows[y]); - } - - const int* rows; - const int* cols; -}; - -} // namespace - -// This constructor gives you a semi-initialized CompressedRowSparseMatrix. -CompressedRowSparseMatrix::CompressedRowSparseMatrix(int num_rows, - int num_cols, - int max_num_nonzeros) { - num_rows_ = num_rows; - num_cols_ = num_cols; - rows_.resize(num_rows + 1, 0); - cols_.resize(max_num_nonzeros, 0); - values_.resize(max_num_nonzeros, 0.0); - - - VLOG(1) << "# of rows: " << num_rows_ - << " # of columns: " << num_cols_ - << " max_num_nonzeros: " << cols_.size() - << ". Allocating " << (num_rows_ + 1) * sizeof(int) + // NOLINT - cols_.size() * sizeof(int) + // NOLINT - cols_.size() * sizeof(double); // NOLINT -} - -CompressedRowSparseMatrix::CompressedRowSparseMatrix( - const TripletSparseMatrix& m) { - num_rows_ = m.num_rows(); - num_cols_ = m.num_cols(); - - rows_.resize(num_rows_ + 1, 0); - cols_.resize(m.num_nonzeros(), 0); - values_.resize(m.max_num_nonzeros(), 0.0); - - // index is the list of indices into the TripletSparseMatrix m. - vector<int> index(m.num_nonzeros(), 0); - for (int i = 0; i < m.num_nonzeros(); ++i) { - index[i] = i; - } - - // Sort index such that the entries of m are ordered by row and ties - // are broken by column. - sort(index.begin(), index.end(), RowColLessThan(m.rows(), m.cols())); - - VLOG(1) << "# of rows: " << num_rows_ - << " # of columns: " << num_cols_ - << " max_num_nonzeros: " << cols_.size() - << ". Allocating " - << ((num_rows_ + 1) * sizeof(int) + // NOLINT - cols_.size() * sizeof(int) + // NOLINT - cols_.size() * sizeof(double)); // NOLINT - - // Copy the contents of the cols and values array in the order given - // by index and count the number of entries in each row. - for (int i = 0; i < m.num_nonzeros(); ++i) { - const int idx = index[i]; - ++rows_[m.rows()[idx] + 1]; - cols_[i] = m.cols()[idx]; - values_[i] = m.values()[idx]; - } - - // Find the cumulative sum of the row counts. - for (int i = 1; i < num_rows_ + 1; ++i) { - rows_[i] += rows_[i - 1]; - } - - CHECK_EQ(num_nonzeros(), m.num_nonzeros()); -} - -CompressedRowSparseMatrix::CompressedRowSparseMatrix(const double* diagonal, - int num_rows) { - CHECK_NOTNULL(diagonal); - - num_rows_ = num_rows; - num_cols_ = num_rows; - rows_.resize(num_rows + 1); - cols_.resize(num_rows); - values_.resize(num_rows); - - rows_[0] = 0; - for (int i = 0; i < num_rows_; ++i) { - cols_[i] = i; - values_[i] = diagonal[i]; - rows_[i + 1] = i + 1; - } - - CHECK_EQ(num_nonzeros(), num_rows); -} - -CompressedRowSparseMatrix::~CompressedRowSparseMatrix() { -} - -void CompressedRowSparseMatrix::SetZero() { - std::fill(values_.begin(), values_.end(), 0); -} - -void CompressedRowSparseMatrix::RightMultiply(const double* x, - double* y) const { - CHECK_NOTNULL(x); - CHECK_NOTNULL(y); - - for (int r = 0; r < num_rows_; ++r) { - for (int idx = rows_[r]; idx < rows_[r + 1]; ++idx) { - y[r] += values_[idx] * x[cols_[idx]]; - } - } -} - -void CompressedRowSparseMatrix::LeftMultiply(const double* x, double* y) const { - CHECK_NOTNULL(x); - CHECK_NOTNULL(y); - - for (int r = 0; r < num_rows_; ++r) { - for (int idx = rows_[r]; idx < rows_[r + 1]; ++idx) { - y[cols_[idx]] += values_[idx] * x[r]; - } - } -} - -void CompressedRowSparseMatrix::SquaredColumnNorm(double* x) const { - CHECK_NOTNULL(x); - - std::fill(x, x + num_cols_, 0.0); - for (int idx = 0; idx < rows_[num_rows_]; ++idx) { - x[cols_[idx]] += values_[idx] * values_[idx]; - } -} - -void CompressedRowSparseMatrix::ScaleColumns(const double* scale) { - CHECK_NOTNULL(scale); - - for (int idx = 0; idx < rows_[num_rows_]; ++idx) { - values_[idx] *= scale[cols_[idx]]; - } -} - -void CompressedRowSparseMatrix::ToDenseMatrix(Matrix* dense_matrix) const { - CHECK_NOTNULL(dense_matrix); - dense_matrix->resize(num_rows_, num_cols_); - dense_matrix->setZero(); - - for (int r = 0; r < num_rows_; ++r) { - for (int idx = rows_[r]; idx < rows_[r + 1]; ++idx) { - (*dense_matrix)(r, cols_[idx]) = values_[idx]; - } - } -} - -void CompressedRowSparseMatrix::DeleteRows(int delta_rows) { - CHECK_GE(delta_rows, 0); - CHECK_LE(delta_rows, num_rows_); - - num_rows_ -= delta_rows; - rows_.resize(num_rows_ + 1); - - // Walk the list of row blocks until we reach the new number of rows - // and the drop the rest of the row blocks. - int num_row_blocks = 0; - int num_rows = 0; - while (num_row_blocks < row_blocks_.size() && num_rows < num_rows_) { - num_rows += row_blocks_[num_row_blocks]; - ++num_row_blocks; - } - - row_blocks_.resize(num_row_blocks); -} - -void CompressedRowSparseMatrix::AppendRows(const CompressedRowSparseMatrix& m) { - CHECK_EQ(m.num_cols(), num_cols_); - - CHECK(row_blocks_.size() == 0 || m.row_blocks().size() !=0) - << "Cannot append a matrix with row blocks to one without and vice versa." - << "This matrix has : " << row_blocks_.size() << " row blocks." - << "The matrix being appended has: " << m.row_blocks().size() - << " row blocks."; - - if (m.num_rows() == 0) { - return; - } - - if (cols_.size() < num_nonzeros() + m.num_nonzeros()) { - cols_.resize(num_nonzeros() + m.num_nonzeros()); - values_.resize(num_nonzeros() + m.num_nonzeros()); - } - - // Copy the contents of m into this matrix. - DCHECK_LT(num_nonzeros(), cols_.size()); - if (m.num_nonzeros() > 0) { - std::copy(m.cols(), m.cols() + m.num_nonzeros(), &cols_[num_nonzeros()]); - std::copy(m.values(), - m.values() + m.num_nonzeros(), - &values_[num_nonzeros()]); - } - - rows_.resize(num_rows_ + m.num_rows() + 1); - // new_rows = [rows_, m.row() + rows_[num_rows_]] - std::fill(rows_.begin() + num_rows_, - rows_.begin() + num_rows_ + m.num_rows() + 1, - rows_[num_rows_]); - - for (int r = 0; r < m.num_rows() + 1; ++r) { - rows_[num_rows_ + r] += m.rows()[r]; - } - - num_rows_ += m.num_rows(); - row_blocks_.insert(row_blocks_.end(), - m.row_blocks().begin(), - m.row_blocks().end()); -} - -void CompressedRowSparseMatrix::ToTextFile(FILE* file) const { - CHECK_NOTNULL(file); - for (int r = 0; r < num_rows_; ++r) { - for (int idx = rows_[r]; idx < rows_[r + 1]; ++idx) { - fprintf(file, - "% 10d % 10d %17f\n", - r, - cols_[idx], - values_[idx]); - } - } -} - -void CompressedRowSparseMatrix::ToCRSMatrix(CRSMatrix* matrix) const { - matrix->num_rows = num_rows_; - matrix->num_cols = num_cols_; - matrix->rows = rows_; - matrix->cols = cols_; - matrix->values = values_; - - // Trim. - matrix->rows.resize(matrix->num_rows + 1); - matrix->cols.resize(matrix->rows[matrix->num_rows]); - matrix->values.resize(matrix->rows[matrix->num_rows]); -} - -void CompressedRowSparseMatrix::SetMaxNumNonZeros(int num_nonzeros) { - CHECK_GE(num_nonzeros, 0); - - cols_.resize(num_nonzeros); - values_.resize(num_nonzeros); -} - -void CompressedRowSparseMatrix::SolveLowerTriangularInPlace( - double* solution) const { - for (int r = 0; r < num_rows_; ++r) { - for (int idx = rows_[r]; idx < rows_[r + 1] - 1; ++idx) { - solution[r] -= values_[idx] * solution[cols_[idx]]; - } - solution[r] /= values_[rows_[r + 1] - 1]; - } -} - -void CompressedRowSparseMatrix::SolveLowerTriangularTransposeInPlace( - double* solution) const { - for (int r = num_rows_ - 1; r >= 0; --r) { - solution[r] /= values_[rows_[r + 1] - 1]; - for (int idx = rows_[r + 1] - 2; idx >= rows_[r]; --idx) { - solution[cols_[idx]] -= values_[idx] * solution[r]; - } - } -} - -CompressedRowSparseMatrix* CompressedRowSparseMatrix::CreateBlockDiagonalMatrix( - const double* diagonal, - const vector<int>& blocks) { - int num_rows = 0; - int num_nonzeros = 0; - for (int i = 0; i < blocks.size(); ++i) { - num_rows += blocks[i]; - num_nonzeros += blocks[i] * blocks[i]; - } - - CompressedRowSparseMatrix* matrix = - new CompressedRowSparseMatrix(num_rows, num_rows, num_nonzeros); - - int* rows = matrix->mutable_rows(); - int* cols = matrix->mutable_cols(); - double* values = matrix->mutable_values(); - std::fill(values, values + num_nonzeros, 0.0); - - int idx_cursor = 0; - int col_cursor = 0; - for (int i = 0; i < blocks.size(); ++i) { - const int block_size = blocks[i]; - for (int r = 0; r < block_size; ++r) { - *(rows++) = idx_cursor; - values[idx_cursor + r] = diagonal[col_cursor + r]; - for (int c = 0; c < block_size; ++c, ++idx_cursor) { - *(cols++) = col_cursor + c; - } - } - col_cursor += block_size; - } - *rows = idx_cursor; - - *matrix->mutable_row_blocks() = blocks; - *matrix->mutable_col_blocks() = blocks; - - CHECK_EQ(idx_cursor, num_nonzeros); - CHECK_EQ(col_cursor, num_rows); - return matrix; -} - -CompressedRowSparseMatrix* CompressedRowSparseMatrix::Transpose() const { - CompressedRowSparseMatrix* transpose = - new CompressedRowSparseMatrix(num_cols_, num_rows_, num_nonzeros()); - - int* transpose_rows = transpose->mutable_rows(); - int* transpose_cols = transpose->mutable_cols(); - double* transpose_values = transpose->mutable_values(); - - for (int idx = 0; idx < num_nonzeros(); ++idx) { - ++transpose_rows[cols_[idx] + 1]; - } - - for (int i = 1; i < transpose->num_rows() + 1; ++i) { - transpose_rows[i] += transpose_rows[i - 1]; - } - - for (int r = 0; r < num_rows(); ++r) { - for (int idx = rows_[r]; idx < rows_[r + 1]; ++idx) { - const int c = cols_[idx]; - const int transpose_idx = transpose_rows[c]++; - transpose_cols[transpose_idx] = r; - transpose_values[transpose_idx] = values_[idx]; - } - } - - for (int i = transpose->num_rows() - 1; i > 0 ; --i) { - transpose_rows[i] = transpose_rows[i - 1]; - } - transpose_rows[0] = 0; - - *(transpose->mutable_row_blocks()) = col_blocks_; - *(transpose->mutable_col_blocks()) = row_blocks_; - - return transpose; -} - -namespace { -// A ProductTerm is a term in the outer product of a matrix with -// itself. -struct ProductTerm { - ProductTerm(const int row, const int col, const int index) - : row(row), col(col), index(index) { - } - - bool operator<(const ProductTerm& right) const { - if (row == right.row) { - if (col == right.col) { - return index < right.index; - } - return col < right.col; - } - return row < right.row; - } - - int row; - int col; - int index; -}; - -CompressedRowSparseMatrix* -CompressAndFillProgram(const int num_rows, - const int num_cols, - const vector<ProductTerm>& product, - vector<int>* program) { - CHECK_GT(product.size(), 0); - - // Count the number of unique product term, which in turn is the - // number of non-zeros in the outer product. - int num_nonzeros = 1; - for (int i = 1; i < product.size(); ++i) { - if (product[i].row != product[i - 1].row || - product[i].col != product[i - 1].col) { - ++num_nonzeros; - } - } - - CompressedRowSparseMatrix* matrix = - new CompressedRowSparseMatrix(num_rows, num_cols, num_nonzeros); - - int* crsm_rows = matrix->mutable_rows(); - std::fill(crsm_rows, crsm_rows + num_rows + 1, 0); - int* crsm_cols = matrix->mutable_cols(); - std::fill(crsm_cols, crsm_cols + num_nonzeros, 0); - - CHECK_NOTNULL(program)->clear(); - program->resize(product.size()); - - // Iterate over the sorted product terms. This means each row is - // filled one at a time, and we are able to assign a position in the - // values array to each term. - // - // If terms repeat, i.e., they contribute to the same entry in the - // result matrix), then they do not affect the sparsity structure of - // the result matrix. - int nnz = 0; - crsm_cols[0] = product[0].col; - crsm_rows[product[0].row + 1]++; - (*program)[product[0].index] = nnz; - for (int i = 1; i < product.size(); ++i) { - const ProductTerm& previous = product[i - 1]; - const ProductTerm& current = product[i]; - - // Sparsity structure is updated only if the term is not a repeat. - if (previous.row != current.row || previous.col != current.col) { - crsm_cols[++nnz] = current.col; - crsm_rows[current.row + 1]++; - } - - // All terms get assigned the position in the values array where - // their value is accumulated. - (*program)[current.index] = nnz; - } - - for (int i = 1; i < num_rows + 1; ++i) { - crsm_rows[i] += crsm_rows[i - 1]; - } - - return matrix; -} - -} // namespace - -CompressedRowSparseMatrix* -CompressedRowSparseMatrix::CreateOuterProductMatrixAndProgram( - const CompressedRowSparseMatrix& m, - vector<int>* program) { - CHECK_NOTNULL(program)->clear(); - CHECK_GT(m.num_nonzeros(), 0) - << "Congratulations, " - << "you found a bug in Ceres. Please report it."; - - vector<ProductTerm> product; - const vector<int>& row_blocks = m.row_blocks(); - int row_block_begin = 0; - // Iterate over row blocks - for (int row_block = 0; row_block < row_blocks.size(); ++row_block) { - const int row_block_end = row_block_begin + row_blocks[row_block]; - // Compute the outer product terms for just one row per row block. - const int r = row_block_begin; - // Compute the lower triangular part of the product. - for (int idx1 = m.rows()[r]; idx1 < m.rows()[r + 1]; ++idx1) { - for (int idx2 = m.rows()[r]; idx2 <= idx1; ++idx2) { - product.push_back(ProductTerm(m.cols()[idx1], - m.cols()[idx2], - product.size())); - } - } - row_block_begin = row_block_end; - } - CHECK_EQ(row_block_begin, m.num_rows()); - sort(product.begin(), product.end()); - return CompressAndFillProgram(m.num_cols(), m.num_cols(), product, program); -} - -void CompressedRowSparseMatrix::ComputeOuterProduct( - const CompressedRowSparseMatrix& m, - const vector<int>& program, - CompressedRowSparseMatrix* result) { - result->SetZero(); - double* values = result->mutable_values(); - const vector<int>& row_blocks = m.row_blocks(); - - int cursor = 0; - int row_block_begin = 0; - const double* m_values = m.values(); - const int* m_rows = m.rows(); - // Iterate over row blocks. - for (int row_block = 0; row_block < row_blocks.size(); ++row_block) { - const int row_block_end = row_block_begin + row_blocks[row_block]; - const int saved_cursor = cursor; - for (int r = row_block_begin; r < row_block_end; ++r) { - // Reuse the program segment for each row in this row block. - cursor = saved_cursor; - const int row_begin = m_rows[r]; - const int row_end = m_rows[r + 1]; - for (int idx1 = row_begin; idx1 < row_end; ++idx1) { - const double v1 = m_values[idx1]; - for (int idx2 = row_begin; idx2 <= idx1; ++idx2, ++cursor) { - values[program[cursor]] += v1 * m_values[idx2]; - } - } - } - row_block_begin = row_block_end; - } - - CHECK_EQ(row_block_begin, m.num_rows()); - CHECK_EQ(cursor, program.size()); -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.h deleted file mode 100644 index 987339d09a1..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.h +++ /dev/null @@ -1,181 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_ -#define CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_ - -#include <vector> -#include "ceres/internal/macros.h" -#include "ceres/internal/port.h" -#include "ceres/sparse_matrix.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { - -struct CRSMatrix; - -namespace internal { - -class TripletSparseMatrix; - -class CompressedRowSparseMatrix : public SparseMatrix { - public: - // Build a matrix with the same content as the TripletSparseMatrix - // m. TripletSparseMatrix objects are easier to construct - // incrementally, so we use them to initialize SparseMatrix - // objects. - // - // We assume that m does not have any repeated entries. - explicit CompressedRowSparseMatrix(const TripletSparseMatrix& m); - - // Use this constructor only if you know what you are doing. This - // creates a "blank" matrix with the appropriate amount of memory - // allocated. However, the object itself is in an inconsistent state - // as the rows and cols matrices do not match the values of - // num_rows, num_cols and max_num_nonzeros. - // - // The use case for this constructor is that when the user knows the - // size of the matrix to begin with and wants to update the layout - // manually, instead of going via the indirect route of first - // constructing a TripletSparseMatrix, which leads to more than - // double the peak memory usage. - CompressedRowSparseMatrix(int num_rows, - int num_cols, - int max_num_nonzeros); - - // Build a square sparse diagonal matrix with num_rows rows and - // columns. The diagonal m(i,i) = diagonal(i); - CompressedRowSparseMatrix(const double* diagonal, int num_rows); - - virtual ~CompressedRowSparseMatrix(); - - // SparseMatrix interface. - virtual void SetZero(); - virtual void RightMultiply(const double* x, double* y) const; - virtual void LeftMultiply(const double* x, double* y) const; - virtual void SquaredColumnNorm(double* x) const; - virtual void ScaleColumns(const double* scale); - - virtual void ToDenseMatrix(Matrix* dense_matrix) const; - virtual void ToTextFile(FILE* file) const; - virtual int num_rows() const { return num_rows_; } - virtual int num_cols() const { return num_cols_; } - virtual int num_nonzeros() const { return rows_[num_rows_]; } - virtual const double* values() const { return &values_[0]; } - virtual double* mutable_values() { return &values_[0]; } - - // Delete the bottom delta_rows. - // num_rows -= delta_rows - void DeleteRows(int delta_rows); - - // Append the contents of m to the bottom of this matrix. m must - // have the same number of columns as this matrix. - void AppendRows(const CompressedRowSparseMatrix& m); - - void ToCRSMatrix(CRSMatrix* matrix) const; - - // Low level access methods that expose the structure of the matrix. - const int* cols() const { return &cols_[0]; } - int* mutable_cols() { return &cols_[0]; } - - const int* rows() const { return &rows_[0]; } - int* mutable_rows() { return &rows_[0]; } - - const std::vector<int>& row_blocks() const { return row_blocks_; } - std::vector<int>* mutable_row_blocks() { return &row_blocks_; } - - const std::vector<int>& col_blocks() const { return col_blocks_; } - std::vector<int>* mutable_col_blocks() { return &col_blocks_; } - - // Destructive array resizing method. - void SetMaxNumNonZeros(int num_nonzeros); - - // Non-destructive array resizing method. - void set_num_rows(const int num_rows) { num_rows_ = num_rows; } - void set_num_cols(const int num_cols) { num_cols_ = num_cols; } - - void SolveLowerTriangularInPlace(double* solution) const; - void SolveLowerTriangularTransposeInPlace(double* solution) const; - - CompressedRowSparseMatrix* Transpose() const; - - static CompressedRowSparseMatrix* CreateBlockDiagonalMatrix( - const double* diagonal, - const std::vector<int>& blocks); - - // Compute the sparsity structure of the product m.transpose() * m - // and create a CompressedRowSparseMatrix corresponding to it. - // - // Also compute a "program" vector, which for every term in the - // outer product points to the entry in the values array of the - // result matrix where it should be accumulated. - // - // This program is used by the ComputeOuterProduct function below to - // compute the outer product. - // - // Since the entries of the program are the same for rows with the - // same sparsity structure, the program only stores the result for - // one row per row block. The ComputeOuterProduct function reuses - // this information for each row in the row block. - static CompressedRowSparseMatrix* CreateOuterProductMatrixAndProgram( - const CompressedRowSparseMatrix& m, - std::vector<int>* program); - - // Compute the values array for the expression m.transpose() * m, - // where the matrix used to store the result and a program have been - // created using the CreateOuterProductMatrixAndProgram function - // above. - static void ComputeOuterProduct(const CompressedRowSparseMatrix& m, - const std::vector<int>& program, - CompressedRowSparseMatrix* result); - - private: - int num_rows_; - int num_cols_; - std::vector<int> rows_; - std::vector<int> cols_; - std::vector<double> values_; - - // If the matrix has an underlying block structure, then it can also - // carry with it row and column block sizes. This is auxilliary and - // optional information for use by algorithms operating on the - // matrix. The class itself does not make use of this information in - // any way. - std::vector<int> row_blocks_; - std::vector<int> col_blocks_; - - CERES_DISALLOW_COPY_AND_ASSIGN(CompressedRowSparseMatrix); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/conditioned_cost_function.cc b/extern/libmv/third_party/ceres/internal/ceres/conditioned_cost_function.cc deleted file mode 100644 index 08899e3d246..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/conditioned_cost_function.cc +++ /dev/null @@ -1,130 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: wjr@google.com (William Rucklidge) -// -// This file contains the implementation of the conditioned cost function. - -#include "ceres/conditioned_cost_function.h" - -#include <cstddef> - -#include "ceres/internal/eigen.h" -#include "ceres/stl_util.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { - -// This cost function has the same dimensions (parameters, residuals) as -// the one it's wrapping. -ConditionedCostFunction::ConditionedCostFunction( - CostFunction* wrapped_cost_function, - const std::vector<CostFunction*>& conditioners, - Ownership ownership) - : wrapped_cost_function_(wrapped_cost_function), - conditioners_(conditioners), - ownership_(ownership) { - // Set up our dimensions. - set_num_residuals(wrapped_cost_function_->num_residuals()); - *mutable_parameter_block_sizes() = - wrapped_cost_function_->parameter_block_sizes(); - - // Sanity-check the conditioners' dimensions. - CHECK_EQ(wrapped_cost_function_->num_residuals(), conditioners_.size()); - for (int i = 0; i < wrapped_cost_function_->num_residuals(); i++) { - if (conditioners[i]) { - CHECK_EQ(1, conditioners[i]->num_residuals()); - CHECK_EQ(1, conditioners[i]->parameter_block_sizes().size()); - CHECK_EQ(1, conditioners[i]->parameter_block_sizes()[0]); - } - } -} - -ConditionedCostFunction::~ConditionedCostFunction() { - if (ownership_ == TAKE_OWNERSHIP) { - STLDeleteElements(&conditioners_); - } else { - wrapped_cost_function_.release(); - } -} - -bool ConditionedCostFunction::Evaluate(double const* const* parameters, - double* residuals, - double** jacobians) const { - bool success = wrapped_cost_function_->Evaluate(parameters, residuals, - jacobians); - if (!success) { - return false; - } - - for (int r = 0; r < wrapped_cost_function_->num_residuals(); r++) { - // On output, we want to have - // residuals[r] = conditioners[r](wrapped_residuals[r]) - // For parameter block i, column c, - // jacobians[i][r*parameter_block_size_[i] + c] = - // = d residual[r] / d parameters[i][c] - // = conditioners[r]'(wrapped_residuals[r]) * - // d wrapped_residuals[r] / d parameters[i][c] - if (conditioners_[r]) { - double conditioner_derivative; - double* conditioner_derivative_pointer = &conditioner_derivative; - double** conditioner_derivative_pointer2 = - &conditioner_derivative_pointer; - if (!jacobians) { - conditioner_derivative_pointer2 = NULL; - } - - double unconditioned_residual = residuals[r]; - double* parameter_pointer = &unconditioned_residual; - success = conditioners_[r]->Evaluate(¶meter_pointer, - &residuals[r], - conditioner_derivative_pointer2); - if (!success) { - return false; - } - - if (jacobians) { - for (int i = 0; - i < wrapped_cost_function_->parameter_block_sizes().size(); - i++) { - if (jacobians[i]) { - int parameter_block_size = - wrapped_cost_function_->parameter_block_sizes()[i]; - VectorRef jacobian_row(jacobians[i] + r * parameter_block_size, - parameter_block_size, 1); - jacobian_row *= conditioner_derivative; - } - } - } - } - } - return true; -} - -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.cc deleted file mode 100644 index 3702276a2fb..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.cc +++ /dev/null @@ -1,248 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// A preconditioned conjugate gradients solver -// (ConjugateGradientsSolver) for positive semidefinite linear -// systems. -// -// We have also augmented the termination criterion used by this -// solver to support not just residual based termination but also -// termination based on decrease in the value of the quadratic model -// that CG optimizes. - -#include "ceres/conjugate_gradients_solver.h" - -#include <cmath> -#include <cstddef> -#include "ceres/fpclassify.h" -#include "ceres/internal/eigen.h" -#include "ceres/linear_operator.h" -#include "ceres/stringprintf.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { -namespace { - -bool IsZeroOrInfinity(double x) { - return ((x == 0.0) || (IsInfinite(x))); -} - -} // namespace - -ConjugateGradientsSolver::ConjugateGradientsSolver( - const LinearSolver::Options& options) - : options_(options) { -} - -LinearSolver::Summary ConjugateGradientsSolver::Solve( - LinearOperator* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x) { - CHECK_NOTNULL(A); - CHECK_NOTNULL(x); - CHECK_NOTNULL(b); - CHECK_EQ(A->num_rows(), A->num_cols()); - - LinearSolver::Summary summary; - summary.termination_type = LINEAR_SOLVER_NO_CONVERGENCE; - summary.message = "Maximum number of iterations reached."; - summary.num_iterations = 0; - - const int num_cols = A->num_cols(); - VectorRef xref(x, num_cols); - ConstVectorRef bref(b, num_cols); - - const double norm_b = bref.norm(); - if (norm_b == 0.0) { - xref.setZero(); - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = "Convergence. |b| = 0."; - return summary; - } - - Vector r(num_cols); - Vector p(num_cols); - Vector z(num_cols); - Vector tmp(num_cols); - - const double tol_r = per_solve_options.r_tolerance * norm_b; - - tmp.setZero(); - A->RightMultiply(x, tmp.data()); - r = bref - tmp; - double norm_r = r.norm(); - if (options_.min_num_iterations == 0 && norm_r <= tol_r) { - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = - StringPrintf("Convergence. |r| = %e <= %e.", norm_r, tol_r); - return summary; - } - - double rho = 1.0; - - // Initial value of the quadratic model Q = x'Ax - 2 * b'x. - double Q0 = -1.0 * xref.dot(bref + r); - - for (summary.num_iterations = 1;; ++summary.num_iterations) { - // Apply preconditioner - if (per_solve_options.preconditioner != NULL) { - z.setZero(); - per_solve_options.preconditioner->RightMultiply(r.data(), z.data()); - } else { - z = r; - } - - double last_rho = rho; - rho = r.dot(z); - if (IsZeroOrInfinity(rho)) { - summary.termination_type = LINEAR_SOLVER_FAILURE; - summary.message = StringPrintf("Numerical failure. rho = r'z = %e.", rho); - break; - } - - if (summary.num_iterations == 1) { - p = z; - } else { - double beta = rho / last_rho; - if (IsZeroOrInfinity(beta)) { - summary.termination_type = LINEAR_SOLVER_FAILURE; - summary.message = StringPrintf( - "Numerical failure. beta = rho_n / rho_{n-1} = %e, " - "rho_n = %e, rho_{n-1} = %e", beta, rho, last_rho); - break; - } - p = z + beta * p; - } - - Vector& q = z; - q.setZero(); - A->RightMultiply(p.data(), q.data()); - const double pq = p.dot(q); - if ((pq <= 0) || IsInfinite(pq)) { - summary.termination_type = LINEAR_SOLVER_NO_CONVERGENCE; - summary.message = StringPrintf( - "Matrix is indefinite, no more progress can be made. " - "p'q = %e. |p| = %e, |q| = %e", - pq, p.norm(), q.norm()); - break; - } - - const double alpha = rho / pq; - if (IsInfinite(alpha)) { - summary.termination_type = LINEAR_SOLVER_FAILURE; - summary.message = - StringPrintf("Numerical failure. alpha = rho / pq = %e, " - "rho = %e, pq = %e.", alpha, rho, pq); - break; - } - - xref = xref + alpha * p; - - // Ideally we would just use the update r = r - alpha*q to keep - // track of the residual vector. However this estimate tends to - // drift over time due to round off errors. Thus every - // residual_reset_period iterations, we calculate the residual as - // r = b - Ax. We do not do this every iteration because this - // requires an additional matrix vector multiply which would - // double the complexity of the CG algorithm. - if (summary.num_iterations % options_.residual_reset_period == 0) { - tmp.setZero(); - A->RightMultiply(x, tmp.data()); - r = bref - tmp; - } else { - r = r - alpha * q; - } - - // Quadratic model based termination. - // Q1 = x'Ax - 2 * b' x. - const double Q1 = -1.0 * xref.dot(bref + r); - - // For PSD matrices A, let - // - // Q(x) = x'Ax - 2b'x - // - // be the cost of the quadratic function defined by A and b. Then, - // the solver terminates at iteration i if - // - // i * (Q(x_i) - Q(x_i-1)) / Q(x_i) < q_tolerance. - // - // This termination criterion is more useful when using CG to - // solve the Newton step. This particular convergence test comes - // from Stephen Nash's work on truncated Newton - // methods. References: - // - // 1. Stephen G. Nash & Ariela Sofer, Assessing A Search - // Direction Within A Truncated Newton Method, Operation - // Research Letters 9(1990) 219-221. - // - // 2. Stephen G. Nash, A Survey of Truncated Newton Methods, - // Journal of Computational and Applied Mathematics, - // 124(1-2), 45-59, 2000. - // - const double zeta = summary.num_iterations * (Q1 - Q0) / Q1; - if (zeta < per_solve_options.q_tolerance && - summary.num_iterations >= options_.min_num_iterations) { - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = - StringPrintf("Iteration: %d Convergence: zeta = %e < %e. |r| = %e", - summary.num_iterations, - zeta, - per_solve_options.q_tolerance, - r.norm()); - break; - } - Q0 = Q1; - - // Residual based termination. - norm_r = r. norm(); - if (norm_r <= tol_r && - summary.num_iterations >= options_.min_num_iterations) { - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = - StringPrintf("Iteration: %d Convergence. |r| = %e <= %e.", - summary.num_iterations, - norm_r, - tol_r); - break; - } - - if (summary.num_iterations >= options_.max_num_iterations) { - break; - } - } - - return summary; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.h b/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.h deleted file mode 100644 index a1e18334414..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.h +++ /dev/null @@ -1,74 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Preconditioned Conjugate Gradients based solver for positive -// semidefinite linear systems. - -#ifndef CERES_INTERNAL_CONJUGATE_GRADIENTS_SOLVER_H_ -#define CERES_INTERNAL_CONJUGATE_GRADIENTS_SOLVER_H_ - -#include "ceres/linear_solver.h" -#include "ceres/internal/macros.h" - -namespace ceres { -namespace internal { - -class LinearOperator; - -// This class implements the now classical Conjugate Gradients -// algorithm of Hestenes & Stiefel for solving postive semidefinite -// linear sytems. Optionally it can use a preconditioner also to -// reduce the condition number of the linear system and improve the -// convergence rate. Modern references for Conjugate Gradients are the -// books by Yousef Saad and Trefethen & Bau. This implementation of CG -// has been augmented with additional termination tests that are -// needed for forcing early termination when used as part of an -// inexact Newton solver. -// -// For more details see the documentation for -// LinearSolver::PerSolveOptions::r_tolerance and -// LinearSolver::PerSolveOptions::q_tolerance in linear_solver.h. -class ConjugateGradientsSolver : public LinearSolver { - public: - explicit ConjugateGradientsSolver(const LinearSolver::Options& options); - virtual Summary Solve(LinearOperator* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x); - - private: - const LinearSolver::Options options_; - CERES_DISALLOW_COPY_AND_ASSIGN(ConjugateGradientsSolver); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_CONJUGATE_GRADIENTS_SOLVER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/coordinate_descent_minimizer.cc b/extern/libmv/third_party/ceres/internal/ceres/coordinate_descent_minimizer.cc deleted file mode 100644 index c6b42cf1516..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/coordinate_descent_minimizer.cc +++ /dev/null @@ -1,278 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/coordinate_descent_minimizer.h" - -#ifdef CERES_USE_OPENMP -#include <omp.h> -#endif - -#include <iterator> -#include <numeric> -#include <vector> -#include "ceres/evaluator.h" -#include "ceres/linear_solver.h" -#include "ceres/minimizer.h" -#include "ceres/parameter_block.h" -#include "ceres/parameter_block_ordering.h" -#include "ceres/problem_impl.h" -#include "ceres/program.h" -#include "ceres/residual_block.h" -#include "ceres/solver.h" -#include "ceres/trust_region_minimizer.h" -#include "ceres/trust_region_strategy.h" - -namespace ceres { -namespace internal { - -using std::map; -using std::max; -using std::min; -using std::set; -using std::string; -using std::vector; - -CoordinateDescentMinimizer::~CoordinateDescentMinimizer() { -} - -bool CoordinateDescentMinimizer::Init( - const Program& program, - const ProblemImpl::ParameterMap& parameter_map, - const ParameterBlockOrdering& ordering, - string* error) { - parameter_blocks_.clear(); - independent_set_offsets_.clear(); - independent_set_offsets_.push_back(0); - - // Serialize the OrderedGroups into a vector of parameter block - // offsets for parallel access. - map<ParameterBlock*, int> parameter_block_index; - map<int, set<double*> > group_to_elements = ordering.group_to_elements(); - for (map<int, set<double*> >::const_iterator it = group_to_elements.begin(); - it != group_to_elements.end(); - ++it) { - for (set<double*>::const_iterator ptr_it = it->second.begin(); - ptr_it != it->second.end(); - ++ptr_it) { - parameter_blocks_.push_back(parameter_map.find(*ptr_it)->second); - parameter_block_index[parameter_blocks_.back()] = - parameter_blocks_.size() - 1; - } - independent_set_offsets_.push_back( - independent_set_offsets_.back() + it->second.size()); - } - - // The ordering does not have to contain all parameter blocks, so - // assign zero offsets/empty independent sets to these parameter - // blocks. - const vector<ParameterBlock*>& parameter_blocks = program.parameter_blocks(); - for (int i = 0; i < parameter_blocks.size(); ++i) { - if (!ordering.IsMember(parameter_blocks[i]->mutable_user_state())) { - parameter_blocks_.push_back(parameter_blocks[i]); - independent_set_offsets_.push_back(independent_set_offsets_.back()); - } - } - - // Compute the set of residual blocks that depend on each parameter - // block. - residual_blocks_.resize(parameter_block_index.size()); - const vector<ResidualBlock*>& residual_blocks = program.residual_blocks(); - for (int i = 0; i < residual_blocks.size(); ++i) { - ResidualBlock* residual_block = residual_blocks[i]; - const int num_parameter_blocks = residual_block->NumParameterBlocks(); - for (int j = 0; j < num_parameter_blocks; ++j) { - ParameterBlock* parameter_block = residual_block->parameter_blocks()[j]; - const map<ParameterBlock*, int>::const_iterator it = - parameter_block_index.find(parameter_block); - if (it != parameter_block_index.end()) { - residual_blocks_[it->second].push_back(residual_block); - } - } - } - - evaluator_options_.linear_solver_type = DENSE_QR; - evaluator_options_.num_eliminate_blocks = 0; - evaluator_options_.num_threads = 1; - - return true; -} - -void CoordinateDescentMinimizer::Minimize( - const Minimizer::Options& options, - double* parameters, - Solver::Summary* summary) { - // Set the state and mark all parameter blocks constant. - for (int i = 0; i < parameter_blocks_.size(); ++i) { - ParameterBlock* parameter_block = parameter_blocks_[i]; - parameter_block->SetState(parameters + parameter_block->state_offset()); - parameter_block->SetConstant(); - } - - scoped_array<LinearSolver*> linear_solvers( - new LinearSolver*[options.num_threads]); - - LinearSolver::Options linear_solver_options; - linear_solver_options.type = DENSE_QR; - - for (int i = 0; i < options.num_threads; ++i) { - linear_solvers[i] = LinearSolver::Create(linear_solver_options); - } - - for (int i = 0; i < independent_set_offsets_.size() - 1; ++i) { - const int num_problems = - independent_set_offsets_[i + 1] - independent_set_offsets_[i]; - // No point paying the price for an OpemMP call if the set is of - // size zero. - if (num_problems == 0) { - continue; - } - -#ifdef CERES_USE_OPENMP - const int num_inner_iteration_threads = - min(options.num_threads, num_problems); - evaluator_options_.num_threads = - max(1, options.num_threads / num_inner_iteration_threads); - - // The parameter blocks in each independent set can be optimized - // in parallel, since they do not co-occur in any residual block. -#pragma omp parallel for num_threads(num_inner_iteration_threads) -#endif - for (int j = independent_set_offsets_[i]; - j < independent_set_offsets_[i + 1]; - ++j) { -#ifdef CERES_USE_OPENMP - int thread_id = omp_get_thread_num(); -#else - int thread_id = 0; -#endif - - ParameterBlock* parameter_block = parameter_blocks_[j]; - const int old_index = parameter_block->index(); - const int old_delta_offset = parameter_block->delta_offset(); - parameter_block->SetVarying(); - parameter_block->set_index(0); - parameter_block->set_delta_offset(0); - - Program inner_program; - inner_program.mutable_parameter_blocks()->push_back(parameter_block); - *inner_program.mutable_residual_blocks() = residual_blocks_[j]; - - // TODO(sameeragarwal): Better error handling. Right now we - // assume that this is not going to lead to problems of any - // sort. Basically we should be checking for numerical failure - // of some sort. - // - // On the other hand, if the optimization is a failure, that in - // some ways is fine, since it won't change the parameters and - // we are fine. - Solver::Summary inner_summary; - Solve(&inner_program, - linear_solvers[thread_id], - parameters + parameter_block->state_offset(), - &inner_summary); - - parameter_block->set_index(old_index); - parameter_block->set_delta_offset(old_delta_offset); - parameter_block->SetState(parameters + parameter_block->state_offset()); - parameter_block->SetConstant(); - } - } - - for (int i = 0; i < parameter_blocks_.size(); ++i) { - parameter_blocks_[i]->SetVarying(); - } - - for (int i = 0; i < options.num_threads; ++i) { - delete linear_solvers[i]; - } -} - -// Solve the optimization problem for one parameter block. -void CoordinateDescentMinimizer::Solve(Program* program, - LinearSolver* linear_solver, - double* parameter, - Solver::Summary* summary) { - *summary = Solver::Summary(); - summary->initial_cost = 0.0; - summary->fixed_cost = 0.0; - summary->final_cost = 0.0; - string error; - - Minimizer::Options minimizer_options; - minimizer_options.evaluator.reset( - CHECK_NOTNULL(Evaluator::Create(evaluator_options_, program, &error))); - minimizer_options.jacobian.reset( - CHECK_NOTNULL(minimizer_options.evaluator->CreateJacobian())); - - TrustRegionStrategy::Options trs_options; - trs_options.linear_solver = linear_solver; - minimizer_options.trust_region_strategy.reset( - CHECK_NOTNULL(TrustRegionStrategy::Create(trs_options))); - minimizer_options.is_silent = true; - - TrustRegionMinimizer minimizer; - minimizer.Minimize(minimizer_options, parameter, summary); -} - -bool CoordinateDescentMinimizer::IsOrderingValid( - const Program& program, - const ParameterBlockOrdering& ordering, - string* message) { - const map<int, set<double*> >& group_to_elements = - ordering.group_to_elements(); - - // Verify that each group is an independent set - map<int, set<double*> >::const_iterator it = group_to_elements.begin(); - for (; it != group_to_elements.end(); ++it) { - if (!program.IsParameterBlockSetIndependent(it->second)) { - *message = - StringPrintf("The user-provided " - "parameter_blocks_for_inner_iterations does not " - "form an independent set. Group Id: %d", it->first); - return false; - } - } - return true; -} - -// Find a recursive decomposition of the Hessian matrix as a set -// of independent sets of decreasing size and invert it. This -// seems to work better in practice, i.e., Cameras before -// points. -ParameterBlockOrdering* CoordinateDescentMinimizer::CreateOrdering( - const Program& program) { - scoped_ptr<ParameterBlockOrdering> ordering(new ParameterBlockOrdering); - ComputeRecursiveIndependentSetOrdering(program, ordering.get()); - ordering->Reverse(); - return ordering.release(); -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/coordinate_descent_minimizer.h b/extern/libmv/third_party/ceres/internal/ceres/coordinate_descent_minimizer.h deleted file mode 100644 index 25ea04ce622..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/coordinate_descent_minimizer.h +++ /dev/null @@ -1,102 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_COORDINATE_DESCENT_MINIMIZER_H_ -#define CERES_INTERNAL_COORDINATE_DESCENT_MINIMIZER_H_ - -#include <string> -#include <vector> - -#include "ceres/evaluator.h" -#include "ceres/minimizer.h" -#include "ceres/problem_impl.h" -#include "ceres/solver.h" - -namespace ceres { -namespace internal { - -class Program; -class LinearSolver; - -// Given a Program, and a ParameterBlockOrdering which partitions -// (non-exhaustively) the Hessian matrix into independent sets, -// perform coordinate descent on the parameter blocks in the -// ordering. The independent set structure allows for all parameter -// blocks in the same independent set to be optimized in parallel, and -// the order of the independent set determines the order in which the -// parameter block groups are optimized. -// -// The minimizer assumes that none of the parameter blocks in the -// program are constant. -class CoordinateDescentMinimizer : public Minimizer { - public: - bool Init(const Program& program, - const ProblemImpl::ParameterMap& parameter_map, - const ParameterBlockOrdering& ordering, - std::string* error); - - // Minimizer interface. - virtual ~CoordinateDescentMinimizer(); - virtual void Minimize(const Minimizer::Options& options, - double* parameters, - Solver::Summary* summary); - - // Verify that each group in the ordering forms an independent set. - static bool IsOrderingValid(const Program& program, - const ParameterBlockOrdering& ordering, - std::string* message); - - // Find a recursive decomposition of the Hessian matrix as a set - // of independent sets of decreasing size and invert it. This - // seems to work better in practice, i.e., Cameras before - // points. - static ParameterBlockOrdering* CreateOrdering(const Program& program); - - private: - void Solve(Program* program, - LinearSolver* linear_solver, - double* parameters, - Solver::Summary* summary); - - std::vector<ParameterBlock*> parameter_blocks_; - std::vector<std::vector<ResidualBlock*> > residual_blocks_; - // The optimization is performed in rounds. In each round all the - // parameter blocks that form one independent set are optimized in - // parallel. This array, marks the boundaries of the independent - // sets in parameter_blocks_. - std::vector<int> independent_set_offsets_; - - Evaluator::Options evaluator_options_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_COORDINATE_DESCENT_MINIMIZER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/corrector.cc b/extern/libmv/third_party/ceres/internal/ceres/corrector.cc deleted file mode 100644 index 720182868c1..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/corrector.cc +++ /dev/null @@ -1,158 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/corrector.h" - -#include <cstddef> -#include <cmath> -#include "ceres/internal/eigen.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -Corrector::Corrector(const double sq_norm, const double rho[3]) { - CHECK_GE(sq_norm, 0.0); - sqrt_rho1_ = sqrt(rho[1]); - - // If sq_norm = 0.0, the correction becomes trivial, the residual - // and the jacobian are scaled by the squareroot of the derivative - // of rho. Handling this case explicitly avoids the divide by zero - // error that would occur below. - // - // The case where rho'' < 0 also gets special handling. Technically - // it shouldn't, and the computation of the scaling should proceed - // as below, however we found in experiments that applying the - // curvature correction when rho'' < 0, which is the case when we - // are in the outlier region slows down the convergence of the - // algorithm significantly. - // - // Thus, we have divided the action of the robustifier into two - // parts. In the inliner region, we do the full second order - // correction which re-wights the gradient of the function by the - // square root of the derivative of rho, and the Gauss-Newton - // Hessian gets both the scaling and the rank-1 curvature - // correction. Normaly, alpha is upper bounded by one, but with this - // change, alpha is bounded above by zero. - // - // Empirically we have observed that the full Triggs correction and - // the clamped correction both start out as very good approximations - // to the loss function when we are in the convex part of the - // function, but as the function starts transitioning from convex to - // concave, the Triggs approximation diverges more and more and - // ultimately becomes linear. The clamped Triggs model however - // remains quadratic. - // - // The reason why the Triggs approximation becomes so poor is - // because the curvature correction that it applies to the gauss - // newton hessian goes from being a full rank correction to a rank - // deficient correction making the inversion of the Hessian fraught - // with all sorts of misery and suffering. - // - // The clamped correction retains its quadratic nature and inverting it - // is always well formed. - if ((sq_norm == 0.0) || (rho[2] <= 0.0)) { - residual_scaling_ = sqrt_rho1_; - alpha_sq_norm_ = 0.0; - return; - } - - // We now require that the first derivative of the loss function be - // positive only if the second derivative is positive. This is - // because when the second derivative is non-positive, we do not use - // the second order correction suggested by BANS and instead use a - // simpler first order strategy which does not use a division by the - // gradient of the loss function. - CHECK_GT(rho[1], 0.0); - - // Calculate the smaller of the two solutions to the equation - // - // 0.5 * alpha^2 - alpha - rho'' / rho' * z'z = 0. - // - // Start by calculating the discriminant D. - const double D = 1.0 + 2.0 * sq_norm * rho[2] / rho[1]; - - // Since both rho[1] and rho[2] are guaranteed to be positive at - // this point, we know that D > 1.0. - - const double alpha = 1.0 - sqrt(D); - - // Calculate the constants needed by the correction routines. - residual_scaling_ = sqrt_rho1_ / (1 - alpha); - alpha_sq_norm_ = alpha / sq_norm; -} - -void Corrector::CorrectResiduals(const int num_rows, double* residuals) { - DCHECK(residuals != NULL); - // Equation 11 in BANS. - VectorRef(residuals, num_rows) *= residual_scaling_; -} - -void Corrector::CorrectJacobian(const int num_rows, - const int num_cols, - double* residuals, - double* jacobian) { - DCHECK(residuals != NULL); - DCHECK(jacobian != NULL); - - // The common case (rho[2] <= 0). - if (alpha_sq_norm_ == 0.0) { - VectorRef(jacobian, num_rows * num_cols) *= sqrt_rho1_; - return; - } - - // Equation 11 in BANS. - // - // J = sqrt(rho) * (J - alpha^2 r * r' J) - // - // In days gone by this loop used to be a single Eigen expression of - // the form - // - // J = sqrt_rho1_ * (J - alpha_sq_norm_ * r* (r.transpose() * J)); - // - // Which turns out to about 17x slower on bal problems. The reason - // is that Eigen is unable to figure out that this expression can be - // evaluated columnwise and ends up creating a temporary. - for (int c = 0; c < num_cols; ++c) { - double r_transpose_j = 0.0; - for (int r = 0; r < num_rows; ++r) { - r_transpose_j += jacobian[r * num_cols + c] * residuals[r]; - } - - for (int r = 0; r < num_rows; ++r) { - jacobian[r * num_cols + c] = sqrt_rho1_ * - (jacobian[r * num_cols + c] - - alpha_sq_norm_ * residuals[r] * r_transpose_j); - } - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/corrector.h b/extern/libmv/third_party/ceres/internal/ceres/corrector.h deleted file mode 100644 index 315f012ab1d..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/corrector.h +++ /dev/null @@ -1,90 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Class definition for the object that is responsible for applying a -// second order correction to the Gauss-Newton based on the ideas in -// BANS by Triggs et al. - -#ifndef CERES_INTERNAL_CORRECTOR_H_ -#define CERES_INTERNAL_CORRECTOR_H_ - -namespace ceres { -namespace internal { - -// Corrector is responsible for applying the second order correction -// to the residual and jacobian of a least squares problem based on a -// radial robust loss. -// -// The key idea here is to look at the expressions for the robustified -// gauss newton approximation and then take its squareroot to get the -// corresponding corrections to the residual and jacobian. For the -// full expressions see Eq. 10 and 11 in BANS by Triggs et al. -class Corrector { - public: - // The constructor takes the squared norm, the value, the first and - // second derivatives of the LossFunction. It precalculates some of - // the constants that are needed to apply the correction. The - // correction constant alpha is constrained to be smaller than 1, if - // it becomes larger than 1, then it will reverse the sign of the - // residual and the correction. If alpha is equal to 1 will result - // in a divide by zero error. Thus we constrain alpha to be upper - // bounded by 1 - epsilon_. - // - // rho[1] needs to be positive. The constructor will crash if this - // condition is not met. - // - // In practical use CorrectJacobian should always be called before - // CorrectResidual, because the jacobian correction depends on the - // value of the uncorrected residual values. - explicit Corrector(double sq_norm, const double rho[3]); - - // residuals *= sqrt(rho[1]) / (1 - alpha) - void CorrectResiduals(int num_rows, double* residuals); - - // jacobian = sqrt(rho[1]) * jacobian - - // sqrt(rho[1]) * alpha / sq_norm * residuals residuals' * jacobian. - // - // The method assumes that the jacobian has row-major storage. It is - // the caller's responsibility to ensure that the pointer to - // jacobian is not null. - void CorrectJacobian(int num_rows, - int num_cols, - double* residuals, - double* jacobian); - - private: - double sqrt_rho1_; - double residual_scaling_; - double alpha_sq_norm_; -}; -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_CORRECTOR_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/covariance.cc b/extern/libmv/third_party/ceres/internal/ceres/covariance.cc deleted file mode 100644 index 690847945a9..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/covariance.cc +++ /dev/null @@ -1,76 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/covariance.h" - -#include <utility> -#include <vector> -#include "ceres/covariance_impl.h" -#include "ceres/problem.h" -#include "ceres/problem_impl.h" - -namespace ceres { - -using std::pair; -using std::vector; - -Covariance::Covariance(const Covariance::Options& options) { - impl_.reset(new internal::CovarianceImpl(options)); -} - -Covariance::~Covariance() { -} - -bool Covariance::Compute( - const vector<pair<const double*, const double*> >& covariance_blocks, - Problem* problem) { - return impl_->Compute(covariance_blocks, problem->problem_impl_.get()); -} - -bool Covariance::GetCovarianceBlock(const double* parameter_block1, - const double* parameter_block2, - double* covariance_block) const { - return impl_->GetCovarianceBlockInTangentOrAmbientSpace(parameter_block1, - parameter_block2, - true, // ambient - covariance_block); -} - -bool Covariance::GetCovarianceBlockInTangentSpace( - const double* parameter_block1, - const double* parameter_block2, - double* covariance_block) const { - return impl_->GetCovarianceBlockInTangentOrAmbientSpace(parameter_block1, - parameter_block2, - false, // tangent - covariance_block); -} - -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/covariance_impl.cc b/extern/libmv/third_party/ceres/internal/ceres/covariance_impl.cc deleted file mode 100644 index 3e8302bed55..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/covariance_impl.cc +++ /dev/null @@ -1,757 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/covariance_impl.h" - -#ifdef CERES_USE_OPENMP -#include <omp.h> -#endif - -#include <algorithm> -#include <cstdlib> -#include <utility> -#include <vector> - -#include "Eigen/SparseCore" -#include "Eigen/SparseQR" -#include "Eigen/SVD" - -#include "ceres/compressed_col_sparse_matrix_utils.h" -#include "ceres/compressed_row_sparse_matrix.h" -#include "ceres/covariance.h" -#include "ceres/crs_matrix.h" -#include "ceres/internal/eigen.h" -#include "ceres/map_util.h" -#include "ceres/parameter_block.h" -#include "ceres/problem_impl.h" -#include "ceres/suitesparse.h" -#include "ceres/wall_time.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::make_pair; -using std::map; -using std::pair; -using std::swap; -using std::vector; - -typedef vector<pair<const double*, const double*> > CovarianceBlocks; - -CovarianceImpl::CovarianceImpl(const Covariance::Options& options) - : options_(options), - is_computed_(false), - is_valid_(false) { -#ifndef CERES_USE_OPENMP - if (options_.num_threads > 1) { - LOG(WARNING) - << "OpenMP support is not compiled into this binary; " - << "only options.num_threads = 1 is supported. Switching " - << "to single threaded mode."; - options_.num_threads = 1; - } -#endif - evaluate_options_.num_threads = options_.num_threads; - evaluate_options_.apply_loss_function = options_.apply_loss_function; -} - -CovarianceImpl::~CovarianceImpl() { -} - -bool CovarianceImpl::Compute(const CovarianceBlocks& covariance_blocks, - ProblemImpl* problem) { - problem_ = problem; - parameter_block_to_row_index_.clear(); - covariance_matrix_.reset(NULL); - is_valid_ = (ComputeCovarianceSparsity(covariance_blocks, problem) && - ComputeCovarianceValues()); - is_computed_ = true; - return is_valid_; -} - -bool CovarianceImpl::GetCovarianceBlockInTangentOrAmbientSpace( - const double* original_parameter_block1, - const double* original_parameter_block2, - bool lift_covariance_to_ambient_space, - double* covariance_block) const { - CHECK(is_computed_) - << "Covariance::GetCovarianceBlock called before Covariance::Compute"; - CHECK(is_valid_) - << "Covariance::GetCovarianceBlock called when Covariance::Compute " - << "returned false."; - - // If either of the two parameter blocks is constant, then the - // covariance block is also zero. - if (constant_parameter_blocks_.count(original_parameter_block1) > 0 || - constant_parameter_blocks_.count(original_parameter_block2) > 0) { - const ProblemImpl::ParameterMap& parameter_map = problem_->parameter_map(); - ParameterBlock* block1 = - FindOrDie(parameter_map, - const_cast<double*>(original_parameter_block1)); - - ParameterBlock* block2 = - FindOrDie(parameter_map, - const_cast<double*>(original_parameter_block2)); - const int block1_size = block1->Size(); - const int block2_size = block2->Size(); - MatrixRef(covariance_block, block1_size, block2_size).setZero(); - return true; - } - - const double* parameter_block1 = original_parameter_block1; - const double* parameter_block2 = original_parameter_block2; - const bool transpose = parameter_block1 > parameter_block2; - if (transpose) { - swap(parameter_block1, parameter_block2); - } - - // Find where in the covariance matrix the block is located. - const int row_begin = - FindOrDie(parameter_block_to_row_index_, parameter_block1); - const int col_begin = - FindOrDie(parameter_block_to_row_index_, parameter_block2); - const int* rows = covariance_matrix_->rows(); - const int* cols = covariance_matrix_->cols(); - const int row_size = rows[row_begin + 1] - rows[row_begin]; - const int* cols_begin = cols + rows[row_begin]; - - // The only part that requires work is walking the compressed column - // vector to determine where the set of columns correspnding to the - // covariance block begin. - int offset = 0; - while (cols_begin[offset] != col_begin && offset < row_size) { - ++offset; - } - - if (offset == row_size) { - LOG(ERROR) << "Unable to find covariance block for " - << original_parameter_block1 << " " - << original_parameter_block2; - return false; - } - - const ProblemImpl::ParameterMap& parameter_map = problem_->parameter_map(); - ParameterBlock* block1 = - FindOrDie(parameter_map, const_cast<double*>(parameter_block1)); - ParameterBlock* block2 = - FindOrDie(parameter_map, const_cast<double*>(parameter_block2)); - const LocalParameterization* local_param1 = block1->local_parameterization(); - const LocalParameterization* local_param2 = block2->local_parameterization(); - const int block1_size = block1->Size(); - const int block1_local_size = block1->LocalSize(); - const int block2_size = block2->Size(); - const int block2_local_size = block2->LocalSize(); - - ConstMatrixRef cov(covariance_matrix_->values() + rows[row_begin], - block1_size, - row_size); - - // Fast path when there are no local parameterizations or if the - // user does not want it lifted to the ambient space. - if ((local_param1 == NULL && local_param2 == NULL) || - !lift_covariance_to_ambient_space) { - if (transpose) { - MatrixRef(covariance_block, block2_local_size, block1_local_size) = - cov.block(0, offset, block1_local_size, - block2_local_size).transpose(); - } else { - MatrixRef(covariance_block, block1_local_size, block2_local_size) = - cov.block(0, offset, block1_local_size, block2_local_size); - } - return true; - } - - // If local parameterizations are used then the covariance that has - // been computed is in the tangent space and it needs to be lifted - // back to the ambient space. - // - // This is given by the formula - // - // C'_12 = J_1 C_12 J_2' - // - // Where C_12 is the local tangent space covariance for parameter - // blocks 1 and 2. J_1 and J_2 are respectively the local to global - // jacobians for parameter blocks 1 and 2. - // - // See Result 5.11 on page 142 of Hartley & Zisserman (2nd Edition) - // for a proof. - // - // TODO(sameeragarwal): Add caching of local parameterization, so - // that they are computed just once per parameter block. - Matrix block1_jacobian(block1_size, block1_local_size); - if (local_param1 == NULL) { - block1_jacobian.setIdentity(); - } else { - local_param1->ComputeJacobian(parameter_block1, block1_jacobian.data()); - } - - Matrix block2_jacobian(block2_size, block2_local_size); - // Fast path if the user is requesting a diagonal block. - if (parameter_block1 == parameter_block2) { - block2_jacobian = block1_jacobian; - } else { - if (local_param2 == NULL) { - block2_jacobian.setIdentity(); - } else { - local_param2->ComputeJacobian(parameter_block2, block2_jacobian.data()); - } - } - - if (transpose) { - MatrixRef(covariance_block, block2_size, block1_size) = - block2_jacobian * - cov.block(0, offset, block1_local_size, block2_local_size).transpose() * - block1_jacobian.transpose(); - } else { - MatrixRef(covariance_block, block1_size, block2_size) = - block1_jacobian * - cov.block(0, offset, block1_local_size, block2_local_size) * - block2_jacobian.transpose(); - } - - return true; -} - -// Determine the sparsity pattern of the covariance matrix based on -// the block pairs requested by the user. -bool CovarianceImpl::ComputeCovarianceSparsity( - const CovarianceBlocks& original_covariance_blocks, - ProblemImpl* problem) { - EventLogger event_logger("CovarianceImpl::ComputeCovarianceSparsity"); - - // Determine an ordering for the parameter block, by sorting the - // parameter blocks by their pointers. - vector<double*> all_parameter_blocks; - problem->GetParameterBlocks(&all_parameter_blocks); - const ProblemImpl::ParameterMap& parameter_map = problem->parameter_map(); - constant_parameter_blocks_.clear(); - vector<double*>& active_parameter_blocks = - evaluate_options_.parameter_blocks; - active_parameter_blocks.clear(); - for (int i = 0; i < all_parameter_blocks.size(); ++i) { - double* parameter_block = all_parameter_blocks[i]; - - ParameterBlock* block = FindOrDie(parameter_map, parameter_block); - if (block->IsConstant()) { - constant_parameter_blocks_.insert(parameter_block); - } else { - active_parameter_blocks.push_back(parameter_block); - } - } - - std::sort(active_parameter_blocks.begin(), active_parameter_blocks.end()); - - // Compute the number of rows. Map each parameter block to the - // first row corresponding to it in the covariance matrix using the - // ordering of parameter blocks just constructed. - int num_rows = 0; - parameter_block_to_row_index_.clear(); - for (int i = 0; i < active_parameter_blocks.size(); ++i) { - double* parameter_block = active_parameter_blocks[i]; - const int parameter_block_size = - problem->ParameterBlockLocalSize(parameter_block); - parameter_block_to_row_index_[parameter_block] = num_rows; - num_rows += parameter_block_size; - } - - // Compute the number of non-zeros in the covariance matrix. Along - // the way flip any covariance blocks which are in the lower - // triangular part of the matrix. - int num_nonzeros = 0; - CovarianceBlocks covariance_blocks; - for (int i = 0; i < original_covariance_blocks.size(); ++i) { - const pair<const double*, const double*>& block_pair = - original_covariance_blocks[i]; - if (constant_parameter_blocks_.count(block_pair.first) > 0 || - constant_parameter_blocks_.count(block_pair.second) > 0) { - continue; - } - - int index1 = FindOrDie(parameter_block_to_row_index_, block_pair.first); - int index2 = FindOrDie(parameter_block_to_row_index_, block_pair.second); - const int size1 = problem->ParameterBlockLocalSize(block_pair.first); - const int size2 = problem->ParameterBlockLocalSize(block_pair.second); - num_nonzeros += size1 * size2; - - // Make sure we are constructing a block upper triangular matrix. - if (index1 > index2) { - covariance_blocks.push_back(make_pair(block_pair.second, - block_pair.first)); - } else { - covariance_blocks.push_back(block_pair); - } - } - - if (covariance_blocks.size() == 0) { - VLOG(2) << "No non-zero covariance blocks found"; - covariance_matrix_.reset(NULL); - return true; - } - - // Sort the block pairs. As a consequence we get the covariance - // blocks as they will occur in the CompressedRowSparseMatrix that - // will store the covariance. - sort(covariance_blocks.begin(), covariance_blocks.end()); - - // Fill the sparsity pattern of the covariance matrix. - covariance_matrix_.reset( - new CompressedRowSparseMatrix(num_rows, num_rows, num_nonzeros)); - - int* rows = covariance_matrix_->mutable_rows(); - int* cols = covariance_matrix_->mutable_cols(); - - // Iterate over parameter blocks and in turn over the rows of the - // covariance matrix. For each parameter block, look in the upper - // triangular part of the covariance matrix to see if there are any - // blocks requested by the user. If this is the case then fill out a - // set of compressed rows corresponding to this parameter block. - // - // The key thing that makes this loop work is the fact that the - // row/columns of the covariance matrix are ordered by the pointer - // values of the parameter blocks. Thus iterating over the keys of - // parameter_block_to_row_index_ corresponds to iterating over the - // rows of the covariance matrix in order. - int i = 0; // index into covariance_blocks. - int cursor = 0; // index into the covariance matrix. - for (map<const double*, int>::const_iterator it = - parameter_block_to_row_index_.begin(); - it != parameter_block_to_row_index_.end(); - ++it) { - const double* row_block = it->first; - const int row_block_size = problem->ParameterBlockLocalSize(row_block); - int row_begin = it->second; - - // Iterate over the covariance blocks contained in this row block - // and count the number of columns in this row block. - int num_col_blocks = 0; - int num_columns = 0; - for (int j = i; j < covariance_blocks.size(); ++j, ++num_col_blocks) { - const pair<const double*, const double*>& block_pair = - covariance_blocks[j]; - if (block_pair.first != row_block) { - break; - } - num_columns += problem->ParameterBlockLocalSize(block_pair.second); - } - - // Fill out all the compressed rows for this parameter block. - for (int r = 0; r < row_block_size; ++r) { - rows[row_begin + r] = cursor; - for (int c = 0; c < num_col_blocks; ++c) { - const double* col_block = covariance_blocks[i + c].second; - const int col_block_size = problem->ParameterBlockLocalSize(col_block); - int col_begin = FindOrDie(parameter_block_to_row_index_, col_block); - for (int k = 0; k < col_block_size; ++k) { - cols[cursor++] = col_begin++; - } - } - } - - i+= num_col_blocks; - } - - rows[num_rows] = cursor; - return true; -} - -bool CovarianceImpl::ComputeCovarianceValues() { - switch (options_.algorithm_type) { - case DENSE_SVD: - return ComputeCovarianceValuesUsingDenseSVD(); -#ifndef CERES_NO_SUITESPARSE - case SUITE_SPARSE_QR: - return ComputeCovarianceValuesUsingSuiteSparseQR(); -#else - LOG(ERROR) << "SuiteSparse is required to use the " - << "SUITE_SPARSE_QR algorithm."; - return false; -#endif - case EIGEN_SPARSE_QR: - return ComputeCovarianceValuesUsingEigenSparseQR(); - default: - LOG(ERROR) << "Unsupported covariance estimation algorithm type: " - << CovarianceAlgorithmTypeToString(options_.algorithm_type); - return false; - } - return false; -} - -bool CovarianceImpl::ComputeCovarianceValuesUsingSuiteSparseQR() { - EventLogger event_logger( - "CovarianceImpl::ComputeCovarianceValuesUsingSparseQR"); - -#ifndef CERES_NO_SUITESPARSE - if (covariance_matrix_.get() == NULL) { - // Nothing to do, all zeros covariance matrix. - return true; - } - - CRSMatrix jacobian; - problem_->Evaluate(evaluate_options_, NULL, NULL, NULL, &jacobian); - event_logger.AddEvent("Evaluate"); - - // Construct a compressed column form of the Jacobian. - const int num_rows = jacobian.num_rows; - const int num_cols = jacobian.num_cols; - const int num_nonzeros = jacobian.values.size(); - - vector<SuiteSparse_long> transpose_rows(num_cols + 1, 0); - vector<SuiteSparse_long> transpose_cols(num_nonzeros, 0); - vector<double> transpose_values(num_nonzeros, 0); - - for (int idx = 0; idx < num_nonzeros; ++idx) { - transpose_rows[jacobian.cols[idx] + 1] += 1; - } - - for (int i = 1; i < transpose_rows.size(); ++i) { - transpose_rows[i] += transpose_rows[i - 1]; - } - - for (int r = 0; r < num_rows; ++r) { - for (int idx = jacobian.rows[r]; idx < jacobian.rows[r + 1]; ++idx) { - const int c = jacobian.cols[idx]; - const int transpose_idx = transpose_rows[c]; - transpose_cols[transpose_idx] = r; - transpose_values[transpose_idx] = jacobian.values[idx]; - ++transpose_rows[c]; - } - } - - for (int i = transpose_rows.size() - 1; i > 0 ; --i) { - transpose_rows[i] = transpose_rows[i - 1]; - } - transpose_rows[0] = 0; - - cholmod_sparse cholmod_jacobian; - cholmod_jacobian.nrow = num_rows; - cholmod_jacobian.ncol = num_cols; - cholmod_jacobian.nzmax = num_nonzeros; - cholmod_jacobian.nz = NULL; - cholmod_jacobian.p = reinterpret_cast<void*>(&transpose_rows[0]); - cholmod_jacobian.i = reinterpret_cast<void*>(&transpose_cols[0]); - cholmod_jacobian.x = reinterpret_cast<void*>(&transpose_values[0]); - cholmod_jacobian.z = NULL; - cholmod_jacobian.stype = 0; // Matrix is not symmetric. - cholmod_jacobian.itype = CHOLMOD_LONG; - cholmod_jacobian.xtype = CHOLMOD_REAL; - cholmod_jacobian.dtype = CHOLMOD_DOUBLE; - cholmod_jacobian.sorted = 1; - cholmod_jacobian.packed = 1; - - cholmod_common cc; - cholmod_l_start(&cc); - - cholmod_sparse* R = NULL; - SuiteSparse_long* permutation = NULL; - - // Compute a Q-less QR factorization of the Jacobian. Since we are - // only interested in inverting J'J = R'R, we do not need Q. This - // saves memory and gives us R as a permuted compressed column - // sparse matrix. - // - // TODO(sameeragarwal): Currently the symbolic factorization and the - // numeric factorization is done at the same time, and this does not - // explicitly account for the block column and row structure in the - // matrix. When using AMD, we have observed in the past that - // computing the ordering with the block matrix is significantly - // more efficient, both in runtime as well as the quality of - // ordering computed. So, it maybe worth doing that analysis - // separately. - const SuiteSparse_long rank = - SuiteSparseQR<double>(SPQR_ORDERING_BESTAMD, - SPQR_DEFAULT_TOL, - cholmod_jacobian.ncol, - &cholmod_jacobian, - &R, - &permutation, - &cc); - event_logger.AddEvent("Numeric Factorization"); - CHECK_NOTNULL(permutation); - CHECK_NOTNULL(R); - - if (rank < cholmod_jacobian.ncol) { - LOG(ERROR) << "Jacobian matrix is rank deficient. " - << "Number of columns: " << cholmod_jacobian.ncol - << " rank: " << rank; - free(permutation); - cholmod_l_free_sparse(&R, &cc); - cholmod_l_finish(&cc); - return false; - } - - vector<int> inverse_permutation(num_cols); - for (SuiteSparse_long i = 0; i < num_cols; ++i) { - inverse_permutation[permutation[i]] = i; - } - - const int* rows = covariance_matrix_->rows(); - const int* cols = covariance_matrix_->cols(); - double* values = covariance_matrix_->mutable_values(); - - // The following loop exploits the fact that the i^th column of A^{-1} - // is given by the solution to the linear system - // - // A x = e_i - // - // where e_i is a vector with e(i) = 1 and all other entries zero. - // - // Since the covariance matrix is symmetric, the i^th row and column - // are equal. - const int num_threads = options_.num_threads; - scoped_array<double> workspace(new double[num_threads * num_cols]); - -#pragma omp parallel for num_threads(num_threads) schedule(dynamic) - for (int r = 0; r < num_cols; ++r) { - const int row_begin = rows[r]; - const int row_end = rows[r + 1]; - if (row_end == row_begin) { - continue; - } - -# ifdef CERES_USE_OPENMP - int thread_id = omp_get_thread_num(); -# else - int thread_id = 0; -# endif - - double* solution = workspace.get() + thread_id * num_cols; - SolveRTRWithSparseRHS<SuiteSparse_long>( - num_cols, - static_cast<SuiteSparse_long*>(R->i), - static_cast<SuiteSparse_long*>(R->p), - static_cast<double*>(R->x), - inverse_permutation[r], - solution); - for (int idx = row_begin; idx < row_end; ++idx) { - const int c = cols[idx]; - values[idx] = solution[inverse_permutation[c]]; - } - } - - free(permutation); - cholmod_l_free_sparse(&R, &cc); - cholmod_l_finish(&cc); - event_logger.AddEvent("Inversion"); - return true; - -#else // CERES_NO_SUITESPARSE - - return false; - -#endif // CERES_NO_SUITESPARSE -} - -bool CovarianceImpl::ComputeCovarianceValuesUsingDenseSVD() { - EventLogger event_logger( - "CovarianceImpl::ComputeCovarianceValuesUsingDenseSVD"); - if (covariance_matrix_.get() == NULL) { - // Nothing to do, all zeros covariance matrix. - return true; - } - - CRSMatrix jacobian; - problem_->Evaluate(evaluate_options_, NULL, NULL, NULL, &jacobian); - event_logger.AddEvent("Evaluate"); - - Matrix dense_jacobian(jacobian.num_rows, jacobian.num_cols); - dense_jacobian.setZero(); - for (int r = 0; r < jacobian.num_rows; ++r) { - for (int idx = jacobian.rows[r]; idx < jacobian.rows[r + 1]; ++idx) { - const int c = jacobian.cols[idx]; - dense_jacobian(r, c) = jacobian.values[idx]; - } - } - event_logger.AddEvent("ConvertToDenseMatrix"); - - Eigen::JacobiSVD<Matrix> svd(dense_jacobian, - Eigen::ComputeThinU | Eigen::ComputeThinV); - - event_logger.AddEvent("SingularValueDecomposition"); - - const Vector singular_values = svd.singularValues(); - const int num_singular_values = singular_values.rows(); - Vector inverse_squared_singular_values(num_singular_values); - inverse_squared_singular_values.setZero(); - - const double max_singular_value = singular_values[0]; - const double min_singular_value_ratio = - sqrt(options_.min_reciprocal_condition_number); - - const bool automatic_truncation = (options_.null_space_rank < 0); - const int max_rank = std::min(num_singular_values, - num_singular_values - options_.null_space_rank); - - // Compute the squared inverse of the singular values. Truncate the - // computation based on min_singular_value_ratio and - // null_space_rank. When either of these two quantities are active, - // the resulting covariance matrix is a Moore-Penrose inverse - // instead of a regular inverse. - for (int i = 0; i < max_rank; ++i) { - const double singular_value_ratio = singular_values[i] / max_singular_value; - if (singular_value_ratio < min_singular_value_ratio) { - // Since the singular values are in decreasing order, if - // automatic truncation is enabled, then from this point on - // all values will fail the ratio test and there is nothing to - // do in this loop. - if (automatic_truncation) { - break; - } else { - LOG(ERROR) << "Cholesky factorization of J'J is not reliable. " - << "Reciprocal condition number: " - << singular_value_ratio * singular_value_ratio << " " - << "min_reciprocal_condition_number: " - << options_.min_reciprocal_condition_number; - return false; - } - } - - inverse_squared_singular_values[i] = - 1.0 / (singular_values[i] * singular_values[i]); - } - - Matrix dense_covariance = - svd.matrixV() * - inverse_squared_singular_values.asDiagonal() * - svd.matrixV().transpose(); - event_logger.AddEvent("PseudoInverse"); - - const int num_rows = covariance_matrix_->num_rows(); - const int* rows = covariance_matrix_->rows(); - const int* cols = covariance_matrix_->cols(); - double* values = covariance_matrix_->mutable_values(); - - for (int r = 0; r < num_rows; ++r) { - for (int idx = rows[r]; idx < rows[r + 1]; ++idx) { - const int c = cols[idx]; - values[idx] = dense_covariance(r, c); - } - } - event_logger.AddEvent("CopyToCovarianceMatrix"); - return true; -} - -bool CovarianceImpl::ComputeCovarianceValuesUsingEigenSparseQR() { - EventLogger event_logger( - "CovarianceImpl::ComputeCovarianceValuesUsingEigenSparseQR"); - if (covariance_matrix_.get() == NULL) { - // Nothing to do, all zeros covariance matrix. - return true; - } - - CRSMatrix jacobian; - problem_->Evaluate(evaluate_options_, NULL, NULL, NULL, &jacobian); - event_logger.AddEvent("Evaluate"); - - typedef Eigen::SparseMatrix<double, Eigen::ColMajor> EigenSparseMatrix; - - // Convert the matrix to column major order as required by SparseQR. - EigenSparseMatrix sparse_jacobian = - Eigen::MappedSparseMatrix<double, Eigen::RowMajor>( - jacobian.num_rows, jacobian.num_cols, - static_cast<int>(jacobian.values.size()), - jacobian.rows.data(), jacobian.cols.data(), jacobian.values.data()); - event_logger.AddEvent("ConvertToSparseMatrix"); - - Eigen::SparseQR<EigenSparseMatrix, Eigen::COLAMDOrdering<int> > - qr_solver(sparse_jacobian); - event_logger.AddEvent("QRDecomposition"); - - if (qr_solver.info() != Eigen::Success) { - LOG(ERROR) << "Eigen::SparseQR decomposition failed."; - return false; - } - - if (qr_solver.rank() < jacobian.num_cols) { - LOG(ERROR) << "Jacobian matrix is rank deficient. " - << "Number of columns: " << jacobian.num_cols - << " rank: " << qr_solver.rank(); - return false; - } - - const int* rows = covariance_matrix_->rows(); - const int* cols = covariance_matrix_->cols(); - double* values = covariance_matrix_->mutable_values(); - - // Compute the inverse column permutation used by QR factorization. - Eigen::PermutationMatrix<Eigen::Dynamic, Eigen::Dynamic> inverse_permutation = - qr_solver.colsPermutation().inverse(); - - // The following loop exploits the fact that the i^th column of A^{-1} - // is given by the solution to the linear system - // - // A x = e_i - // - // where e_i is a vector with e(i) = 1 and all other entries zero. - // - // Since the covariance matrix is symmetric, the i^th row and column - // are equal. - const int num_cols = jacobian.num_cols; - const int num_threads = options_.num_threads; - scoped_array<double> workspace(new double[num_threads * num_cols]); - -#pragma omp parallel for num_threads(num_threads) schedule(dynamic) - for (int r = 0; r < num_cols; ++r) { - const int row_begin = rows[r]; - const int row_end = rows[r + 1]; - if (row_end == row_begin) { - continue; - } - -# ifdef CERES_USE_OPENMP - int thread_id = omp_get_thread_num(); -# else - int thread_id = 0; -# endif - - double* solution = workspace.get() + thread_id * num_cols; - SolveRTRWithSparseRHS<int>( - num_cols, - qr_solver.matrixR().innerIndexPtr(), - qr_solver.matrixR().outerIndexPtr(), - &qr_solver.matrixR().data().value(0), - inverse_permutation.indices().coeff(r), - solution); - - // Assign the values of the computed covariance using the - // inverse permutation used in the QR factorization. - for (int idx = row_begin; idx < row_end; ++idx) { - const int c = cols[idx]; - values[idx] = solution[inverse_permutation.indices().coeff(c)]; - } - } - - event_logger.AddEvent("Inverse"); - - return true; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/covariance_impl.h b/extern/libmv/third_party/ceres/internal/ceres/covariance_impl.h deleted file mode 100644 index eb0cd040666..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/covariance_impl.h +++ /dev/null @@ -1,92 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_COVARIANCE_IMPL_H_ -#define CERES_INTERNAL_COVARIANCE_IMPL_H_ - -#include <map> -#include <set> -#include <utility> -#include <vector> -#include "ceres/covariance.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/problem_impl.h" -#include "ceres/suitesparse.h" - -namespace ceres { -namespace internal { - -class CompressedRowSparseMatrix; - -class CovarianceImpl { - public: - explicit CovarianceImpl(const Covariance::Options& options); - ~CovarianceImpl(); - - bool Compute( - const std::vector<std::pair<const double*, - const double*> >& covariance_blocks, - ProblemImpl* problem); - - bool GetCovarianceBlockInTangentOrAmbientSpace( - const double* parameter_block1, - const double* parameter_block2, - bool lift_covariance_to_ambient_space, - double* covariance_block) const; - - bool ComputeCovarianceSparsity( - const std::vector<std::pair<const double*, - const double*> >& covariance_blocks, - ProblemImpl* problem); - - bool ComputeCovarianceValues(); - bool ComputeCovarianceValuesUsingDenseSVD(); - bool ComputeCovarianceValuesUsingSuiteSparseQR(); - bool ComputeCovarianceValuesUsingEigenSparseQR(); - - const CompressedRowSparseMatrix* covariance_matrix() const { - return covariance_matrix_.get(); - } - - private: - ProblemImpl* problem_; - Covariance::Options options_; - Problem::EvaluateOptions evaluate_options_; - bool is_computed_; - bool is_valid_; - std::map<const double*, int> parameter_block_to_row_index_; - std::set<const double*> constant_parameter_blocks_; - scoped_ptr<CompressedRowSparseMatrix> covariance_matrix_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_COVARIANCE_IMPL_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/cxsparse.h b/extern/libmv/third_party/ceres/internal/ceres/cxsparse.h deleted file mode 100644 index 26dd1927a78..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/cxsparse.h +++ /dev/null @@ -1,140 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: strandmark@google.com (Petter Strandmark) - -#ifndef CERES_INTERNAL_CXSPARSE_H_ -#define CERES_INTERNAL_CXSPARSE_H_ - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_NO_CXSPARSE - -#include <vector> -#include "cs.h" - -namespace ceres { -namespace internal { - -class CompressedRowSparseMatrix; -class TripletSparseMatrix; - -// This object provides access to solving linear systems using Cholesky -// factorization with a known symbolic factorization. This features does not -// explicity exist in CXSparse. The methods in the class are nonstatic because -// the class manages internal scratch space. -class CXSparse { - public: - CXSparse(); - ~CXSparse(); - - // Solves a symmetric linear system A * x = b using Cholesky factorization. - // A - The system matrix. - // symbolic_factorization - The symbolic factorization of A. This is obtained - // from AnalyzeCholesky. - // b - The right hand size of the linear equation. This - // array will also recieve the solution. - // Returns false if Cholesky factorization of A fails. - bool SolveCholesky(cs_di* A, cs_dis* symbolic_factorization, double* b); - - // Creates a sparse matrix from a compressed-column form. No memory is - // allocated or copied; the structure A is filled out with info from the - // argument. - cs_di CreateSparseMatrixTransposeView(CompressedRowSparseMatrix* A); - - // Creates a new matrix from a triplet form. Deallocate the returned matrix - // with Free. May return NULL if the compression or allocation fails. - cs_di* CreateSparseMatrix(TripletSparseMatrix* A); - - // B = A' - // - // The returned matrix should be deallocated with Free when not used - // anymore. - cs_di* TransposeMatrix(cs_di* A); - - // C = A * B - // - // The returned matrix should be deallocated with Free when not used - // anymore. - cs_di* MatrixMatrixMultiply(cs_di* A, cs_di* B); - - // Computes a symbolic factorization of A that can be used in SolveCholesky. - // - // The returned matrix should be deallocated with Free when not used anymore. - cs_dis* AnalyzeCholesky(cs_di* A); - - // Computes a symbolic factorization of A that can be used in - // SolveCholesky, but does not compute a fill-reducing ordering. - // - // The returned matrix should be deallocated with Free when not used anymore. - cs_dis* AnalyzeCholeskyWithNaturalOrdering(cs_di* A); - - // Computes a symbolic factorization of A that can be used in - // SolveCholesky. The difference from AnalyzeCholesky is that this - // function first detects the block sparsity of the matrix using - // information about the row and column blocks and uses this block - // sparse matrix to find a fill-reducing ordering. This ordering is - // then used to find a symbolic factorization. This can result in a - // significant performance improvement AnalyzeCholesky on block - // sparse matrices. - // - // The returned matrix should be deallocated with Free when not used - // anymore. - cs_dis* BlockAnalyzeCholesky(cs_di* A, - const std::vector<int>& row_blocks, - const std::vector<int>& col_blocks); - - // Compute an fill-reducing approximate minimum degree ordering of - // the matrix A. ordering should be non-NULL and should point to - // enough memory to hold the ordering for the rows of A. - void ApproximateMinimumDegreeOrdering(cs_di* A, int* ordering); - - void Free(cs_di* sparse_matrix); - void Free(cs_dis* symbolic_factorization); - - private: - // Cached scratch space - CS_ENTRY* scratch_; - int scratch_size_; -}; - -} // namespace internal -} // namespace ceres - -#else // CERES_NO_CXSPARSE - -typedef void cs_dis; - -class CXSparse { - public: - void Free(void* arg) {} -}; -#endif // CERES_NO_CXSPARSE - -#endif // CERES_INTERNAL_CXSPARSE_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/dense_jacobian_writer.h b/extern/libmv/third_party/ceres/internal/ceres/dense_jacobian_writer.h deleted file mode 100644 index 1b04f383f09..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dense_jacobian_writer.h +++ /dev/null @@ -1,108 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// A jacobian writer that writes to dense Eigen matrices. - -#ifndef CERES_INTERNAL_DENSE_JACOBIAN_WRITER_H_ -#define CERES_INTERNAL_DENSE_JACOBIAN_WRITER_H_ - -#include "ceres/casts.h" -#include "ceres/dense_sparse_matrix.h" -#include "ceres/parameter_block.h" -#include "ceres/program.h" -#include "ceres/residual_block.h" -#include "ceres/scratch_evaluate_preparer.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -class DenseJacobianWriter { - public: - DenseJacobianWriter(Evaluator::Options /* ignored */, - Program* program) - : program_(program) { - } - - // JacobianWriter interface. - - // Since the dense matrix has different layout than that assumed by the cost - // functions, use scratch space to store the jacobians temporarily then copy - // them over to the larger jacobian later. - ScratchEvaluatePreparer* CreateEvaluatePreparers(int num_threads) { - return ScratchEvaluatePreparer::Create(*program_, num_threads); - } - - SparseMatrix* CreateJacobian() const { - return new DenseSparseMatrix(program_->NumResiduals(), - program_->NumEffectiveParameters(), - true); - } - - void Write(int residual_id, - int residual_offset, - double **jacobians, - SparseMatrix* jacobian) { - DenseSparseMatrix* dense_jacobian = down_cast<DenseSparseMatrix*>(jacobian); - const ResidualBlock* residual_block = - program_->residual_blocks()[residual_id]; - int num_parameter_blocks = residual_block->NumParameterBlocks(); - int num_residuals = residual_block->NumResiduals(); - - // Now copy the jacobians for each parameter into the dense jacobian matrix. - for (int j = 0; j < num_parameter_blocks; ++j) { - ParameterBlock* parameter_block = residual_block->parameter_blocks()[j]; - - // If the parameter block is fixed, then there is nothing to do. - if (parameter_block->IsConstant()) { - continue; - } - - const int parameter_block_size = parameter_block->LocalSize(); - ConstMatrixRef parameter_jacobian(jacobians[j], - num_residuals, - parameter_block_size); - - dense_jacobian->mutable_matrix().block( - residual_offset, - parameter_block->delta_offset(), - num_residuals, - parameter_block_size) = parameter_jacobian; - } - } - - private: - Program* program_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_DENSE_JACOBIAN_WRITER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/dense_normal_cholesky_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/dense_normal_cholesky_solver.cc deleted file mode 100644 index b13cf3fc9f6..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dense_normal_cholesky_solver.cc +++ /dev/null @@ -1,166 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/dense_normal_cholesky_solver.h" - -#include <cstddef> - -#include "Eigen/Dense" -#include "ceres/blas.h" -#include "ceres/dense_sparse_matrix.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/lapack.h" -#include "ceres/linear_solver.h" -#include "ceres/types.h" -#include "ceres/wall_time.h" - -namespace ceres { -namespace internal { - -DenseNormalCholeskySolver::DenseNormalCholeskySolver( - const LinearSolver::Options& options) - : options_(options) {} - -LinearSolver::Summary DenseNormalCholeskySolver::SolveImpl( - DenseSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x) { - if (options_.dense_linear_algebra_library_type == EIGEN) { - return SolveUsingEigen(A, b, per_solve_options, x); - } else { - return SolveUsingLAPACK(A, b, per_solve_options, x); - } -} - -LinearSolver::Summary DenseNormalCholeskySolver::SolveUsingEigen( - DenseSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x) { - EventLogger event_logger("DenseNormalCholeskySolver::Solve"); - - const int num_rows = A->num_rows(); - const int num_cols = A->num_cols(); - - ConstColMajorMatrixRef Aref = A->matrix(); - Matrix lhs(num_cols, num_cols); - lhs.setZero(); - - event_logger.AddEvent("Setup"); - - // lhs += A'A - // - // Using rankUpdate instead of GEMM, exposes the fact that its the - // same matrix being multiplied with itself and that the product is - // symmetric. - lhs.selfadjointView<Eigen::Upper>().rankUpdate(Aref.transpose()); - - // rhs = A'b - Vector rhs = Aref.transpose() * ConstVectorRef(b, num_rows); - - if (per_solve_options.D != NULL) { - ConstVectorRef D(per_solve_options.D, num_cols); - lhs += D.array().square().matrix().asDiagonal(); - } - event_logger.AddEvent("Product"); - - LinearSolver::Summary summary; - summary.num_iterations = 1; - summary.termination_type = LINEAR_SOLVER_SUCCESS; - Eigen::LLT<Matrix, Eigen::Upper> llt = - lhs.selfadjointView<Eigen::Upper>().llt(); - - if (llt.info() != Eigen::Success) { - summary.termination_type = LINEAR_SOLVER_FAILURE; - summary.message = "Eigen LLT decomposition failed."; - } else { - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = "Success."; - } - - VectorRef(x, num_cols) = llt.solve(rhs); - event_logger.AddEvent("Solve"); - return summary; -} - -LinearSolver::Summary DenseNormalCholeskySolver::SolveUsingLAPACK( - DenseSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x) { - EventLogger event_logger("DenseNormalCholeskySolver::Solve"); - - if (per_solve_options.D != NULL) { - // Temporarily append a diagonal block to the A matrix, but undo - // it before returning the matrix to the user. - A->AppendDiagonal(per_solve_options.D); - } - - const int num_cols = A->num_cols(); - Matrix lhs(num_cols, num_cols); - event_logger.AddEvent("Setup"); - - // lhs = A'A - // - // Note: This is a bit delicate, it assumes that the stride on this - // matrix is the same as the number of rows. - BLAS::SymmetricRankKUpdate(A->num_rows(), - num_cols, - A->values(), - true, - 1.0, - 0.0, - lhs.data()); - - if (per_solve_options.D != NULL) { - // Undo the modifications to the matrix A. - A->RemoveDiagonal(); - } - - // TODO(sameeragarwal): Replace this with a gemv call for true blasness. - // rhs = A'b - VectorRef(x, num_cols) = - A->matrix().transpose() * ConstVectorRef(b, A->num_rows()); - event_logger.AddEvent("Product"); - - LinearSolver::Summary summary; - summary.num_iterations = 1; - summary.termination_type = - LAPACK::SolveInPlaceUsingCholesky(num_cols, - lhs.data(), - x, - &summary.message); - event_logger.AddEvent("Solve"); - return summary; -} -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/dense_normal_cholesky_solver.h b/extern/libmv/third_party/ceres/internal/ceres/dense_normal_cholesky_solver.h deleted file mode 100644 index 11287ebf675..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dense_normal_cholesky_solver.h +++ /dev/null @@ -1,107 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Solve dense rectangular systems Ax = b by forming the normal -// equations and solving them using the Cholesky factorization. - -#ifndef CERES_INTERNAL_DENSE_NORMAL_CHOLESKY_SOLVER_H_ -#define CERES_INTERNAL_DENSE_NORMAL_CHOLESKY_SOLVER_H_ - -#include "ceres/linear_solver.h" -#include "ceres/internal/macros.h" - -namespace ceres { -namespace internal { - -class DenseSparseMatrix; - -// This class implements the LinearSolver interface for solving -// rectangular/unsymmetric (well constrained) linear systems of the -// form -// -// Ax = b -// -// Since there does not usually exist a solution that satisfies these -// equations, the solver instead solves the linear least squares -// problem -// -// min_x |Ax - b|^2 -// -// Setting the gradient of the above optimization problem to zero -// gives us the normal equations -// -// A'Ax = A'b -// -// A'A is a positive definite matrix (hopefully), and the resulting -// linear system can be solved using Cholesky factorization. -// -// If the PerSolveOptions struct has a non-null array D, then the -// augmented/regularized linear system -// -// [ A ]x = [b] -// [ diag(D) ] [0] -// -// is solved. -// -// This class uses the LDLT factorization routines from the Eigen -// library. This solver always returns a solution, it is the user's -// responsibility to judge if the solution is good enough for their -// purposes. -class DenseNormalCholeskySolver: public DenseSparseMatrixSolver { - public: - explicit DenseNormalCholeskySolver(const LinearSolver::Options& options); - - private: - virtual LinearSolver::Summary SolveImpl( - DenseSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x); - - LinearSolver::Summary SolveUsingLAPACK( - DenseSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x); - - LinearSolver::Summary SolveUsingEigen( - DenseSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x); - - const LinearSolver::Options options_; - CERES_DISALLOW_COPY_AND_ASSIGN(DenseNormalCholeskySolver); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_DENSE_NORMAL_CHOLESKY_SOLVER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.cc deleted file mode 100644 index e85fdfc0c68..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.cc +++ /dev/null @@ -1,170 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/dense_qr_solver.h" - - -#include <cstddef> -#include "Eigen/Dense" -#include "ceres/dense_sparse_matrix.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/lapack.h" -#include "ceres/linear_solver.h" -#include "ceres/types.h" -#include "ceres/wall_time.h" - -namespace ceres { -namespace internal { - -DenseQRSolver::DenseQRSolver(const LinearSolver::Options& options) - : options_(options) { - work_.resize(1); -} - -LinearSolver::Summary DenseQRSolver::SolveImpl( - DenseSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x) { - if (options_.dense_linear_algebra_library_type == EIGEN) { - return SolveUsingEigen(A, b, per_solve_options, x); - } else { - return SolveUsingLAPACK(A, b, per_solve_options, x); - } -} - -LinearSolver::Summary DenseQRSolver::SolveUsingLAPACK( - DenseSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x) { - EventLogger event_logger("DenseQRSolver::Solve"); - - const int num_rows = A->num_rows(); - const int num_cols = A->num_cols(); - - if (per_solve_options.D != NULL) { - // Temporarily append a diagonal block to the A matrix, but undo - // it before returning the matrix to the user. - A->AppendDiagonal(per_solve_options.D); - } - - // TODO(sameeragarwal): Since we are copying anyways, the diagonal - // can be appended to the matrix instead of doing it on A. - lhs_ = A->matrix(); - - if (per_solve_options.D != NULL) { - // Undo the modifications to the matrix A. - A->RemoveDiagonal(); - } - - // rhs = [b;0] to account for the additional rows in the lhs. - if (rhs_.rows() != lhs_.rows()) { - rhs_.resize(lhs_.rows()); - } - rhs_.setZero(); - rhs_.head(num_rows) = ConstVectorRef(b, num_rows); - - if (work_.rows() == 1) { - const int work_size = - LAPACK::EstimateWorkSizeForQR(lhs_.rows(), lhs_.cols()); - VLOG(3) << "Working memory for Dense QR factorization: " - << work_size * sizeof(double); - work_.resize(work_size); - } - - LinearSolver::Summary summary; - summary.num_iterations = 1; - summary.termination_type = LAPACK::SolveInPlaceUsingQR(lhs_.rows(), - lhs_.cols(), - lhs_.data(), - work_.rows(), - work_.data(), - rhs_.data(), - &summary.message); - event_logger.AddEvent("Solve"); - if (summary.termination_type == LINEAR_SOLVER_SUCCESS) { - VectorRef(x, num_cols) = rhs_.head(num_cols); - } - - event_logger.AddEvent("TearDown"); - return summary; -} - -LinearSolver::Summary DenseQRSolver::SolveUsingEigen( - DenseSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x) { - EventLogger event_logger("DenseQRSolver::Solve"); - - const int num_rows = A->num_rows(); - const int num_cols = A->num_cols(); - - if (per_solve_options.D != NULL) { - // Temporarily append a diagonal block to the A matrix, but undo - // it before returning the matrix to the user. - A->AppendDiagonal(per_solve_options.D); - } - - // rhs = [b;0] to account for the additional rows in the lhs. - const int augmented_num_rows = - num_rows + ((per_solve_options.D != NULL) ? num_cols : 0); - if (rhs_.rows() != augmented_num_rows) { - rhs_.resize(augmented_num_rows); - rhs_.setZero(); - } - rhs_.head(num_rows) = ConstVectorRef(b, num_rows); - event_logger.AddEvent("Setup"); - - // Solve the system. - VectorRef(x, num_cols) = A->matrix().householderQr().solve(rhs_); - event_logger.AddEvent("Solve"); - - if (per_solve_options.D != NULL) { - // Undo the modifications to the matrix A. - A->RemoveDiagonal(); - } - - // We always succeed, since the QR solver returns the best solution - // it can. It is the job of the caller to determine if the solution - // is good enough or not. - LinearSolver::Summary summary; - summary.num_iterations = 1; - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = "Success."; - - event_logger.AddEvent("TearDown"); - return summary; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.h b/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.h deleted file mode 100644 index 1a6e0898c56..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.h +++ /dev/null @@ -1,115 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Solve dense rectangular systems Ax = b using the QR factorization. -#ifndef CERES_INTERNAL_DENSE_QR_SOLVER_H_ -#define CERES_INTERNAL_DENSE_QR_SOLVER_H_ - -#include "ceres/linear_solver.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/macros.h" - -namespace ceres { -namespace internal { - -class DenseSparseMatrix; - -// This class implements the LinearSolver interface for solving -// rectangular/unsymmetric (well constrained) linear systems of the -// form -// -// Ax = b -// -// Since there does not usually exist a solution that satisfies these -// equations, the solver instead solves the linear least squares -// problem -// -// min_x |Ax - b|^2 -// -// The solution strategy is based on computing the QR decomposition of -// A, i.e. -// -// A = QR -// -// Where Q is an orthonormal matrix and R is an upper triangular -// matrix. Then -// -// Ax = b -// QRx = b -// Q'QRx = Q'b -// Rx = Q'b -// x = R^{-1} Q'b -// -// If the PerSolveOptions struct has a non-null array D, then the -// augmented/regularized linear system -// -// [ A ]x = [b] -// [ diag(D) ] [0] -// -// is solved. -// -// This class uses the dense QR factorization routines from the Eigen -// library. This solver always returns a solution, it is the user's -// responsibility to judge if the solution is good enough for their -// purposes. -class DenseQRSolver: public DenseSparseMatrixSolver { - public: - explicit DenseQRSolver(const LinearSolver::Options& options); - - private: - virtual LinearSolver::Summary SolveImpl( - DenseSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x); - - LinearSolver::Summary SolveUsingEigen( - DenseSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x); - - LinearSolver::Summary SolveUsingLAPACK( - DenseSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x); - - const LinearSolver::Options options_; - ColMajorMatrix lhs_; - Vector rhs_; - Vector work_; - CERES_DISALLOW_COPY_AND_ASSIGN(DenseQRSolver); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_DENSE_QR_SOLVER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.cc deleted file mode 100644 index 19db867d4aa..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.cc +++ /dev/null @@ -1,183 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#include "ceres/dense_sparse_matrix.h" - -#include <algorithm> -#include "ceres/triplet_sparse_matrix.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/port.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -DenseSparseMatrix::DenseSparseMatrix(int num_rows, int num_cols) - : has_diagonal_appended_(false), - has_diagonal_reserved_(false) { - m_.resize(num_rows, num_cols); - m_.setZero(); -} - -DenseSparseMatrix::DenseSparseMatrix(int num_rows, - int num_cols, - bool reserve_diagonal) - : has_diagonal_appended_(false), - has_diagonal_reserved_(reserve_diagonal) { - if (reserve_diagonal) { - // Allocate enough space for the diagonal. - m_.resize(num_rows + num_cols, num_cols); - } else { - m_.resize(num_rows, num_cols); - } - m_.setZero(); -} - -DenseSparseMatrix::DenseSparseMatrix(const TripletSparseMatrix& m) - : m_(Eigen::MatrixXd::Zero(m.num_rows(), m.num_cols())), - has_diagonal_appended_(false), - has_diagonal_reserved_(false) { - const double *values = m.values(); - const int *rows = m.rows(); - const int *cols = m.cols(); - int num_nonzeros = m.num_nonzeros(); - - for (int i = 0; i < num_nonzeros; ++i) { - m_(rows[i], cols[i]) += values[i]; - } -} - -DenseSparseMatrix::DenseSparseMatrix(const ColMajorMatrix& m) - : m_(m), - has_diagonal_appended_(false), - has_diagonal_reserved_(false) { -} - -void DenseSparseMatrix::SetZero() { - m_.setZero(); -} - -void DenseSparseMatrix::RightMultiply(const double* x, double* y) const { - VectorRef(y, num_rows()) += matrix() * ConstVectorRef(x, num_cols()); -} - -void DenseSparseMatrix::LeftMultiply(const double* x, double* y) const { - VectorRef(y, num_cols()) += - matrix().transpose() * ConstVectorRef(x, num_rows()); -} - -void DenseSparseMatrix::SquaredColumnNorm(double* x) const { - VectorRef(x, num_cols()) = m_.colwise().squaredNorm(); -} - -void DenseSparseMatrix::ScaleColumns(const double* scale) { - m_ *= ConstVectorRef(scale, num_cols()).asDiagonal(); -} - -void DenseSparseMatrix::ToDenseMatrix(Matrix* dense_matrix) const { - *dense_matrix = m_.block(0, 0, num_rows(), num_cols()); -} - -void DenseSparseMatrix::AppendDiagonal(double *d) { - CHECK(!has_diagonal_appended_); - if (!has_diagonal_reserved_) { - ColMajorMatrix tmp = m_; - m_.resize(m_.rows() + m_.cols(), m_.cols()); - m_.setZero(); - m_.block(0, 0, tmp.rows(), tmp.cols()) = tmp; - has_diagonal_reserved_ = true; - } - - m_.bottomLeftCorner(m_.cols(), m_.cols()) = - ConstVectorRef(d, m_.cols()).asDiagonal(); - has_diagonal_appended_ = true; -} - -void DenseSparseMatrix::RemoveDiagonal() { - CHECK(has_diagonal_appended_); - has_diagonal_appended_ = false; - // Leave the diagonal reserved. -} - -int DenseSparseMatrix::num_rows() const { - if (has_diagonal_reserved_ && !has_diagonal_appended_) { - return m_.rows() - m_.cols(); - } - return m_.rows(); -} - -int DenseSparseMatrix::num_cols() const { - return m_.cols(); -} - -int DenseSparseMatrix::num_nonzeros() const { - if (has_diagonal_reserved_ && !has_diagonal_appended_) { - return (m_.rows() - m_.cols()) * m_.cols(); - } - return m_.rows() * m_.cols(); -} - -ConstColMajorMatrixRef DenseSparseMatrix::matrix() const { - return ConstColMajorMatrixRef( - m_.data(), - ((has_diagonal_reserved_ && !has_diagonal_appended_) - ? m_.rows() - m_.cols() - : m_.rows()), - m_.cols(), - Eigen::Stride<Eigen::Dynamic, 1>(m_.rows(), 1)); -} - -ColMajorMatrixRef DenseSparseMatrix::mutable_matrix() { - return ColMajorMatrixRef( - m_.data(), - ((has_diagonal_reserved_ && !has_diagonal_appended_) - ? m_.rows() - m_.cols() - : m_.rows()), - m_.cols(), - Eigen::Stride<Eigen::Dynamic, 1>(m_.rows(), 1)); -} - - -void DenseSparseMatrix::ToTextFile(FILE* file) const { - CHECK_NOTNULL(file); - const int active_rows = - (has_diagonal_reserved_ && !has_diagonal_appended_) - ? (m_.rows() - m_.cols()) - : m_.rows(); - - for (int r = 0; r < active_rows; ++r) { - for (int c = 0; c < m_.cols(); ++c) { - fprintf(file, "% 10d % 10d %17f\n", r, c, m_(r, c)); - } - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.h deleted file mode 100644 index b011bfddee7..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.h +++ /dev/null @@ -1,109 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// A dense matrix implemented under the SparseMatrix interface. - -#ifndef CERES_INTERNAL_DENSE_SPARSE_MATRIX_H_ -#define CERES_INTERNAL_DENSE_SPARSE_MATRIX_H_ - -#include "ceres/sparse_matrix.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/macros.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -class TripletSparseMatrix; - -class DenseSparseMatrix : public SparseMatrix { - public: - // Build a matrix with the same content as the TripletSparseMatrix - // m. This assumes that m does not have any repeated entries. - explicit DenseSparseMatrix(const TripletSparseMatrix& m); - explicit DenseSparseMatrix(const ColMajorMatrix& m); - - DenseSparseMatrix(int num_rows, int num_cols); - DenseSparseMatrix(int num_rows, int num_cols, bool reserve_diagonal); - - virtual ~DenseSparseMatrix() {} - - // SparseMatrix interface. - virtual void SetZero(); - virtual void RightMultiply(const double* x, double* y) const; - virtual void LeftMultiply(const double* x, double* y) const; - virtual void SquaredColumnNorm(double* x) const; - virtual void ScaleColumns(const double* scale); - virtual void ToDenseMatrix(Matrix* dense_matrix) const; - virtual void ToTextFile(FILE* file) const; - virtual int num_rows() const; - virtual int num_cols() const; - virtual int num_nonzeros() const; - virtual const double* values() const { return m_.data(); } - virtual double* mutable_values() { return m_.data(); } - - ConstColMajorMatrixRef matrix() const; - ColMajorMatrixRef mutable_matrix(); - - // Only one diagonal can be appended at a time. The diagonal is appended to - // as a new set of rows, e.g. - // - // Original matrix: - // - // x x x - // x x x - // x x x - // - // After append diagonal (1, 2, 3): - // - // x x x - // x x x - // x x x - // 1 0 0 - // 0 2 0 - // 0 0 3 - // - // Calling RemoveDiagonal removes the block. It is a fatal error to append a - // diagonal to a matrix that already has an appended diagonal, and it is also - // a fatal error to remove a diagonal from a matrix that has none. - void AppendDiagonal(double *d); - void RemoveDiagonal(); - - private: - ColMajorMatrix m_; - bool has_diagonal_appended_; - bool has_diagonal_reserved_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_DENSE_SPARSE_MATRIX_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/detect_structure.cc b/extern/libmv/third_party/ceres/internal/ceres/detect_structure.cc deleted file mode 100644 index 959a0ee3c84..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/detect_structure.cc +++ /dev/null @@ -1,120 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/detect_structure.h" -#include "ceres/internal/eigen.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -void DetectStructure(const CompressedRowBlockStructure& bs, - const int num_eliminate_blocks, - int* row_block_size, - int* e_block_size, - int* f_block_size) { - const int num_row_blocks = bs.rows.size(); - *row_block_size = 0; - *e_block_size = 0; - *f_block_size = 0; - - // Iterate over row blocks of the matrix, checking if row_block, - // e_block or f_block sizes remain constant. - for (int r = 0; r < num_row_blocks; ++r) { - const CompressedRow& row = bs.rows[r]; - // We do not care about the sizes of the blocks in rows which do - // not contain e_blocks. - if (row.cells.front().block_id >= num_eliminate_blocks) { - break; - } - - // Detect fixed or dynamic row block size. - if (*row_block_size == 0) { - *row_block_size = row.block.size; - } else if (*row_block_size != Eigen::Dynamic && - *row_block_size != row.block.size) { - VLOG(2) << "Dynamic row block size because the block size changed from " - << *row_block_size << " to " - << row.block.size; - *row_block_size = Eigen::Dynamic; - } - - // Detect fixed or dynamic e-block size. - const int e_block_id = row.cells.front().block_id; - if (*e_block_size == 0) { - *e_block_size = bs.cols[e_block_id].size; - } else if (*e_block_size != Eigen::Dynamic && - *e_block_size != bs.cols[e_block_id].size) { - VLOG(2) << "Dynamic e block size because the block size changed from " - << *e_block_size << " to " - << bs.cols[e_block_id].size; - *e_block_size = Eigen::Dynamic; - } - - // Detect fixed or dynamic f-block size. We are only interested in - // rows with e-blocks, and the e-block is always the first block, - // so only rows of size greater than 1 are of interest. - if (row.cells.size() > 1) { - if (*f_block_size == 0) { - const int f_block_id = row.cells[1].block_id; - *f_block_size = bs.cols[f_block_id].size; - } - - for (int c = 1; - (c < row.cells.size()) && (*f_block_size != Eigen::Dynamic); - ++c) { - const int f_block_id = row.cells[c].block_id; - if (*f_block_size != bs.cols[f_block_id].size) { - VLOG(2) << "Dynamic f block size because the block size " - << "changed from " << *f_block_size << " to " - << bs.cols[f_block_id].size; - *f_block_size = Eigen::Dynamic; - } - } - } - - const bool is_everything_dynamic = (*row_block_size == Eigen::Dynamic && - *e_block_size == Eigen::Dynamic && - *f_block_size == Eigen::Dynamic); - if (is_everything_dynamic) { - break; - } - } - - CHECK_NE(*row_block_size, 0) << "No rows found"; - CHECK_NE(*e_block_size, 0) << "No e type blocks found"; - VLOG(1) << "Schur complement static structure <" - << *row_block_size << "," - << *e_block_size << "," - << *f_block_size << ">."; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/detect_structure.h b/extern/libmv/third_party/ceres/internal/ceres/detect_structure.h deleted file mode 100644 index 602581c846e..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/detect_structure.h +++ /dev/null @@ -1,67 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_DETECT_STRUCTURE_H_ -#define CERES_INTERNAL_DETECT_STRUCTURE_H_ - -#include "ceres/block_structure.h" - -namespace ceres { -namespace internal { - -// Detect static blocks in the problem sparsity. For rows containing -// e_blocks, we are interested in detecting if the size of the row -// blocks, e_blocks and the f_blocks remain constant. If they do, then -// we can use template specialization to improve the performance of -// the block level linear algebra operations used by the -// SchurEliminator. -// -// If a block size is not constant, we return Eigen::Dynamic as the -// value. This just means that the eliminator uses dynamically sized -// linear algebra operations rather than static operations whose size -// is known as compile time. -// -// For more details about e_blocks and f_blocks, see -// schur_eliminator.h. This information is used to initialized an -// appropriate template specialization of SchurEliminator. -// -// Note: The structure of rows without any e-blocks has no effect on -// the values returned by this function. It is entirely possible that -// the f_block_size and row_blocks_size is not constant in such rows. -void DetectStructure(const CompressedRowBlockStructure& bs, - const int num_eliminate_blocks, - int* row_block_size, - int* e_block_size, - int* f_block_size); - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_DETECT_STRUCTURE_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.cc b/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.cc deleted file mode 100644 index 839e1816338..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.cc +++ /dev/null @@ -1,718 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/dogleg_strategy.h" - -#include <cmath> -#include "Eigen/Dense" -#include "ceres/array_utils.h" -#include "ceres/internal/eigen.h" -#include "ceres/linear_least_squares_problems.h" -#include "ceres/linear_solver.h" -#include "ceres/polynomial.h" -#include "ceres/sparse_matrix.h" -#include "ceres/trust_region_strategy.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { -namespace { -const double kMaxMu = 1.0; -const double kMinMu = 1e-8; -} - -DoglegStrategy::DoglegStrategy(const TrustRegionStrategy::Options& options) - : linear_solver_(options.linear_solver), - radius_(options.initial_radius), - max_radius_(options.max_radius), - min_diagonal_(options.min_lm_diagonal), - max_diagonal_(options.max_lm_diagonal), - mu_(kMinMu), - min_mu_(kMinMu), - max_mu_(kMaxMu), - mu_increase_factor_(10.0), - increase_threshold_(0.75), - decrease_threshold_(0.25), - dogleg_step_norm_(0.0), - reuse_(false), - dogleg_type_(options.dogleg_type) { - CHECK_NOTNULL(linear_solver_); - CHECK_GT(min_diagonal_, 0.0); - CHECK_LE(min_diagonal_, max_diagonal_); - CHECK_GT(max_radius_, 0.0); -} - -// If the reuse_ flag is not set, then the Cauchy point (scaled -// gradient) and the new Gauss-Newton step are computed from -// scratch. The Dogleg step is then computed as interpolation of these -// two vectors. -TrustRegionStrategy::Summary DoglegStrategy::ComputeStep( - const TrustRegionStrategy::PerSolveOptions& per_solve_options, - SparseMatrix* jacobian, - const double* residuals, - double* step) { - CHECK_NOTNULL(jacobian); - CHECK_NOTNULL(residuals); - CHECK_NOTNULL(step); - - const int n = jacobian->num_cols(); - if (reuse_) { - // Gauss-Newton and gradient vectors are always available, only a - // new interpolant need to be computed. For the subspace case, - // the subspace and the two-dimensional model are also still valid. - switch (dogleg_type_) { - case TRADITIONAL_DOGLEG: - ComputeTraditionalDoglegStep(step); - break; - - case SUBSPACE_DOGLEG: - ComputeSubspaceDoglegStep(step); - break; - } - TrustRegionStrategy::Summary summary; - summary.num_iterations = 0; - summary.termination_type = LINEAR_SOLVER_SUCCESS; - return summary; - } - - reuse_ = true; - // Check that we have the storage needed to hold the various - // temporary vectors. - if (diagonal_.rows() != n) { - diagonal_.resize(n, 1); - gradient_.resize(n, 1); - gauss_newton_step_.resize(n, 1); - } - - // Vector used to form the diagonal matrix that is used to - // regularize the Gauss-Newton solve and that defines the - // elliptical trust region - // - // || D * step || <= radius_ . - // - jacobian->SquaredColumnNorm(diagonal_.data()); - for (int i = 0; i < n; ++i) { - diagonal_[i] = std::min(std::max(diagonal_[i], min_diagonal_), - max_diagonal_); - } - diagonal_ = diagonal_.array().sqrt(); - - ComputeGradient(jacobian, residuals); - ComputeCauchyPoint(jacobian); - - LinearSolver::Summary linear_solver_summary = - ComputeGaussNewtonStep(per_solve_options, jacobian, residuals); - - TrustRegionStrategy::Summary summary; - summary.residual_norm = linear_solver_summary.residual_norm; - summary.num_iterations = linear_solver_summary.num_iterations; - summary.termination_type = linear_solver_summary.termination_type; - - if (linear_solver_summary.termination_type == LINEAR_SOLVER_FATAL_ERROR) { - return summary; - } - - if (linear_solver_summary.termination_type != LINEAR_SOLVER_FAILURE) { - switch (dogleg_type_) { - // Interpolate the Cauchy point and the Gauss-Newton step. - case TRADITIONAL_DOGLEG: - ComputeTraditionalDoglegStep(step); - break; - - // Find the minimum in the subspace defined by the - // Cauchy point and the (Gauss-)Newton step. - case SUBSPACE_DOGLEG: - if (!ComputeSubspaceModel(jacobian)) { - summary.termination_type = LINEAR_SOLVER_FAILURE; - break; - } - ComputeSubspaceDoglegStep(step); - break; - } - } - - return summary; -} - -// The trust region is assumed to be elliptical with the -// diagonal scaling matrix D defined by sqrt(diagonal_). -// It is implemented by substituting step' = D * step. -// The trust region for step' is spherical. -// The gradient, the Gauss-Newton step, the Cauchy point, -// and all calculations involving the Jacobian have to -// be adjusted accordingly. -void DoglegStrategy::ComputeGradient( - SparseMatrix* jacobian, - const double* residuals) { - gradient_.setZero(); - jacobian->LeftMultiply(residuals, gradient_.data()); - gradient_.array() /= diagonal_.array(); -} - -// The Cauchy point is the global minimizer of the quadratic model -// along the one-dimensional subspace spanned by the gradient. -void DoglegStrategy::ComputeCauchyPoint(SparseMatrix* jacobian) { - // alpha * -gradient is the Cauchy point. - Vector Jg(jacobian->num_rows()); - Jg.setZero(); - // The Jacobian is scaled implicitly by computing J * (D^-1 * (D^-1 * g)) - // instead of (J * D^-1) * (D^-1 * g). - Vector scaled_gradient = - (gradient_.array() / diagonal_.array()).matrix(); - jacobian->RightMultiply(scaled_gradient.data(), Jg.data()); - alpha_ = gradient_.squaredNorm() / Jg.squaredNorm(); -} - -// The dogleg step is defined as the intersection of the trust region -// boundary with the piecewise linear path from the origin to the Cauchy -// point and then from there to the Gauss-Newton point (global minimizer -// of the model function). The Gauss-Newton point is taken if it lies -// within the trust region. -void DoglegStrategy::ComputeTraditionalDoglegStep(double* dogleg) { - VectorRef dogleg_step(dogleg, gradient_.rows()); - - // Case 1. The Gauss-Newton step lies inside the trust region, and - // is therefore the optimal solution to the trust-region problem. - const double gradient_norm = gradient_.norm(); - const double gauss_newton_norm = gauss_newton_step_.norm(); - if (gauss_newton_norm <= radius_) { - dogleg_step = gauss_newton_step_; - dogleg_step_norm_ = gauss_newton_norm; - dogleg_step.array() /= diagonal_.array(); - VLOG(3) << "GaussNewton step size: " << dogleg_step_norm_ - << " radius: " << radius_; - return; - } - - // Case 2. The Cauchy point and the Gauss-Newton steps lie outside - // the trust region. Rescale the Cauchy point to the trust region - // and return. - if (gradient_norm * alpha_ >= radius_) { - dogleg_step = -(radius_ / gradient_norm) * gradient_; - dogleg_step_norm_ = radius_; - dogleg_step.array() /= diagonal_.array(); - VLOG(3) << "Cauchy step size: " << dogleg_step_norm_ - << " radius: " << radius_; - return; - } - - // Case 3. The Cauchy point is inside the trust region and the - // Gauss-Newton step is outside. Compute the line joining the two - // points and the point on it which intersects the trust region - // boundary. - - // a = alpha * -gradient - // b = gauss_newton_step - const double b_dot_a = -alpha_ * gradient_.dot(gauss_newton_step_); - const double a_squared_norm = pow(alpha_ * gradient_norm, 2.0); - const double b_minus_a_squared_norm = - a_squared_norm - 2 * b_dot_a + pow(gauss_newton_norm, 2); - - // c = a' (b - a) - // = alpha * -gradient' gauss_newton_step - alpha^2 |gradient|^2 - const double c = b_dot_a - a_squared_norm; - const double d = sqrt(c * c + b_minus_a_squared_norm * - (pow(radius_, 2.0) - a_squared_norm)); - - double beta = - (c <= 0) - ? (d - c) / b_minus_a_squared_norm - : (radius_ * radius_ - a_squared_norm) / (d + c); - dogleg_step = (-alpha_ * (1.0 - beta)) * gradient_ - + beta * gauss_newton_step_; - dogleg_step_norm_ = dogleg_step.norm(); - dogleg_step.array() /= diagonal_.array(); - VLOG(3) << "Dogleg step size: " << dogleg_step_norm_ - << " radius: " << radius_; -} - -// The subspace method finds the minimum of the two-dimensional problem -// -// min. 1/2 x' B' H B x + g' B x -// s.t. || B x ||^2 <= r^2 -// -// where r is the trust region radius and B is the matrix with unit columns -// spanning the subspace defined by the steepest descent and Newton direction. -// This subspace by definition includes the Gauss-Newton point, which is -// therefore taken if it lies within the trust region. -void DoglegStrategy::ComputeSubspaceDoglegStep(double* dogleg) { - VectorRef dogleg_step(dogleg, gradient_.rows()); - - // The Gauss-Newton point is inside the trust region if |GN| <= radius_. - // This test is valid even though radius_ is a length in the two-dimensional - // subspace while gauss_newton_step_ is expressed in the (scaled) - // higher dimensional original space. This is because - // - // 1. gauss_newton_step_ by definition lies in the subspace, and - // 2. the subspace basis is orthonormal. - // - // As a consequence, the norm of the gauss_newton_step_ in the subspace is - // the same as its norm in the original space. - const double gauss_newton_norm = gauss_newton_step_.norm(); - if (gauss_newton_norm <= radius_) { - dogleg_step = gauss_newton_step_; - dogleg_step_norm_ = gauss_newton_norm; - dogleg_step.array() /= diagonal_.array(); - VLOG(3) << "GaussNewton step size: " << dogleg_step_norm_ - << " radius: " << radius_; - return; - } - - // The optimum lies on the boundary of the trust region. The above problem - // therefore becomes - // - // min. 1/2 x^T B^T H B x + g^T B x - // s.t. || B x ||^2 = r^2 - // - // Notice the equality in the constraint. - // - // This can be solved by forming the Lagrangian, solving for x(y), where - // y is the Lagrange multiplier, using the gradient of the objective, and - // putting x(y) back into the constraint. This results in a fourth order - // polynomial in y, which can be solved using e.g. the companion matrix. - // See the description of MakePolynomialForBoundaryConstrainedProblem for - // details. The result is up to four real roots y*, not all of which - // correspond to feasible points. The feasible points x(y*) have to be - // tested for optimality. - - if (subspace_is_one_dimensional_) { - // The subspace is one-dimensional, so both the gradient and - // the Gauss-Newton step point towards the same direction. - // In this case, we move along the gradient until we reach the trust - // region boundary. - dogleg_step = -(radius_ / gradient_.norm()) * gradient_; - dogleg_step_norm_ = radius_; - dogleg_step.array() /= diagonal_.array(); - VLOG(3) << "Dogleg subspace step size (1D): " << dogleg_step_norm_ - << " radius: " << radius_; - return; - } - - Vector2d minimum(0.0, 0.0); - if (!FindMinimumOnTrustRegionBoundary(&minimum)) { - // For the positive semi-definite case, a traditional dogleg step - // is taken in this case. - LOG(WARNING) << "Failed to compute polynomial roots. " - << "Taking traditional dogleg step instead."; - ComputeTraditionalDoglegStep(dogleg); - return; - } - - // Test first order optimality at the minimum. - // The first order KKT conditions state that the minimum x* - // has to satisfy either || x* ||^2 < r^2 (i.e. has to lie within - // the trust region), or - // - // (B x* + g) + y x* = 0 - // - // for some positive scalar y. - // Here, as it is already known that the minimum lies on the boundary, the - // latter condition is tested. To allow for small imprecisions, we test if - // the angle between (B x* + g) and -x* is smaller than acos(0.99). - // The exact value of the cosine is arbitrary but should be close to 1. - // - // This condition should not be violated. If it is, the minimum was not - // correctly determined. - const double kCosineThreshold = 0.99; - const Vector2d grad_minimum = subspace_B_ * minimum + subspace_g_; - const double cosine_angle = -minimum.dot(grad_minimum) / - (minimum.norm() * grad_minimum.norm()); - if (cosine_angle < kCosineThreshold) { - LOG(WARNING) << "First order optimality seems to be violated " - << "in the subspace method!\n" - << "Cosine of angle between x and B x + g is " - << cosine_angle << ".\n" - << "Taking a regular dogleg step instead.\n" - << "Please consider filing a bug report if this " - << "happens frequently or consistently.\n"; - ComputeTraditionalDoglegStep(dogleg); - return; - } - - // Create the full step from the optimal 2d solution. - dogleg_step = subspace_basis_ * minimum; - dogleg_step_norm_ = radius_; - dogleg_step.array() /= diagonal_.array(); - VLOG(3) << "Dogleg subspace step size: " << dogleg_step_norm_ - << " radius: " << radius_; -} - -// Build the polynomial that defines the optimal Lagrange multipliers. -// Let the Lagrangian be -// -// L(x, y) = 0.5 x^T B x + x^T g + y (0.5 x^T x - 0.5 r^2). (1) -// -// Stationary points of the Lagrangian are given by -// -// 0 = d L(x, y) / dx = Bx + g + y x (2) -// 0 = d L(x, y) / dy = 0.5 x^T x - 0.5 r^2 (3) -// -// For any given y, we can solve (2) for x as -// -// x(y) = -(B + y I)^-1 g . (4) -// -// As B + y I is 2x2, we form the inverse explicitly: -// -// (B + y I)^-1 = (1 / det(B + y I)) adj(B + y I) (5) -// -// where adj() denotes adjugation. This should be safe, as B is positive -// semi-definite and y is necessarily positive, so (B + y I) is indeed -// invertible. -// Plugging (5) into (4) and the result into (3), then dividing by 0.5 we -// obtain -// -// 0 = (1 / det(B + y I))^2 g^T adj(B + y I)^T adj(B + y I) g - r^2 -// (6) -// -// or -// -// det(B + y I)^2 r^2 = g^T adj(B + y I)^T adj(B + y I) g (7a) -// = g^T adj(B)^T adj(B) g -// + 2 y g^T adj(B)^T g + y^2 g^T g (7b) -// -// as -// -// adj(B + y I) = adj(B) + y I = adj(B)^T + y I . (8) -// -// The left hand side can be expressed explicitly using -// -// det(B + y I) = det(B) + y tr(B) + y^2 . (9) -// -// So (7) is a polynomial in y of degree four. -// Bringing everything back to the left hand side, the coefficients can -// be read off as -// -// y^4 r^2 -// + y^3 2 r^2 tr(B) -// + y^2 (r^2 tr(B)^2 + 2 r^2 det(B) - g^T g) -// + y^1 (2 r^2 det(B) tr(B) - 2 g^T adj(B)^T g) -// + y^0 (r^2 det(B)^2 - g^T adj(B)^T adj(B) g) -// -Vector DoglegStrategy::MakePolynomialForBoundaryConstrainedProblem() const { - const double detB = subspace_B_.determinant(); - const double trB = subspace_B_.trace(); - const double r2 = radius_ * radius_; - Matrix2d B_adj; - B_adj << subspace_B_(1, 1) , -subspace_B_(0, 1), - -subspace_B_(1, 0) , subspace_B_(0, 0); - - Vector polynomial(5); - polynomial(0) = r2; - polynomial(1) = 2.0 * r2 * trB; - polynomial(2) = r2 * (trB * trB + 2.0 * detB) - subspace_g_.squaredNorm(); - polynomial(3) = -2.0 * (subspace_g_.transpose() * B_adj * subspace_g_ - - r2 * detB * trB); - polynomial(4) = r2 * detB * detB - (B_adj * subspace_g_).squaredNorm(); - - return polynomial; -} - -// Given a Lagrange multiplier y that corresponds to a stationary point -// of the Lagrangian L(x, y), compute the corresponding x from the -// equation -// -// 0 = d L(x, y) / dx -// = B * x + g + y * x -// = (B + y * I) * x + g -// -DoglegStrategy::Vector2d DoglegStrategy::ComputeSubspaceStepFromRoot( - double y) const { - const Matrix2d B_i = subspace_B_ + y * Matrix2d::Identity(); - return -B_i.partialPivLu().solve(subspace_g_); -} - -// This function evaluates the quadratic model at a point x in the -// subspace spanned by subspace_basis_. -double DoglegStrategy::EvaluateSubspaceModel(const Vector2d& x) const { - return 0.5 * x.dot(subspace_B_ * x) + subspace_g_.dot(x); -} - -// This function attempts to solve the boundary-constrained subspace problem -// -// min. 1/2 x^T B^T H B x + g^T B x -// s.t. || B x ||^2 = r^2 -// -// where B is an orthonormal subspace basis and r is the trust-region radius. -// -// This is done by finding the roots of a fourth degree polynomial. If the -// root finding fails, the function returns false and minimum will be set -// to (0, 0). If it succeeds, true is returned. -// -// In the failure case, another step should be taken, such as the traditional -// dogleg step. -bool DoglegStrategy::FindMinimumOnTrustRegionBoundary(Vector2d* minimum) const { - CHECK_NOTNULL(minimum); - - // Return (0, 0) in all error cases. - minimum->setZero(); - - // Create the fourth-degree polynomial that is a necessary condition for - // optimality. - const Vector polynomial = MakePolynomialForBoundaryConstrainedProblem(); - - // Find the real parts y_i of its roots (not only the real roots). - Vector roots_real; - if (!FindPolynomialRoots(polynomial, &roots_real, NULL)) { - // Failed to find the roots of the polynomial, i.e. the candidate - // solutions of the constrained problem. Report this back to the caller. - return false; - } - - // For each root y, compute B x(y) and check for feasibility. - // Notice that there should always be four roots, as the leading term of - // the polynomial is r^2 and therefore non-zero. However, as some roots - // may be complex, the real parts are not necessarily unique. - double minimum_value = std::numeric_limits<double>::max(); - bool valid_root_found = false; - for (int i = 0; i < roots_real.size(); ++i) { - const Vector2d x_i = ComputeSubspaceStepFromRoot(roots_real(i)); - - // Not all roots correspond to points on the trust region boundary. - // There are at most four candidate solutions. As we are interested - // in the minimum, it is safe to consider all of them after projecting - // them onto the trust region boundary. - if (x_i.norm() > 0) { - const double f_i = EvaluateSubspaceModel((radius_ / x_i.norm()) * x_i); - valid_root_found = true; - if (f_i < minimum_value) { - minimum_value = f_i; - *minimum = x_i; - } - } - } - - return valid_root_found; -} - -LinearSolver::Summary DoglegStrategy::ComputeGaussNewtonStep( - const PerSolveOptions& per_solve_options, - SparseMatrix* jacobian, - const double* residuals) { - const int n = jacobian->num_cols(); - LinearSolver::Summary linear_solver_summary; - linear_solver_summary.termination_type = LINEAR_SOLVER_FAILURE; - - // The Jacobian matrix is often quite poorly conditioned. Thus it is - // necessary to add a diagonal matrix at the bottom to prevent the - // linear solver from failing. - // - // We do this by computing the same diagonal matrix as the one used - // by Levenberg-Marquardt (other choices are possible), and scaling - // it by a small constant (independent of the trust region radius). - // - // If the solve fails, the multiplier to the diagonal is increased - // up to max_mu_ by a factor of mu_increase_factor_ every time. If - // the linear solver is still not successful, the strategy returns - // with LINEAR_SOLVER_FAILURE. - // - // Next time when a new Gauss-Newton step is requested, the - // multiplier starts out from the last successful solve. - // - // When a step is declared successful, the multiplier is decreased - // by half of mu_increase_factor_. - - while (mu_ < max_mu_) { - // Dogleg, as far as I (sameeragarwal) understand it, requires a - // reasonably good estimate of the Gauss-Newton step. This means - // that we need to solve the normal equations more or less - // exactly. This is reflected in the values of the tolerances set - // below. - // - // For now, this strategy should only be used with exact - // factorization based solvers, for which these tolerances are - // automatically satisfied. - // - // The right way to combine inexact solves with trust region - // methods is to use Stiehaug's method. - LinearSolver::PerSolveOptions solve_options; - solve_options.q_tolerance = 0.0; - solve_options.r_tolerance = 0.0; - - lm_diagonal_ = diagonal_ * std::sqrt(mu_); - solve_options.D = lm_diagonal_.data(); - - // As in the LevenbergMarquardtStrategy, solve Jy = r instead - // of Jx = -r and later set x = -y to avoid having to modify - // either jacobian or residuals. - InvalidateArray(n, gauss_newton_step_.data()); - linear_solver_summary = linear_solver_->Solve(jacobian, - residuals, - solve_options, - gauss_newton_step_.data()); - - if (per_solve_options.dump_format_type == CONSOLE || - (per_solve_options.dump_format_type != CONSOLE && - !per_solve_options.dump_filename_base.empty())) { - if (!DumpLinearLeastSquaresProblem(per_solve_options.dump_filename_base, - per_solve_options.dump_format_type, - jacobian, - solve_options.D, - residuals, - gauss_newton_step_.data(), - 0)) { - LOG(ERROR) << "Unable to dump trust region problem." - << " Filename base: " - << per_solve_options.dump_filename_base; - } - } - - if (linear_solver_summary.termination_type == LINEAR_SOLVER_FATAL_ERROR) { - return linear_solver_summary; - } - - if (linear_solver_summary.termination_type == LINEAR_SOLVER_FAILURE || - !IsArrayValid(n, gauss_newton_step_.data())) { - mu_ *= mu_increase_factor_; - VLOG(2) << "Increasing mu " << mu_; - linear_solver_summary.termination_type = LINEAR_SOLVER_FAILURE; - continue; - } - break; - } - - if (linear_solver_summary.termination_type != LINEAR_SOLVER_FAILURE) { - // The scaled Gauss-Newton step is D * GN: - // - // - (D^-1 J^T J D^-1)^-1 (D^-1 g) - // = - D (J^T J)^-1 D D^-1 g - // = D -(J^T J)^-1 g - // - gauss_newton_step_.array() *= -diagonal_.array(); - } - - return linear_solver_summary; -} - -void DoglegStrategy::StepAccepted(double step_quality) { - CHECK_GT(step_quality, 0.0); - - if (step_quality < decrease_threshold_) { - radius_ *= 0.5; - } - - if (step_quality > increase_threshold_) { - radius_ = std::max(radius_, 3.0 * dogleg_step_norm_); - } - - // Reduce the regularization multiplier, in the hope that whatever - // was causing the rank deficiency has gone away and we can return - // to doing a pure Gauss-Newton solve. - mu_ = std::max(min_mu_, 2.0 * mu_ / mu_increase_factor_); - reuse_ = false; -} - -void DoglegStrategy::StepRejected(double step_quality) { - radius_ *= 0.5; - reuse_ = true; -} - -void DoglegStrategy::StepIsInvalid() { - mu_ *= mu_increase_factor_; - reuse_ = false; -} - -double DoglegStrategy::Radius() const { - return radius_; -} - -bool DoglegStrategy::ComputeSubspaceModel(SparseMatrix* jacobian) { - // Compute an orthogonal basis for the subspace using QR decomposition. - Matrix basis_vectors(jacobian->num_cols(), 2); - basis_vectors.col(0) = gradient_; - basis_vectors.col(1) = gauss_newton_step_; - Eigen::ColPivHouseholderQR<Matrix> basis_qr(basis_vectors); - - switch (basis_qr.rank()) { - case 0: - // This should never happen, as it implies that both the gradient - // and the Gauss-Newton step are zero. In this case, the minimizer should - // have stopped due to the gradient being too small. - LOG(ERROR) << "Rank of subspace basis is 0. " - << "This means that the gradient at the current iterate is " - << "zero but the optimization has not been terminated. " - << "You may have found a bug in Ceres."; - return false; - - case 1: - // Gradient and Gauss-Newton step coincide, so we lie on one of the - // major axes of the quadratic problem. In this case, we simply move - // along the gradient until we reach the trust region boundary. - subspace_is_one_dimensional_ = true; - return true; - - case 2: - subspace_is_one_dimensional_ = false; - break; - - default: - LOG(ERROR) << "Rank of the subspace basis matrix is reported to be " - << "greater than 2. As the matrix contains only two " - << "columns this cannot be true and is indicative of " - << "a bug."; - return false; - } - - // The subspace is two-dimensional, so compute the subspace model. - // Given the basis U, this is - // - // subspace_g_ = g_scaled^T U - // - // and - // - // subspace_B_ = U^T (J_scaled^T J_scaled) U - // - // As J_scaled = J * D^-1, the latter becomes - // - // subspace_B_ = ((U^T D^-1) J^T) (J (D^-1 U)) - // = (J (D^-1 U))^T (J (D^-1 U)) - - subspace_basis_ = - basis_qr.householderQ() * Matrix::Identity(jacobian->num_cols(), 2); - - subspace_g_ = subspace_basis_.transpose() * gradient_; - - Eigen::Matrix<double, 2, Eigen::Dynamic, Eigen::RowMajor> - Jb(2, jacobian->num_rows()); - Jb.setZero(); - - Vector tmp; - tmp = (subspace_basis_.col(0).array() / diagonal_.array()).matrix(); - jacobian->RightMultiply(tmp.data(), Jb.row(0).data()); - tmp = (subspace_basis_.col(1).array() / diagonal_.array()).matrix(); - jacobian->RightMultiply(tmp.data(), Jb.row(1).data()); - - subspace_B_ = Jb * Jb.transpose(); - - return true; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.h b/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.h deleted file mode 100644 index 046b9d824c9..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.h +++ /dev/null @@ -1,165 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_DOGLEG_STRATEGY_H_ -#define CERES_INTERNAL_DOGLEG_STRATEGY_H_ - -#include "ceres/linear_solver.h" -#include "ceres/trust_region_strategy.h" - -namespace ceres { -namespace internal { - -// Dogleg step computation and trust region sizing strategy based on -// on "Methods for Nonlinear Least Squares" by K. Madsen, H.B. Nielsen -// and O. Tingleff. Available to download from -// -// http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/3215/pdf/imm3215.pdf -// -// One minor modification is that instead of computing the pure -// Gauss-Newton step, we compute a regularized version of it. This is -// because the Jacobian is often rank-deficient and in such cases -// using a direct solver leads to numerical failure. -// -// If SUBSPACE is passed as the type argument to the constructor, the -// DoglegStrategy follows the approach by Shultz, Schnabel, Byrd. -// This finds the exact optimum over the two-dimensional subspace -// spanned by the two Dogleg vectors. -class DoglegStrategy : public TrustRegionStrategy { - public: - explicit DoglegStrategy(const TrustRegionStrategy::Options& options); - virtual ~DoglegStrategy() {} - - // TrustRegionStrategy interface - virtual Summary ComputeStep(const PerSolveOptions& per_solve_options, - SparseMatrix* jacobian, - const double* residuals, - double* step); - virtual void StepAccepted(double step_quality); - virtual void StepRejected(double step_quality); - virtual void StepIsInvalid(); - - virtual double Radius() const; - - // These functions are predominantly for testing. - Vector gradient() const { return gradient_; } - Vector gauss_newton_step() const { return gauss_newton_step_; } - Matrix subspace_basis() const { return subspace_basis_; } - Vector subspace_g() const { return subspace_g_; } - Matrix subspace_B() const { return subspace_B_; } - - private: - typedef Eigen::Matrix<double, 2, 1, Eigen::DontAlign> Vector2d; - typedef Eigen::Matrix<double, 2, 2, Eigen::DontAlign> Matrix2d; - - LinearSolver::Summary ComputeGaussNewtonStep( - const PerSolveOptions& per_solve_options, - SparseMatrix* jacobian, - const double* residuals); - void ComputeCauchyPoint(SparseMatrix* jacobian); - void ComputeGradient(SparseMatrix* jacobian, const double* residuals); - void ComputeTraditionalDoglegStep(double* step); - bool ComputeSubspaceModel(SparseMatrix* jacobian); - void ComputeSubspaceDoglegStep(double* step); - - bool FindMinimumOnTrustRegionBoundary(Vector2d* minimum) const; - Vector MakePolynomialForBoundaryConstrainedProblem() const; - Vector2d ComputeSubspaceStepFromRoot(double lambda) const; - double EvaluateSubspaceModel(const Vector2d& x) const; - - LinearSolver* linear_solver_; - double radius_; - const double max_radius_; - - const double min_diagonal_; - const double max_diagonal_; - - // mu is used to scale the diagonal matrix used to make the - // Gauss-Newton solve full rank. In each solve, the strategy starts - // out with mu = min_mu, and tries values upto max_mu. If the user - // reports an invalid step, the value of mu_ is increased so that - // the next solve starts with a stronger regularization. - // - // If a successful step is reported, then the value of mu_ is - // decreased with a lower bound of min_mu_. - double mu_; - const double min_mu_; - const double max_mu_; - const double mu_increase_factor_; - const double increase_threshold_; - const double decrease_threshold_; - - Vector diagonal_; // sqrt(diag(J^T J)) - Vector lm_diagonal_; - - Vector gradient_; - Vector gauss_newton_step_; - - // cauchy_step = alpha * gradient - double alpha_; - double dogleg_step_norm_; - - // When, ComputeStep is called, reuse_ indicates whether the - // Gauss-Newton and Cauchy steps from the last call to ComputeStep - // can be reused or not. - // - // If the user called StepAccepted, then it is expected that the - // user has recomputed the Jacobian matrix and new Gauss-Newton - // solve is needed and reuse is set to false. - // - // If the user called StepRejected, then it is expected that the - // user wants to solve the trust region problem with the same matrix - // but a different trust region radius and the Gauss-Newton and - // Cauchy steps can be reused to compute the Dogleg, thus reuse is - // set to true. - // - // If the user called StepIsInvalid, then there was a numerical - // problem with the step computed in the last call to ComputeStep, - // and the regularization used to do the Gauss-Newton solve is - // increased and a new solve should be done when ComputeStep is - // called again, thus reuse is set to false. - bool reuse_; - - // The dogleg type determines how the minimum of the local - // quadratic model is found. - DoglegType dogleg_type_; - - // If the type is SUBSPACE_DOGLEG, the two-dimensional - // model 1/2 x^T B x + g^T x has to be computed and stored. - bool subspace_is_one_dimensional_; - Matrix subspace_basis_; - Vector2d subspace_g_; - Matrix2d subspace_B_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_DOGLEG_STRATEGY_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_finalizer.h b/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_finalizer.h deleted file mode 100644 index a25a3083120..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_finalizer.h +++ /dev/null @@ -1,51 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: richie.stebbing@gmail.com (Richard Stebbing) - -#ifndef CERES_INTERNAL_DYNAMIC_COMPRESED_ROW_FINALIZER_H_ -#define CERES_INTERNAL_DYNAMIC_COMPRESED_ROW_FINALIZER_H_ - -#include "ceres/casts.h" -#include "ceres/dynamic_compressed_row_sparse_matrix.h" - -namespace ceres { -namespace internal { - -struct DynamicCompressedRowJacobianFinalizer { - void operator()(SparseMatrix* base_jacobian, int num_parameters) { - DynamicCompressedRowSparseMatrix* jacobian = - down_cast<DynamicCompressedRowSparseMatrix*>(base_jacobian); - jacobian->Finalize(num_parameters); - } -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_DYNAMIC_COMPRESED_ROW_FINALISER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_jacobian_writer.cc b/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_jacobian_writer.cc deleted file mode 100644 index fd5d89e350a..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_jacobian_writer.cc +++ /dev/null @@ -1,117 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: richie.stebbing@gmail.com (Richard Stebbing) - -#include "ceres/compressed_row_jacobian_writer.h" -#include "ceres/dynamic_compressed_row_jacobian_writer.h" -#include "ceres/casts.h" -#include "ceres/dynamic_compressed_row_sparse_matrix.h" -#include "ceres/parameter_block.h" -#include "ceres/program.h" -#include "ceres/residual_block.h" - -namespace ceres { -namespace internal { - -using std::pair; -using std::vector; - -ScratchEvaluatePreparer* -DynamicCompressedRowJacobianWriter::CreateEvaluatePreparers(int num_threads) { - return ScratchEvaluatePreparer::Create(*program_, num_threads); -} - -SparseMatrix* DynamicCompressedRowJacobianWriter::CreateJacobian() const { - // Initialize `jacobian` with zero number of `max_num_nonzeros`. - const int num_residuals = program_->NumResiduals(); - const int num_effective_parameters = program_->NumEffectiveParameters(); - - DynamicCompressedRowSparseMatrix* jacobian = - new DynamicCompressedRowSparseMatrix(num_residuals, - num_effective_parameters, - 0); - - vector<int>* row_blocks = jacobian->mutable_row_blocks(); - for (int i = 0; i < jacobian->num_rows(); ++i) { - row_blocks->push_back(1); - } - - vector<int>* col_blocks = jacobian->mutable_col_blocks(); - for (int i = 0; i < jacobian->num_cols(); ++i) { - col_blocks->push_back(1); - } - - return jacobian; -} - -void DynamicCompressedRowJacobianWriter::Write(int residual_id, - int residual_offset, - double **jacobians, - SparseMatrix* base_jacobian) { - DynamicCompressedRowSparseMatrix* jacobian = - down_cast<DynamicCompressedRowSparseMatrix*>(base_jacobian); - - // Get the `residual_block` of interest. - const ResidualBlock* residual_block = - program_->residual_blocks()[residual_id]; - const int num_residuals = residual_block->NumResiduals(); - - vector<pair<int, int> > evaluated_jacobian_blocks; - CompressedRowJacobianWriter::GetOrderedParameterBlocks( - program_, residual_id, &evaluated_jacobian_blocks); - - // `residual_offset` is the residual row in the global jacobian. - // Empty the jacobian rows. - jacobian->ClearRows(residual_offset, num_residuals); - - // Iterate over each parameter block. - for (int i = 0; i < evaluated_jacobian_blocks.size(); ++i) { - const ParameterBlock* parameter_block = - program_->parameter_blocks()[evaluated_jacobian_blocks[i].first]; - const int parameter_block_jacobian_index = - evaluated_jacobian_blocks[i].second; - const int parameter_block_size = parameter_block->LocalSize(); - - // For each parameter block only insert its non-zero entries. - for (int r = 0; r < num_residuals; ++r) { - for (int c = 0; c < parameter_block_size; ++c) { - const double& v = jacobians[parameter_block_jacobian_index][ - r * parameter_block_size + c]; - // Only insert non-zero entries. - if (v != 0.0) { - jacobian->InsertEntry( - residual_offset + r, parameter_block->delta_offset() + c, v); - } - } - } - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_jacobian_writer.h b/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_jacobian_writer.h deleted file mode 100644 index 6e5ac38f07e..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_jacobian_writer.h +++ /dev/null @@ -1,83 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: richie.stebbing@gmail.com (Richard Stebbing) -// -// A jacobian writer that directly writes to dynamic compressed row sparse -// matrices. - -#ifndef CERES_INTERNAL_DYNAMIC_COMPRESSED_ROW_JACOBIAN_WRITER_H_ -#define CERES_INTERNAL_DYNAMIC_COMPRESSED_ROW_JACOBIAN_WRITER_H_ - -#include "ceres/evaluator.h" -#include "ceres/scratch_evaluate_preparer.h" - -namespace ceres { -namespace internal { - -class Program; -class SparseMatrix; - -class DynamicCompressedRowJacobianWriter { - public: - DynamicCompressedRowJacobianWriter(Evaluator::Options /* ignored */, - Program* program) - : program_(program) { - } - - // JacobianWriter interface. - - // The compressed row matrix has different layout than that assumed by - // the cost functions. The scratch space is therefore used to store - // the jacobians (including zeros) temporarily before only the non-zero - // entries are copied over to the larger jacobian in `Write`. - ScratchEvaluatePreparer* CreateEvaluatePreparers(int num_threads); - - // Return a `DynamicCompressedRowSparseMatrix` which is filled by - // `Write`. Note that `Finalize` must be called to make the - // `CompressedRowSparseMatrix` interface valid. - SparseMatrix* CreateJacobian() const; - - // Write only the non-zero jacobian entries for a residual block - // (specified by `residual_id`) into `base_jacobian`, starting at the row - // specifed by `residual_offset`. - // - // This method is thread-safe over residual blocks (each `residual_id`). - void Write(int residual_id, - int residual_offset, - double **jacobians, - SparseMatrix* base_jacobian); - - private: - Program* program_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_DYNAMIC_COMPRESSED_ROW_JACOBIAN_WRITER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_sparse_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_sparse_matrix.cc deleted file mode 100644 index f020768ce10..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_sparse_matrix.cc +++ /dev/null @@ -1,107 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: richie.stebbing@gmail.com (Richard Stebbing) - -#include <cstring> -#include "ceres/dynamic_compressed_row_sparse_matrix.h" - -namespace ceres { -namespace internal { - -DynamicCompressedRowSparseMatrix::DynamicCompressedRowSparseMatrix( - int num_rows, - int num_cols, - int initial_max_num_nonzeros) - : CompressedRowSparseMatrix(num_rows, - num_cols, - initial_max_num_nonzeros) { - dynamic_cols_.resize(num_rows); - dynamic_values_.resize(num_rows); - } - -void DynamicCompressedRowSparseMatrix::InsertEntry(int row, - int col, - const double& value) { - CHECK_GE(row, 0); - CHECK_LT(row, num_rows()); - CHECK_GE(col, 0); - CHECK_LT(col, num_cols()); - dynamic_cols_[row].push_back(col); - dynamic_values_[row].push_back(value); -} - -void DynamicCompressedRowSparseMatrix::ClearRows(int row_start, - int num_rows) { - for (int r = 0; r < num_rows; ++r) { - const int i = row_start + r; - CHECK_GE(i, 0); - CHECK_LT(i, this->num_rows()); - dynamic_cols_[i].resize(0); - dynamic_values_[i].resize(0); - } -} - -void DynamicCompressedRowSparseMatrix::Finalize(int num_additional_elements) { - // `num_additional_elements` is provided as an argument so that additional - // storage can be reserved when it is known by the finalizer. - CHECK_GE(num_additional_elements, 0); - - // Count the number of non-zeros and resize `cols_` and `values_`. - int num_jacobian_nonzeros = 0; - for (int i = 0; i < dynamic_cols_.size(); ++i) { - num_jacobian_nonzeros += dynamic_cols_[i].size(); - } - - SetMaxNumNonZeros(num_jacobian_nonzeros + num_additional_elements); - - // Flatten `dynamic_cols_` into `cols_` and `dynamic_values_` - // into `values_`. - int index_into_values_and_cols = 0; - for (int i = 0; i < num_rows(); ++i) { - mutable_rows()[i] = index_into_values_and_cols; - const int num_nonzero_columns = dynamic_cols_[i].size(); - if (num_nonzero_columns > 0) { - memcpy(mutable_cols() + index_into_values_and_cols, - &dynamic_cols_[i][0], - dynamic_cols_[i].size() * sizeof(dynamic_cols_[0][0])); - memcpy(mutable_values() + index_into_values_and_cols, - &dynamic_values_[i][0], - dynamic_values_[i].size() * sizeof(dynamic_values_[0][0])); - index_into_values_and_cols += dynamic_cols_[i].size(); - } - } - mutable_rows()[num_rows()] = index_into_values_and_cols; - - CHECK_EQ(index_into_values_and_cols, num_jacobian_nonzeros) - << "Ceres bug: final index into values_ and cols_ should be equal to " - << "the number of jacobian nonzeros. Please contact the developers!"; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_sparse_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_sparse_matrix.h deleted file mode 100644 index cab860bddbd..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/dynamic_compressed_row_sparse_matrix.h +++ /dev/null @@ -1,101 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: richie.stebbing@gmail.com (Richard Stebbing) -// -// A compressed row sparse matrix that provides an extended interface to -// allow dynamic insertion of entries. This is provided for the use case -// where the sparsity structure and number of non-zero entries is dynamic. -// This flexibility is achieved by using an (internal) scratch space that -// allows independent insertion of entries into each row (thread-safe). -// Once insertion is complete, the `Finalize` method must be called to ensure -// that the underlying `CompressedRowSparseMatrix` is consistent. -// -// This should only be used if you really do need a dynamic sparsity pattern. - -#ifndef CERES_INTERNAL_DYNAMIC_COMPRESSED_ROW_SPARSE_MATRIX_H_ -#define CERES_INTERNAL_DYNAMIC_COMPRESSED_ROW_SPARSE_MATRIX_H_ - -#include <vector> - -#include "ceres/compressed_row_sparse_matrix.h" - -namespace ceres { -namespace internal { - -class DynamicCompressedRowSparseMatrix : public CompressedRowSparseMatrix { - public: - // Set the number of rows and columns for the underlyig - // `CompressedRowSparseMatrix` and set the initial number of maximum non-zero - // entries. Note that following the insertion of entries, when `Finalize` - // is called the number of non-zeros is determined and all internal - // structures are adjusted as required. If you know the upper limit on the - // number of non-zeros, then passing this value here can prevent future - // memory reallocations which may improve performance. Otherwise, if no - // upper limit is available a value of 0 is sufficient. - // - // Typical usage of this class is to define a new instance with a given - // number of rows, columns and maximum number of non-zero elements - // (if available). Next, entries are inserted at row and column positions - // using `InsertEntry`. Finally, once all elements have been inserted, - // `Finalize` must be called to make the underlying - // `CompressedRowSparseMatrix` consistent. - DynamicCompressedRowSparseMatrix(int num_rows, - int num_cols, - int initial_max_num_nonzeros); - - // Insert an entry at a given row and column position. This method is - // thread-safe across rows i.e. different threads can insert values - // simultaneously into different rows. It should be emphasised that this - // method always inserts a new entry and does not check for existing - // entries at the specified row and column position. Duplicate entries - // for a given row and column position will result in undefined - // behavior. - void InsertEntry(int row, int col, const double& value); - - // Clear all entries for rows, starting from row index `row_start` - // and proceeding for `num_rows`. - void ClearRows(int row_start, int num_rows); - - // Make the underlying internal `CompressedRowSparseMatrix` data structures - // consistent. Additional space for non-zero entries in the - // `CompressedRowSparseMatrix` can be reserved by specifying - // `num_additional_elements`. This is useful when it is known that rows will - // be appended to the `CompressedRowSparseMatrix` (e.g. appending a diagonal - // matrix to the jacobian) as it prevents need for future reallocation. - void Finalize(int num_additional_elements); - - private: - std::vector<std::vector<int> > dynamic_cols_; - std::vector<std::vector<double> > dynamic_values_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_DYNAMIC_COMPRESSED_ROW_SPARSE_MATRIX_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/evaluator.cc b/extern/libmv/third_party/ceres/internal/ceres/evaluator.cc deleted file mode 100644 index baba9afa11b..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/evaluator.cc +++ /dev/null @@ -1,86 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#include <vector> -#include "ceres/block_evaluate_preparer.h" -#include "ceres/block_jacobian_writer.h" -#include "ceres/compressed_row_jacobian_writer.h" -#include "ceres/compressed_row_sparse_matrix.h" -#include "ceres/crs_matrix.h" -#include "ceres/dense_jacobian_writer.h" -#include "ceres/dynamic_compressed_row_finalizer.h" -#include "ceres/dynamic_compressed_row_jacobian_writer.h" -#include "ceres/evaluator.h" -#include "ceres/internal/port.h" -#include "ceres/program_evaluator.h" -#include "ceres/scratch_evaluate_preparer.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -Evaluator::~Evaluator() {} - -Evaluator* Evaluator::Create(const Evaluator::Options& options, - Program* program, - std::string* error) { - switch (options.linear_solver_type) { - case DENSE_QR: - case DENSE_NORMAL_CHOLESKY: - return new ProgramEvaluator<ScratchEvaluatePreparer, - DenseJacobianWriter>(options, - program); - case DENSE_SCHUR: - case SPARSE_SCHUR: - case ITERATIVE_SCHUR: - case CGNR: - return new ProgramEvaluator<BlockEvaluatePreparer, - BlockJacobianWriter>(options, - program); - case SPARSE_NORMAL_CHOLESKY: - if (options.dynamic_sparsity) { - return new ProgramEvaluator<ScratchEvaluatePreparer, - DynamicCompressedRowJacobianWriter, - DynamicCompressedRowJacobianFinalizer>( - options, program); - } else { - return new ProgramEvaluator<ScratchEvaluatePreparer, - CompressedRowJacobianWriter>(options, - program); - } - - default: - *error = "Invalid Linear Solver Type. Unable to create evaluator."; - return NULL; - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/evaluator.h b/extern/libmv/third_party/ceres/internal/ceres/evaluator.h deleted file mode 100644 index fea307919d0..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/evaluator.h +++ /dev/null @@ -1,205 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// keir@google.com (Keir Mierle) - -#ifndef CERES_INTERNAL_EVALUATOR_H_ -#define CERES_INTERNAL_EVALUATOR_H_ - -#include <map> -#include <string> -#include <vector> - -#include "ceres/execution_summary.h" -#include "ceres/internal/port.h" -#include "ceres/types.h" - -namespace ceres { - -struct CRSMatrix; - -namespace internal { - -class Program; -class SparseMatrix; - -// The Evaluator interface offers a way to interact with a least squares cost -// function that is useful for an optimizer that wants to minimize the least -// squares objective. This insulates the optimizer from issues like Jacobian -// storage, parameterization, etc. -class Evaluator { - public: - virtual ~Evaluator(); - - struct Options { - Options() - : num_threads(1), - num_eliminate_blocks(-1), - linear_solver_type(DENSE_QR), - dynamic_sparsity(false) {} - - int num_threads; - int num_eliminate_blocks; - LinearSolverType linear_solver_type; - bool dynamic_sparsity; - }; - - static Evaluator* Create(const Options& options, - Program* program, - std::string* error); - - // This is used for computing the cost, residual and Jacobian for - // returning to the user. For actually solving the optimization - // problem, the optimization algorithm uses the ProgramEvaluator - // objects directly. - // - // The residual, gradients and jacobian pointers can be NULL, in - // which case they will not be evaluated. cost cannot be NULL. - // - // The parallelism of the evaluator is controlled by num_threads; it - // should be at least 1. - // - // Note: That this function does not take a parameter vector as - // input. The parameter blocks are evaluated on the values contained - // in the arrays pointed to by their user_state pointers. - // - // Also worth noting is that this function mutates program by - // calling Program::SetParameterOffsetsAndIndex() on it so that an - // evaluator object can be constructed. - static bool Evaluate(Program* program, - int num_threads, - double* cost, - std::vector<double>* residuals, - std::vector<double>* gradient, - CRSMatrix* jacobian); - - // Build and return a sparse matrix for storing and working with the Jacobian - // of the objective function. The jacobian has dimensions - // NumEffectiveParameters() by NumParameters(), and is typically extremely - // sparse. Since the sparsity pattern of the Jacobian remains constant over - // the lifetime of the optimization problem, this method is used to - // instantiate a SparseMatrix object with the appropriate sparsity structure - // (which can be an expensive operation) and then reused by the optimization - // algorithm and the various linear solvers. - // - // It is expected that the classes implementing this interface will be aware - // of their client's requirements for the kind of sparse matrix storage and - // layout that is needed for an efficient implementation. For example - // CompressedRowOptimizationProblem creates a compressed row representation of - // the jacobian for use with CHOLMOD, where as BlockOptimizationProblem - // creates a BlockSparseMatrix representation of the jacobian for use in the - // Schur complement based methods. - virtual SparseMatrix* CreateJacobian() const = 0; - - - // Options struct to control Evaluator::Evaluate; - struct EvaluateOptions { - EvaluateOptions() - : apply_loss_function(true) { - } - - // If false, the loss function correction is not applied to the - // residual blocks. - bool apply_loss_function; - }; - - // Evaluate the cost function for the given state. Returns the cost, - // residuals, and jacobian in the corresponding arguments. Both residuals and - // jacobian are optional; to avoid computing them, pass NULL. - // - // If non-NULL, the Jacobian must have a suitable sparsity pattern; only the - // values array of the jacobian is modified. - // - // state is an array of size NumParameters(), cost is a pointer to a single - // double, and residuals is an array of doubles of size NumResiduals(). - virtual bool Evaluate(const EvaluateOptions& evaluate_options, - const double* state, - double* cost, - double* residuals, - double* gradient, - SparseMatrix* jacobian) = 0; - - // Variant of Evaluator::Evaluate where the user wishes to use the - // default EvaluateOptions struct. This is mostly here as a - // convenience method. - bool Evaluate(const double* state, - double* cost, - double* residuals, - double* gradient, - SparseMatrix* jacobian) { - return Evaluate(EvaluateOptions(), - state, - cost, - residuals, - gradient, - jacobian); - } - - // Make a change delta (of size NumEffectiveParameters()) to state (of size - // NumParameters()) and store the result in state_plus_delta. - // - // In the case that there are no parameterizations used, this is equivalent to - // - // state_plus_delta[i] = state[i] + delta[i] ; - // - // however, the mapping is more complicated in the case of parameterizations - // like quaternions. This is the same as the "Plus()" operation in - // local_parameterization.h, but operating over the entire state vector for a - // problem. - virtual bool Plus(const double* state, - const double* delta, - double* state_plus_delta) const = 0; - - // The number of parameters in the optimization problem. - virtual int NumParameters() const = 0; - - // This is the effective number of parameters that the optimizer may adjust. - // This applies when there are parameterizations on some of the parameters. - virtual int NumEffectiveParameters() const = 0; - - // The number of residuals in the optimization problem. - virtual int NumResiduals() const = 0; - - // The following two methods return copies instead of references so - // that the base class implementation does not have to worry about - // life time issues. Further, these calls are not expected to be - // frequent or performance sensitive. - virtual std::map<std::string, int> CallStatistics() const { - return std::map<std::string, int>(); - } - - virtual std::map<std::string, double> TimeStatistics() const { - return std::map<std::string, double>(); - } -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_EVALUATOR_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/execution_summary.h b/extern/libmv/third_party/ceres/internal/ceres/execution_summary.h deleted file mode 100644 index aa9929d8974..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/execution_summary.h +++ /dev/null @@ -1,90 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_EXECUTION_SUMMARY_H_ -#define CERES_INTERNAL_EXECUTION_SUMMARY_H_ - -#include <map> -#include <string> - -#include "ceres/internal/port.h" -#include "ceres/wall_time.h" -#include "ceres/mutex.h" - -namespace ceres { -namespace internal { - -// Struct used by various objects to report statistics and other -// information about their execution. e.g., ExecutionSummary::times -// can be used for reporting times associated with various activities. -class ExecutionSummary { - public: - void IncrementTimeBy(const std::string& name, const double value) { - CeresMutexLock l(×_mutex_); - times_[name] += value; - } - - void IncrementCall(const std::string& name) { - CeresMutexLock l(&calls_mutex_); - calls_[name] += 1; - } - - const std::map<std::string, double>& times() const { return times_; } - const std::map<std::string, int>& calls() const { return calls_; } - - private: - Mutex times_mutex_; - std::map<std::string, double> times_; - - Mutex calls_mutex_; - std::map<std::string, int> calls_; -}; - -class ScopedExecutionTimer { - public: - ScopedExecutionTimer(const std::string& name, ExecutionSummary* summary) - : start_time_(WallTimeInSeconds()), - name_(name), - summary_(summary) {} - - ~ScopedExecutionTimer() { - summary_->IncrementTimeBy(name_, WallTimeInSeconds() - start_time_); - } - - private: - const double start_time_; - const std::string name_; - ExecutionSummary* summary_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_EXECUTION_SUMMARY_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/file.cc b/extern/libmv/third_party/ceres/internal/ceres/file.cc deleted file mode 100644 index c95a44d2c38..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/file.cc +++ /dev/null @@ -1,95 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// Really simple file IO. - -#include "ceres/file.h" - -#include <cstdio> -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::string; - -void WriteStringToFileOrDie(const string &data, const string &filename) { - FILE* file_descriptor = fopen(filename.c_str(), "wb"); - if (!file_descriptor) { - LOG(FATAL) << "Couldn't write to file: " << filename; - } - fwrite(data.c_str(), 1, data.size(), file_descriptor); - fclose(file_descriptor); -} - -void ReadFileToStringOrDie(const string &filename, string *data) { - FILE* file_descriptor = fopen(filename.c_str(), "r"); - - if (!file_descriptor) { - LOG(FATAL) << "Couldn't read file: " << filename; - } - - // Resize the input buffer appropriately. - fseek(file_descriptor, 0L, SEEK_END); - int num_bytes = ftell(file_descriptor); - data->resize(num_bytes); - - // Read the data. - fseek(file_descriptor, 0L, SEEK_SET); - int num_read = fread(&((*data)[0]), - sizeof((*data)[0]), - num_bytes, - file_descriptor); - if (num_read != num_bytes) { - LOG(FATAL) << "Couldn't read all of " << filename - << "expected bytes: " << num_bytes * sizeof((*data)[0]) - << "actual bytes: " << num_read; - } - fclose(file_descriptor); -} - -string JoinPath(const string& dirname, const string& basename) { -#ifdef _WIN32 - static const char separator = '\\'; -#else - static const char separator = '/'; -#endif // _WIN32 - - if ((!basename.empty() && basename[0] == separator) || dirname.empty()) { - return basename; - } else if (dirname[dirname.size() - 1] == separator) { - return dirname + basename; - } else { - return dirname + string(&separator, 1) + basename; - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/file.h b/extern/libmv/third_party/ceres/internal/ceres/file.h deleted file mode 100644 index 219b459b919..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/file.h +++ /dev/null @@ -1,53 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// Simple file IO support. This is a portability shim. - -#ifndef CERES_INTERNAL_FILE_H_ -#define CERES_INTERNAL_FILE_H_ - -#include <string> -#include "ceres/internal/port.h" - -namespace ceres { -namespace internal { - -void WriteStringToFileOrDie(const std::string &data, - const std::string &filename); -void ReadFileToStringOrDie(const std::string &filename, std::string *data); - -// Join two path components, adding a slash if necessary. If basename is an -// absolute path then JoinPath ignores dirname and simply returns basename. -std::string JoinPath(const std::string& dirname, const std::string& basename); - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_FILE_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/generate_eliminator_specialization.py b/extern/libmv/third_party/ceres/internal/ceres/generate_eliminator_specialization.py deleted file mode 100644 index e89e7a48c98..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generate_eliminator_specialization.py +++ /dev/null @@ -1,231 +0,0 @@ -# Ceres Solver - A fast non-linear least squares minimizer -# Copyright 2015 Google Inc. All rights reserved. -# http://ceres-solver.org/ -# -# Redistribution and use in source and binary forms, with or without -# modification, are permitted provided that the following conditions are met: -# -# * Redistributions of source code must retain the above copyright notice, -# this list of conditions and the following disclaimer. -# * Redistributions in binary form must reproduce the above copyright notice, -# this list of conditions and the following disclaimer in the documentation -# and/or other materials provided with the distribution. -# * Neither the name of Google Inc. nor the names of its contributors may be -# used to endorse or promote products derived from this software without -# specific prior written permission. -# -# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -# POSSIBILITY OF SUCH DAMAGE. -# -# Author: sameeragarwal@google.com (Sameer Agarwal) -# -# Script for explicitly generating template specialization of the -# SchurEliminator class. It is a rather large class -# and the number of explicit instantiations is also large. Explicitly -# generating these instantiations in separate .cc files breaks the -# compilation into separate compilation unit rather than one large cc -# file which takes 2+GB of RAM to compile. -# -# This script creates two sets of files. -# -# 1. schur_eliminator_x_x_x.cc -# where, the x indicates the template parameters and -# -# 2. schur_eliminator.cc -# -# that contains a factory function for instantiating these classes -# based on runtime parameters. -# -# The list of tuples, specializations indicates the set of -# specializations that is generated. - -# Set of template specializations to generate -SPECIALIZATIONS = [(2, 2, 2), - (2, 2, 3), - (2, 2, 4), - (2, 2, "Eigen::Dynamic"), - (2, 3, 3), - (2, 3, 4), - (2, 3, 6), - (2, 3, 9), - (2, 3, "Eigen::Dynamic"), - (2, 4, 3), - (2, 4, 4), - (2, 4, 8), - (2, 4, 9), - (2, 4, "Eigen::Dynamic"), - (2, "Eigen::Dynamic", "Eigen::Dynamic"), - (4, 4, 2), - (4, 4, 3), - (4, 4, 4), - (4, 4, "Eigen::Dynamic"), - ("Eigen::Dynamic", "Eigen::Dynamic", "Eigen::Dynamic")] -HEADER = """// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. -""" - -DYNAMIC_FILE = """ - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<%s, %s, %s>; - -} // namespace internal -} // namespace ceres -""" - -SPECIALIZATION_FILE = """ -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<%s, %s, %s>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION -""" - -FACTORY_FILE_HEADER = """ -#include "ceres/linear_solver.h" -#include "ceres/schur_eliminator.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -SchurEliminatorBase* -SchurEliminatorBase::Create(const LinearSolver::Options& options) { -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION -""" - -FACTORY_CONDITIONAL = """ if ((options.row_block_size == %s) && - (options.e_block_size == %s) && - (options.f_block_size == %s)) { - return new SchurEliminator<%s, %s, %s>(options); - } -""" - -FACTORY_FOOTER = """ -#endif - VLOG(1) << "Template specializations not found for <" - << options.row_block_size << "," - << options.e_block_size << "," - << options.f_block_size << ">"; - return new SchurEliminator<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic>(options); -} - -} // namespace internal -} // namespace ceres -""" - - -def SuffixForSize(size): - if size == "Eigen::Dynamic": - return "d" - return str(size) - - -def SpecializationFilename(prefix, row_block_size, e_block_size, f_block_size): - return "_".join([prefix] + map(SuffixForSize, (row_block_size, - e_block_size, - f_block_size))) - - -def Specialize(): - """ - Generate specialization code and the conditionals to instantiate it. - """ - f = open("schur_eliminator.cc", "w") - f.write(HEADER) - f.write(FACTORY_FILE_HEADER) - - for row_block_size, e_block_size, f_block_size in SPECIALIZATIONS: - output = SpecializationFilename("generated/schur_eliminator", - row_block_size, - e_block_size, - f_block_size) + ".cc" - fptr = open(output, "w") - fptr.write(HEADER) - - template = SPECIALIZATION_FILE - if (row_block_size == "Eigen::Dynamic" and - e_block_size == "Eigen::Dynamic" and - f_block_size == "Eigen::Dynamic"): - template = DYNAMIC_FILE - - fptr.write(template % (row_block_size, e_block_size, f_block_size)) - fptr.close() - - f.write(FACTORY_CONDITIONAL % (row_block_size, - e_block_size, - f_block_size, - row_block_size, - e_block_size, - f_block_size)) - f.write(FACTORY_FOOTER) - f.close() - - -if __name__ == "__main__": - Specialize() diff --git a/extern/libmv/third_party/ceres/internal/ceres/generate_partitioned_matrix_view_specializations.py b/extern/libmv/third_party/ceres/internal/ceres/generate_partitioned_matrix_view_specializations.py deleted file mode 100644 index c4ac3cf2332..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generate_partitioned_matrix_view_specializations.py +++ /dev/null @@ -1,232 +0,0 @@ -# Ceres Solver - A fast non-linear least squares minimizer -# Copyright 2015 Google Inc. All rights reserved. -# http://ceres-solver.org/ -# -# Redistribution and use in source and binary forms, with or without -# modification, are permitted provided that the following conditions are met: -# -# * Redistributions of source code must retain the above copyright notice, -# this list of conditions and the following disclaimer. -# * Redistributions in binary form must reproduce the above copyright notice, -# this list of conditions and the following disclaimer in the documentation -# and/or other materials provided with the distribution. -# * Neither the name of Google Inc. nor the names of its contributors may be -# used to endorse or promote products derived from this software without -# specific prior written permission. -# -# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -# POSSIBILITY OF SUCH DAMAGE. -# -# Author: sameeragarwal@google.com (Sameer Agarwal) -# -# Script for explicitly generating template specialization of the -# PartitionedMatrixView class. Explicitly generating these -# instantiations in separate .cc files breaks the compilation into -# separate compilation unit rather than one large cc file. -# -# This script creates two sets of files. -# -# 1. partitioned_matrix_view_x_x_x.cc -# where the x indicates the template parameters and -# -# 2. partitioned_matrix_view.cc -# -# that contains a factory function for instantiating these classes -# based on runtime parameters. -# -# The list of tuples, specializations indicates the set of -# specializations that is generated. - -# Set of template specializations to generate -SPECIALIZATIONS = [(2, 2, 2), - (2, 2, 3), - (2, 2, 4), - (2, 2, "Eigen::Dynamic"), - (2, 3, 3), - (2, 3, 4), - (2, 3, 6), - (2, 3, 9), - (2, 3, "Eigen::Dynamic"), - (2, 4, 3), - (2, 4, 4), - (2, 4, 8), - (2, 4, 9), - (2, 4, "Eigen::Dynamic"), - (2, "Eigen::Dynamic", "Eigen::Dynamic"), - (4, 4, 2), - (4, 4, 3), - (4, 4, 4), - (4, 4, "Eigen::Dynamic"), - ("Eigen::Dynamic", "Eigen::Dynamic", "Eigen::Dynamic")] -HEADER = """// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. -""" - -DYNAMIC_FILE = """ - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<%s, %s, %s>; - -} // namespace internal -} // namespace ceres -""" - -SPECIALIZATION_FILE = """ -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<%s, %s, %s>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION -""" - -FACTORY_FILE_HEADER = """ -#include "ceres/linear_solver.h" -#include "ceres/partitioned_matrix_view.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -PartitionedMatrixViewBase* -PartitionedMatrixViewBase::Create(const LinearSolver::Options& options, - const BlockSparseMatrix& matrix) { -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION -""" - -FACTORY_CONDITIONAL = """ if ((options.row_block_size == %s) && - (options.e_block_size == %s) && - (options.f_block_size == %s)) { - return new PartitionedMatrixView<%s, %s, %s>( - matrix, options.elimination_groups[0]); - } -""" - -FACTORY_FOOTER = """ -#endif - VLOG(1) << "Template specializations not found for <" - << options.row_block_size << "," - << options.e_block_size << "," - << options.f_block_size << ">"; - return new PartitionedMatrixView<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic>( - matrix, options.elimination_groups[0]); -}; - -} // namespace internal -} // namespace ceres -""" - - -def SuffixForSize(size): - if size == "Eigen::Dynamic": - return "d" - return str(size) - - -def SpecializationFilename(prefix, row_block_size, e_block_size, f_block_size): - return "_".join([prefix] + map(SuffixForSize, (row_block_size, - e_block_size, - f_block_size))) - - -def Specialize(): - """ - Generate specialization code and the conditionals to instantiate it. - """ - f = open("partitioned_matrix_view.cc", "w") - f.write(HEADER) - f.write(FACTORY_FILE_HEADER) - - for row_block_size, e_block_size, f_block_size in SPECIALIZATIONS: - output = SpecializationFilename("generated/partitioned_matrix_view", - row_block_size, - e_block_size, - f_block_size) + ".cc" - fptr = open(output, "w") - fptr.write(HEADER) - - template = SPECIALIZATION_FILE - if (row_block_size == "Eigen::Dynamic" and - e_block_size == "Eigen::Dynamic" and - f_block_size == "Eigen::Dynamic"): - template = DYNAMIC_FILE - - fptr.write(template % (row_block_size, e_block_size, f_block_size)) - fptr.close() - - f.write(FACTORY_CONDITIONAL % (row_block_size, - e_block_size, - f_block_size, - row_block_size, - e_block_size, - f_block_size)) - f.write(FACTORY_FOOTER) - f.close() - - -if __name__ == "__main__": - Specialize() diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_2_2.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_2_2.cc deleted file mode 100644 index 500115b9897..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_2_2.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 2, 2>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_2_3.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_2_3.cc deleted file mode 100644 index 1384cb619e3..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_2_3.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 2, 3>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_2_4.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_2_4.cc deleted file mode 100644 index 030035ec97b..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_2_4.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 2, 4>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_2_d.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_2_d.cc deleted file mode 100644 index c9501b50170..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_2_d.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 2, Eigen::Dynamic>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_3.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_3.cc deleted file mode 100644 index c2639bff69e..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_3.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 3, 3>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_4.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_4.cc deleted file mode 100644 index 693e43959c1..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_4.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 3, 4>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_6.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_6.cc deleted file mode 100644 index 7b9368ffefd..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_6.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 3, 6>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_9.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_9.cc deleted file mode 100644 index e72c5f6937a..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_9.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 3, 9>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_d.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_d.cc deleted file mode 100644 index c1f410eb64c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_3_d.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 3, Eigen::Dynamic>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_3.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_3.cc deleted file mode 100644 index 7292c333d5d..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_3.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 4, 3>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_4.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_4.cc deleted file mode 100644 index 891d65a8646..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_4.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 4, 4>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_8.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_8.cc deleted file mode 100644 index 395f6bd4c13..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_8.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 4, 8>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_9.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_9.cc deleted file mode 100644 index 88952b10e34..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_9.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 4, 9>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_d.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_d.cc deleted file mode 100644 index 7733e1993eb..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_4_d.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, 4, Eigen::Dynamic>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_d_d.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_d_d.cc deleted file mode 100644 index 117a0cdb8c1..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_2_d_d.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<2, Eigen::Dynamic, Eigen::Dynamic>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_4_4_2.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_4_4_2.cc deleted file mode 100644 index a620bb70dba..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_4_4_2.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<4, 4, 2>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_4_4_3.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_4_4_3.cc deleted file mode 100644 index 2978630832c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_4_4_3.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<4, 4, 3>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_4_4_4.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_4_4_4.cc deleted file mode 100644 index bcd03b02e3a..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_4_4_4.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<4, 4, 4>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_4_4_d.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_4_4_d.cc deleted file mode 100644 index 6b541ecf0d9..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_4_4_d.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<4, 4, Eigen::Dynamic>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_d_d_d.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_d_d_d.cc deleted file mode 100644 index 85111e722c4..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/partitioned_matrix_view_d_d_d.cc +++ /dev/null @@ -1,53 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - - -#include "ceres/partitioned_matrix_view_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class PartitionedMatrixView<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic>; - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_2_2.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_2_2.cc deleted file mode 100644 index ac07a3f229e..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_2_2.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 2, 2>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_2_3.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_2_3.cc deleted file mode 100644 index 0ec09553f9e..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_2_3.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 2, 3>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_2_4.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_2_4.cc deleted file mode 100644 index 74a42cc4a16..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_2_4.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 2, 4>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_2_d.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_2_d.cc deleted file mode 100644 index 5ce757fda5d..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_2_d.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 2, Eigen::Dynamic>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_3.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_3.cc deleted file mode 100644 index 2e7ae28b4ea..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_3.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 3, 3>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_4.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_4.cc deleted file mode 100644 index 443207070cf..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_4.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 3, 4>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_6.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_6.cc deleted file mode 100644 index ac2f358b383..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_6.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 3, 6>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_9.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_9.cc deleted file mode 100644 index 930ab440fa5..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_9.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 3, 9>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_d.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_d.cc deleted file mode 100644 index 486c53d36f4..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_3_d.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 3, Eigen::Dynamic>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_3.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_3.cc deleted file mode 100644 index 6f247a7b832..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_3.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 4, 3>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_4.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_4.cc deleted file mode 100644 index c44cd045263..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_4.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 4, 4>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_8.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_8.cc deleted file mode 100644 index c9a0d5fc729..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_8.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 4, 8>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_9.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_9.cc deleted file mode 100644 index b0455b0bca0..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_9.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 4, 9>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_d.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_d.cc deleted file mode 100644 index 3234380f23c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_4_d.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, 4, Eigen::Dynamic>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_d_d.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_d_d.cc deleted file mode 100644 index 311f8556932..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_2_d_d.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<2, Eigen::Dynamic, Eigen::Dynamic>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_4_4_2.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_4_4_2.cc deleted file mode 100644 index bc40bd55296..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_4_4_2.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<4, 4, 2>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_4_4_3.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_4_4_3.cc deleted file mode 100644 index cca88c802b0..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_4_4_3.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<4, 4, 3>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_4_4_4.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_4_4_4.cc deleted file mode 100644 index 33c94a907b9..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_4_4_4.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<4, 4, 4>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_4_4_d.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_4_4_d.cc deleted file mode 100644 index 1a1866f93a8..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_4_4_d.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<4, 4, Eigen::Dynamic>; - -} // namespace internal -} // namespace ceres - -#endif // CERES_RESTRICT_SCHUR_SPECIALIZATION diff --git a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_d_d_d.cc b/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_d_d_d.cc deleted file mode 100644 index 6b18ef8c863..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/generated/schur_eliminator_d_d_d.cc +++ /dev/null @@ -1,53 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - - -#include "ceres/schur_eliminator_impl.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -template class SchurEliminator<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic>; - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/gradient_checking_cost_function.cc b/extern/libmv/third_party/ceres/internal/ceres/gradient_checking_cost_function.cc deleted file mode 100644 index 580fd260e15..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/gradient_checking_cost_function.cc +++ /dev/null @@ -1,337 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#include "ceres/gradient_checking_cost_function.h" - -#include <algorithm> -#include <cmath> -#include <numeric> -#include <string> -#include <vector> - -#include "ceres/cost_function.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/parameter_block.h" -#include "ceres/problem.h" -#include "ceres/problem_impl.h" -#include "ceres/program.h" -#include "ceres/residual_block.h" -#include "ceres/dynamic_numeric_diff_cost_function.h" -#include "ceres/stringprintf.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::abs; -using std::max; -using std::string; -using std::vector; - -namespace { - -// True if x and y have an absolute relative difference less than -// relative_precision and false otherwise. Stores the relative and absolute -// difference in relative/absolute_error if non-NULL. -bool IsClose(double x, double y, double relative_precision, - double *relative_error, - double *absolute_error) { - double local_absolute_error; - double local_relative_error; - if (!absolute_error) { - absolute_error = &local_absolute_error; - } - if (!relative_error) { - relative_error = &local_relative_error; - } - *absolute_error = abs(x - y); - *relative_error = *absolute_error / max(abs(x), abs(y)); - if (x == 0 || y == 0) { - // If x or y is exactly zero, then relative difference doesn't have any - // meaning. Take the absolute difference instead. - *relative_error = *absolute_error; - } - return abs(*relative_error) < abs(relative_precision); -} - -class GradientCheckingCostFunction : public CostFunction { - public: - GradientCheckingCostFunction(const CostFunction* function, - const NumericDiffOptions& options, - double relative_precision, - const string& extra_info) - : function_(function), - relative_precision_(relative_precision), - extra_info_(extra_info) { - DynamicNumericDiffCostFunction<CostFunction, CENTRAL>* - finite_diff_cost_function = - new DynamicNumericDiffCostFunction<CostFunction, CENTRAL>( - function, - DO_NOT_TAKE_OWNERSHIP, - options); - - const vector<int32>& parameter_block_sizes = - function->parameter_block_sizes(); - for (int i = 0; i < parameter_block_sizes.size(); ++i) { - finite_diff_cost_function->AddParameterBlock(parameter_block_sizes[i]); - } - *mutable_parameter_block_sizes() = parameter_block_sizes; - set_num_residuals(function->num_residuals()); - finite_diff_cost_function->SetNumResiduals(num_residuals()); - finite_diff_cost_function_.reset(finite_diff_cost_function); - } - - virtual ~GradientCheckingCostFunction() { } - - virtual bool Evaluate(double const* const* parameters, - double* residuals, - double** jacobians) const { - if (!jacobians) { - // Nothing to check in this case; just forward. - return function_->Evaluate(parameters, residuals, NULL); - } - - int num_residuals = function_->num_residuals(); - - // Make space for the jacobians of the two methods. - const vector<int32>& block_sizes = function_->parameter_block_sizes(); - vector<Matrix> term_jacobians(block_sizes.size()); - vector<Matrix> finite_difference_jacobians(block_sizes.size()); - vector<double*> term_jacobian_pointers(block_sizes.size()); - vector<double*> finite_difference_jacobian_pointers(block_sizes.size()); - for (int i = 0; i < block_sizes.size(); i++) { - term_jacobians[i].resize(num_residuals, block_sizes[i]); - term_jacobian_pointers[i] = term_jacobians[i].data(); - finite_difference_jacobians[i].resize(num_residuals, block_sizes[i]); - finite_difference_jacobian_pointers[i] = - finite_difference_jacobians[i].data(); - } - - // Evaluate the derivative using the user supplied code. - if (!function_->Evaluate(parameters, - residuals, - &term_jacobian_pointers[0])) { - LOG(WARNING) << "Function evaluation failed."; - return false; - } - - // Evaluate the derivative using numeric derivatives. - finite_diff_cost_function_->Evaluate( - parameters, - residuals, - &finite_difference_jacobian_pointers[0]); - - // See if any elements have relative error larger than the threshold. - int num_bad_jacobian_components = 0; - double worst_relative_error = 0; - - // Accumulate the error message for all the jacobians, since it won't get - // output if there are no bad jacobian components. - string m; - for (int k = 0; k < block_sizes.size(); k++) { - // Copy the original jacobian blocks into the jacobians array. - if (jacobians[k] != NULL) { - MatrixRef(jacobians[k], - term_jacobians[k].rows(), - term_jacobians[k].cols()) = term_jacobians[k]; - } - - StringAppendF(&m, - "========== " - "Jacobian for " "block %d: (%ld by %ld)) " - "==========\n", - k, - static_cast<long>(term_jacobians[k].rows()), - static_cast<long>(term_jacobians[k].cols())); - // The funny spacing creates appropriately aligned column headers. - m += " block row col user dx/dy num diff dx/dy " - "abs error relative error parameter residual\n"; - - for (int i = 0; i < term_jacobians[k].rows(); i++) { - for (int j = 0; j < term_jacobians[k].cols(); j++) { - double term_jacobian = term_jacobians[k](i, j); - double finite_jacobian = finite_difference_jacobians[k](i, j); - double relative_error, absolute_error; - bool bad_jacobian_entry = - !IsClose(term_jacobian, - finite_jacobian, - relative_precision_, - &relative_error, - &absolute_error); - worst_relative_error = max(worst_relative_error, relative_error); - - StringAppendF(&m, "%6d %4d %4d %17g %17g %17g %17g %17g %17g", - k, i, j, - term_jacobian, finite_jacobian, - absolute_error, relative_error, - parameters[k][j], - residuals[i]); - - if (bad_jacobian_entry) { - num_bad_jacobian_components++; - StringAppendF( - &m, " ------ (%d,%d,%d) Relative error worse than %g", - k, i, j, relative_precision_); - } - m += "\n"; - } - } - } - - // Since there were some bad errors, dump comprehensive debug info. - if (num_bad_jacobian_components) { - string header = StringPrintf("Detected %d bad jacobian component(s). " - "Worst relative error was %g.\n", - num_bad_jacobian_components, - worst_relative_error); - if (!extra_info_.empty()) { - header += "Extra info for this residual: " + extra_info_ + "\n"; - } - LOG(WARNING) << "\n" << header << m; - } - return true; - } - - private: - const CostFunction* function_; - internal::scoped_ptr<CostFunction> finite_diff_cost_function_; - double relative_precision_; - string extra_info_; -}; - -} // namespace - -CostFunction *CreateGradientCheckingCostFunction( - const CostFunction *cost_function, - double relative_step_size, - double relative_precision, - const string& extra_info) { - NumericDiffOptions numeric_diff_options; - numeric_diff_options.relative_step_size = relative_step_size; - - return new GradientCheckingCostFunction(cost_function, - numeric_diff_options, - relative_precision, - extra_info); -} - -ProblemImpl* CreateGradientCheckingProblemImpl(ProblemImpl* problem_impl, - double relative_step_size, - double relative_precision) { - // We create new CostFunctions by wrapping the original CostFunction - // in a gradient checking CostFunction. So its okay for the - // ProblemImpl to take ownership of it and destroy it. The - // LossFunctions and LocalParameterizations are reused and since - // they are owned by problem_impl, gradient_checking_problem_impl - // should not take ownership of it. - Problem::Options gradient_checking_problem_options; - gradient_checking_problem_options.cost_function_ownership = TAKE_OWNERSHIP; - gradient_checking_problem_options.loss_function_ownership = - DO_NOT_TAKE_OWNERSHIP; - gradient_checking_problem_options.local_parameterization_ownership = - DO_NOT_TAKE_OWNERSHIP; - - ProblemImpl* gradient_checking_problem_impl = new ProblemImpl( - gradient_checking_problem_options); - - Program* program = problem_impl->mutable_program(); - - // For every ParameterBlock in problem_impl, create a new parameter - // block with the same local parameterization and constancy. - const vector<ParameterBlock*>& parameter_blocks = program->parameter_blocks(); - for (int i = 0; i < parameter_blocks.size(); ++i) { - ParameterBlock* parameter_block = parameter_blocks[i]; - gradient_checking_problem_impl->AddParameterBlock( - parameter_block->mutable_user_state(), - parameter_block->Size(), - parameter_block->mutable_local_parameterization()); - - if (parameter_block->IsConstant()) { - gradient_checking_problem_impl->SetParameterBlockConstant( - parameter_block->mutable_user_state()); - } - } - - // For every ResidualBlock in problem_impl, create a new - // ResidualBlock by wrapping its CostFunction inside a - // GradientCheckingCostFunction. - const vector<ResidualBlock*>& residual_blocks = program->residual_blocks(); - for (int i = 0; i < residual_blocks.size(); ++i) { - ResidualBlock* residual_block = residual_blocks[i]; - - // Build a human readable string which identifies the - // ResidualBlock. This is used by the GradientCheckingCostFunction - // when logging debugging information. - string extra_info = StringPrintf( - "Residual block id %d; depends on parameters [", i); - vector<double*> parameter_blocks; - for (int j = 0; j < residual_block->NumParameterBlocks(); ++j) { - ParameterBlock* parameter_block = residual_block->parameter_blocks()[j]; - parameter_blocks.push_back(parameter_block->mutable_user_state()); - StringAppendF(&extra_info, "%p", parameter_block->mutable_user_state()); - extra_info += (j < residual_block->NumParameterBlocks() - 1) ? ", " : "]"; - } - - // Wrap the original CostFunction in a GradientCheckingCostFunction. - CostFunction* gradient_checking_cost_function = - CreateGradientCheckingCostFunction(residual_block->cost_function(), - relative_step_size, - relative_precision, - extra_info); - - // The const_cast is necessary because - // ProblemImpl::AddResidualBlock can potentially take ownership of - // the LossFunction, but in this case we are guaranteed that this - // will not be the case, so this const_cast is harmless. - gradient_checking_problem_impl->AddResidualBlock( - gradient_checking_cost_function, - const_cast<LossFunction*>(residual_block->loss_function()), - parameter_blocks); - } - - // Normally, when a problem is given to the solver, we guarantee - // that the state pointers for each parameter block point to the - // user provided data. Since we are creating this new problem from a - // problem given to us at an arbitrary stage of the solve, we cannot - // depend on this being the case, so we explicitly call - // SetParameterBlockStatePtrsToUserStatePtrs to ensure that this is - // the case. - gradient_checking_problem_impl - ->mutable_program() - ->SetParameterBlockStatePtrsToUserStatePtrs(); - - return gradient_checking_problem_impl; -} - - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/gradient_checking_cost_function.h b/extern/libmv/third_party/ceres/internal/ceres/gradient_checking_cost_function.h deleted file mode 100644 index cf92cb72bc5..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/gradient_checking_cost_function.h +++ /dev/null @@ -1,85 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#ifndef CERES_INTERNAL_GRADIENT_CHECKING_COST_FUNCTION_H_ -#define CERES_INTERNAL_GRADIENT_CHECKING_COST_FUNCTION_H_ - -#include <string> - -#include "ceres/cost_function.h" - -namespace ceres { -namespace internal { - -class ProblemImpl; - -// Creates a CostFunction that checks the jacobians that cost_function computes -// with finite differences. Bad results are logged; required precision is -// controlled by relative_precision and the numeric differentiation step size is -// controlled with relative_step_size. See solver.h for a better explanation of -// relative_step_size. Caller owns result. -// -// The condition enforced is that -// -// (J_actual(i, j) - J_numeric(i, j)) -// ------------------------------------ < relative_precision -// max(J_actual(i, j), J_numeric(i, j)) -// -// where J_actual(i, j) is the jacobian as computed by the supplied cost -// function (by the user) and J_numeric is the jacobian as computed by finite -// differences. -// -// Note: This is quite inefficient and is intended only for debugging. -CostFunction* CreateGradientCheckingCostFunction( - const CostFunction* cost_function, - double relative_step_size, - double relative_precision, - const std::string& extra_info); - -// Create a new ProblemImpl object from the input problem_impl, where -// each CostFunctions in problem_impl are wrapped inside a -// GradientCheckingCostFunctions. This gives us a ProblemImpl object -// which checks its derivatives against estimates from numeric -// differentiation everytime a ResidualBlock is evaluated. -// -// relative_step_size and relative_precision are parameters to control -// the numeric differentiation and the relative tolerance between the -// jacobian computed by the CostFunctions in problem_impl and -// jacobians obtained by numerically differentiating them. For more -// details see the documentation for -// CreateGradientCheckingCostFunction above. -ProblemImpl* CreateGradientCheckingProblemImpl(ProblemImpl* problem_impl, - double relative_step_size, - double relative_precision); - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_GRADIENT_CHECKING_COST_FUNCTION_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/gradient_problem.cc b/extern/libmv/third_party/ceres/internal/ceres/gradient_problem.cc deleted file mode 100644 index 4ebd3e60610..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/gradient_problem.cc +++ /dev/null @@ -1,81 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/gradient_problem.h" -#include "ceres/local_parameterization.h" -#include "glog/logging.h" - -namespace ceres { - -GradientProblem::GradientProblem(FirstOrderFunction* function) - : function_(function), - parameterization_( - new IdentityParameterization(function_->NumParameters())), - scratch_(new double[function_->NumParameters()]) { -} - -GradientProblem::GradientProblem(FirstOrderFunction* function, - LocalParameterization* parameterization) - : function_(function), - parameterization_(parameterization), - scratch_(new double[function_->NumParameters()]) { - CHECK_EQ(function_->NumParameters(), parameterization_->GlobalSize()); -} - -int GradientProblem::NumParameters() const { - return function_->NumParameters(); -} - -int GradientProblem::NumLocalParameters() const { - return parameterization_->LocalSize(); -} - - -bool GradientProblem::Evaluate(const double* parameters, - double* cost, - double* gradient) const { - if (gradient == NULL) { - return function_->Evaluate(parameters, cost, NULL); - } - - return (function_->Evaluate(parameters, cost, scratch_.get()) && - parameterization_->MultiplyByJacobian(parameters, - 1, - scratch_.get(), - gradient)); -} - -bool GradientProblem::Plus(const double* x, - const double* delta, - double* x_plus_delta) const { - return parameterization_->Plus(x, delta, x_plus_delta); -} - -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/gradient_problem_evaluator.h b/extern/libmv/third_party/ceres/internal/ceres/gradient_problem_evaluator.h deleted file mode 100644 index 2c562544768..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/gradient_problem_evaluator.h +++ /dev/null @@ -1,98 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_GRADIENT_PROBLEM_EVALUATOR_H_ -#define CERES_INTERNAL_GRADIENT_PROBLEM_EVALUATOR_H_ - -#include <map> -#include <string> - -#include "ceres/evaluator.h" -#include "ceres/execution_summary.h" -#include "ceres/gradient_problem.h" -#include "ceres/internal/port.h" -#include "ceres/wall_time.h" - -namespace ceres { -namespace internal { - -class GradientProblemEvaluator : public Evaluator { - public: - explicit GradientProblemEvaluator(const GradientProblem& problem) - : problem_(problem) {} - virtual ~GradientProblemEvaluator() {} - virtual SparseMatrix* CreateJacobian() const { return NULL; } - virtual bool Evaluate(const EvaluateOptions& evaluate_options, - const double* state, - double* cost, - double* residuals, - double* gradient, - SparseMatrix* jacobian) { - CHECK(jacobian == NULL); - ScopedExecutionTimer total_timer("Evaluator::Total", &execution_summary_); - ScopedExecutionTimer call_type_timer( - gradient == NULL ? "Evaluator::Cost" : "Evaluator::Gradient", - &execution_summary_); - return problem_.Evaluate(state, cost, gradient); - } - - virtual bool Plus(const double* state, - const double* delta, - double* state_plus_delta) const { - return problem_.Plus(state, delta, state_plus_delta); - } - - virtual int NumParameters() const { - return problem_.NumParameters(); - } - - virtual int NumEffectiveParameters() const { - return problem_.NumLocalParameters(); - } - - virtual int NumResiduals() const { return 1; } - - virtual std::map<std::string, int> CallStatistics() const { - return execution_summary_.calls(); - } - - virtual std::map<std::string, double> TimeStatistics() const { - return execution_summary_.times(); - } - - private: - const GradientProblem& problem_; - ::ceres::internal::ExecutionSummary execution_summary_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_GRADIENT_PROBLEM_EVALUATOR_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/gradient_problem_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/gradient_problem_solver.cc deleted file mode 100644 index 9a549c23dac..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/gradient_problem_solver.cc +++ /dev/null @@ -1,277 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/gradient_problem_solver.h" - -#include "ceres/callbacks.h" -#include "ceres/gradient_problem.h" -#include "ceres/gradient_problem_evaluator.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/port.h" -#include "ceres/map_util.h" -#include "ceres/minimizer.h" -#include "ceres/solver.h" -#include "ceres/solver_utils.h" -#include "ceres/stringprintf.h" -#include "ceres/types.h" -#include "ceres/wall_time.h" - -namespace ceres { -using internal::StringPrintf; -using internal::StringAppendF; -using std::string; - -namespace { - -Solver::Options GradientProblemSolverOptionsToSolverOptions( - const GradientProblemSolver::Options& options) { -#define COPY_OPTION(x) solver_options.x = options.x - - Solver::Options solver_options; - solver_options.minimizer_type = LINE_SEARCH; - COPY_OPTION(line_search_direction_type); - COPY_OPTION(line_search_type); - COPY_OPTION(nonlinear_conjugate_gradient_type); - COPY_OPTION(max_lbfgs_rank); - COPY_OPTION(use_approximate_eigenvalue_bfgs_scaling); - COPY_OPTION(line_search_interpolation_type); - COPY_OPTION(min_line_search_step_size); - COPY_OPTION(line_search_sufficient_function_decrease); - COPY_OPTION(max_line_search_step_contraction); - COPY_OPTION(min_line_search_step_contraction); - COPY_OPTION(max_num_line_search_step_size_iterations); - COPY_OPTION(max_num_line_search_direction_restarts); - COPY_OPTION(line_search_sufficient_curvature_decrease); - COPY_OPTION(max_line_search_step_expansion); - COPY_OPTION(max_num_iterations); - COPY_OPTION(max_solver_time_in_seconds); - COPY_OPTION(function_tolerance); - COPY_OPTION(gradient_tolerance); - COPY_OPTION(logging_type); - COPY_OPTION(minimizer_progress_to_stdout); - COPY_OPTION(callbacks); - return solver_options; -#undef COPY_OPTION -} - - -} // namespace - -GradientProblemSolver::~GradientProblemSolver() { -} - -void GradientProblemSolver::Solve(const GradientProblemSolver::Options& options, - const GradientProblem& problem, - double* parameters_ptr, - GradientProblemSolver::Summary* summary) { - using internal::scoped_ptr; - using internal::WallTimeInSeconds; - using internal::Minimizer; - using internal::GradientProblemEvaluator; - using internal::LoggingCallback; - using internal::SetSummaryFinalCost; - - double start_time = WallTimeInSeconds(); - Solver::Options solver_options = - GradientProblemSolverOptionsToSolverOptions(options); - - *CHECK_NOTNULL(summary) = Summary(); - summary->num_parameters = problem.NumParameters(); - summary->num_local_parameters = problem.NumLocalParameters(); - summary->line_search_direction_type = options.line_search_direction_type; // NOLINT - summary->line_search_interpolation_type = options.line_search_interpolation_type; // NOLINT - summary->line_search_type = options.line_search_type; - summary->max_lbfgs_rank = options.max_lbfgs_rank; - summary->nonlinear_conjugate_gradient_type = options.nonlinear_conjugate_gradient_type; // NOLINT - - // Check validity - if (!solver_options.IsValid(&summary->message)) { - LOG(ERROR) << "Terminating: " << summary->message; - return; - } - - // Assuming that the parameter blocks in the program have been - Minimizer::Options minimizer_options; - minimizer_options = Minimizer::Options(solver_options); - minimizer_options.evaluator.reset(new GradientProblemEvaluator(problem)); - - scoped_ptr<IterationCallback> logging_callback; - if (options.logging_type != SILENT) { - logging_callback.reset( - new LoggingCallback(LINE_SEARCH, options.minimizer_progress_to_stdout)); - minimizer_options.callbacks.insert(minimizer_options.callbacks.begin(), - logging_callback.get()); - } - - scoped_ptr<Minimizer> minimizer(Minimizer::Create(LINE_SEARCH)); - Vector solution(problem.NumParameters()); - VectorRef parameters(parameters_ptr, problem.NumParameters()); - solution = parameters; - - Solver::Summary solver_summary; - solver_summary.fixed_cost = 0.0; - solver_summary.preprocessor_time_in_seconds = 0.0; - solver_summary.postprocessor_time_in_seconds = 0.0; - solver_summary.line_search_polynomial_minimization_time_in_seconds = 0.0; - - minimizer->Minimize(minimizer_options, solution.data(), &solver_summary); - - summary->termination_type = solver_summary.termination_type; - summary->message = solver_summary.message; - summary->initial_cost = solver_summary.initial_cost; - summary->final_cost = solver_summary.final_cost; - summary->iterations = solver_summary.iterations; - summary->line_search_polynomial_minimization_time_in_seconds = - solver_summary.line_search_polynomial_minimization_time_in_seconds; - - if (summary->IsSolutionUsable()) { - parameters = solution; - SetSummaryFinalCost(summary); - } - - const std::map<string, double>& evaluator_time_statistics = - minimizer_options.evaluator->TimeStatistics(); - summary->cost_evaluation_time_in_seconds = - FindWithDefault(evaluator_time_statistics, "Evaluator::Residual", 0.0); - summary->gradient_evaluation_time_in_seconds = - FindWithDefault(evaluator_time_statistics, "Evaluator::Jacobian", 0.0); - - summary->total_time_in_seconds = WallTimeInSeconds() - start_time; -} - -// Invalid values for most fields, to ensure that we are not -// accidentally reporting default values. -GradientProblemSolver::Summary::Summary() - : termination_type(FAILURE), - message("ceres::GradientProblemSolve was not called."), - initial_cost(-1.0), - final_cost(-1.0), - total_time_in_seconds(-1.0), - cost_evaluation_time_in_seconds(-1.0), - gradient_evaluation_time_in_seconds(-1.0), - line_search_polynomial_minimization_time_in_seconds(-1.0), - num_parameters(-1), - num_local_parameters(-1), - line_search_direction_type(LBFGS), - line_search_type(ARMIJO), - line_search_interpolation_type(BISECTION), - nonlinear_conjugate_gradient_type(FLETCHER_REEVES), - max_lbfgs_rank(-1) { -} - -bool GradientProblemSolver::Summary::IsSolutionUsable() const { - return internal::IsSolutionUsable(*this); -} - -string GradientProblemSolver::Summary::BriefReport() const { - return StringPrintf("Ceres GradientProblemSolver Report: " - "Iterations: %d, " - "Initial cost: %e, " - "Final cost: %e, " - "Termination: %s", - static_cast<int>(iterations.size()), - initial_cost, - final_cost, - TerminationTypeToString(termination_type)); -} - -string GradientProblemSolver::Summary::FullReport() const { - using internal::VersionString; - - string report = string("\nSolver Summary (v " + VersionString() + ")\n\n"); - - StringAppendF(&report, "Parameters % 25d\n", num_parameters); - if (num_local_parameters != num_parameters) { - StringAppendF(&report, "Local parameters % 25d\n", - num_local_parameters); - } - - string line_search_direction_string; - if (line_search_direction_type == LBFGS) { - line_search_direction_string = StringPrintf("LBFGS (%d)", max_lbfgs_rank); - } else if (line_search_direction_type == NONLINEAR_CONJUGATE_GRADIENT) { - line_search_direction_string = - NonlinearConjugateGradientTypeToString( - nonlinear_conjugate_gradient_type); - } else { - line_search_direction_string = - LineSearchDirectionTypeToString(line_search_direction_type); - } - - StringAppendF(&report, "Line search direction %19s\n", - line_search_direction_string.c_str()); - - const string line_search_type_string = - StringPrintf("%s %s", - LineSearchInterpolationTypeToString( - line_search_interpolation_type), - LineSearchTypeToString(line_search_type)); - StringAppendF(&report, "Line search type %19s\n", - line_search_type_string.c_str()); - StringAppendF(&report, "\n"); - - StringAppendF(&report, "\nCost:\n"); - StringAppendF(&report, "Initial % 30e\n", initial_cost); - if (termination_type != FAILURE && - termination_type != USER_FAILURE) { - StringAppendF(&report, "Final % 30e\n", final_cost); - StringAppendF(&report, "Change % 30e\n", - initial_cost - final_cost); - } - - StringAppendF(&report, "\nMinimizer iterations % 16d\n", - static_cast<int>(iterations.size())); - - StringAppendF(&report, "\nTime (in seconds):\n"); - - StringAppendF(&report, "\n Cost evaluation %23.4f\n", - cost_evaluation_time_in_seconds); - StringAppendF(&report, " Gradient evaluation %23.4f\n", - gradient_evaluation_time_in_seconds); - StringAppendF(&report, " Polynomial minimization %17.4f\n", - line_search_polynomial_minimization_time_in_seconds); - - StringAppendF(&report, "Total %25.4f\n\n", - total_time_in_seconds); - - StringAppendF(&report, "Termination: %25s (%s)\n", - TerminationTypeToString(termination_type), message.c_str()); - return report; -} - -void Solve(const GradientProblemSolver::Options& options, - const GradientProblem& problem, - double* parameters, - GradientProblemSolver::Summary* summary) { - GradientProblemSolver solver; - solver.Solve(options, problem, parameters, summary); -} - -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/graph.h b/extern/libmv/third_party/ceres/internal/ceres/graph.h deleted file mode 100644 index b96b67265cb..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/graph.h +++ /dev/null @@ -1,225 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_GRAPH_H_ -#define CERES_INTERNAL_GRAPH_H_ - -#include <limits> -#include <utility> -#include "ceres/integral_types.h" -#include "ceres/map_util.h" -#include "ceres/collections_port.h" -#include "ceres/internal/macros.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -// A unweighted undirected graph templated over the vertex ids. Vertex -// should be hashable. -template <typename Vertex> -class Graph { - public: - Graph() {} - - // Add a vertex. - void AddVertex(const Vertex& vertex) { - if (vertices_.insert(vertex).second) { - edges_[vertex] = HashSet<Vertex>(); - } - } - - bool RemoveVertex(const Vertex& vertex) { - if (vertices_.find(vertex) == vertices_.end()) { - return false; - } - - vertices_.erase(vertex); - const HashSet<Vertex>& sinks = edges_[vertex]; - for (typename HashSet<Vertex>::const_iterator it = sinks.begin(); - it != sinks.end(); ++it) { - edges_[*it].erase(vertex); - } - - edges_.erase(vertex); - return true; - } - - // Add an edge between the vertex1 and vertex2. Calling AddEdge on a - // pair of vertices which do not exist in the graph yet will result - // in undefined behavior. - // - // It is legal to call this method repeatedly for the same set of - // vertices. - void AddEdge(const Vertex& vertex1, const Vertex& vertex2) { - DCHECK(vertices_.find(vertex1) != vertices_.end()); - DCHECK(vertices_.find(vertex2) != vertices_.end()); - - if (edges_[vertex1].insert(vertex2).second) { - edges_[vertex2].insert(vertex1); - } - } - - // Calling Neighbors on a vertex not in the graph will result in - // undefined behaviour. - const HashSet<Vertex>& Neighbors(const Vertex& vertex) const { - return FindOrDie(edges_, vertex); - } - - const HashSet<Vertex>& vertices() const { - return vertices_; - } - - private: - HashSet<Vertex> vertices_; - HashMap<Vertex, HashSet<Vertex> > edges_; - - CERES_DISALLOW_COPY_AND_ASSIGN(Graph); -}; - -// A weighted undirected graph templated over the vertex ids. Vertex -// should be hashable and comparable. -template <typename Vertex> -class WeightedGraph { - public: - WeightedGraph() {} - - // Add a weighted vertex. If the vertex already exists in the graph, - // its weight is set to the new weight. - void AddVertex(const Vertex& vertex, double weight) { - if (vertices_.find(vertex) == vertices_.end()) { - vertices_.insert(vertex); - edges_[vertex] = HashSet<Vertex>(); - } - vertex_weights_[vertex] = weight; - } - - // Uses weight = 1.0. If vertex already exists, its weight is set to - // 1.0. - void AddVertex(const Vertex& vertex) { - AddVertex(vertex, 1.0); - } - - bool RemoveVertex(const Vertex& vertex) { - if (vertices_.find(vertex) == vertices_.end()) { - return false; - } - - vertices_.erase(vertex); - vertex_weights_.erase(vertex); - const HashSet<Vertex>& sinks = edges_[vertex]; - for (typename HashSet<Vertex>::const_iterator it = sinks.begin(); - it != sinks.end(); ++it) { - if (vertex < *it) { - edge_weights_.erase(std::make_pair(vertex, *it)); - } else { - edge_weights_.erase(std::make_pair(*it, vertex)); - } - edges_[*it].erase(vertex); - } - - edges_.erase(vertex); - return true; - } - - // Add a weighted edge between the vertex1 and vertex2. Calling - // AddEdge on a pair of vertices which do not exist in the graph yet - // will result in undefined behavior. - // - // It is legal to call this method repeatedly for the same set of - // vertices. - void AddEdge(const Vertex& vertex1, const Vertex& vertex2, double weight) { - DCHECK(vertices_.find(vertex1) != vertices_.end()); - DCHECK(vertices_.find(vertex2) != vertices_.end()); - - if (edges_[vertex1].insert(vertex2).second) { - edges_[vertex2].insert(vertex1); - } - - if (vertex1 < vertex2) { - edge_weights_[std::make_pair(vertex1, vertex2)] = weight; - } else { - edge_weights_[std::make_pair(vertex2, vertex1)] = weight; - } - } - - // Uses weight = 1.0. - void AddEdge(const Vertex& vertex1, const Vertex& vertex2) { - AddEdge(vertex1, vertex2, 1.0); - } - - // Calling VertexWeight on a vertex not in the graph will result in - // undefined behavior. - double VertexWeight(const Vertex& vertex) const { - return FindOrDie(vertex_weights_, vertex); - } - - // Calling EdgeWeight on a pair of vertices where either one of the - // vertices is not present in the graph will result in undefined - // behaviour. If there is no edge connecting vertex1 and vertex2, - // the edge weight is zero. - double EdgeWeight(const Vertex& vertex1, const Vertex& vertex2) const { - if (vertex1 < vertex2) { - return FindWithDefault(edge_weights_, - std::make_pair(vertex1, vertex2), 0.0); - } else { - return FindWithDefault(edge_weights_, - std::make_pair(vertex2, vertex1), 0.0); - } - } - - // Calling Neighbors on a vertex not in the graph will result in - // undefined behaviour. - const HashSet<Vertex>& Neighbors(const Vertex& vertex) const { - return FindOrDie(edges_, vertex); - } - - const HashSet<Vertex>& vertices() const { - return vertices_; - } - - static double InvalidWeight() { - return std::numeric_limits<double>::quiet_NaN(); - } - - private: - HashSet<Vertex> vertices_; - HashMap<Vertex, double> vertex_weights_; - HashMap<Vertex, HashSet<Vertex> > edges_; - HashMap<std::pair<Vertex, Vertex>, double> edge_weights_; - - CERES_DISALLOW_COPY_AND_ASSIGN(WeightedGraph); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_GRAPH_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/graph_algorithms.h b/extern/libmv/third_party/ceres/internal/ceres/graph_algorithms.h deleted file mode 100644 index d1d3f52cd22..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/graph_algorithms.h +++ /dev/null @@ -1,364 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Various algorithms that operate on undirected graphs. - -#ifndef CERES_INTERNAL_GRAPH_ALGORITHMS_H_ -#define CERES_INTERNAL_GRAPH_ALGORITHMS_H_ - -#include <algorithm> -#include <vector> -#include <utility> -#include "ceres/collections_port.h" -#include "ceres/graph.h" -#include "ceres/wall_time.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -// Compare two vertices of a graph by their degrees, if the degrees -// are equal then order them by their ids. -template <typename Vertex> -class VertexTotalOrdering { - public: - explicit VertexTotalOrdering(const Graph<Vertex>& graph) - : graph_(graph) {} - - bool operator()(const Vertex& lhs, const Vertex& rhs) const { - if (graph_.Neighbors(lhs).size() == graph_.Neighbors(rhs).size()) { - return lhs < rhs; - } - return graph_.Neighbors(lhs).size() < graph_.Neighbors(rhs).size(); - } - - private: - const Graph<Vertex>& graph_; -}; - -template <typename Vertex> -class VertexDegreeLessThan { - public: - explicit VertexDegreeLessThan(const Graph<Vertex>& graph) - : graph_(graph) {} - - bool operator()(const Vertex& lhs, const Vertex& rhs) const { - return graph_.Neighbors(lhs).size() < graph_.Neighbors(rhs).size(); - } - - private: - const Graph<Vertex>& graph_; -}; - -// Order the vertices of a graph using its (approximately) largest -// independent set, where an independent set of a graph is a set of -// vertices that have no edges connecting them. The maximum -// independent set problem is NP-Hard, but there are effective -// approximation algorithms available. The implementation here uses a -// breadth first search that explores the vertices in order of -// increasing degree. The same idea is used by Saad & Li in "MIQR: A -// multilevel incomplete QR preconditioner for large sparse -// least-squares problems", SIMAX, 2007. -// -// Given a undirected graph G(V,E), the algorithm is a greedy BFS -// search where the vertices are explored in increasing order of their -// degree. The output vector ordering contains elements of S in -// increasing order of their degree, followed by elements of V - S in -// increasing order of degree. The return value of the function is the -// cardinality of S. -template <typename Vertex> -int IndependentSetOrdering(const Graph<Vertex>& graph, - std::vector<Vertex>* ordering) { - const HashSet<Vertex>& vertices = graph.vertices(); - const int num_vertices = vertices.size(); - - CHECK_NOTNULL(ordering); - ordering->clear(); - ordering->reserve(num_vertices); - - // Colors for labeling the graph during the BFS. - const char kWhite = 0; - const char kGrey = 1; - const char kBlack = 2; - - // Mark all vertices white. - HashMap<Vertex, char> vertex_color; - std::vector<Vertex> vertex_queue; - for (typename HashSet<Vertex>::const_iterator it = vertices.begin(); - it != vertices.end(); - ++it) { - vertex_color[*it] = kWhite; - vertex_queue.push_back(*it); - } - - - std::sort(vertex_queue.begin(), vertex_queue.end(), - VertexTotalOrdering<Vertex>(graph)); - - // Iterate over vertex_queue. Pick the first white vertex, add it - // to the independent set. Mark it black and its neighbors grey. - for (int i = 0; i < vertex_queue.size(); ++i) { - const Vertex& vertex = vertex_queue[i]; - if (vertex_color[vertex] != kWhite) { - continue; - } - - ordering->push_back(vertex); - vertex_color[vertex] = kBlack; - const HashSet<Vertex>& neighbors = graph.Neighbors(vertex); - for (typename HashSet<Vertex>::const_iterator it = neighbors.begin(); - it != neighbors.end(); - ++it) { - vertex_color[*it] = kGrey; - } - } - - int independent_set_size = ordering->size(); - - // Iterate over the vertices and add all the grey vertices to the - // ordering. At this stage there should only be black or grey - // vertices in the graph. - for (typename std::vector<Vertex>::const_iterator it = vertex_queue.begin(); - it != vertex_queue.end(); - ++it) { - const Vertex vertex = *it; - DCHECK(vertex_color[vertex] != kWhite); - if (vertex_color[vertex] != kBlack) { - ordering->push_back(vertex); - } - } - - CHECK_EQ(ordering->size(), num_vertices); - return independent_set_size; -} - -// Same as above with one important difference. The ordering parameter -// is an input/output parameter which carries an initial ordering of -// the vertices of the graph. The greedy independent set algorithm -// starts by sorting the vertices in increasing order of their -// degree. The input ordering is used to stabilize this sort, i.e., if -// two vertices have the same degree then they are ordered in the same -// order in which they occur in "ordering". -// -// This is useful in eliminating non-determinism from the Schur -// ordering algorithm over all. -template <typename Vertex> -int StableIndependentSetOrdering(const Graph<Vertex>& graph, - std::vector<Vertex>* ordering) { - CHECK_NOTNULL(ordering); - const HashSet<Vertex>& vertices = graph.vertices(); - const int num_vertices = vertices.size(); - CHECK_EQ(vertices.size(), ordering->size()); - - // Colors for labeling the graph during the BFS. - const char kWhite = 0; - const char kGrey = 1; - const char kBlack = 2; - - std::vector<Vertex> vertex_queue(*ordering); - - std::stable_sort(vertex_queue.begin(), vertex_queue.end(), - VertexDegreeLessThan<Vertex>(graph)); - - // Mark all vertices white. - HashMap<Vertex, char> vertex_color; - for (typename HashSet<Vertex>::const_iterator it = vertices.begin(); - it != vertices.end(); - ++it) { - vertex_color[*it] = kWhite; - } - - ordering->clear(); - ordering->reserve(num_vertices); - // Iterate over vertex_queue. Pick the first white vertex, add it - // to the independent set. Mark it black and its neighbors grey. - for (int i = 0; i < vertex_queue.size(); ++i) { - const Vertex& vertex = vertex_queue[i]; - if (vertex_color[vertex] != kWhite) { - continue; - } - - ordering->push_back(vertex); - vertex_color[vertex] = kBlack; - const HashSet<Vertex>& neighbors = graph.Neighbors(vertex); - for (typename HashSet<Vertex>::const_iterator it = neighbors.begin(); - it != neighbors.end(); - ++it) { - vertex_color[*it] = kGrey; - } - } - - int independent_set_size = ordering->size(); - - // Iterate over the vertices and add all the grey vertices to the - // ordering. At this stage there should only be black or grey - // vertices in the graph. - for (typename std::vector<Vertex>::const_iterator it = vertex_queue.begin(); - it != vertex_queue.end(); - ++it) { - const Vertex vertex = *it; - DCHECK(vertex_color[vertex] != kWhite); - if (vertex_color[vertex] != kBlack) { - ordering->push_back(vertex); - } - } - - CHECK_EQ(ordering->size(), num_vertices); - return independent_set_size; -} - -// Find the connected component for a vertex implemented using the -// find and update operation for disjoint-set. Recursively traverse -// the disjoint set structure till you reach a vertex whose connected -// component has the same id as the vertex itself. Along the way -// update the connected components of all the vertices. This updating -// is what gives this data structure its efficiency. -template <typename Vertex> -Vertex FindConnectedComponent(const Vertex& vertex, - HashMap<Vertex, Vertex>* union_find) { - typename HashMap<Vertex, Vertex>::iterator it = union_find->find(vertex); - DCHECK(it != union_find->end()); - if (it->second != vertex) { - it->second = FindConnectedComponent(it->second, union_find); - } - - return it->second; -} - -// Compute a degree two constrained Maximum Spanning Tree/forest of -// the input graph. Caller owns the result. -// -// Finding degree 2 spanning tree of a graph is not always -// possible. For example a star graph, i.e. a graph with n-nodes -// where one node is connected to the other n-1 nodes does not have -// a any spanning trees of degree less than n-1.Even if such a tree -// exists, finding such a tree is NP-Hard. - -// We get around both of these problems by using a greedy, degree -// constrained variant of Kruskal's algorithm. We start with a graph -// G_T with the same vertex set V as the input graph G(V,E) but an -// empty edge set. We then iterate over the edges of G in decreasing -// order of weight, adding them to G_T if doing so does not create a -// cycle in G_T} and the degree of all the vertices in G_T remains -// bounded by two. This O(|E|) algorithm results in a degree-2 -// spanning forest, or a collection of linear paths that span the -// graph G. -template <typename Vertex> -WeightedGraph<Vertex>* -Degree2MaximumSpanningForest(const WeightedGraph<Vertex>& graph) { - // Array of edges sorted in decreasing order of their weights. - std::vector<std::pair<double, std::pair<Vertex, Vertex> > > weighted_edges; - WeightedGraph<Vertex>* forest = new WeightedGraph<Vertex>(); - - // Disjoint-set to keep track of the connected components in the - // maximum spanning tree. - HashMap<Vertex, Vertex> disjoint_set; - - // Sort of the edges in the graph in decreasing order of their - // weight. Also add the vertices of the graph to the Maximum - // Spanning Tree graph and set each vertex to be its own connected - // component in the disjoint_set structure. - const HashSet<Vertex>& vertices = graph.vertices(); - for (typename HashSet<Vertex>::const_iterator it = vertices.begin(); - it != vertices.end(); - ++it) { - const Vertex vertex1 = *it; - forest->AddVertex(vertex1, graph.VertexWeight(vertex1)); - disjoint_set[vertex1] = vertex1; - - const HashSet<Vertex>& neighbors = graph.Neighbors(vertex1); - for (typename HashSet<Vertex>::const_iterator it2 = neighbors.begin(); - it2 != neighbors.end(); - ++it2) { - const Vertex vertex2 = *it2; - if (vertex1 >= vertex2) { - continue; - } - const double weight = graph.EdgeWeight(vertex1, vertex2); - weighted_edges.push_back( - std::make_pair(weight, std::make_pair(vertex1, vertex2))); - } - } - - // The elements of this vector, are pairs<edge_weight, - // edge>. Sorting it using the reverse iterators gives us the edges - // in decreasing order of edges. - std::sort(weighted_edges.rbegin(), weighted_edges.rend()); - - // Greedily add edges to the spanning tree/forest as long as they do - // not violate the degree/cycle constraint. - for (int i =0; i < weighted_edges.size(); ++i) { - const std::pair<Vertex, Vertex>& edge = weighted_edges[i].second; - const Vertex vertex1 = edge.first; - const Vertex vertex2 = edge.second; - - // Check if either of the vertices are of degree 2 already, in - // which case adding this edge will violate the degree 2 - // constraint. - if ((forest->Neighbors(vertex1).size() == 2) || - (forest->Neighbors(vertex2).size() == 2)) { - continue; - } - - // Find the id of the connected component to which the two - // vertices belong to. If the id is the same, it means that the - // two of them are already connected to each other via some other - // vertex, and adding this edge will create a cycle. - Vertex root1 = FindConnectedComponent(vertex1, &disjoint_set); - Vertex root2 = FindConnectedComponent(vertex2, &disjoint_set); - - if (root1 == root2) { - continue; - } - - // This edge can be added, add an edge in either direction with - // the same weight as the original graph. - const double edge_weight = graph.EdgeWeight(vertex1, vertex2); - forest->AddEdge(vertex1, vertex2, edge_weight); - forest->AddEdge(vertex2, vertex1, edge_weight); - - // Connected the two connected components by updating the - // disjoint_set structure. Always connect the connected component - // with the greater index with the connected component with the - // smaller index. This should ensure shallower trees, for quicker - // lookup. - if (root2 < root1) { - std::swap(root1, root2); - } - - disjoint_set[root2] = root1; - } - return forest; -} - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_GRAPH_ALGORITHMS_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/householder_vector.h b/extern/libmv/third_party/ceres/internal/ceres/householder_vector.h deleted file mode 100644 index f54feea054d..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/householder_vector.h +++ /dev/null @@ -1,85 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://code.google.com/p/ceres-solver/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: vitus@google.com (Michael Vitus) - -#ifndef CERES_PUBLIC_HOUSEHOLDER_VECTOR_H_ -#define CERES_PUBLIC_HOUSEHOLDER_VECTOR_H_ - -#include "Eigen/Core" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -// Algorithm 5.1.1 from 'Matrix Computations' by Golub et al. (Johns Hopkins -// Studies in Mathematical Sciences) but using the nth element of the input -// vector as pivot instead of first. This computes the vector v with v(n) = 1 -// and beta such that H = I - beta * v * v^T is orthogonal and -// H * x = ||x||_2 * e_n. -template <typename Scalar> -void ComputeHouseholderVector(const Eigen::Matrix<Scalar, Eigen::Dynamic, 1>& x, - Eigen::Matrix<Scalar, Eigen::Dynamic, 1>* v, - Scalar* beta) { - CHECK_NOTNULL(beta); - CHECK_NOTNULL(v); - CHECK_GT(x.rows(), 1); - CHECK_EQ(x.rows(), v->rows()); - - Scalar sigma = x.head(x.rows() - 1).squaredNorm(); - *v = x; - (*v)(v->rows() - 1) = Scalar(1.0); - - *beta = Scalar(0.0); - const Scalar& x_pivot = x(x.rows() - 1); - - if (sigma <= Scalar(std::numeric_limits<double>::epsilon())) { - if (x_pivot < Scalar(0.0)) { - *beta = Scalar(2.0); - } - return; - } - - const Scalar mu = sqrt(x_pivot * x_pivot + sigma); - Scalar v_pivot = Scalar(1.0); - - if (x_pivot <= Scalar(0.0)) { - v_pivot = x_pivot - mu; - } else { - v_pivot = -sigma / (x_pivot + mu); - } - - *beta = Scalar(2.0) * v_pivot * v_pivot / (sigma + v_pivot * v_pivot); - - v->head(v->rows() - 1) /= v_pivot; -} - -} // namespace internal -} // namespace ceres - -#endif // CERES_PUBLIC_HOUSEHOLDER_VECTOR_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.cc b/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.cc deleted file mode 100644 index d05f03817b7..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.cc +++ /dev/null @@ -1,225 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/implicit_schur_complement.h" - -#include "Eigen/Dense" -#include "ceres/block_sparse_matrix.h" -#include "ceres/block_structure.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/linear_solver.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -ImplicitSchurComplement::ImplicitSchurComplement( - const LinearSolver::Options& options) - : options_(options), - D_(NULL), - b_(NULL) { -} - -ImplicitSchurComplement::~ImplicitSchurComplement() { -} - -void ImplicitSchurComplement::Init(const BlockSparseMatrix& A, - const double* D, - const double* b) { - // Since initialization is reasonably heavy, perhaps we can save on - // constructing a new object everytime. - if (A_ == NULL) { - A_.reset(PartitionedMatrixViewBase::Create(options_, A)); - } - - D_ = D; - b_ = b; - - // Initialize temporary storage and compute the block diagonals of - // E'E and F'E. - if (block_diagonal_EtE_inverse_ == NULL) { - block_diagonal_EtE_inverse_.reset(A_->CreateBlockDiagonalEtE()); - if (options_.preconditioner_type == JACOBI) { - block_diagonal_FtF_inverse_.reset(A_->CreateBlockDiagonalFtF()); - } - rhs_.resize(A_->num_cols_f()); - rhs_.setZero(); - tmp_rows_.resize(A_->num_rows()); - tmp_e_cols_.resize(A_->num_cols_e()); - tmp_e_cols_2_.resize(A_->num_cols_e()); - tmp_f_cols_.resize(A_->num_cols_f()); - } else { - A_->UpdateBlockDiagonalEtE(block_diagonal_EtE_inverse_.get()); - if (options_.preconditioner_type == JACOBI) { - A_->UpdateBlockDiagonalFtF(block_diagonal_FtF_inverse_.get()); - } - } - - // The block diagonals of the augmented linear system contain - // contributions from the diagonal D if it is non-null. Add that to - // the block diagonals and invert them. - AddDiagonalAndInvert(D_, block_diagonal_EtE_inverse_.get()); - if (options_.preconditioner_type == JACOBI) { - AddDiagonalAndInvert((D_ == NULL) ? NULL : D_ + A_->num_cols_e(), - block_diagonal_FtF_inverse_.get()); - } - - // Compute the RHS of the Schur complement system. - UpdateRhs(); -} - -// Evaluate the product -// -// Sx = [F'F - F'E (E'E)^-1 E'F]x -// -// By breaking it down into individual matrix vector products -// involving the matrices E and F. This is implemented using a -// PartitionedMatrixView of the input matrix A. -void ImplicitSchurComplement::RightMultiply(const double* x, double* y) const { - // y1 = F x - tmp_rows_.setZero(); - A_->RightMultiplyF(x, tmp_rows_.data()); - - // y2 = E' y1 - tmp_e_cols_.setZero(); - A_->LeftMultiplyE(tmp_rows_.data(), tmp_e_cols_.data()); - - // y3 = -(E'E)^-1 y2 - tmp_e_cols_2_.setZero(); - block_diagonal_EtE_inverse_->RightMultiply(tmp_e_cols_.data(), - tmp_e_cols_2_.data()); - tmp_e_cols_2_ *= -1.0; - - // y1 = y1 + E y3 - A_->RightMultiplyE(tmp_e_cols_2_.data(), tmp_rows_.data()); - - // y5 = D * x - if (D_ != NULL) { - ConstVectorRef Dref(D_ + A_->num_cols_e(), num_cols()); - VectorRef(y, num_cols()) = - (Dref.array().square() * - ConstVectorRef(x, num_cols()).array()).matrix(); - } else { - VectorRef(y, num_cols()).setZero(); - } - - // y = y5 + F' y1 - A_->LeftMultiplyF(tmp_rows_.data(), y); -} - -// Given a block diagonal matrix and an optional array of diagonal -// entries D, add them to the diagonal of the matrix and compute the -// inverse of each diagonal block. -void ImplicitSchurComplement::AddDiagonalAndInvert( - const double* D, - BlockSparseMatrix* block_diagonal) { - const CompressedRowBlockStructure* block_diagonal_structure = - block_diagonal->block_structure(); - for (int r = 0; r < block_diagonal_structure->rows.size(); ++r) { - const int row_block_pos = block_diagonal_structure->rows[r].block.position; - const int row_block_size = block_diagonal_structure->rows[r].block.size; - const Cell& cell = block_diagonal_structure->rows[r].cells[0]; - MatrixRef m(block_diagonal->mutable_values() + cell.position, - row_block_size, row_block_size); - - if (D != NULL) { - ConstVectorRef d(D + row_block_pos, row_block_size); - m += d.array().square().matrix().asDiagonal(); - } - - m = m - .selfadjointView<Eigen::Upper>() - .llt() - .solve(Matrix::Identity(row_block_size, row_block_size)); - } -} - -// Similar to RightMultiply, use the block structure of the matrix A -// to compute y = (E'E)^-1 (E'b - E'F x). -void ImplicitSchurComplement::BackSubstitute(const double* x, double* y) { - const int num_cols_e = A_->num_cols_e(); - const int num_cols_f = A_->num_cols_f(); - const int num_cols = A_->num_cols(); - const int num_rows = A_->num_rows(); - - // y1 = F x - tmp_rows_.setZero(); - A_->RightMultiplyF(x, tmp_rows_.data()); - - // y2 = b - y1 - tmp_rows_ = ConstVectorRef(b_, num_rows) - tmp_rows_; - - // y3 = E' y2 - tmp_e_cols_.setZero(); - A_->LeftMultiplyE(tmp_rows_.data(), tmp_e_cols_.data()); - - // y = (E'E)^-1 y3 - VectorRef(y, num_cols).setZero(); - block_diagonal_EtE_inverse_->RightMultiply(tmp_e_cols_.data(), y); - - // The full solution vector y has two blocks. The first block of - // variables corresponds to the eliminated variables, which we just - // computed via back substitution. The second block of variables - // corresponds to the Schur complement system, so we just copy those - // values from the solution to the Schur complement. - VectorRef(y + num_cols_e, num_cols_f) = ConstVectorRef(x, num_cols_f); -} - -// Compute the RHS of the Schur complement system. -// -// rhs = F'b - F'E (E'E)^-1 E'b -// -// Like BackSubstitute, we use the block structure of A to implement -// this using a series of matrix vector products. -void ImplicitSchurComplement::UpdateRhs() { - // y1 = E'b - tmp_e_cols_.setZero(); - A_->LeftMultiplyE(b_, tmp_e_cols_.data()); - - // y2 = (E'E)^-1 y1 - Vector y2 = Vector::Zero(A_->num_cols_e()); - block_diagonal_EtE_inverse_->RightMultiply(tmp_e_cols_.data(), y2.data()); - - // y3 = E y2 - tmp_rows_.setZero(); - A_->RightMultiplyE(y2.data(), tmp_rows_.data()); - - // y3 = b - y3 - tmp_rows_ = ConstVectorRef(b_, A_->num_rows()) - tmp_rows_; - - // rhs = F' y3 - rhs_.setZero(); - A_->LeftMultiplyF(tmp_rows_.data(), rhs_.data()); -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.h b/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.h deleted file mode 100644 index 5d822ebaeef..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.h +++ /dev/null @@ -1,167 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// An iterative solver for solving the Schur complement/reduced camera -// linear system that arise in SfM problems. - -#ifndef CERES_INTERNAL_IMPLICIT_SCHUR_COMPLEMENT_H_ -#define CERES_INTERNAL_IMPLICIT_SCHUR_COMPLEMENT_H_ - -#include "ceres/linear_operator.h" -#include "ceres/linear_solver.h" -#include "ceres/partitioned_matrix_view.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -class BlockSparseMatrix; - -// This class implements various linear algebraic operations related -// to the Schur complement without explicitly forming it. -// -// -// Given a reactangular linear system Ax = b, where -// -// A = [E F] -// -// The normal equations are given by -// -// A'Ax = A'b -// -// |E'E E'F||y| = |E'b| -// |F'E F'F||z| |F'b| -// -// and the Schur complement system is given by -// -// [F'F - F'E (E'E)^-1 E'F] z = F'b - F'E (E'E)^-1 E'b -// -// Now if we wish to solve Ax = b in the least squares sense, one way -// is to form this Schur complement system and solve it using -// Preconditioned Conjugate Gradients. -// -// The key operation in a conjugate gradient solver is the evaluation of the -// matrix vector product with the Schur complement -// -// S = F'F - F'E (E'E)^-1 E'F -// -// It is straightforward to see that matrix vector products with S can -// be evaluated without storing S in memory. Instead, given (E'E)^-1 -// (which for our purposes is an easily inverted block diagonal -// matrix), it can be done in terms of matrix vector products with E, -// F and (E'E)^-1. This class implements this functionality and other -// auxilliary bits needed to implement a CG solver on the Schur -// complement using the PartitionedMatrixView object. -// -// THREAD SAFETY: This class is nqot thread safe. In particular, the -// RightMultiply (and the LeftMultiply) methods are not thread safe as -// they depend on mutable arrays used for the temporaries needed to -// compute the product y += Sx; -class ImplicitSchurComplement : public LinearOperator { - public: - // num_eliminate_blocks is the number of E blocks in the matrix - // A. - // - // preconditioner indicates whether the inverse of the matrix F'F - // should be computed or not as a preconditioner for the Schur - // Complement. - // - // TODO(sameeragarwal): Get rid of the two bools below and replace - // them with enums. - explicit ImplicitSchurComplement(const LinearSolver::Options& options); - virtual ~ImplicitSchurComplement(); - - // Initialize the Schur complement for a linear least squares - // problem of the form - // - // |A | x = |b| - // |diag(D)| |0| - // - // If D is null, then it is treated as a zero dimensional matrix. It - // is important that the matrix A have a BlockStructure object - // associated with it and has a block structure that is compatible - // with the SchurComplement solver. - void Init(const BlockSparseMatrix& A, const double* D, const double* b); - - // y += Sx, where S is the Schur complement. - virtual void RightMultiply(const double* x, double* y) const; - - // The Schur complement is a symmetric positive definite matrix, - // thus the left and right multiply operators are the same. - virtual void LeftMultiply(const double* x, double* y) const { - RightMultiply(x, y); - } - - // y = (E'E)^-1 (E'b - E'F x). Given an estimate of the solution to - // the Schur complement system, this method computes the value of - // the e_block variables that were eliminated to form the Schur - // complement. - void BackSubstitute(const double* x, double* y); - - virtual int num_rows() const { return A_->num_cols_f(); } - virtual int num_cols() const { return A_->num_cols_f(); } - const Vector& rhs() const { return rhs_; } - - const BlockSparseMatrix* block_diagonal_EtE_inverse() const { - return block_diagonal_EtE_inverse_.get(); - } - - const BlockSparseMatrix* block_diagonal_FtF_inverse() const { - return block_diagonal_FtF_inverse_.get(); - } - - private: - void AddDiagonalAndInvert(const double* D, BlockSparseMatrix* matrix); - void UpdateRhs(); - - const LinearSolver::Options& options_; - - scoped_ptr<PartitionedMatrixViewBase> A_; - const double* D_; - const double* b_; - - scoped_ptr<BlockSparseMatrix> block_diagonal_EtE_inverse_; - scoped_ptr<BlockSparseMatrix> block_diagonal_FtF_inverse_; - - Vector rhs_; - - // Temporary storage vectors used to implement RightMultiply. - mutable Vector tmp_rows_; - mutable Vector tmp_e_cols_; - mutable Vector tmp_e_cols_2_; - mutable Vector tmp_f_cols_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_IMPLICIT_SCHUR_COMPLEMENT_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/integral_types.h b/extern/libmv/third_party/ceres/internal/ceres/integral_types.h deleted file mode 100644 index 98a746f13ff..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/integral_types.h +++ /dev/null @@ -1,91 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// Portable typedefs for various fixed-size integers. Uses template -// metaprogramming instead of fragile compiler defines. - -#ifndef CERES_INTERNAL_INTEGRAL_TYPES_H_ -#define CERES_INTERNAL_INTEGRAL_TYPES_H_ - -namespace ceres { -namespace internal { - -// Compile time ternary on types. -template<bool kCondition, typename kTrueType, typename kFalseType> -struct Ternary { - typedef kTrueType type; -}; -template<typename kTrueType, typename kFalseType> -struct Ternary<false, kTrueType, kFalseType> { - typedef kFalseType type; -}; - -#define CERES_INTSIZE(TYPE) \ - typename Ternary<sizeof(TYPE) * 8 == kBits, TYPE, - -template<int kBits> -struct Integer { - typedef - CERES_INTSIZE(char) - CERES_INTSIZE(short) - CERES_INTSIZE(int) - CERES_INTSIZE(long int) - CERES_INTSIZE(long long) - void>::type >::type >::type >::type >::type - type; -}; - -template<int kBits> -struct UnsignedInteger { - typedef - CERES_INTSIZE(unsigned char) - CERES_INTSIZE(unsigned short) - CERES_INTSIZE(unsigned int) - CERES_INTSIZE(unsigned long int) - CERES_INTSIZE(unsigned long long) - void>::type >::type >::type >::type >::type - type; -}; - -#undef CERES_INTSIZE - -typedef Integer< 8>::type int8; -typedef Integer<32>::type int32; -typedef Integer<64>::type int64; - -typedef UnsignedInteger< 8>::type uint8; -typedef UnsignedInteger<16>::type uint16; -typedef UnsignedInteger<32>::type uint32; -typedef UnsignedInteger<64>::type uint64; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_INTEGRAL_TYPES_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/iterative_schur_complement_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/iterative_schur_complement_solver.cc deleted file mode 100644 index 9d4e30d69d2..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/iterative_schur_complement_solver.cc +++ /dev/null @@ -1,182 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/iterative_schur_complement_solver.h" - -#include <algorithm> -#include <cstring> -#include <vector> - -#include "Eigen/Dense" -#include "ceres/block_sparse_matrix.h" -#include "ceres/block_structure.h" -#include "ceres/conjugate_gradients_solver.h" -#include "ceres/detect_structure.h" -#include "ceres/implicit_schur_complement.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/linear_solver.h" -#include "ceres/preconditioner.h" -#include "ceres/schur_jacobi_preconditioner.h" -#include "ceres/triplet_sparse_matrix.h" -#include "ceres/types.h" -#include "ceres/visibility_based_preconditioner.h" -#include "ceres/wall_time.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -IterativeSchurComplementSolver::IterativeSchurComplementSolver( - const LinearSolver::Options& options) - : options_(options) { -} - -IterativeSchurComplementSolver::~IterativeSchurComplementSolver() { -} - -LinearSolver::Summary IterativeSchurComplementSolver::SolveImpl( - BlockSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x) { - EventLogger event_logger("IterativeSchurComplementSolver::Solve"); - - CHECK_NOTNULL(A->block_structure()); - const int num_eliminate_blocks = options_.elimination_groups[0]; - // Initialize a ImplicitSchurComplement object. - if (schur_complement_ == NULL) { - DetectStructure(*(A->block_structure()), - num_eliminate_blocks, - &options_.row_block_size, - &options_.e_block_size, - &options_.f_block_size); - schur_complement_.reset(new ImplicitSchurComplement(options_)); - } - schur_complement_->Init(*A, per_solve_options.D, b); - - const int num_schur_complement_blocks = - A->block_structure()->cols.size() - num_eliminate_blocks; - if (num_schur_complement_blocks == 0) { - VLOG(2) << "No parameter blocks left in the schur complement."; - LinearSolver::Summary cg_summary; - cg_summary.num_iterations = 0; - cg_summary.termination_type = LINEAR_SOLVER_SUCCESS; - schur_complement_->BackSubstitute(NULL, x); - return cg_summary; - } - - // Initialize the solution to the Schur complement system to zero. - reduced_linear_system_solution_.resize(schur_complement_->num_rows()); - reduced_linear_system_solution_.setZero(); - - // Instantiate a conjugate gradient solver that runs on the Schur - // complement matrix with the block diagonal of the matrix F'F as - // the preconditioner. - LinearSolver::Options cg_options; - cg_options.min_num_iterations = options_.min_num_iterations; - cg_options.max_num_iterations = options_.max_num_iterations; - ConjugateGradientsSolver cg_solver(cg_options); - LinearSolver::PerSolveOptions cg_per_solve_options; - - cg_per_solve_options.r_tolerance = per_solve_options.r_tolerance; - cg_per_solve_options.q_tolerance = per_solve_options.q_tolerance; - - Preconditioner::Options preconditioner_options; - preconditioner_options.type = options_.preconditioner_type; - preconditioner_options.visibility_clustering_type = - options_.visibility_clustering_type; - preconditioner_options.sparse_linear_algebra_library_type = - options_.sparse_linear_algebra_library_type; - preconditioner_options.num_threads = options_.num_threads; - preconditioner_options.row_block_size = options_.row_block_size; - preconditioner_options.e_block_size = options_.e_block_size; - preconditioner_options.f_block_size = options_.f_block_size; - preconditioner_options.elimination_groups = options_.elimination_groups; - - switch (options_.preconditioner_type) { - case IDENTITY: - break; - case JACOBI: - preconditioner_.reset( - new SparseMatrixPreconditionerWrapper( - schur_complement_->block_diagonal_FtF_inverse())); - break; - case SCHUR_JACOBI: - if (preconditioner_.get() == NULL) { - preconditioner_.reset( - new SchurJacobiPreconditioner(*A->block_structure(), - preconditioner_options)); - } - break; - case CLUSTER_JACOBI: - case CLUSTER_TRIDIAGONAL: - if (preconditioner_.get() == NULL) { - preconditioner_.reset( - new VisibilityBasedPreconditioner(*A->block_structure(), - preconditioner_options)); - } - break; - default: - LOG(FATAL) << "Unknown Preconditioner Type"; - } - - bool preconditioner_update_was_successful = true; - if (preconditioner_.get() != NULL) { - preconditioner_update_was_successful = - preconditioner_->Update(*A, per_solve_options.D); - cg_per_solve_options.preconditioner = preconditioner_.get(); - } - event_logger.AddEvent("Setup"); - - LinearSolver::Summary cg_summary; - cg_summary.num_iterations = 0; - cg_summary.termination_type = LINEAR_SOLVER_FAILURE; - - // TODO(sameeragarwal): Refactor preconditioners to return a more - // sane message. - cg_summary.message = "Preconditioner update failed."; - if (preconditioner_update_was_successful) { - cg_summary = cg_solver.Solve(schur_complement_.get(), - schur_complement_->rhs().data(), - cg_per_solve_options, - reduced_linear_system_solution_.data()); - if (cg_summary.termination_type != LINEAR_SOLVER_FAILURE && - cg_summary.termination_type != LINEAR_SOLVER_FATAL_ERROR) { - schur_complement_->BackSubstitute( - reduced_linear_system_solution_.data(), x); - } - } - event_logger.AddEvent("Solve"); - return cg_summary; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/iterative_schur_complement_solver.h b/extern/libmv/third_party/ceres/internal/ceres/iterative_schur_complement_solver.h deleted file mode 100644 index e90d310de07..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/iterative_schur_complement_solver.h +++ /dev/null @@ -1,92 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_ITERATIVE_SCHUR_COMPLEMENT_SOLVER_H_ -#define CERES_INTERNAL_ITERATIVE_SCHUR_COMPLEMENT_SOLVER_H_ - -#include "ceres/linear_solver.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -class BlockSparseMatrix; -class ImplicitSchurComplement; -class Preconditioner; - -// This class implements an iterative solver for the linear least -// squares problems that have a bi-partite sparsity structure common -// to Structure from Motion problems. -// -// The algorithm used by this solver was developed in a series of -// papers - "Agarwal et al, Bundle Adjustment in the Large, ECCV 2010" -// and "Wu et al, Multicore Bundle Adjustment, submitted to CVPR -// 2011" at the Univeristy of Washington. -// -// The key idea is that one can run Conjugate Gradients on the Schur -// Complement system without explicitly forming the Schur Complement -// in memory. The heavy lifting for this is done by the -// ImplicitSchurComplement class. Not forming the Schur complement in -// memory and factoring it results in substantial savings in time and -// memory. Further, iterative solvers like this open up the -// possibility of solving the Newton equations in a non-linear solver -// only approximately and terminating early, thereby saving even more -// time. -// -// For the curious, running CG on the Schur complement is the same as -// running CG on the Normal Equations with an SSOR preconditioner. For -// a proof of this fact and others related to this solver please see -// the section on Domain Decomposition Methods in Saad's book -// "Iterative Methods for Sparse Linear Systems". -class IterativeSchurComplementSolver : public BlockSparseMatrixSolver { - public: - explicit IterativeSchurComplementSolver(const LinearSolver::Options& options); - virtual ~IterativeSchurComplementSolver(); - - private: - virtual LinearSolver::Summary SolveImpl( - BlockSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& options, - double* x); - - LinearSolver::Options options_; - scoped_ptr<internal::ImplicitSchurComplement> schur_complement_; - scoped_ptr<Preconditioner> preconditioner_; - Vector reduced_linear_system_solution_; - CERES_DISALLOW_COPY_AND_ASSIGN(IterativeSchurComplementSolver); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_ITERATIVE_SCHUR_COMPLEMENT_SOLVER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/lapack.cc b/extern/libmv/third_party/ceres/internal/ceres/lapack.cc deleted file mode 100644 index 6fc23f4e658..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/lapack.cc +++ /dev/null @@ -1,193 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/lapack.h" - -#include "ceres/internal/port.h" -#include "ceres/linear_solver.h" -#include "glog/logging.h" - -// C interface to the LAPACK Cholesky factorization and triangular solve. -extern "C" void dpotrf_(char* uplo, - int* n, - double* a, - int* lda, - int* info); - -extern "C" void dpotrs_(char* uplo, - int* n, - int* nrhs, - double* a, - int* lda, - double* b, - int* ldb, - int* info); - -extern "C" void dgels_(char* uplo, - int* m, - int* n, - int* nrhs, - double* a, - int* lda, - double* b, - int* ldb, - double* work, - int* lwork, - int* info); - - -namespace ceres { -namespace internal { - -LinearSolverTerminationType LAPACK::SolveInPlaceUsingCholesky( - int num_rows, - const double* in_lhs, - double* rhs_and_solution, - std::string* message) { -#ifdef CERES_NO_LAPACK - LOG(FATAL) << "Ceres was built without a BLAS library."; - return LINEAR_SOLVER_FATAL_ERROR; -#else - char uplo = 'L'; - int n = num_rows; - int info = 0; - int nrhs = 1; - double* lhs = const_cast<double*>(in_lhs); - - dpotrf_(&uplo, &n, lhs, &n, &info); - if (info < 0) { - LOG(FATAL) << "Congratulations, you found a bug in Ceres." - << "Please report it." - << "LAPACK::dpotrf fatal error." - << "Argument: " << -info << " is invalid."; - return LINEAR_SOLVER_FATAL_ERROR; - } - - if (info > 0) { - *message = - StringPrintf( - "LAPACK::dpotrf numerical failure. " - "The leading minor of order %d is not positive definite.", info); - return LINEAR_SOLVER_FAILURE; - } - - dpotrs_(&uplo, &n, &nrhs, lhs, &n, rhs_and_solution, &n, &info); - if (info < 0) { - LOG(FATAL) << "Congratulations, you found a bug in Ceres." - << "Please report it." - << "LAPACK::dpotrs fatal error." - << "Argument: " << -info << " is invalid."; - return LINEAR_SOLVER_FATAL_ERROR; - } - - *message = "Success"; - return LINEAR_SOLVER_SUCCESS; -#endif -} - -int LAPACK::EstimateWorkSizeForQR(int num_rows, int num_cols) { -#ifdef CERES_NO_LAPACK - LOG(FATAL) << "Ceres was built without a LAPACK library."; - return -1; -#else - char trans = 'N'; - int nrhs = 1; - int lwork = -1; - double work; - int info = 0; - dgels_(&trans, - &num_rows, - &num_cols, - &nrhs, - NULL, - &num_rows, - NULL, - &num_rows, - &work, - &lwork, - &info); - - if (info < 0) { - LOG(FATAL) << "Congratulations, you found a bug in Ceres." - << "Please report it." - << "LAPACK::dgels fatal error." - << "Argument: " << -info << " is invalid."; - } - return static_cast<int>(work); -#endif -} - -LinearSolverTerminationType LAPACK::SolveInPlaceUsingQR( - int num_rows, - int num_cols, - const double* in_lhs, - int work_size, - double* work, - double* rhs_and_solution, - std::string* message) { -#ifdef CERES_NO_LAPACK - LOG(FATAL) << "Ceres was built without a LAPACK library."; - return LINEAR_SOLVER_FATAL_ERROR; -#else - char trans = 'N'; - int m = num_rows; - int n = num_cols; - int nrhs = 1; - int lda = num_rows; - int ldb = num_rows; - int info = 0; - double* lhs = const_cast<double*>(in_lhs); - - dgels_(&trans, - &m, - &n, - &nrhs, - lhs, - &lda, - rhs_and_solution, - &ldb, - work, - &work_size, - &info); - - if (info < 0) { - LOG(FATAL) << "Congratulations, you found a bug in Ceres." - << "Please report it." - << "LAPACK::dgels fatal error." - << "Argument: " << -info << " is invalid."; - } - - *message = "Success."; - return LINEAR_SOLVER_SUCCESS; -#endif -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/lapack.h b/extern/libmv/third_party/ceres/internal/ceres/lapack.h deleted file mode 100644 index 5bb1a220c26..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/lapack.h +++ /dev/null @@ -1,100 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_LAPACK_H_ -#define CERES_INTERNAL_LAPACK_H_ - -#include <string> -#include "ceres/internal/port.h" -#include "ceres/linear_solver.h" - -namespace ceres { -namespace internal { - -class LAPACK { - public: - // Solve - // - // lhs * solution = rhs - // - // using a Cholesky factorization. Here - // lhs is a symmetric positive definite matrix. It is assumed to be - // column major and only the lower triangular part of the matrix is - // referenced. - // - // This function uses the LAPACK dpotrf and dpotrs routines. - // - // The return value and the message string together describe whether - // the solver terminated successfully or not and if so, what was the - // reason for failure. - static LinearSolverTerminationType SolveInPlaceUsingCholesky( - int num_rows, - const double* lhs, - double* rhs_and_solution, - std::string* message); - - // The SolveUsingQR function requires a buffer for its temporary - // computation. This function given the size of the lhs matrix will - // return the size of the buffer needed. - static int EstimateWorkSizeForQR(int num_rows, int num_cols); - - // Solve - // - // lhs * solution = rhs - // - // using a dense QR factorization. lhs is an arbitrary (possibly - // rectangular) matrix with full column rank. - // - // work is an array of size work_size that this routine uses for its - // temporary storage. The optimal size of this array can be obtained - // by calling EstimateWorkSizeForQR. - // - // When calling, rhs_and_solution contains the rhs, and upon return - // the first num_col entries are the solution. - // - // This function uses the LAPACK dgels routine. - // - // The return value and the message string together describe whether - // the solver terminated successfully or not and if so, what was the - // reason for failure. - static LinearSolverTerminationType SolveInPlaceUsingQR( - int num_rows, - int num_cols, - const double* lhs, - int work_size, - double* work, - double* rhs_and_solution, - std::string* message); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_LAPACK_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt_strategy.cc b/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt_strategy.cc deleted file mode 100644 index e9833805ef5..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt_strategy.cc +++ /dev/null @@ -1,167 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/levenberg_marquardt_strategy.h" - -#include <cmath> -#include "Eigen/Core" -#include "ceres/array_utils.h" -#include "ceres/internal/eigen.h" -#include "ceres/linear_least_squares_problems.h" -#include "ceres/linear_solver.h" -#include "ceres/sparse_matrix.h" -#include "ceres/trust_region_strategy.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -LevenbergMarquardtStrategy::LevenbergMarquardtStrategy( - const TrustRegionStrategy::Options& options) - : linear_solver_(options.linear_solver), - radius_(options.initial_radius), - max_radius_(options.max_radius), - min_diagonal_(options.min_lm_diagonal), - max_diagonal_(options.max_lm_diagonal), - decrease_factor_(2.0), - reuse_diagonal_(false) { - CHECK_NOTNULL(linear_solver_); - CHECK_GT(min_diagonal_, 0.0); - CHECK_LE(min_diagonal_, max_diagonal_); - CHECK_GT(max_radius_, 0.0); -} - -LevenbergMarquardtStrategy::~LevenbergMarquardtStrategy() { -} - -TrustRegionStrategy::Summary LevenbergMarquardtStrategy::ComputeStep( - const TrustRegionStrategy::PerSolveOptions& per_solve_options, - SparseMatrix* jacobian, - const double* residuals, - double* step) { - CHECK_NOTNULL(jacobian); - CHECK_NOTNULL(residuals); - CHECK_NOTNULL(step); - - const int num_parameters = jacobian->num_cols(); - if (!reuse_diagonal_) { - if (diagonal_.rows() != num_parameters) { - diagonal_.resize(num_parameters, 1); - } - - jacobian->SquaredColumnNorm(diagonal_.data()); - for (int i = 0; i < num_parameters; ++i) { - diagonal_[i] = std::min(std::max(diagonal_[i], min_diagonal_), - max_diagonal_); - } - } - - lm_diagonal_ = (diagonal_ / radius_).array().sqrt(); - - LinearSolver::PerSolveOptions solve_options; - solve_options.D = lm_diagonal_.data(); - solve_options.q_tolerance = per_solve_options.eta; - // Disable r_tolerance checking. Since we only care about - // termination via the q_tolerance. As Nash and Sofer show, - // r_tolerance based termination is essentially useless in - // Truncated Newton methods. - solve_options.r_tolerance = -1.0; - - // Invalidate the output array lm_step, so that we can detect if - // the linear solver generated numerical garbage. This is known - // to happen for the DENSE_QR and then DENSE_SCHUR solver when - // the Jacobin is severly rank deficient and mu is too small. - InvalidateArray(num_parameters, step); - - // Instead of solving Jx = -r, solve Jy = r. - // Then x can be found as x = -y, but the inputs jacobian and residuals - // do not need to be modified. - LinearSolver::Summary linear_solver_summary = - linear_solver_->Solve(jacobian, residuals, solve_options, step); - - if (linear_solver_summary.termination_type == LINEAR_SOLVER_FATAL_ERROR) { - LOG(WARNING) << "Linear solver fatal error: " - << linear_solver_summary.message; - } else if (linear_solver_summary.termination_type == LINEAR_SOLVER_FAILURE) { - LOG(WARNING) << "Linear solver failure. Failed to compute a step: " - << linear_solver_summary.message; - } else if (!IsArrayValid(num_parameters, step)) { - LOG(WARNING) << "Linear solver failure. Failed to compute a finite step."; - linear_solver_summary.termination_type = LINEAR_SOLVER_FAILURE; - } else { - VectorRef(step, num_parameters) *= -1.0; - } - reuse_diagonal_ = true; - - if (per_solve_options.dump_format_type == CONSOLE || - (per_solve_options.dump_format_type != CONSOLE && - !per_solve_options.dump_filename_base.empty())) { - if (!DumpLinearLeastSquaresProblem(per_solve_options.dump_filename_base, - per_solve_options.dump_format_type, - jacobian, - solve_options.D, - residuals, - step, - 0)) { - LOG(ERROR) << "Unable to dump trust region problem." - << " Filename base: " << per_solve_options.dump_filename_base; - } - } - - - TrustRegionStrategy::Summary summary; - summary.residual_norm = linear_solver_summary.residual_norm; - summary.num_iterations = linear_solver_summary.num_iterations; - summary.termination_type = linear_solver_summary.termination_type; - return summary; -} - -void LevenbergMarquardtStrategy::StepAccepted(double step_quality) { - CHECK_GT(step_quality, 0.0); - radius_ = radius_ / std::max(1.0 / 3.0, - 1.0 - pow(2.0 * step_quality - 1.0, 3)); - radius_ = std::min(max_radius_, radius_); - decrease_factor_ = 2.0; - reuse_diagonal_ = false; -} - -void LevenbergMarquardtStrategy::StepRejected(double step_quality) { - radius_ = radius_ / decrease_factor_; - decrease_factor_ *= 2.0; - reuse_diagonal_ = true; -} - -double LevenbergMarquardtStrategy::Radius() const { - return radius_; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt_strategy.h b/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt_strategy.h deleted file mode 100644 index c87a016c8f4..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt_strategy.h +++ /dev/null @@ -1,87 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_LEVENBERG_MARQUARDT_STRATEGY_H_ -#define CERES_INTERNAL_LEVENBERG_MARQUARDT_STRATEGY_H_ - -#include "ceres/internal/eigen.h" -#include "ceres/trust_region_strategy.h" - -namespace ceres { -namespace internal { - -// Levenberg-Marquardt step computation and trust region sizing -// strategy based on on "Methods for Nonlinear Least Squares" by -// K. Madsen, H.B. Nielsen and O. Tingleff. Available to download from -// -// http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/3215/pdf/imm3215.pdf -class LevenbergMarquardtStrategy : public TrustRegionStrategy { - public: - explicit LevenbergMarquardtStrategy( - const TrustRegionStrategy::Options& options); - virtual ~LevenbergMarquardtStrategy(); - - // TrustRegionStrategy interface - virtual TrustRegionStrategy::Summary ComputeStep( - const TrustRegionStrategy::PerSolveOptions& per_solve_options, - SparseMatrix* jacobian, - const double* residuals, - double* step); - virtual void StepAccepted(double step_quality); - virtual void StepRejected(double step_quality); - virtual void StepIsInvalid() { - // Treat the current step as a rejected step with no increase in - // solution quality. Since rejected steps lead to decrease in the - // size of the trust region, the next time ComputeStep is called, - // this will lead to a better conditioned system. - StepRejected(0.0); - } - - virtual double Radius() const; - - private: - LinearSolver* linear_solver_; - double radius_; - double max_radius_; - const double min_diagonal_; - const double max_diagonal_; - double decrease_factor_; - bool reuse_diagonal_; - Vector diagonal_; // diagonal_ = diag(J'J) - // Scaled copy of diagonal_. Stored here as optimization to prevent - // allocations in every iteration and reuse when a step fails and - // ComputeStep is called again. - Vector lm_diagonal_; // lm_diagonal_ = diagonal_ / radius_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_LEVENBERG_MARQUARDT_STRATEGY_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/line_search.cc b/extern/libmv/third_party/ceres/internal/ceres/line_search.cc deleted file mode 100644 index 9cdcb7b77e5..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/line_search.cc +++ /dev/null @@ -1,881 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/line_search.h" - -#include <iomanip> -#include <iostream> // NOLINT - -#include "glog/logging.h" -#include "ceres/evaluator.h" -#include "ceres/internal/eigen.h" -#include "ceres/fpclassify.h" -#include "ceres/map_util.h" -#include "ceres/polynomial.h" -#include "ceres/stringprintf.h" -#include "ceres/wall_time.h" - -namespace ceres { -namespace internal { - -using std::map; -using std::ostream; -using std::string; -using std::vector; - -namespace { -// Precision used for floating point values in error message output. -const int kErrorMessageNumericPrecision = 8; - -FunctionSample ValueSample(const double x, const double value) { - FunctionSample sample; - sample.x = x; - sample.value = value; - sample.value_is_valid = true; - return sample; -} - -FunctionSample ValueAndGradientSample(const double x, - const double value, - const double gradient) { - FunctionSample sample; - sample.x = x; - sample.value = value; - sample.gradient = gradient; - sample.value_is_valid = true; - sample.gradient_is_valid = true; - return sample; -} - -} // namespace - - -ostream& operator<<(ostream &os, const FunctionSample& sample); - -// Convenience stream operator for pushing FunctionSamples into log messages. -ostream& operator<<(ostream &os, const FunctionSample& sample) { - os << sample.ToDebugString(); - return os; -} - -LineSearch::LineSearch(const LineSearch::Options& options) - : options_(options) {} - -LineSearch* LineSearch::Create(const LineSearchType line_search_type, - const LineSearch::Options& options, - string* error) { - LineSearch* line_search = NULL; - switch (line_search_type) { - case ceres::ARMIJO: - line_search = new ArmijoLineSearch(options); - break; - case ceres::WOLFE: - line_search = new WolfeLineSearch(options); - break; - default: - *error = string("Invalid line search algorithm type: ") + - LineSearchTypeToString(line_search_type) + - string(", unable to create line search."); - return NULL; - } - return line_search; -} - -LineSearchFunction::LineSearchFunction(Evaluator* evaluator) - : evaluator_(evaluator), - position_(evaluator->NumParameters()), - direction_(evaluator->NumEffectiveParameters()), - evaluation_point_(evaluator->NumParameters()), - scaled_direction_(evaluator->NumEffectiveParameters()), - gradient_(evaluator->NumEffectiveParameters()), - initial_evaluator_residual_time_in_seconds(0.0), - initial_evaluator_jacobian_time_in_seconds(0.0) {} - -void LineSearchFunction::Init(const Vector& position, - const Vector& direction) { - position_ = position; - direction_ = direction; -} - -bool LineSearchFunction::Evaluate(double x, double* f, double* g) { - scaled_direction_ = x * direction_; - if (!evaluator_->Plus(position_.data(), - scaled_direction_.data(), - evaluation_point_.data())) { - return false; - } - - if (g == NULL) { - return (evaluator_->Evaluate(evaluation_point_.data(), - f, NULL, NULL, NULL) && - IsFinite(*f)); - } - - if (!evaluator_->Evaluate(evaluation_point_.data(), - f, NULL, gradient_.data(), NULL)) { - return false; - } - - *g = direction_.dot(gradient_); - return IsFinite(*f) && IsFinite(*g); -} - -double LineSearchFunction::DirectionInfinityNorm() const { - return direction_.lpNorm<Eigen::Infinity>(); -} - -void LineSearchFunction::ResetTimeStatistics() { - const map<string, double> evaluator_time_statistics = - evaluator_->TimeStatistics(); - initial_evaluator_residual_time_in_seconds = - FindWithDefault(evaluator_time_statistics, "Evaluator::Residual", 0.0); - initial_evaluator_jacobian_time_in_seconds = - FindWithDefault(evaluator_time_statistics, "Evaluator::Jacobian", 0.0); -} - -void LineSearchFunction::TimeStatistics( - double* cost_evaluation_time_in_seconds, - double* gradient_evaluation_time_in_seconds) const { - const map<string, double> evaluator_time_statistics = - evaluator_->TimeStatistics(); - *cost_evaluation_time_in_seconds = - FindWithDefault(evaluator_time_statistics, "Evaluator::Residual", 0.0) - - initial_evaluator_residual_time_in_seconds; - // Strictly speaking this will slightly underestimate the time spent - // evaluating the gradient of the line search univariate cost function as it - // does not count the time spent performing the dot product with the direction - // vector. However, this will typically be small by comparison, and also - // allows direct subtraction of the timing information from the totals for - // the evaluator returned in the solver summary. - *gradient_evaluation_time_in_seconds = - FindWithDefault(evaluator_time_statistics, "Evaluator::Jacobian", 0.0) - - initial_evaluator_jacobian_time_in_seconds; -} - -void LineSearch::Search(double step_size_estimate, - double initial_cost, - double initial_gradient, - Summary* summary) const { - const double start_time = WallTimeInSeconds(); - *CHECK_NOTNULL(summary) = LineSearch::Summary(); - - summary->cost_evaluation_time_in_seconds = 0.0; - summary->gradient_evaluation_time_in_seconds = 0.0; - summary->polynomial_minimization_time_in_seconds = 0.0; - - options().function->ResetTimeStatistics(); - this->DoSearch(step_size_estimate, initial_cost, initial_gradient, summary); - options().function-> - TimeStatistics(&summary->cost_evaluation_time_in_seconds, - &summary->gradient_evaluation_time_in_seconds); - - summary->total_time_in_seconds = WallTimeInSeconds() - start_time; -} - -// Returns step_size \in [min_step_size, max_step_size] which minimizes the -// polynomial of degree defined by interpolation_type which interpolates all -// of the provided samples with valid values. -double LineSearch::InterpolatingPolynomialMinimizingStepSize( - const LineSearchInterpolationType& interpolation_type, - const FunctionSample& lowerbound, - const FunctionSample& previous, - const FunctionSample& current, - const double min_step_size, - const double max_step_size) const { - if (!current.value_is_valid || - (interpolation_type == BISECTION && - max_step_size <= current.x)) { - // Either: sample is invalid; or we are using BISECTION and contracting - // the step size. - return std::min(std::max(current.x * 0.5, min_step_size), max_step_size); - } else if (interpolation_type == BISECTION) { - CHECK_GT(max_step_size, current.x); - // We are expanding the search (during a Wolfe bracketing phase) using - // BISECTION interpolation. Using BISECTION when trying to expand is - // strictly speaking an oxymoron, but we define this to mean always taking - // the maximum step size so that the Armijo & Wolfe implementations are - // agnostic to the interpolation type. - return max_step_size; - } - // Only check if lower-bound is valid here, where it is required - // to avoid replicating current.value_is_valid == false - // behaviour in WolfeLineSearch. - CHECK(lowerbound.value_is_valid) - << std::scientific << std::setprecision(kErrorMessageNumericPrecision) - << "Ceres bug: lower-bound sample for interpolation is invalid, " - << "please contact the developers!, interpolation_type: " - << LineSearchInterpolationTypeToString(interpolation_type) - << ", lowerbound: " << lowerbound << ", previous: " << previous - << ", current: " << current; - - // Select step size by interpolating the function and gradient values - // and minimizing the corresponding polynomial. - vector<FunctionSample> samples; - samples.push_back(lowerbound); - - if (interpolation_type == QUADRATIC) { - // Two point interpolation using function values and the - // gradient at the lower bound. - samples.push_back(ValueSample(current.x, current.value)); - - if (previous.value_is_valid) { - // Three point interpolation, using function values and the - // gradient at the lower bound. - samples.push_back(ValueSample(previous.x, previous.value)); - } - } else if (interpolation_type == CUBIC) { - // Two point interpolation using the function values and the gradients. - samples.push_back(current); - - if (previous.value_is_valid) { - // Three point interpolation using the function values and - // the gradients. - samples.push_back(previous); - } - } else { - LOG(FATAL) << "Ceres bug: No handler for interpolation_type: " - << LineSearchInterpolationTypeToString(interpolation_type) - << ", please contact the developers!"; - } - - double step_size = 0.0, unused_min_value = 0.0; - MinimizeInterpolatingPolynomial(samples, min_step_size, max_step_size, - &step_size, &unused_min_value); - return step_size; -} - -ArmijoLineSearch::ArmijoLineSearch(const LineSearch::Options& options) - : LineSearch(options) {} - -void ArmijoLineSearch::DoSearch(const double step_size_estimate, - const double initial_cost, - const double initial_gradient, - Summary* summary) const { - CHECK_GE(step_size_estimate, 0.0); - CHECK_GT(options().sufficient_decrease, 0.0); - CHECK_LT(options().sufficient_decrease, 1.0); - CHECK_GT(options().max_num_iterations, 0); - LineSearchFunction* function = options().function; - - // Note initial_cost & initial_gradient are evaluated at step_size = 0, - // not step_size_estimate, which is our starting guess. - const FunctionSample initial_position = - ValueAndGradientSample(0.0, initial_cost, initial_gradient); - - FunctionSample previous = ValueAndGradientSample(0.0, 0.0, 0.0); - previous.value_is_valid = false; - - FunctionSample current = ValueAndGradientSample(step_size_estimate, 0.0, 0.0); - current.value_is_valid = false; - - // As the Armijo line search algorithm always uses the initial point, for - // which both the function value and derivative are known, when fitting a - // minimizing polynomial, we can fit up to a quadratic without requiring the - // gradient at the current query point. - const bool interpolation_uses_gradient_at_current_sample = - options().interpolation_type == CUBIC; - const double descent_direction_max_norm = function->DirectionInfinityNorm(); - - ++summary->num_function_evaluations; - if (interpolation_uses_gradient_at_current_sample) { - ++summary->num_gradient_evaluations; - } - current.value_is_valid = - function->Evaluate(current.x, - ¤t.value, - interpolation_uses_gradient_at_current_sample - ? ¤t.gradient : NULL); - current.gradient_is_valid = - interpolation_uses_gradient_at_current_sample && current.value_is_valid; - while (!current.value_is_valid || - current.value > (initial_cost - + options().sufficient_decrease - * initial_gradient - * current.x)) { - // If current.value_is_valid is false, we treat it as if the cost at that - // point is not large enough to satisfy the sufficient decrease condition. - ++summary->num_iterations; - if (summary->num_iterations >= options().max_num_iterations) { - summary->error = - StringPrintf("Line search failed: Armijo failed to find a point " - "satisfying the sufficient decrease condition within " - "specified max_num_iterations: %d.", - options().max_num_iterations); - LOG_IF(WARNING, !options().is_silent) << summary->error; - return; - } - - const double polynomial_minimization_start_time = WallTimeInSeconds(); - const double step_size = - this->InterpolatingPolynomialMinimizingStepSize( - options().interpolation_type, - initial_position, - previous, - current, - (options().max_step_contraction * current.x), - (options().min_step_contraction * current.x)); - summary->polynomial_minimization_time_in_seconds += - (WallTimeInSeconds() - polynomial_minimization_start_time); - - if (step_size * descent_direction_max_norm < options().min_step_size) { - summary->error = - StringPrintf("Line search failed: step_size too small: %.5e " - "with descent_direction_max_norm: %.5e.", step_size, - descent_direction_max_norm); - LOG_IF(WARNING, !options().is_silent) << summary->error; - return; - } - - previous = current; - current.x = step_size; - - ++summary->num_function_evaluations; - if (interpolation_uses_gradient_at_current_sample) { - ++summary->num_gradient_evaluations; - } - current.value_is_valid = - function->Evaluate(current.x, - ¤t.value, - interpolation_uses_gradient_at_current_sample - ? ¤t.gradient : NULL); - current.gradient_is_valid = - interpolation_uses_gradient_at_current_sample && current.value_is_valid; - } - - summary->optimal_step_size = current.x; - summary->success = true; -} - -WolfeLineSearch::WolfeLineSearch(const LineSearch::Options& options) - : LineSearch(options) {} - -void WolfeLineSearch::DoSearch(const double step_size_estimate, - const double initial_cost, - const double initial_gradient, - Summary* summary) const { - // All parameters should have been validated by the Solver, but as - // invalid values would produce crazy nonsense, hard check them here. - CHECK_GE(step_size_estimate, 0.0); - CHECK_GT(options().sufficient_decrease, 0.0); - CHECK_GT(options().sufficient_curvature_decrease, - options().sufficient_decrease); - CHECK_LT(options().sufficient_curvature_decrease, 1.0); - CHECK_GT(options().max_step_expansion, 1.0); - - // Note initial_cost & initial_gradient are evaluated at step_size = 0, - // not step_size_estimate, which is our starting guess. - const FunctionSample initial_position = - ValueAndGradientSample(0.0, initial_cost, initial_gradient); - - bool do_zoom_search = false; - // Important: The high/low in bracket_high & bracket_low refer to their - // _function_ values, not their step sizes i.e. it is _not_ required that - // bracket_low.x < bracket_high.x. - FunctionSample solution, bracket_low, bracket_high; - - // Wolfe bracketing phase: Increases step_size until either it finds a point - // that satisfies the (strong) Wolfe conditions, or an interval that brackets - // step sizes which satisfy the conditions. From Nocedal & Wright [1] p61 the - // interval: (step_size_{k-1}, step_size_{k}) contains step lengths satisfying - // the strong Wolfe conditions if one of the following conditions are met: - // - // 1. step_size_{k} violates the sufficient decrease (Armijo) condition. - // 2. f(step_size_{k}) >= f(step_size_{k-1}). - // 3. f'(step_size_{k}) >= 0. - // - // Caveat: If f(step_size_{k}) is invalid, then step_size is reduced, ignoring - // this special case, step_size monotonically increases during bracketing. - if (!this->BracketingPhase(initial_position, - step_size_estimate, - &bracket_low, - &bracket_high, - &do_zoom_search, - summary)) { - // Failed to find either a valid point, a valid bracket satisfying the Wolfe - // conditions, or even a step size > minimum tolerance satisfying the Armijo - // condition. - return; - } - - if (!do_zoom_search) { - // Either: Bracketing phase already found a point satisfying the strong - // Wolfe conditions, thus no Zoom required. - // - // Or: Bracketing failed to find a valid bracket or a point satisfying the - // strong Wolfe conditions within max_num_iterations, or whilst searching - // shrank the bracket width until it was below our minimum tolerance. - // As these are 'artificial' constraints, and we would otherwise fail to - // produce a valid point when ArmijoLineSearch would succeed, we return the - // point with the lowest cost found thus far which satsifies the Armijo - // condition (but not the Wolfe conditions). - summary->optimal_step_size = bracket_low.x; - summary->success = true; - return; - } - - VLOG(3) << std::scientific << std::setprecision(kErrorMessageNumericPrecision) - << "Starting line search zoom phase with bracket_low: " - << bracket_low << ", bracket_high: " << bracket_high - << ", bracket width: " << fabs(bracket_low.x - bracket_high.x) - << ", bracket abs delta cost: " - << fabs(bracket_low.value - bracket_high.value); - - // Wolfe Zoom phase: Called when the Bracketing phase finds an interval of - // non-zero, finite width that should bracket step sizes which satisfy the - // (strong) Wolfe conditions (before finding a step size that satisfies the - // conditions). Zoom successively decreases the size of the interval until a - // step size which satisfies the Wolfe conditions is found. The interval is - // defined by bracket_low & bracket_high, which satisfy: - // - // 1. The interval bounded by step sizes: bracket_low.x & bracket_high.x - // contains step sizes that satsify the strong Wolfe conditions. - // 2. bracket_low.x is of all the step sizes evaluated *which satisifed the - // Armijo sufficient decrease condition*, the one which generated the - // smallest function value, i.e. bracket_low.value < - // f(all other steps satisfying Armijo). - // - Note that this does _not_ (necessarily) mean that initially - // bracket_low.value < bracket_high.value (although this is typical) - // e.g. when bracket_low = initial_position, and bracket_high is the - // first sample, and which does not satisfy the Armijo condition, - // but still has bracket_high.value < initial_position.value. - // 3. bracket_high is chosen after bracket_low, s.t. - // bracket_low.gradient * (bracket_high.x - bracket_low.x) < 0. - if (!this->ZoomPhase(initial_position, - bracket_low, - bracket_high, - &solution, - summary) && !solution.value_is_valid) { - // Failed to find a valid point (given the specified decrease parameters) - // within the specified bracket. - return; - } - // Ensure that if we ran out of iterations whilst zooming the bracket, or - // shrank the bracket width to < tolerance and failed to find a point which - // satisfies the strong Wolfe curvature condition, that we return the point - // amongst those found thus far, which minimizes f() and satisfies the Armijo - // condition. - solution = - solution.value_is_valid && solution.value <= bracket_low.value - ? solution : bracket_low; - - summary->optimal_step_size = solution.x; - summary->success = true; -} - -// Returns true if either: -// -// A termination condition satisfying the (strong) Wolfe bracketing conditions -// is found: -// -// - A valid point, defined as a bracket of zero width [zoom not required]. -// - A valid bracket (of width > tolerance), [zoom required]. -// -// Or, searching was stopped due to an 'artificial' constraint, i.e. not -// a condition imposed / required by the underlying algorithm, but instead an -// engineering / implementation consideration. But a step which exceeds the -// minimum step size, and satsifies the Armijo condition was still found, -// and should thus be used [zoom not required]. -// -// Returns false if no step size > minimum step size was found which -// satisfies at least the Armijo condition. -bool WolfeLineSearch::BracketingPhase( - const FunctionSample& initial_position, - const double step_size_estimate, - FunctionSample* bracket_low, - FunctionSample* bracket_high, - bool* do_zoom_search, - Summary* summary) const { - LineSearchFunction* function = options().function; - - FunctionSample previous = initial_position; - FunctionSample current = ValueAndGradientSample(step_size_estimate, 0.0, 0.0); - current.value_is_valid = false; - - const double descent_direction_max_norm = - function->DirectionInfinityNorm(); - - *do_zoom_search = false; - *bracket_low = initial_position; - - // As we require the gradient to evaluate the Wolfe condition, we always - // calculate it together with the value, irrespective of the interpolation - // type. As opposed to only calculating the gradient after the Armijo - // condition is satisifed, as the computational saving from this approach - // would be slight (perhaps even negative due to the extra call). Also, - // always calculating the value & gradient together protects against us - // reporting invalid solutions if the cost function returns slightly different - // function values when evaluated with / without gradients (due to numerical - // issues). - ++summary->num_function_evaluations; - ++summary->num_gradient_evaluations; - current.value_is_valid = - function->Evaluate(current.x, - ¤t.value, - ¤t.gradient); - current.gradient_is_valid = current.value_is_valid; - - while (true) { - ++summary->num_iterations; - - if (current.value_is_valid && - (current.value > (initial_position.value - + options().sufficient_decrease - * initial_position.gradient - * current.x) || - (previous.value_is_valid && current.value > previous.value))) { - // Bracket found: current step size violates Armijo sufficient decrease - // condition, or has stepped past an inflection point of f() relative to - // previous step size. - *do_zoom_search = true; - *bracket_low = previous; - *bracket_high = current; - VLOG(3) << std::scientific - << std::setprecision(kErrorMessageNumericPrecision) - << "Bracket found: current step (" << current.x - << ") violates Armijo sufficient condition, or has passed an " - << "inflection point of f() based on value."; - break; - } - - if (current.value_is_valid && - fabs(current.gradient) <= - -options().sufficient_curvature_decrease * initial_position.gradient) { - // Current step size satisfies the strong Wolfe conditions, and is thus a - // valid termination point, therefore a Zoom not required. - *bracket_low = current; - *bracket_high = current; - VLOG(3) << std::scientific - << std::setprecision(kErrorMessageNumericPrecision) - << "Bracketing phase found step size: " << current.x - << ", satisfying strong Wolfe conditions, initial_position: " - << initial_position << ", current: " << current; - break; - - } else if (current.value_is_valid && current.gradient >= 0) { - // Bracket found: current step size has stepped past an inflection point - // of f(), but Armijo sufficient decrease is still satisfied and - // f(current) is our best minimum thus far. Remember step size - // monotonically increases, thus previous_step_size < current_step_size - // even though f(previous) > f(current). - *do_zoom_search = true; - // Note inverse ordering from first bracket case. - *bracket_low = current; - *bracket_high = previous; - VLOG(3) << "Bracket found: current step (" << current.x - << ") satisfies Armijo, but has gradient >= 0, thus have passed " - << "an inflection point of f()."; - break; - - } else if (current.value_is_valid && - fabs(current.x - previous.x) * descent_direction_max_norm - < options().min_step_size) { - // We have shrunk the search bracket to a width less than our tolerance, - // and still not found either a point satisfying the strong Wolfe - // conditions, or a valid bracket containing such a point. Stop searching - // and set bracket_low to the size size amongst all those tested which - // minimizes f() and satisfies the Armijo condition. - LOG_IF(WARNING, !options().is_silent) - << "Line search failed: Wolfe bracketing phase shrank " - << "bracket width: " << fabs(current.x - previous.x) - << ", to < tolerance: " << options().min_step_size - << ", with descent_direction_max_norm: " - << descent_direction_max_norm << ", and failed to find " - << "a point satisfying the strong Wolfe conditions or a " - << "bracketing containing such a point. Accepting " - << "point found satisfying Armijo condition only, to " - << "allow continuation."; - *bracket_low = current; - break; - - } else if (summary->num_iterations >= options().max_num_iterations) { - // Check num iterations bound here so that we always evaluate the - // max_num_iterations-th iteration against all conditions, and - // then perform no additional (unused) evaluations. - summary->error = - StringPrintf("Line search failed: Wolfe bracketing phase failed to " - "find a point satisfying strong Wolfe conditions, or a " - "bracket containing such a point within specified " - "max_num_iterations: %d", options().max_num_iterations); - LOG_IF(WARNING, !options().is_silent) << summary->error; - // Ensure that bracket_low is always set to the step size amongst all - // those tested which minimizes f() and satisfies the Armijo condition - // when we terminate due to the 'artificial' max_num_iterations condition. - *bracket_low = - current.value_is_valid && current.value < bracket_low->value - ? current : *bracket_low; - break; - } - // Either: f(current) is invalid; or, f(current) is valid, but does not - // satisfy the strong Wolfe conditions itself, or the conditions for - // being a boundary of a bracket. - - // If f(current) is valid, (but meets no criteria) expand the search by - // increasing the step size. - const double max_step_size = - current.value_is_valid - ? (current.x * options().max_step_expansion) : current.x; - - // We are performing 2-point interpolation only here, but the API of - // InterpolatingPolynomialMinimizingStepSize() allows for up to - // 3-point interpolation, so pad call with a sample with an invalid - // value that will therefore be ignored. - const FunctionSample unused_previous; - DCHECK(!unused_previous.value_is_valid); - // Contracts step size if f(current) is not valid. - const double polynomial_minimization_start_time = WallTimeInSeconds(); - const double step_size = - this->InterpolatingPolynomialMinimizingStepSize( - options().interpolation_type, - previous, - unused_previous, - current, - previous.x, - max_step_size); - summary->polynomial_minimization_time_in_seconds += - (WallTimeInSeconds() - polynomial_minimization_start_time); - if (step_size * descent_direction_max_norm < options().min_step_size) { - summary->error = - StringPrintf("Line search failed: step_size too small: %.5e " - "with descent_direction_max_norm: %.5e", step_size, - descent_direction_max_norm); - LOG_IF(WARNING, !options().is_silent) << summary->error; - return false; - } - - previous = current.value_is_valid ? current : previous; - current.x = step_size; - - ++summary->num_function_evaluations; - ++summary->num_gradient_evaluations; - current.value_is_valid = - function->Evaluate(current.x, - ¤t.value, - ¤t.gradient); - current.gradient_is_valid = current.value_is_valid; - } - - // Ensure that even if a valid bracket was found, we will only mark a zoom - // as required if the bracket's width is greater than our minimum tolerance. - if (*do_zoom_search && - fabs(bracket_high->x - bracket_low->x) * descent_direction_max_norm - < options().min_step_size) { - *do_zoom_search = false; - } - - return true; -} - -// Returns true iff solution satisfies the strong Wolfe conditions. Otherwise, -// on return false, if we stopped searching due to the 'artificial' condition of -// reaching max_num_iterations, solution is the step size amongst all those -// tested, which satisfied the Armijo decrease condition and minimized f(). -bool WolfeLineSearch::ZoomPhase(const FunctionSample& initial_position, - FunctionSample bracket_low, - FunctionSample bracket_high, - FunctionSample* solution, - Summary* summary) const { - LineSearchFunction* function = options().function; - - CHECK(bracket_low.value_is_valid && bracket_low.gradient_is_valid) - << std::scientific << std::setprecision(kErrorMessageNumericPrecision) - << "Ceres bug: f_low input to Wolfe Zoom invalid, please contact " - << "the developers!, initial_position: " << initial_position - << ", bracket_low: " << bracket_low - << ", bracket_high: "<< bracket_high; - // We do not require bracket_high.gradient_is_valid as the gradient condition - // for a valid bracket is only dependent upon bracket_low.gradient, and - // in order to minimize jacobian evaluations, bracket_high.gradient may - // not have been calculated (if bracket_high.value does not satisfy the - // Armijo sufficient decrease condition and interpolation method does not - // require it). - // - // We also do not require that: bracket_low.value < bracket_high.value, - // although this is typical. This is to deal with the case when - // bracket_low = initial_position, bracket_high is the first sample, - // and bracket_high does not satisfy the Armijo condition, but still has - // bracket_high.value < initial_position.value. - CHECK(bracket_high.value_is_valid) - << std::scientific << std::setprecision(kErrorMessageNumericPrecision) - << "Ceres bug: f_high input to Wolfe Zoom invalid, please " - << "contact the developers!, initial_position: " << initial_position - << ", bracket_low: " << bracket_low - << ", bracket_high: "<< bracket_high; - - if (bracket_low.gradient * (bracket_high.x - bracket_low.x) >= 0) { - // The third condition for a valid initial bracket: - // - // 3. bracket_high is chosen after bracket_low, s.t. - // bracket_low.gradient * (bracket_high.x - bracket_low.x) < 0. - // - // is not satisfied. As this can happen when the users' cost function - // returns inconsistent gradient values relative to the function values, - // we do not CHECK_LT(), but we do stop processing and return an invalid - // value. - summary->error = - StringPrintf("Line search failed: Wolfe zoom phase passed a bracket " - "which does not satisfy: bracket_low.gradient * " - "(bracket_high.x - bracket_low.x) < 0 [%.8e !< 0] " - "with initial_position: %s, bracket_low: %s, bracket_high:" - " %s, the most likely cause of which is the cost function " - "returning inconsistent gradient & function values.", - bracket_low.gradient * (bracket_high.x - bracket_low.x), - initial_position.ToDebugString().c_str(), - bracket_low.ToDebugString().c_str(), - bracket_high.ToDebugString().c_str()); - LOG_IF(WARNING, !options().is_silent) << summary->error; - solution->value_is_valid = false; - return false; - } - - const int num_bracketing_iterations = summary->num_iterations; - const double descent_direction_max_norm = function->DirectionInfinityNorm(); - - while (true) { - // Set solution to bracket_low, as it is our best step size (smallest f()) - // found thus far and satisfies the Armijo condition, even though it does - // not satisfy the Wolfe condition. - *solution = bracket_low; - if (summary->num_iterations >= options().max_num_iterations) { - summary->error = - StringPrintf("Line search failed: Wolfe zoom phase failed to " - "find a point satisfying strong Wolfe conditions " - "within specified max_num_iterations: %d, " - "(num iterations taken for bracketing: %d).", - options().max_num_iterations, num_bracketing_iterations); - LOG_IF(WARNING, !options().is_silent) << summary->error; - return false; - } - if (fabs(bracket_high.x - bracket_low.x) * descent_direction_max_norm - < options().min_step_size) { - // Bracket width has been reduced below tolerance, and no point satisfying - // the strong Wolfe conditions has been found. - summary->error = - StringPrintf("Line search failed: Wolfe zoom bracket width: %.5e " - "too small with descent_direction_max_norm: %.5e.", - fabs(bracket_high.x - bracket_low.x), - descent_direction_max_norm); - LOG_IF(WARNING, !options().is_silent) << summary->error; - return false; - } - - ++summary->num_iterations; - // Polynomial interpolation requires inputs ordered according to step size, - // not f(step size). - const FunctionSample& lower_bound_step = - bracket_low.x < bracket_high.x ? bracket_low : bracket_high; - const FunctionSample& upper_bound_step = - bracket_low.x < bracket_high.x ? bracket_high : bracket_low; - // We are performing 2-point interpolation only here, but the API of - // InterpolatingPolynomialMinimizingStepSize() allows for up to - // 3-point interpolation, so pad call with a sample with an invalid - // value that will therefore be ignored. - const FunctionSample unused_previous; - DCHECK(!unused_previous.value_is_valid); - const double polynomial_minimization_start_time = WallTimeInSeconds(); - solution->x = - this->InterpolatingPolynomialMinimizingStepSize( - options().interpolation_type, - lower_bound_step, - unused_previous, - upper_bound_step, - lower_bound_step.x, - upper_bound_step.x); - summary->polynomial_minimization_time_in_seconds += - (WallTimeInSeconds() - polynomial_minimization_start_time); - // No check on magnitude of step size being too small here as it is - // lower-bounded by the initial bracket start point, which was valid. - // - // As we require the gradient to evaluate the Wolfe condition, we always - // calculate it together with the value, irrespective of the interpolation - // type. As opposed to only calculating the gradient after the Armijo - // condition is satisifed, as the computational saving from this approach - // would be slight (perhaps even negative due to the extra call). Also, - // always calculating the value & gradient together protects against us - // reporting invalid solutions if the cost function returns slightly - // different function values when evaluated with / without gradients (due - // to numerical issues). - ++summary->num_function_evaluations; - ++summary->num_gradient_evaluations; - solution->value_is_valid = - function->Evaluate(solution->x, - &solution->value, - &solution->gradient); - solution->gradient_is_valid = solution->value_is_valid; - if (!solution->value_is_valid) { - summary->error = - StringPrintf("Line search failed: Wolfe Zoom phase found " - "step_size: %.5e, for which function is invalid, " - "between low_step: %.5e and high_step: %.5e " - "at which function is valid.", - solution->x, bracket_low.x, bracket_high.x); - LOG_IF(WARNING, !options().is_silent) << summary->error; - return false; - } - - VLOG(3) << "Zoom iteration: " - << summary->num_iterations - num_bracketing_iterations - << ", bracket_low: " << bracket_low - << ", bracket_high: " << bracket_high - << ", minimizing solution: " << *solution; - - if ((solution->value > (initial_position.value - + options().sufficient_decrease - * initial_position.gradient - * solution->x)) || - (solution->value >= bracket_low.value)) { - // Armijo sufficient decrease not satisfied, or not better - // than current lowest sample, use as new upper bound. - bracket_high = *solution; - continue; - } - - // Armijo sufficient decrease satisfied, check strong Wolfe condition. - if (fabs(solution->gradient) <= - -options().sufficient_curvature_decrease * initial_position.gradient) { - // Found a valid termination point satisfying strong Wolfe conditions. - VLOG(3) << std::scientific - << std::setprecision(kErrorMessageNumericPrecision) - << "Zoom phase found step size: " << solution->x - << ", satisfying strong Wolfe conditions."; - break; - - } else if (solution->gradient * (bracket_high.x - bracket_low.x) >= 0) { - bracket_high = bracket_low; - } - - bracket_low = *solution; - } - // Solution contains a valid point which satisfies the strong Wolfe - // conditions. - return true; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/line_search.h b/extern/libmv/third_party/ceres/internal/ceres/line_search.h deleted file mode 100644 index 6a21cbeac11..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/line_search.h +++ /dev/null @@ -1,327 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Interface for and implementation of various Line search algorithms. - -#ifndef CERES_INTERNAL_LINE_SEARCH_H_ -#define CERES_INTERNAL_LINE_SEARCH_H_ - -#include <string> -#include <vector> -#include "ceres/internal/eigen.h" -#include "ceres/internal/port.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -class Evaluator; -struct FunctionSample; -class LineSearchFunction; - -// Line search is another name for a one dimensional optimization -// algorithm. The name "line search" comes from the fact one -// dimensional optimization problems that arise as subproblems of -// general multidimensional optimization problems. -// -// While finding the exact minimum of a one dimensionl function is -// hard, instances of LineSearch find a point that satisfies a -// sufficient decrease condition. Depending on the particular -// condition used, we get a variety of different line search -// algorithms, e.g., Armijo, Wolfe etc. -class LineSearch { - public: - struct Summary; - - struct Options { - Options() - : interpolation_type(CUBIC), - sufficient_decrease(1e-4), - max_step_contraction(1e-3), - min_step_contraction(0.9), - min_step_size(1e-9), - max_num_iterations(20), - sufficient_curvature_decrease(0.9), - max_step_expansion(10.0), - is_silent(false), - function(NULL) {} - - // Degree of the polynomial used to approximate the objective - // function. - LineSearchInterpolationType interpolation_type; - - // Armijo and Wolfe line search parameters. - - // Solving the line search problem exactly is computationally - // prohibitive. Fortunately, line search based optimization - // algorithms can still guarantee convergence if instead of an - // exact solution, the line search algorithm returns a solution - // which decreases the value of the objective function - // sufficiently. More precisely, we are looking for a step_size - // s.t. - // - // f(step_size) <= f(0) + sufficient_decrease * f'(0) * step_size - double sufficient_decrease; - - // In each iteration of the Armijo / Wolfe line search, - // - // new_step_size >= max_step_contraction * step_size - // - // Note that by definition, for contraction: - // - // 0 < max_step_contraction < min_step_contraction < 1 - // - double max_step_contraction; - - // In each iteration of the Armijo / Wolfe line search, - // - // new_step_size <= min_step_contraction * step_size - // Note that by definition, for contraction: - // - // 0 < max_step_contraction < min_step_contraction < 1 - // - double min_step_contraction; - - // If during the line search, the step_size falls below this - // value, it is truncated to zero. - double min_step_size; - - // Maximum number of trial step size iterations during each line search, - // if a step size satisfying the search conditions cannot be found within - // this number of trials, the line search will terminate. - int max_num_iterations; - - // Wolfe-specific line search parameters. - - // The strong Wolfe conditions consist of the Armijo sufficient - // decrease condition, and an additional requirement that the - // step-size be chosen s.t. the _magnitude_ ('strong' Wolfe - // conditions) of the gradient along the search direction - // decreases sufficiently. Precisely, this second condition - // is that we seek a step_size s.t. - // - // |f'(step_size)| <= sufficient_curvature_decrease * |f'(0)| - // - // Where f() is the line search objective and f'() is the derivative - // of f w.r.t step_size (d f / d step_size). - double sufficient_curvature_decrease; - - // During the bracketing phase of the Wolfe search, the step size is - // increased until either a point satisfying the Wolfe conditions is - // found, or an upper bound for a bracket containing a point satisfying - // the conditions is found. Precisely, at each iteration of the - // expansion: - // - // new_step_size <= max_step_expansion * step_size. - // - // By definition for expansion, max_step_expansion > 1.0. - double max_step_expansion; - - bool is_silent; - - // The one dimensional function that the line search algorithm - // minimizes. - LineSearchFunction* function; - }; - - // Result of the line search. - struct Summary { - Summary() - : success(false), - optimal_step_size(0.0), - num_function_evaluations(0), - num_gradient_evaluations(0), - num_iterations(0), - cost_evaluation_time_in_seconds(-1.0), - gradient_evaluation_time_in_seconds(-1.0), - polynomial_minimization_time_in_seconds(-1.0), - total_time_in_seconds(-1.0) {} - - bool success; - double optimal_step_size; - int num_function_evaluations; - int num_gradient_evaluations; - int num_iterations; - // Cumulative time spent evaluating the value of the cost function across - // all iterations. - double cost_evaluation_time_in_seconds; - // Cumulative time spent evaluating the gradient of the cost function across - // all iterations. - double gradient_evaluation_time_in_seconds; - // Cumulative time spent minimizing the interpolating polynomial to compute - // the next candidate step size across all iterations. - double polynomial_minimization_time_in_seconds; - double total_time_in_seconds; - std::string error; - }; - - explicit LineSearch(const LineSearch::Options& options); - virtual ~LineSearch() {} - - static LineSearch* Create(const LineSearchType line_search_type, - const LineSearch::Options& options, - std::string* error); - - // Perform the line search. - // - // step_size_estimate must be a positive number. - // - // initial_cost and initial_gradient are the values and gradient of - // the function at zero. - // summary must not be null and will contain the result of the line - // search. - // - // Summary::success is true if a non-zero step size is found. - void Search(double step_size_estimate, - double initial_cost, - double initial_gradient, - Summary* summary) const; - double InterpolatingPolynomialMinimizingStepSize( - const LineSearchInterpolationType& interpolation_type, - const FunctionSample& lowerbound_sample, - const FunctionSample& previous_sample, - const FunctionSample& current_sample, - const double min_step_size, - const double max_step_size) const; - - protected: - const LineSearch::Options& options() const { return options_; } - - private: - virtual void DoSearch(double step_size_estimate, - double initial_cost, - double initial_gradient, - Summary* summary) const = 0; - - private: - LineSearch::Options options_; -}; - -// An object used by the line search to access the function values -// and gradient of the one dimensional function being optimized. -// -// In practice, this object provides access to the objective -// function value and the directional derivative of the underlying -// optimization problem along a specific search direction. -class LineSearchFunction { - public: - explicit LineSearchFunction(Evaluator* evaluator); - void Init(const Vector& position, const Vector& direction); - // Evaluate the line search objective - // - // f(x) = p(position + x * direction) - // - // Where, p is the objective function of the general optimization - // problem. - // - // g is the gradient f'(x) at x. - // - // f must not be null. The gradient is computed only if g is not null. - bool Evaluate(double x, double* f, double* g); - double DirectionInfinityNorm() const; - // Resets to now, the start point for the results from TimeStatistics(). - void ResetTimeStatistics(); - void TimeStatistics(double* cost_evaluation_time_in_seconds, - double* gradient_evaluation_time_in_seconds) const; - - private: - Evaluator* evaluator_; - Vector position_; - Vector direction_; - - // evaluation_point = Evaluator::Plus(position_, x * direction_); - Vector evaluation_point_; - - // scaled_direction = x * direction_; - Vector scaled_direction_; - Vector gradient_; - - // We may not exclusively own the evaluator (e.g. in the Trust Region - // minimizer), hence we need to save the initial evaluation durations for the - // value & gradient to accurately determine the duration of the evaluations - // we invoked. These are reset by a call to ResetTimeStatistics(). - double initial_evaluator_residual_time_in_seconds; - double initial_evaluator_jacobian_time_in_seconds; -}; - -// Backtracking and interpolation based Armijo line search. This -// implementation is based on the Armijo line search that ships in the -// minFunc package by Mark Schmidt. -// -// For more details: http://www.di.ens.fr/~mschmidt/Software/minFunc.html -class ArmijoLineSearch : public LineSearch { - public: - explicit ArmijoLineSearch(const LineSearch::Options& options); - virtual ~ArmijoLineSearch() {} - - private: - virtual void DoSearch(double step_size_estimate, - double initial_cost, - double initial_gradient, - Summary* summary) const; -}; - -// Bracketing / Zoom Strong Wolfe condition line search. This implementation -// is based on the pseudo-code algorithm presented in Nocedal & Wright [1] -// (p60-61) with inspiration from the WolfeLineSearch which ships with the -// minFunc package by Mark Schmidt [2]. -// -// [1] Nocedal J., Wright S., Numerical Optimization, 2nd Ed., Springer, 1999. -// [2] http://www.di.ens.fr/~mschmidt/Software/minFunc.html. -class WolfeLineSearch : public LineSearch { - public: - explicit WolfeLineSearch(const LineSearch::Options& options); - virtual ~WolfeLineSearch() {} - - // Returns true iff either a valid point, or valid bracket are found. - bool BracketingPhase(const FunctionSample& initial_position, - const double step_size_estimate, - FunctionSample* bracket_low, - FunctionSample* bracket_high, - bool* perform_zoom_search, - Summary* summary) const; - // Returns true iff final_line_sample satisfies strong Wolfe conditions. - bool ZoomPhase(const FunctionSample& initial_position, - FunctionSample bracket_low, - FunctionSample bracket_high, - FunctionSample* solution, - Summary* summary) const; - - private: - virtual void DoSearch(double step_size_estimate, - double initial_cost, - double initial_gradient, - Summary* summary) const; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_LINE_SEARCH_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/line_search_direction.cc b/extern/libmv/third_party/ceres/internal/ceres/line_search_direction.cc deleted file mode 100644 index 1f9d205bff5..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/line_search_direction.cc +++ /dev/null @@ -1,372 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/line_search_direction.h" -#include "ceres/line_search_minimizer.h" -#include "ceres/low_rank_inverse_hessian.h" -#include "ceres/internal/eigen.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -class SteepestDescent : public LineSearchDirection { - public: - virtual ~SteepestDescent() {} - bool NextDirection(const LineSearchMinimizer::State& previous, - const LineSearchMinimizer::State& current, - Vector* search_direction) { - *search_direction = -current.gradient; - return true; - } -}; - -class NonlinearConjugateGradient : public LineSearchDirection { - public: - NonlinearConjugateGradient(const NonlinearConjugateGradientType type, - const double function_tolerance) - : type_(type), - function_tolerance_(function_tolerance) { - } - - bool NextDirection(const LineSearchMinimizer::State& previous, - const LineSearchMinimizer::State& current, - Vector* search_direction) { - double beta = 0.0; - Vector gradient_change; - switch (type_) { - case FLETCHER_REEVES: - beta = current.gradient_squared_norm / previous.gradient_squared_norm; - break; - case POLAK_RIBIERE: - gradient_change = current.gradient - previous.gradient; - beta = (current.gradient.dot(gradient_change) / - previous.gradient_squared_norm); - break; - case HESTENES_STIEFEL: - gradient_change = current.gradient - previous.gradient; - beta = (current.gradient.dot(gradient_change) / - previous.search_direction.dot(gradient_change)); - break; - default: - LOG(FATAL) << "Unknown nonlinear conjugate gradient type: " << type_; - } - - *search_direction = -current.gradient + beta * previous.search_direction; - const double directional_derivative = - current.gradient.dot(*search_direction); - if (directional_derivative > -function_tolerance_) { - LOG(WARNING) << "Restarting non-linear conjugate gradients: " - << directional_derivative; - *search_direction = -current.gradient; - } - - return true; - } - - private: - const NonlinearConjugateGradientType type_; - const double function_tolerance_; -}; - -class LBFGS : public LineSearchDirection { - public: - LBFGS(const int num_parameters, - const int max_lbfgs_rank, - const bool use_approximate_eigenvalue_bfgs_scaling) - : low_rank_inverse_hessian_(num_parameters, - max_lbfgs_rank, - use_approximate_eigenvalue_bfgs_scaling), - is_positive_definite_(true) {} - - virtual ~LBFGS() {} - - bool NextDirection(const LineSearchMinimizer::State& previous, - const LineSearchMinimizer::State& current, - Vector* search_direction) { - CHECK(is_positive_definite_) - << "Ceres bug: NextDirection() called on L-BFGS after inverse Hessian " - << "approximation has become indefinite, please contact the " - << "developers!"; - - low_rank_inverse_hessian_.Update( - previous.search_direction * previous.step_size, - current.gradient - previous.gradient); - - search_direction->setZero(); - low_rank_inverse_hessian_.RightMultiply(current.gradient.data(), - search_direction->data()); - *search_direction *= -1.0; - - if (search_direction->dot(current.gradient) >= 0.0) { - LOG(WARNING) << "Numerical failure in L-BFGS update: inverse Hessian " - << "approximation is not positive definite, and thus " - << "initial gradient for search direction is positive: " - << search_direction->dot(current.gradient); - is_positive_definite_ = false; - return false; - } - - return true; - } - - private: - LowRankInverseHessian low_rank_inverse_hessian_; - bool is_positive_definite_; -}; - -class BFGS : public LineSearchDirection { - public: - BFGS(const int num_parameters, - const bool use_approximate_eigenvalue_scaling) - : num_parameters_(num_parameters), - use_approximate_eigenvalue_scaling_(use_approximate_eigenvalue_scaling), - initialized_(false), - is_positive_definite_(true) { - LOG_IF(WARNING, num_parameters_ >= 1e3) - << "BFGS line search being created with: " << num_parameters_ - << " parameters, this will allocate a dense approximate inverse Hessian" - << " of size: " << num_parameters_ << " x " << num_parameters_ - << ", consider using the L-BFGS memory-efficient line search direction " - << "instead."; - // Construct inverse_hessian_ after logging warning about size s.t. if the - // allocation crashes us, the log will highlight what the issue likely was. - inverse_hessian_ = Matrix::Identity(num_parameters, num_parameters); - } - - virtual ~BFGS() {} - - bool NextDirection(const LineSearchMinimizer::State& previous, - const LineSearchMinimizer::State& current, - Vector* search_direction) { - CHECK(is_positive_definite_) - << "Ceres bug: NextDirection() called on BFGS after inverse Hessian " - << "approximation has become indefinite, please contact the " - << "developers!"; - - const Vector delta_x = previous.search_direction * previous.step_size; - const Vector delta_gradient = current.gradient - previous.gradient; - const double delta_x_dot_delta_gradient = delta_x.dot(delta_gradient); - - // The (L)BFGS algorithm explicitly requires that the secant equation: - // - // B_{k+1} * s_k = y_k - // - // Is satisfied at each iteration, where B_{k+1} is the approximated - // Hessian at the k+1-th iteration, s_k = (x_{k+1} - x_{k}) and - // y_k = (grad_{k+1} - grad_{k}). As the approximated Hessian must be - // positive definite, this is equivalent to the condition: - // - // s_k^T * y_k > 0 [s_k^T * B_{k+1} * s_k = s_k^T * y_k > 0] - // - // This condition would always be satisfied if the function was strictly - // convex, alternatively, it is always satisfied provided that a Wolfe line - // search is used (even if the function is not strictly convex). See [1] - // (p138) for a proof. - // - // Although Ceres will always use a Wolfe line search when using (L)BFGS, - // practical implementation considerations mean that the line search - // may return a point that satisfies only the Armijo condition, and thus - // could violate the Secant equation. As such, we will only use a step - // to update the Hessian approximation if: - // - // s_k^T * y_k > tolerance - // - // It is important that tolerance is very small (and >=0), as otherwise we - // might skip the update too often and fail to capture important curvature - // information in the Hessian. For example going from 1e-10 -> 1e-14 - // improves the NIST benchmark score from 43/54 to 53/54. - // - // [1] Nocedal J, Wright S, Numerical Optimization, 2nd Ed. Springer, 1999. - // - // TODO(alexs.mac): Consider using Damped BFGS update instead of - // skipping update. - const double kBFGSSecantConditionHessianUpdateTolerance = 1e-14; - if (delta_x_dot_delta_gradient <= - kBFGSSecantConditionHessianUpdateTolerance) { - VLOG(2) << "Skipping BFGS Update, delta_x_dot_delta_gradient too " - << "small: " << delta_x_dot_delta_gradient << ", tolerance: " - << kBFGSSecantConditionHessianUpdateTolerance - << " (Secant condition)."; - } else { - // Update dense inverse Hessian approximation. - - if (!initialized_ && use_approximate_eigenvalue_scaling_) { - // Rescale the initial inverse Hessian approximation (H_0) to be - // iteratively updated so that it is of similar 'size' to the true - // inverse Hessian at the start point. As shown in [1]: - // - // \gamma = (delta_gradient_{0}' * delta_x_{0}) / - // (delta_gradient_{0}' * delta_gradient_{0}) - // - // Satisfies: - // - // (1 / \lambda_m) <= \gamma <= (1 / \lambda_1) - // - // Where \lambda_1 & \lambda_m are the smallest and largest eigenvalues - // of the true initial Hessian (not the inverse) respectively. Thus, - // \gamma is an approximate eigenvalue of the true inverse Hessian, and - // choosing: H_0 = I * \gamma will yield a starting point that has a - // similar scale to the true inverse Hessian. This technique is widely - // reported to often improve convergence, however this is not - // universally true, particularly if there are errors in the initial - // gradients, or if there are significant differences in the sensitivity - // of the problem to the parameters (i.e. the range of the magnitudes of - // the components of the gradient is large). - // - // The original origin of this rescaling trick is somewhat unclear, the - // earliest reference appears to be Oren [1], however it is widely - // discussed without specific attributation in various texts including - // [2] (p143). - // - // [1] Oren S.S., Self-scaling variable metric (SSVM) algorithms - // Part II: Implementation and experiments, Management Science, - // 20(5), 863-874, 1974. - // [2] Nocedal J., Wright S., Numerical Optimization, Springer, 1999. - const double approximate_eigenvalue_scale = - delta_x_dot_delta_gradient / delta_gradient.dot(delta_gradient); - inverse_hessian_ *= approximate_eigenvalue_scale; - - VLOG(4) << "Applying approximate_eigenvalue_scale: " - << approximate_eigenvalue_scale << " to initial inverse " - << "Hessian approximation."; - } - initialized_ = true; - - // Efficient O(num_parameters^2) BFGS update [2]. - // - // Starting from dense BFGS update detailed in Nocedal [2] p140/177 and - // using: y_k = delta_gradient, s_k = delta_x: - // - // \rho_k = 1.0 / (s_k' * y_k) - // V_k = I - \rho_k * y_k * s_k' - // H_k = (V_k' * H_{k-1} * V_k) + (\rho_k * s_k * s_k') - // - // This update involves matrix, matrix products which naively O(N^3), - // however we can exploit our knowledge that H_k is positive definite - // and thus by defn. symmetric to reduce the cost of the update: - // - // Expanding the update above yields: - // - // H_k = H_{k-1} + - // \rho_k * ( (1.0 + \rho_k * y_k' * H_k * y_k) * s_k * s_k' - - // (s_k * y_k' * H_k + H_k * y_k * s_k') ) - // - // Using: A = (s_k * y_k' * H_k), and the knowledge that H_k = H_k', the - // last term simplifies to (A + A'). Note that although A is not symmetric - // (A + A') is symmetric. For ease of construction we also define - // B = (1 + \rho_k * y_k' * H_k * y_k) * s_k * s_k', which is by defn - // symmetric due to construction from: s_k * s_k'. - // - // Now we can write the BFGS update as: - // - // H_k = H_{k-1} + \rho_k * (B - (A + A')) - - // For efficiency, as H_k is by defn. symmetric, we will only maintain the - // *lower* triangle of H_k (and all intermediary terms). - - const double rho_k = 1.0 / delta_x_dot_delta_gradient; - - // Calculate: A = s_k * y_k' * H_k - Matrix A = delta_x * (delta_gradient.transpose() * - inverse_hessian_.selfadjointView<Eigen::Lower>()); - - // Calculate scalar: (1 + \rho_k * y_k' * H_k * y_k) - const double delta_x_times_delta_x_transpose_scale_factor = - (1.0 + (rho_k * delta_gradient.transpose() * - inverse_hessian_.selfadjointView<Eigen::Lower>() * - delta_gradient)); - // Calculate: B = (1 + \rho_k * y_k' * H_k * y_k) * s_k * s_k' - Matrix B = Matrix::Zero(num_parameters_, num_parameters_); - B.selfadjointView<Eigen::Lower>(). - rankUpdate(delta_x, delta_x_times_delta_x_transpose_scale_factor); - - // Finally, update inverse Hessian approximation according to: - // H_k = H_{k-1} + \rho_k * (B - (A + A')). Note that (A + A') is - // symmetric, even though A is not. - inverse_hessian_.triangularView<Eigen::Lower>() += - rho_k * (B - A - A.transpose()); - } - - *search_direction = - inverse_hessian_.selfadjointView<Eigen::Lower>() * - (-1.0 * current.gradient); - - if (search_direction->dot(current.gradient) >= 0.0) { - LOG(WARNING) << "Numerical failure in BFGS update: inverse Hessian " - << "approximation is not positive definite, and thus " - << "initial gradient for search direction is positive: " - << search_direction->dot(current.gradient); - is_positive_definite_ = false; - return false; - } - - return true; - } - - private: - const int num_parameters_; - const bool use_approximate_eigenvalue_scaling_; - Matrix inverse_hessian_; - bool initialized_; - bool is_positive_definite_; -}; - -LineSearchDirection* -LineSearchDirection::Create(const LineSearchDirection::Options& options) { - if (options.type == STEEPEST_DESCENT) { - return new SteepestDescent; - } - - if (options.type == NONLINEAR_CONJUGATE_GRADIENT) { - return new NonlinearConjugateGradient( - options.nonlinear_conjugate_gradient_type, - options.function_tolerance); - } - - if (options.type == ceres::LBFGS) { - return new ceres::internal::LBFGS( - options.num_parameters, - options.max_lbfgs_rank, - options.use_approximate_eigenvalue_bfgs_scaling); - } - - if (options.type == ceres::BFGS) { - return new ceres::internal::BFGS( - options.num_parameters, - options.use_approximate_eigenvalue_bfgs_scaling); - } - - LOG(ERROR) << "Unknown line search direction type: " << options.type; - return NULL; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/line_search_direction.h b/extern/libmv/third_party/ceres/internal/ceres/line_search_direction.h deleted file mode 100644 index 467578d5f7c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/line_search_direction.h +++ /dev/null @@ -1,72 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_LINE_SEARCH_DIRECTION_H_ -#define CERES_INTERNAL_LINE_SEARCH_DIRECTION_H_ - -#include "ceres/internal/eigen.h" -#include "ceres/line_search_minimizer.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -class LineSearchDirection { - public: - struct Options { - Options() - : num_parameters(0), - type(LBFGS), - nonlinear_conjugate_gradient_type(FLETCHER_REEVES), - function_tolerance(1e-12), - max_lbfgs_rank(20), - use_approximate_eigenvalue_bfgs_scaling(true) { - } - - int num_parameters; - LineSearchDirectionType type; - NonlinearConjugateGradientType nonlinear_conjugate_gradient_type; - double function_tolerance; - int max_lbfgs_rank; - bool use_approximate_eigenvalue_bfgs_scaling; - }; - - static LineSearchDirection* Create(const Options& options); - - virtual ~LineSearchDirection() {} - virtual bool NextDirection(const LineSearchMinimizer::State& previous, - const LineSearchMinimizer::State& current, - Vector* search_direction) = 0; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_LINE_SEARCH_DIRECTION_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/line_search_minimizer.cc b/extern/libmv/third_party/ceres/internal/ceres/line_search_minimizer.cc deleted file mode 100644 index 62264fb0b64..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/line_search_minimizer.cc +++ /dev/null @@ -1,432 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Generic loop for line search based optimization algorithms. -// -// This is primarily inpsired by the minFunc packaged written by Mark -// Schmidt. -// -// http://www.di.ens.fr/~mschmidt/Software/minFunc.html -// -// For details on the theory and implementation see "Numerical -// Optimization" by Nocedal & Wright. - -#include "ceres/line_search_minimizer.h" - -#include <algorithm> -#include <cstdlib> -#include <cmath> -#include <string> -#include <vector> - -#include "Eigen/Dense" -#include "ceres/array_utils.h" -#include "ceres/evaluator.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/line_search.h" -#include "ceres/line_search_direction.h" -#include "ceres/stringprintf.h" -#include "ceres/types.h" -#include "ceres/wall_time.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { -namespace { - -// TODO(sameeragarwal): I think there is a small bug here, in that if -// the evaluation fails, then the state can contain garbage. Look at -// this more carefully. -bool Evaluate(Evaluator* evaluator, - const Vector& x, - LineSearchMinimizer::State* state, - std::string* message) { - if (!evaluator->Evaluate(x.data(), - &(state->cost), - NULL, - state->gradient.data(), - NULL)) { - *message = "Gradient evaluation failed."; - return false; - } - - Vector negative_gradient = -state->gradient; - Vector projected_gradient_step(x.size()); - if (!evaluator->Plus(x.data(), - negative_gradient.data(), - projected_gradient_step.data())) { - *message = "projected_gradient_step = Plus(x, -gradient) failed."; - return false; - } - - state->gradient_squared_norm = (x - projected_gradient_step).squaredNorm(); - state->gradient_max_norm = - (x - projected_gradient_step).lpNorm<Eigen::Infinity>(); - return true; -} - -} // namespace - -void LineSearchMinimizer::Minimize(const Minimizer::Options& options, - double* parameters, - Solver::Summary* summary) { - const bool is_not_silent = !options.is_silent; - double start_time = WallTimeInSeconds(); - double iteration_start_time = start_time; - - Evaluator* evaluator = CHECK_NOTNULL(options.evaluator.get()); - const int num_parameters = evaluator->NumParameters(); - const int num_effective_parameters = evaluator->NumEffectiveParameters(); - - summary->termination_type = NO_CONVERGENCE; - summary->num_successful_steps = 0; - summary->num_unsuccessful_steps = 0; - - VectorRef x(parameters, num_parameters); - - State current_state(num_parameters, num_effective_parameters); - State previous_state(num_parameters, num_effective_parameters); - - Vector delta(num_effective_parameters); - Vector x_plus_delta(num_parameters); - - IterationSummary iteration_summary; - iteration_summary.iteration = 0; - iteration_summary.step_is_valid = false; - iteration_summary.step_is_successful = false; - iteration_summary.cost_change = 0.0; - iteration_summary.gradient_max_norm = 0.0; - iteration_summary.gradient_norm = 0.0; - iteration_summary.step_norm = 0.0; - iteration_summary.linear_solver_iterations = 0; - iteration_summary.step_solver_time_in_seconds = 0; - - // Do initial cost and Jacobian evaluation. - if (!Evaluate(evaluator, x, ¤t_state, &summary->message)) { - summary->termination_type = FAILURE; - summary->message = "Initial cost and jacobian evaluation failed. " - "More details: " + summary->message; - LOG_IF(WARNING, is_not_silent) << "Terminating: " << summary->message; - return; - } - - summary->initial_cost = current_state.cost + summary->fixed_cost; - iteration_summary.cost = current_state.cost + summary->fixed_cost; - - iteration_summary.gradient_max_norm = current_state.gradient_max_norm; - iteration_summary.gradient_norm = sqrt(current_state.gradient_squared_norm); - - if (iteration_summary.gradient_max_norm <= options.gradient_tolerance) { - summary->message = StringPrintf("Gradient tolerance reached. " - "Gradient max norm: %e <= %e", - iteration_summary.gradient_max_norm, - options.gradient_tolerance); - summary->termination_type = CONVERGENCE; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - return; - } - - iteration_summary.iteration_time_in_seconds = - WallTimeInSeconds() - iteration_start_time; - iteration_summary.cumulative_time_in_seconds = - WallTimeInSeconds() - start_time - + summary->preprocessor_time_in_seconds; - summary->iterations.push_back(iteration_summary); - - LineSearchDirection::Options line_search_direction_options; - line_search_direction_options.num_parameters = num_effective_parameters; - line_search_direction_options.type = options.line_search_direction_type; - line_search_direction_options.nonlinear_conjugate_gradient_type = - options.nonlinear_conjugate_gradient_type; - line_search_direction_options.max_lbfgs_rank = options.max_lbfgs_rank; - line_search_direction_options.use_approximate_eigenvalue_bfgs_scaling = - options.use_approximate_eigenvalue_bfgs_scaling; - scoped_ptr<LineSearchDirection> line_search_direction( - LineSearchDirection::Create(line_search_direction_options)); - - LineSearchFunction line_search_function(evaluator); - - LineSearch::Options line_search_options; - line_search_options.interpolation_type = - options.line_search_interpolation_type; - line_search_options.min_step_size = options.min_line_search_step_size; - line_search_options.sufficient_decrease = - options.line_search_sufficient_function_decrease; - line_search_options.max_step_contraction = - options.max_line_search_step_contraction; - line_search_options.min_step_contraction = - options.min_line_search_step_contraction; - line_search_options.max_num_iterations = - options.max_num_line_search_step_size_iterations; - line_search_options.sufficient_curvature_decrease = - options.line_search_sufficient_curvature_decrease; - line_search_options.max_step_expansion = - options.max_line_search_step_expansion; - line_search_options.function = &line_search_function; - - scoped_ptr<LineSearch> - line_search(LineSearch::Create(options.line_search_type, - line_search_options, - &summary->message)); - if (line_search.get() == NULL) { - summary->termination_type = FAILURE; - LOG_IF(ERROR, is_not_silent) << "Terminating: " << summary->message; - return; - } - - LineSearch::Summary line_search_summary; - int num_line_search_direction_restarts = 0; - - while (true) { - if (!RunCallbacks(options, iteration_summary, summary)) { - break; - } - - iteration_start_time = WallTimeInSeconds(); - if (iteration_summary.iteration >= options.max_num_iterations) { - summary->message = "Maximum number of iterations reached."; - summary->termination_type = NO_CONVERGENCE; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - break; - } - - const double total_solver_time = iteration_start_time - start_time + - summary->preprocessor_time_in_seconds; - if (total_solver_time >= options.max_solver_time_in_seconds) { - summary->message = "Maximum solver time reached."; - summary->termination_type = NO_CONVERGENCE; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - break; - } - - iteration_summary = IterationSummary(); - iteration_summary.iteration = summary->iterations.back().iteration + 1; - iteration_summary.step_is_valid = false; - iteration_summary.step_is_successful = false; - - bool line_search_status = true; - if (iteration_summary.iteration == 1) { - current_state.search_direction = -current_state.gradient; - } else { - line_search_status = line_search_direction->NextDirection( - previous_state, - current_state, - ¤t_state.search_direction); - } - - if (!line_search_status && - num_line_search_direction_restarts >= - options.max_num_line_search_direction_restarts) { - // Line search direction failed to generate a new direction, and we - // have already reached our specified maximum number of restarts, - // terminate optimization. - summary->message = - StringPrintf("Line search direction failure: specified " - "max_num_line_search_direction_restarts: %d reached.", - options.max_num_line_search_direction_restarts); - summary->termination_type = FAILURE; - LOG_IF(WARNING, is_not_silent) << "Terminating: " << summary->message; - break; - } else if (!line_search_status) { - // Restart line search direction with gradient descent on first iteration - // as we have not yet reached our maximum number of restarts. - CHECK_LT(num_line_search_direction_restarts, - options.max_num_line_search_direction_restarts); - - ++num_line_search_direction_restarts; - LOG_IF(WARNING, is_not_silent) - << "Line search direction algorithm: " - << LineSearchDirectionTypeToString( - options.line_search_direction_type) - << ", failed to produce a valid new direction at " - << "iteration: " << iteration_summary.iteration - << ". Restarting, number of restarts: " - << num_line_search_direction_restarts << " / " - << options.max_num_line_search_direction_restarts - << " [max]."; - line_search_direction.reset( - LineSearchDirection::Create(line_search_direction_options)); - current_state.search_direction = -current_state.gradient; - } - - line_search_function.Init(x, current_state.search_direction); - current_state.directional_derivative = - current_state.gradient.dot(current_state.search_direction); - - // TODO(sameeragarwal): Refactor this into its own object and add - // explanations for the various choices. - // - // Note that we use !line_search_status to ensure that we treat cases when - // we restarted the line search direction equivalently to the first - // iteration. - const double initial_step_size = - (iteration_summary.iteration == 1 || !line_search_status) - ? std::min(1.0, 1.0 / current_state.gradient_max_norm) - : std::min(1.0, 2.0 * (current_state.cost - previous_state.cost) / - current_state.directional_derivative); - // By definition, we should only ever go forwards along the specified search - // direction in a line search, most likely cause for this being violated - // would be a numerical failure in the line search direction calculation. - if (initial_step_size < 0.0) { - summary->message = - StringPrintf("Numerical failure in line search, initial_step_size is " - "negative: %.5e, directional_derivative: %.5e, " - "(current_cost - previous_cost): %.5e", - initial_step_size, current_state.directional_derivative, - (current_state.cost - previous_state.cost)); - summary->termination_type = FAILURE; - LOG_IF(WARNING, is_not_silent) << "Terminating: " << summary->message; - break; - } - - line_search->Search(initial_step_size, - current_state.cost, - current_state.directional_derivative, - &line_search_summary); - if (!line_search_summary.success) { - summary->message = - StringPrintf("Numerical failure in line search, failed to find " - "a valid step size, (did not run out of iterations) " - "using initial_step_size: %.5e, initial_cost: %.5e, " - "initial_gradient: %.5e.", - initial_step_size, current_state.cost, - current_state.directional_derivative); - LOG_IF(WARNING, is_not_silent) << "Terminating: " << summary->message; - summary->termination_type = FAILURE; - break; - } - - current_state.step_size = line_search_summary.optimal_step_size; - delta = current_state.step_size * current_state.search_direction; - - previous_state = current_state; - iteration_summary.step_solver_time_in_seconds = - WallTimeInSeconds() - iteration_start_time; - - const double x_norm = x.norm(); - - if (!evaluator->Plus(x.data(), delta.data(), x_plus_delta.data())) { - summary->termination_type = FAILURE; - summary->message = - "x_plus_delta = Plus(x, delta) failed. This should not happen " - "as the step was valid when it was selected by the line search."; - LOG_IF(WARNING, is_not_silent) << "Terminating: " << summary->message; - break; - } else if (!Evaluate(evaluator, - x_plus_delta, - ¤t_state, - &summary->message)) { - summary->termination_type = FAILURE; - summary->message = - "Step failed to evaluate. This should not happen as the step was " - "valid when it was selected by the line search. More details: " + - summary->message; - LOG_IF(WARNING, is_not_silent) << "Terminating: " << summary->message; - break; - } else { - x = x_plus_delta; - } - - iteration_summary.gradient_max_norm = current_state.gradient_max_norm; - iteration_summary.gradient_norm = sqrt(current_state.gradient_squared_norm); - iteration_summary.cost_change = previous_state.cost - current_state.cost; - iteration_summary.cost = current_state.cost + summary->fixed_cost; - iteration_summary.step_norm = delta.norm(); - iteration_summary.step_is_valid = true; - iteration_summary.step_is_successful = true; - iteration_summary.step_size = current_state.step_size; - iteration_summary.line_search_function_evaluations = - line_search_summary.num_function_evaluations; - iteration_summary.line_search_gradient_evaluations = - line_search_summary.num_gradient_evaluations; - iteration_summary.line_search_iterations = - line_search_summary.num_iterations; - iteration_summary.iteration_time_in_seconds = - WallTimeInSeconds() - iteration_start_time; - iteration_summary.cumulative_time_in_seconds = - WallTimeInSeconds() - start_time - + summary->preprocessor_time_in_seconds; - - summary->line_search_cost_evaluation_time_in_seconds += - line_search_summary.cost_evaluation_time_in_seconds; - summary->line_search_gradient_evaluation_time_in_seconds += - line_search_summary.gradient_evaluation_time_in_seconds; - summary->line_search_polynomial_minimization_time_in_seconds += - line_search_summary.polynomial_minimization_time_in_seconds; - summary->line_search_total_time_in_seconds += - line_search_summary.total_time_in_seconds; - ++summary->num_successful_steps; - - const double step_size_tolerance = options.parameter_tolerance * - (x_norm + options.parameter_tolerance); - if (iteration_summary.step_norm <= step_size_tolerance) { - summary->message = - StringPrintf("Parameter tolerance reached. " - "Relative step_norm: %e <= %e.", - (iteration_summary.step_norm / - (x_norm + options.parameter_tolerance)), - options.parameter_tolerance); - summary->termination_type = CONVERGENCE; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - return; - } - - if (iteration_summary.gradient_max_norm <= options.gradient_tolerance) { - summary->message = StringPrintf("Gradient tolerance reached. " - "Gradient max norm: %e <= %e", - iteration_summary.gradient_max_norm, - options.gradient_tolerance); - summary->termination_type = CONVERGENCE; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - break; - } - - const double absolute_function_tolerance = - options.function_tolerance * previous_state.cost; - if (fabs(iteration_summary.cost_change) <= absolute_function_tolerance) { - summary->message = - StringPrintf("Function tolerance reached. " - "|cost_change|/cost: %e <= %e", - fabs(iteration_summary.cost_change) / - previous_state.cost, - options.function_tolerance); - summary->termination_type = CONVERGENCE; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - break; - } - - summary->iterations.push_back(iteration_summary); - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/line_search_minimizer.h b/extern/libmv/third_party/ceres/internal/ceres/line_search_minimizer.h deleted file mode 100644 index 54b7202e0c3..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/line_search_minimizer.h +++ /dev/null @@ -1,77 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_LINE_SEARCH_MINIMIZER_H_ -#define CERES_INTERNAL_LINE_SEARCH_MINIMIZER_H_ - -#include "ceres/minimizer.h" -#include "ceres/solver.h" -#include "ceres/types.h" -#include "ceres/internal/eigen.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -// Generic line search minimization algorithm. -// -// For example usage, see SolverImpl::Minimize. -class LineSearchMinimizer : public Minimizer { - public: - struct State { - State(int num_parameters, - int num_effective_parameters) - : cost(0.0), - gradient(num_effective_parameters), - gradient_squared_norm(0.0), - search_direction(num_effective_parameters), - directional_derivative(0.0), - step_size(0.0) { - } - - double cost; - Vector gradient; - double gradient_squared_norm; - double gradient_max_norm; - Vector search_direction; - double directional_derivative; - double step_size; - }; - - ~LineSearchMinimizer() {} - virtual void Minimize(const Minimizer::Options& options, - double* parameters, - Solver::Summary* summary); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_LINE_SEARCH_MINIMIZER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/line_search_preprocessor.cc b/extern/libmv/third_party/ceres/internal/ceres/line_search_preprocessor.cc deleted file mode 100644 index 831f5e8d079..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/line_search_preprocessor.cc +++ /dev/null @@ -1,106 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/line_search_preprocessor.h" - -#include <numeric> -#include <string> -#include "ceres/evaluator.h" -#include "ceres/minimizer.h" -#include "ceres/problem_impl.h" -#include "ceres/program.h" -#include "ceres/wall_time.h" - -namespace ceres { -namespace internal { -namespace { - -bool IsProgramValid(const Program& program, std::string* error) { - if (program.IsBoundsConstrained()) { - *error = "LINE_SEARCH Minimizer does not support bounds."; - return false; - } - return program.ParameterBlocksAreFinite(error); -} - -bool SetupEvaluator(PreprocessedProblem* pp) { - pp->evaluator_options = Evaluator::Options(); - // This ensures that we get a Block Jacobian Evaluator without any - // requirement on orderings. - pp->evaluator_options.linear_solver_type = CGNR; - pp->evaluator_options.num_eliminate_blocks = 0; - pp->evaluator_options.num_threads = pp->options.num_threads; - pp->evaluator.reset(Evaluator::Create(pp->evaluator_options, - pp->reduced_program.get(), - &pp->error)); - return (pp->evaluator.get() != NULL); -} - -} // namespace - -LineSearchPreprocessor::~LineSearchPreprocessor() { -} - -bool LineSearchPreprocessor::Preprocess(const Solver::Options& options, - ProblemImpl* problem, - PreprocessedProblem* pp) { - CHECK_NOTNULL(pp); - pp->options = options; - ChangeNumThreadsIfNeeded(&pp->options); - - pp->problem = problem; - Program* program = problem->mutable_program(); - if (!IsProgramValid(*program, &pp->error)) { - return false; - } - - pp->reduced_program.reset( - program->CreateReducedProgram(&pp->removed_parameter_blocks, - &pp->fixed_cost, - &pp->error)); - - if (pp->reduced_program.get() == NULL) { - return false; - } - - if (pp->reduced_program->NumParameterBlocks() == 0) { - return true; - } - - if (!SetupEvaluator(pp)) { - return false; - } - - SetupCommonMinimizerOptions(pp); - return true; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/line_search_preprocessor.h b/extern/libmv/third_party/ceres/internal/ceres/line_search_preprocessor.h deleted file mode 100644 index 132d83a0a9a..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/line_search_preprocessor.h +++ /dev/null @@ -1,50 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_LINE_SEARCH_PREPROCESSOR_H_ -#define CERES_INTERNAL_LINE_SEARCH_PREPROCESSOR_H_ - -#include "ceres/preprocessor.h" - -namespace ceres { -namespace internal { - -class LineSearchPreprocessor : public Preprocessor { - public: - virtual ~LineSearchPreprocessor(); - virtual bool Preprocess(const Solver::Options& options, - ProblemImpl* problem, - PreprocessedProblem* preprocessed_problem); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_LINE_SEARCH_PREPROCESSOR_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/linear_least_squares_problems.cc b/extern/libmv/third_party/ceres/internal/ceres/linear_least_squares_problems.cc deleted file mode 100644 index 0a69375f7b5..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/linear_least_squares_problems.cc +++ /dev/null @@ -1,732 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/linear_least_squares_problems.h" - -#include <cstdio> -#include <string> -#include <vector> -#include "ceres/block_sparse_matrix.h" -#include "ceres/block_structure.h" -#include "ceres/casts.h" -#include "ceres/file.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/stringprintf.h" -#include "ceres/triplet_sparse_matrix.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::string; - -LinearLeastSquaresProblem* CreateLinearLeastSquaresProblemFromId(int id) { - switch (id) { - case 0: - return LinearLeastSquaresProblem0(); - case 1: - return LinearLeastSquaresProblem1(); - case 2: - return LinearLeastSquaresProblem2(); - case 3: - return LinearLeastSquaresProblem3(); - case 4: - return LinearLeastSquaresProblem4(); - default: - LOG(FATAL) << "Unknown problem id requested " << id; - } - return NULL; -} - -/* -A = [1 2] - [3 4] - [6 -10] - -b = [ 8 - 18 - -18] - -x = [2 - 3] - -D = [1 - 2] - -x_D = [1.78448275; - 2.82327586;] - */ -LinearLeastSquaresProblem* LinearLeastSquaresProblem0() { - LinearLeastSquaresProblem* problem = new LinearLeastSquaresProblem; - - TripletSparseMatrix* A = new TripletSparseMatrix(3, 2, 6); - problem->b.reset(new double[3]); - problem->D.reset(new double[2]); - - problem->x.reset(new double[2]); - problem->x_D.reset(new double[2]); - - int* Ai = A->mutable_rows(); - int* Aj = A->mutable_cols(); - double* Ax = A->mutable_values(); - - int counter = 0; - for (int i = 0; i < 3; ++i) { - for (int j = 0; j< 2; ++j) { - Ai[counter] = i; - Aj[counter] = j; - ++counter; - } - } - - Ax[0] = 1.; - Ax[1] = 2.; - Ax[2] = 3.; - Ax[3] = 4.; - Ax[4] = 6; - Ax[5] = -10; - A->set_num_nonzeros(6); - problem->A.reset(A); - - problem->b[0] = 8; - problem->b[1] = 18; - problem->b[2] = -18; - - problem->x[0] = 2.0; - problem->x[1] = 3.0; - - problem->D[0] = 1; - problem->D[1] = 2; - - problem->x_D[0] = 1.78448275; - problem->x_D[1] = 2.82327586; - return problem; -} - - -/* - A = [1 0 | 2 0 0 - 3 0 | 0 4 0 - 0 5 | 0 0 6 - 0 7 | 8 0 0 - 0 9 | 1 0 0 - 0 0 | 1 1 1] - - b = [0 - 1 - 2 - 3 - 4 - 5] - - c = A'* b = [ 3 - 67 - 33 - 9 - 17] - - A'A = [10 0 2 12 0 - 0 155 65 0 30 - 2 65 70 1 1 - 12 0 1 17 1 - 0 30 1 1 37] - - S = [ 42.3419 -1.4000 -11.5806 - -1.4000 2.6000 1.0000 - 11.5806 1.0000 31.1935] - - r = [ 4.3032 - 5.4000 - 5.0323] - - S\r = [ 0.2102 - 2.1367 - 0.1388] - - A\b = [-2.3061 - 0.3172 - 0.2102 - 2.1367 - 0.1388] -*/ -// The following two functions create a TripletSparseMatrix and a -// BlockSparseMatrix version of this problem. - -// TripletSparseMatrix version. -LinearLeastSquaresProblem* LinearLeastSquaresProblem1() { - int num_rows = 6; - int num_cols = 5; - - LinearLeastSquaresProblem* problem = new LinearLeastSquaresProblem; - TripletSparseMatrix* A = new TripletSparseMatrix(num_rows, - num_cols, - num_rows * num_cols); - problem->b.reset(new double[num_rows]); - problem->D.reset(new double[num_cols]); - problem->num_eliminate_blocks = 2; - - int* rows = A->mutable_rows(); - int* cols = A->mutable_cols(); - double* values = A->mutable_values(); - - int nnz = 0; - - // Row 1 - { - rows[nnz] = 0; - cols[nnz] = 0; - values[nnz++] = 1; - - rows[nnz] = 0; - cols[nnz] = 2; - values[nnz++] = 2; - } - - // Row 2 - { - rows[nnz] = 1; - cols[nnz] = 0; - values[nnz++] = 3; - - rows[nnz] = 1; - cols[nnz] = 3; - values[nnz++] = 4; - } - - // Row 3 - { - rows[nnz] = 2; - cols[nnz] = 1; - values[nnz++] = 5; - - rows[nnz] = 2; - cols[nnz] = 4; - values[nnz++] = 6; - } - - // Row 4 - { - rows[nnz] = 3; - cols[nnz] = 1; - values[nnz++] = 7; - - rows[nnz] = 3; - cols[nnz] = 2; - values[nnz++] = 8; - } - - // Row 5 - { - rows[nnz] = 4; - cols[nnz] = 1; - values[nnz++] = 9; - - rows[nnz] = 4; - cols[nnz] = 2; - values[nnz++] = 1; - } - - // Row 6 - { - rows[nnz] = 5; - cols[nnz] = 2; - values[nnz++] = 1; - - rows[nnz] = 5; - cols[nnz] = 3; - values[nnz++] = 1; - - rows[nnz] = 5; - cols[nnz] = 4; - values[nnz++] = 1; - } - - A->set_num_nonzeros(nnz); - CHECK(A->IsValid()); - - problem->A.reset(A); - - for (int i = 0; i < num_cols; ++i) { - problem->D.get()[i] = 1; - } - - for (int i = 0; i < num_rows; ++i) { - problem->b.get()[i] = i; - } - - return problem; -} - -// BlockSparseMatrix version -LinearLeastSquaresProblem* LinearLeastSquaresProblem2() { - int num_rows = 6; - int num_cols = 5; - - LinearLeastSquaresProblem* problem = new LinearLeastSquaresProblem; - - problem->b.reset(new double[num_rows]); - problem->D.reset(new double[num_cols]); - problem->num_eliminate_blocks = 2; - - CompressedRowBlockStructure* bs = new CompressedRowBlockStructure; - scoped_array<double> values(new double[num_rows * num_cols]); - - for (int c = 0; c < num_cols; ++c) { - bs->cols.push_back(Block()); - bs->cols.back().size = 1; - bs->cols.back().position = c; - } - - int nnz = 0; - - // Row 1 - { - values[nnz++] = 1; - values[nnz++] = 2; - - bs->rows.push_back(CompressedRow()); - CompressedRow& row = bs->rows.back(); - row.block.size = 1; - row.block.position = 0; - row.cells.push_back(Cell(0, 0)); - row.cells.push_back(Cell(2, 1)); - } - - // Row 2 - { - values[nnz++] = 3; - values[nnz++] = 4; - - bs->rows.push_back(CompressedRow()); - CompressedRow& row = bs->rows.back(); - row.block.size = 1; - row.block.position = 1; - row.cells.push_back(Cell(0, 2)); - row.cells.push_back(Cell(3, 3)); - } - - // Row 3 - { - values[nnz++] = 5; - values[nnz++] = 6; - - bs->rows.push_back(CompressedRow()); - CompressedRow& row = bs->rows.back(); - row.block.size = 1; - row.block.position = 2; - row.cells.push_back(Cell(1, 4)); - row.cells.push_back(Cell(4, 5)); - } - - // Row 4 - { - values[nnz++] = 7; - values[nnz++] = 8; - - bs->rows.push_back(CompressedRow()); - CompressedRow& row = bs->rows.back(); - row.block.size = 1; - row.block.position = 3; - row.cells.push_back(Cell(1, 6)); - row.cells.push_back(Cell(2, 7)); - } - - // Row 5 - { - values[nnz++] = 9; - values[nnz++] = 1; - - bs->rows.push_back(CompressedRow()); - CompressedRow& row = bs->rows.back(); - row.block.size = 1; - row.block.position = 4; - row.cells.push_back(Cell(1, 8)); - row.cells.push_back(Cell(2, 9)); - } - - // Row 6 - { - values[nnz++] = 1; - values[nnz++] = 1; - values[nnz++] = 1; - - bs->rows.push_back(CompressedRow()); - CompressedRow& row = bs->rows.back(); - row.block.size = 1; - row.block.position = 5; - row.cells.push_back(Cell(2, 10)); - row.cells.push_back(Cell(3, 11)); - row.cells.push_back(Cell(4, 12)); - } - - BlockSparseMatrix* A = new BlockSparseMatrix(bs); - memcpy(A->mutable_values(), values.get(), nnz * sizeof(*A->values())); - - for (int i = 0; i < num_cols; ++i) { - problem->D.get()[i] = 1; - } - - for (int i = 0; i < num_rows; ++i) { - problem->b.get()[i] = i; - } - - problem->A.reset(A); - - return problem; -} - - -/* - A = [1 0 - 3 0 - 0 5 - 0 7 - 0 9 - 0 0] - - b = [0 - 1 - 2 - 3 - 4 - 5] -*/ -// BlockSparseMatrix version -LinearLeastSquaresProblem* LinearLeastSquaresProblem3() { - int num_rows = 5; - int num_cols = 2; - - LinearLeastSquaresProblem* problem = new LinearLeastSquaresProblem; - - problem->b.reset(new double[num_rows]); - problem->D.reset(new double[num_cols]); - problem->num_eliminate_blocks = 2; - - CompressedRowBlockStructure* bs = new CompressedRowBlockStructure; - scoped_array<double> values(new double[num_rows * num_cols]); - - for (int c = 0; c < num_cols; ++c) { - bs->cols.push_back(Block()); - bs->cols.back().size = 1; - bs->cols.back().position = c; - } - - int nnz = 0; - - // Row 1 - { - values[nnz++] = 1; - bs->rows.push_back(CompressedRow()); - CompressedRow& row = bs->rows.back(); - row.block.size = 1; - row.block.position = 0; - row.cells.push_back(Cell(0, 0)); - } - - // Row 2 - { - values[nnz++] = 3; - bs->rows.push_back(CompressedRow()); - CompressedRow& row = bs->rows.back(); - row.block.size = 1; - row.block.position = 1; - row.cells.push_back(Cell(0, 1)); - } - - // Row 3 - { - values[nnz++] = 5; - bs->rows.push_back(CompressedRow()); - CompressedRow& row = bs->rows.back(); - row.block.size = 1; - row.block.position = 2; - row.cells.push_back(Cell(1, 2)); - } - - // Row 4 - { - values[nnz++] = 7; - bs->rows.push_back(CompressedRow()); - CompressedRow& row = bs->rows.back(); - row.block.size = 1; - row.block.position = 3; - row.cells.push_back(Cell(1, 3)); - } - - // Row 5 - { - values[nnz++] = 9; - bs->rows.push_back(CompressedRow()); - CompressedRow& row = bs->rows.back(); - row.block.size = 1; - row.block.position = 4; - row.cells.push_back(Cell(1, 4)); - } - - BlockSparseMatrix* A = new BlockSparseMatrix(bs); - memcpy(A->mutable_values(), values.get(), nnz * sizeof(*A->values())); - - for (int i = 0; i < num_cols; ++i) { - problem->D.get()[i] = 1; - } - - for (int i = 0; i < num_rows; ++i) { - problem->b.get()[i] = i; - } - - problem->A.reset(A); - - return problem; -} - -/* - A = [1 2 0 0 0 1 1 - 1 4 0 0 0 5 6 - 0 0 9 0 0 3 1] - - b = [0 - 1 - 2] -*/ -// BlockSparseMatrix version -// -// This problem has the unique property that it has two different -// sized f-blocks, but only one of them occurs in the rows involving -// the one e-block. So performing Schur elimination on this problem -// tests the Schur Eliminator's ability to handle non-e-block rows -// correctly when their structure does not conform to the static -// structure determined by DetectStructure. -// -// NOTE: This problem is too small and rank deficient to be solved without -// the diagonal regularization. -LinearLeastSquaresProblem* LinearLeastSquaresProblem4() { - int num_rows = 3; - int num_cols = 7; - - LinearLeastSquaresProblem* problem = new LinearLeastSquaresProblem; - - problem->b.reset(new double[num_rows]); - problem->D.reset(new double[num_cols]); - problem->num_eliminate_blocks = 1; - - CompressedRowBlockStructure* bs = new CompressedRowBlockStructure; - scoped_array<double> values(new double[num_rows * num_cols]); - - // Column block structure - bs->cols.push_back(Block()); - bs->cols.back().size = 2; - bs->cols.back().position = 0; - - bs->cols.push_back(Block()); - bs->cols.back().size = 3; - bs->cols.back().position = 2; - - bs->cols.push_back(Block()); - bs->cols.back().size = 2; - bs->cols.back().position = 5; - - int nnz = 0; - - // Row 1 & 2 - { - bs->rows.push_back(CompressedRow()); - CompressedRow& row = bs->rows.back(); - row.block.size = 2; - row.block.position = 0; - - row.cells.push_back(Cell(0, nnz)); - values[nnz++] = 1; - values[nnz++] = 2; - values[nnz++] = 1; - values[nnz++] = 4; - - row.cells.push_back(Cell(2, nnz)); - values[nnz++] = 1; - values[nnz++] = 1; - values[nnz++] = 5; - values[nnz++] = 6; - } - - // Row 3 - { - bs->rows.push_back(CompressedRow()); - CompressedRow& row = bs->rows.back(); - row.block.size = 1; - row.block.position = 2; - - row.cells.push_back(Cell(1, nnz)); - values[nnz++] = 9; - values[nnz++] = 0; - values[nnz++] = 0; - - row.cells.push_back(Cell(2, nnz)); - values[nnz++] = 3; - values[nnz++] = 1; - } - - BlockSparseMatrix* A = new BlockSparseMatrix(bs); - memcpy(A->mutable_values(), values.get(), nnz * sizeof(*A->values())); - - for (int i = 0; i < num_cols; ++i) { - problem->D.get()[i] = (i + 1) * 100; - } - - for (int i = 0; i < num_rows; ++i) { - problem->b.get()[i] = i; - } - - problem->A.reset(A); - return problem; -} - -namespace { -bool DumpLinearLeastSquaresProblemToConsole(const SparseMatrix* A, - const double* D, - const double* b, - const double* x, - int num_eliminate_blocks) { - CHECK_NOTNULL(A); - Matrix AA; - A->ToDenseMatrix(&AA); - LOG(INFO) << "A^T: \n" << AA.transpose(); - - if (D != NULL) { - LOG(INFO) << "A's appended diagonal:\n" - << ConstVectorRef(D, A->num_cols()); - } - - if (b != NULL) { - LOG(INFO) << "b: \n" << ConstVectorRef(b, A->num_rows()); - } - - if (x != NULL) { - LOG(INFO) << "x: \n" << ConstVectorRef(x, A->num_cols()); - } - return true; -} - -void WriteArrayToFileOrDie(const string& filename, - const double* x, - const int size) { - CHECK_NOTNULL(x); - VLOG(2) << "Writing array to: " << filename; - FILE* fptr = fopen(filename.c_str(), "w"); - CHECK_NOTNULL(fptr); - for (int i = 0; i < size; ++i) { - fprintf(fptr, "%17f\n", x[i]); - } - fclose(fptr); -} - -bool DumpLinearLeastSquaresProblemToTextFile(const string& filename_base, - const SparseMatrix* A, - const double* D, - const double* b, - const double* x, - int num_eliminate_blocks) { - CHECK_NOTNULL(A); - LOG(INFO) << "writing to: " << filename_base << "*"; - - string matlab_script; - StringAppendF(&matlab_script, - "function lsqp = load_trust_region_problem()\n"); - StringAppendF(&matlab_script, - "lsqp.num_rows = %d;\n", A->num_rows()); - StringAppendF(&matlab_script, - "lsqp.num_cols = %d;\n", A->num_cols()); - - { - string filename = filename_base + "_A.txt"; - FILE* fptr = fopen(filename.c_str(), "w"); - CHECK_NOTNULL(fptr); - A->ToTextFile(fptr); - fclose(fptr); - StringAppendF(&matlab_script, - "tmp = load('%s', '-ascii');\n", filename.c_str()); - StringAppendF( - &matlab_script, - "lsqp.A = sparse(tmp(:, 1) + 1, tmp(:, 2) + 1, tmp(:, 3), %d, %d);\n", - A->num_rows(), - A->num_cols()); - } - - - if (D != NULL) { - string filename = filename_base + "_D.txt"; - WriteArrayToFileOrDie(filename, D, A->num_cols()); - StringAppendF(&matlab_script, - "lsqp.D = load('%s', '-ascii');\n", filename.c_str()); - } - - if (b != NULL) { - string filename = filename_base + "_b.txt"; - WriteArrayToFileOrDie(filename, b, A->num_rows()); - StringAppendF(&matlab_script, - "lsqp.b = load('%s', '-ascii');\n", filename.c_str()); - } - - if (x != NULL) { - string filename = filename_base + "_x.txt"; - WriteArrayToFileOrDie(filename, x, A->num_cols()); - StringAppendF(&matlab_script, - "lsqp.x = load('%s', '-ascii');\n", filename.c_str()); - } - - string matlab_filename = filename_base + ".m"; - WriteStringToFileOrDie(matlab_script, matlab_filename); - return true; -} -} // namespace - -bool DumpLinearLeastSquaresProblem(const string& filename_base, - DumpFormatType dump_format_type, - const SparseMatrix* A, - const double* D, - const double* b, - const double* x, - int num_eliminate_blocks) { - switch (dump_format_type) { - case CONSOLE: - return DumpLinearLeastSquaresProblemToConsole(A, D, b, x, - num_eliminate_blocks); - case TEXTFILE: - return DumpLinearLeastSquaresProblemToTextFile(filename_base, - A, D, b, x, - num_eliminate_blocks); - default: - LOG(FATAL) << "Unknown DumpFormatType " << dump_format_type; - } - - return true; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/linear_least_squares_problems.h b/extern/libmv/third_party/ceres/internal/ceres/linear_least_squares_problems.h deleted file mode 100644 index 384efb59a2b..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/linear_least_squares_problems.h +++ /dev/null @@ -1,85 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_LINEAR_LEAST_SQUARES_PROBLEMS_H_ -#define CERES_INTERNAL_LINEAR_LEAST_SQUARES_PROBLEMS_H_ - -#include <string> -#include <vector> -#include "ceres/sparse_matrix.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" - -namespace ceres { -namespace internal { - -// Structure defining a linear least squares problem and if possible -// ground truth solutions. To be used by various LinearSolver tests. -struct LinearLeastSquaresProblem { - LinearLeastSquaresProblem() - : A(NULL), b(NULL), D(NULL), num_eliminate_blocks(0), - x(NULL), x_D(NULL) { - } - - scoped_ptr<SparseMatrix> A; - scoped_array<double> b; - scoped_array<double> D; - // If using the schur eliminator then how many of the variable - // blocks are e_type blocks. - int num_eliminate_blocks; - - // Solution to min_x |Ax - b|^2 - scoped_array<double> x; - // Solution to min_x |Ax - b|^2 + |Dx|^2 - scoped_array<double> x_D; -}; - -// Factories for linear least squares problem. -LinearLeastSquaresProblem* CreateLinearLeastSquaresProblemFromId(int id); - -LinearLeastSquaresProblem* LinearLeastSquaresProblem0(); -LinearLeastSquaresProblem* LinearLeastSquaresProblem1(); -LinearLeastSquaresProblem* LinearLeastSquaresProblem2(); -LinearLeastSquaresProblem* LinearLeastSquaresProblem3(); -LinearLeastSquaresProblem* LinearLeastSquaresProblem4(); - -// Write the linear least squares problem to disk. The exact format -// depends on dump_format_type. -bool DumpLinearLeastSquaresProblem(const std::string& filename_base, - DumpFormatType dump_format_type, - const SparseMatrix* A, - const double* D, - const double* b, - const double* x, - int num_eliminate_blocks); -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_LINEAR_LEAST_SQUARES_PROBLEMS_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/linear_operator.cc b/extern/libmv/third_party/ceres/internal/ceres/linear_operator.cc deleted file mode 100644 index 9d291bd3465..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/linear_operator.cc +++ /dev/null @@ -1,40 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/linear_operator.h" - -namespace ceres { -namespace internal { - -LinearOperator::~LinearOperator() { -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/linear_operator.h b/extern/libmv/third_party/ceres/internal/ceres/linear_operator.h deleted file mode 100644 index 6463fb5089a..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/linear_operator.h +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Base classes for access to an linear operator. - -#ifndef CERES_INTERNAL_LINEAR_OPERATOR_H_ -#define CERES_INTERNAL_LINEAR_OPERATOR_H_ - -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -// This is an abstract base class for linear operators. It supports -// access to size information and left and right multiply operators. -class LinearOperator { - public: - virtual ~LinearOperator(); - - // y = y + Ax; - virtual void RightMultiply(const double* x, double* y) const = 0; - // y = y + A'x; - virtual void LeftMultiply(const double* x, double* y) const = 0; - - virtual int num_rows() const = 0; - virtual int num_cols() const = 0; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_LINEAR_OPERATOR_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/linear_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/linear_solver.cc deleted file mode 100644 index 38e4625f747..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/linear_solver.cc +++ /dev/null @@ -1,119 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/linear_solver.h" - -#include "ceres/cgnr_solver.h" -#include "ceres/dense_normal_cholesky_solver.h" -#include "ceres/dense_qr_solver.h" -#include "ceres/iterative_schur_complement_solver.h" -#include "ceres/schur_complement_solver.h" -#include "ceres/sparse_normal_cholesky_solver.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -LinearSolver::~LinearSolver() { -} - -LinearSolverType LinearSolver::LinearSolverForZeroEBlocks( - LinearSolverType linear_solver_type) { - if (!IsSchurType(linear_solver_type)) { - return linear_solver_type; - } - - if (linear_solver_type == SPARSE_SCHUR) { - return SPARSE_NORMAL_CHOLESKY; - } - - if (linear_solver_type == DENSE_SCHUR) { - // TODO(sameeragarwal): This is probably not a great choice. - // Ideally, we should have a DENSE_NORMAL_CHOLESKY, that can take - // a BlockSparseMatrix as input. - return DENSE_QR; - } - - if (linear_solver_type == ITERATIVE_SCHUR) { - return CGNR; - } - - return linear_solver_type; -} - -LinearSolver* LinearSolver::Create(const LinearSolver::Options& options) { - switch (options.type) { - case CGNR: - return new CgnrSolver(options); - - case SPARSE_NORMAL_CHOLESKY: -#if defined(CERES_NO_SUITESPARSE) && \ - defined(CERES_NO_CXSPARSE) && \ - !defined(CERES_USE_EIGEN_SPARSE) - return NULL; -#else - return new SparseNormalCholeskySolver(options); -#endif - - case SPARSE_SCHUR: -#if defined(CERES_NO_SUITESPARSE) && \ - defined(CERES_NO_CXSPARSE) && \ - !defined(CERES_USE_EIGEN_SPARSE) - return NULL; -#else - return new SparseSchurComplementSolver(options); -#endif - - case DENSE_SCHUR: - return new DenseSchurComplementSolver(options); - - case ITERATIVE_SCHUR: - if (options.use_explicit_schur_complement) { - return new SparseSchurComplementSolver(options); - } else { - return new IterativeSchurComplementSolver(options); - } - - case DENSE_QR: - return new DenseQRSolver(options); - - case DENSE_NORMAL_CHOLESKY: - return new DenseNormalCholeskySolver(options); - - default: - LOG(FATAL) << "Unknown linear solver type :" - << options.type; - return NULL; // MSVC doesn't understand that LOG(FATAL) never returns. - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/linear_solver.h b/extern/libmv/third_party/ceres/internal/ceres/linear_solver.h deleted file mode 100644 index fb9332ca6e3..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/linear_solver.h +++ /dev/null @@ -1,362 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Abstract interface for objects solving linear systems of various -// kinds. - -#ifndef CERES_INTERNAL_LINEAR_SOLVER_H_ -#define CERES_INTERNAL_LINEAR_SOLVER_H_ - -#include <cstddef> -#include <map> -#include <string> -#include <vector> -#include "ceres/block_sparse_matrix.h" -#include "ceres/casts.h" -#include "ceres/compressed_row_sparse_matrix.h" -#include "ceres/dense_sparse_matrix.h" -#include "ceres/execution_summary.h" -#include "ceres/triplet_sparse_matrix.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -enum LinearSolverTerminationType { - // Termination criterion was met. - LINEAR_SOLVER_SUCCESS, - - // Solver ran for max_num_iterations and terminated before the - // termination tolerance could be satisfied. - LINEAR_SOLVER_NO_CONVERGENCE, - - // Solver was terminated due to numerical problems, generally due to - // the linear system being poorly conditioned. - LINEAR_SOLVER_FAILURE, - - // Solver failed with a fatal error that cannot be recovered from, - // e.g. CHOLMOD ran out of memory when computing the symbolic or - // numeric factorization or an underlying library was called with - // the wrong arguments. - LINEAR_SOLVER_FATAL_ERROR -}; - - -class LinearOperator; - -// Abstract base class for objects that implement algorithms for -// solving linear systems -// -// Ax = b -// -// It is expected that a single instance of a LinearSolver object -// maybe used multiple times for solving multiple linear systems with -// the same sparsity structure. This allows them to cache and reuse -// information across solves. This means that calling Solve on the -// same LinearSolver instance with two different linear systems will -// result in undefined behaviour. -// -// Subclasses of LinearSolver use two structs to configure themselves. -// The Options struct configures the LinearSolver object for its -// lifetime. The PerSolveOptions struct is used to specify options for -// a particular Solve call. -class LinearSolver { - public: - struct Options { - Options() - : type(SPARSE_NORMAL_CHOLESKY), - preconditioner_type(JACOBI), - visibility_clustering_type(CANONICAL_VIEWS), - dense_linear_algebra_library_type(EIGEN), - sparse_linear_algebra_library_type(SUITE_SPARSE), - use_postordering(false), - dynamic_sparsity(false), - use_explicit_schur_complement(false), - min_num_iterations(1), - max_num_iterations(1), - num_threads(1), - residual_reset_period(10), - row_block_size(Eigen::Dynamic), - e_block_size(Eigen::Dynamic), - f_block_size(Eigen::Dynamic) { - } - - LinearSolverType type; - PreconditionerType preconditioner_type; - VisibilityClusteringType visibility_clustering_type; - DenseLinearAlgebraLibraryType dense_linear_algebra_library_type; - SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type; - - // See solver.h for information about these flags. - bool use_postordering; - bool dynamic_sparsity; - bool use_explicit_schur_complement; - - // Number of internal iterations that the solver uses. This - // parameter only makes sense for iterative solvers like CG. - int min_num_iterations; - int max_num_iterations; - - // If possible, how many threads can the solver use. - int num_threads; - - // Hints about the order in which the parameter blocks should be - // eliminated by the linear solver. - // - // For example if elimination_groups is a vector of size k, then - // the linear solver is informed that it should eliminate the - // parameter blocks 0 ... elimination_groups[0] - 1 first, and - // then elimination_groups[0] ... elimination_groups[1] - 1 and so - // on. Within each elimination group, the linear solver is free to - // choose how the parameter blocks are ordered. Different linear - // solvers have differing requirements on elimination_groups. - // - // The most common use is for Schur type solvers, where there - // should be at least two elimination groups and the first - // elimination group must form an independent set in the normal - // equations. The first elimination group corresponds to the - // num_eliminate_blocks in the Schur type solvers. - std::vector<int> elimination_groups; - - // Iterative solvers, e.g. Preconditioned Conjugate Gradients - // maintain a cheap estimate of the residual which may become - // inaccurate over time. Thus for non-zero values of this - // parameter, the solver can be told to recalculate the value of - // the residual using a |b - Ax| evaluation. - int residual_reset_period; - - // If the block sizes in a BlockSparseMatrix are fixed, then in - // some cases the Schur complement based solvers can detect and - // specialize on them. - // - // It is expected that these parameters are set programmatically - // rather than manually. - // - // Please see schur_complement_solver.h and schur_eliminator.h for - // more details. - int row_block_size; - int e_block_size; - int f_block_size; - }; - - // Options for the Solve method. - struct PerSolveOptions { - PerSolveOptions() - : D(NULL), - preconditioner(NULL), - r_tolerance(0.0), - q_tolerance(0.0) { - } - - // This option only makes sense for unsymmetric linear solvers - // that can solve rectangular linear systems. - // - // Given a matrix A, an optional diagonal matrix D as a vector, - // and a vector b, the linear solver will solve for - // - // | A | x = | b | - // | D | | 0 | - // - // If D is null, then it is treated as zero, and the solver returns - // the solution to - // - // A x = b - // - // In either case, x is the vector that solves the following - // optimization problem. - // - // arg min_x ||Ax - b||^2 + ||Dx||^2 - // - // Here A is a matrix of size m x n, with full column rank. If A - // does not have full column rank, the results returned by the - // solver cannot be relied on. D, if it is not null is an array of - // size n. b is an array of size m and x is an array of size n. - double * D; - - // This option only makes sense for iterative solvers. - // - // In general the performance of an iterative linear solver - // depends on the condition number of the matrix A. For example - // the convergence rate of the conjugate gradients algorithm - // is proportional to the square root of the condition number. - // - // One particularly useful technique for improving the - // conditioning of a linear system is to precondition it. In its - // simplest form a preconditioner is a matrix M such that instead - // of solving Ax = b, we solve the linear system AM^{-1} y = b - // instead, where M is such that the condition number k(AM^{-1}) - // is smaller than the conditioner k(A). Given the solution to - // this system, x = M^{-1} y. The iterative solver takes care of - // the mechanics of solving the preconditioned system and - // returning the corrected solution x. The user only needs to - // supply a linear operator. - // - // A null preconditioner is equivalent to an identity matrix being - // used a preconditioner. - LinearOperator* preconditioner; - - - // The following tolerance related options only makes sense for - // iterative solvers. Direct solvers ignore them. - - // Solver terminates when - // - // |Ax - b| <= r_tolerance * |b|. - // - // This is the most commonly used termination criterion for - // iterative solvers. - double r_tolerance; - - // For PSD matrices A, let - // - // Q(x) = x'Ax - 2b'x - // - // be the cost of the quadratic function defined by A and b. Then, - // the solver terminates at iteration i if - // - // i * (Q(x_i) - Q(x_i-1)) / Q(x_i) < q_tolerance. - // - // This termination criterion is more useful when using CG to - // solve the Newton step. This particular convergence test comes - // from Stephen Nash's work on truncated Newton - // methods. References: - // - // 1. Stephen G. Nash & Ariela Sofer, Assessing A Search - // Direction Within A Truncated Newton Method, Operation - // Research Letters 9(1990) 219-221. - // - // 2. Stephen G. Nash, A Survey of Truncated Newton Methods, - // Journal of Computational and Applied Mathematics, - // 124(1-2), 45-59, 2000. - // - double q_tolerance; - }; - - // Summary of a call to the Solve method. We should move away from - // the true/false method for determining solver success. We should - // let the summary object do the talking. - struct Summary { - Summary() - : residual_norm(0.0), - num_iterations(-1), - termination_type(LINEAR_SOLVER_FAILURE) { - } - - double residual_norm; - int num_iterations; - LinearSolverTerminationType termination_type; - std::string message; - }; - - // If the optimization problem is such that there are no remaining - // e-blocks, a Schur type linear solver cannot be used. If the - // linear solver is of Schur type, this function implements a policy - // to select an alternate nearest linear solver to the one selected - // by the user. The input linear_solver_type is returned otherwise. - static LinearSolverType LinearSolverForZeroEBlocks( - LinearSolverType linear_solver_type); - - virtual ~LinearSolver(); - - // Solve Ax = b. - virtual Summary Solve(LinearOperator* A, - const double* b, - const PerSolveOptions& per_solve_options, - double* x) = 0; - - // The following two methods return copies instead of references so - // that the base class implementation does not have to worry about - // life time issues. Further, these calls are not expected to be - // frequent or performance sensitive. - virtual std::map<std::string, int> CallStatistics() const { - return std::map<std::string, int>(); - } - - virtual std::map<std::string, double> TimeStatistics() const { - return std::map<std::string, double>(); - } - - // Factory - static LinearSolver* Create(const Options& options); -}; - -// This templated subclass of LinearSolver serves as a base class for -// other linear solvers that depend on the particular matrix layout of -// the underlying linear operator. For example some linear solvers -// need low level access to the TripletSparseMatrix implementing the -// LinearOperator interface. This class hides those implementation -// details behind a private virtual method, and has the Solve method -// perform the necessary upcasting. -template <typename MatrixType> -class TypedLinearSolver : public LinearSolver { - public: - virtual ~TypedLinearSolver() {} - virtual LinearSolver::Summary Solve( - LinearOperator* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x) { - ScopedExecutionTimer total_time("LinearSolver::Solve", &execution_summary_); - CHECK_NOTNULL(A); - CHECK_NOTNULL(b); - CHECK_NOTNULL(x); - return SolveImpl(down_cast<MatrixType*>(A), b, per_solve_options, x); - } - - virtual std::map<std::string, int> CallStatistics() const { - return execution_summary_.calls(); - } - - virtual std::map<std::string, double> TimeStatistics() const { - return execution_summary_.times(); - } - - private: - virtual LinearSolver::Summary SolveImpl( - MatrixType* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x) = 0; - - ExecutionSummary execution_summary_; -}; - -// Linear solvers that depend on acccess to the low level structure of -// a SparseMatrix. -typedef TypedLinearSolver<BlockSparseMatrix> BlockSparseMatrixSolver; // NOLINT -typedef TypedLinearSolver<CompressedRowSparseMatrix> CompressedRowSparseMatrixSolver; // NOLINT -typedef TypedLinearSolver<DenseSparseMatrix> DenseSparseMatrixSolver; // NOLINT -typedef TypedLinearSolver<TripletSparseMatrix> TripletSparseMatrixSolver; // NOLINT - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_LINEAR_SOLVER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/local_parameterization.cc b/extern/libmv/third_party/ceres/internal/ceres/local_parameterization.cc deleted file mode 100644 index 82004761ec0..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/local_parameterization.cc +++ /dev/null @@ -1,345 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/local_parameterization.h" - -#include "ceres/householder_vector.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/fixed_array.h" -#include "ceres/rotation.h" -#include "glog/logging.h" - -namespace ceres { - -using std::vector; - -LocalParameterization::~LocalParameterization() { -} - -bool LocalParameterization::MultiplyByJacobian(const double* x, - const int num_rows, - const double* global_matrix, - double* local_matrix) const { - Matrix jacobian(GlobalSize(), LocalSize()); - if (!ComputeJacobian(x, jacobian.data())) { - return false; - } - - MatrixRef(local_matrix, num_rows, LocalSize()) = - ConstMatrixRef(global_matrix, num_rows, GlobalSize()) * jacobian; - return true; -} - -IdentityParameterization::IdentityParameterization(const int size) - : size_(size) { - CHECK_GT(size, 0); -} - -bool IdentityParameterization::Plus(const double* x, - const double* delta, - double* x_plus_delta) const { - VectorRef(x_plus_delta, size_) = - ConstVectorRef(x, size_) + ConstVectorRef(delta, size_); - return true; -} - -bool IdentityParameterization::ComputeJacobian(const double* x, - double* jacobian) const { - MatrixRef(jacobian, size_, size_) = Matrix::Identity(size_, size_); - return true; -} - -bool IdentityParameterization::MultiplyByJacobian(const double* x, - const int num_cols, - const double* global_matrix, - double* local_matrix) const { - std::copy(global_matrix, - global_matrix + num_cols * GlobalSize(), - local_matrix); - return true; -} - -SubsetParameterization::SubsetParameterization( - int size, - const vector<int>& constant_parameters) - : local_size_(size - constant_parameters.size()), - constancy_mask_(size, 0) { - CHECK_GT(constant_parameters.size(), 0) - << "The set of constant parameters should contain at least " - << "one element. If you do not wish to hold any parameters " - << "constant, then do not use a SubsetParameterization"; - - vector<int> constant = constant_parameters; - sort(constant.begin(), constant.end()); - CHECK(unique(constant.begin(), constant.end()) == constant.end()) - << "The set of constant parameters cannot contain duplicates"; - CHECK_LT(constant_parameters.size(), size) - << "Number of parameters held constant should be less " - << "than the size of the parameter block. If you wish " - << "to hold the entire parameter block constant, then a " - << "efficient way is to directly mark it as constant " - << "instead of using a LocalParameterization to do so."; - CHECK_GE(*min_element(constant.begin(), constant.end()), 0); - CHECK_LT(*max_element(constant.begin(), constant.end()), size); - - for (int i = 0; i < constant_parameters.size(); ++i) { - constancy_mask_[constant_parameters[i]] = 1; - } -} - -bool SubsetParameterization::Plus(const double* x, - const double* delta, - double* x_plus_delta) const { - for (int i = 0, j = 0; i < constancy_mask_.size(); ++i) { - if (constancy_mask_[i]) { - x_plus_delta[i] = x[i]; - } else { - x_plus_delta[i] = x[i] + delta[j++]; - } - } - return true; -} - -bool SubsetParameterization::ComputeJacobian(const double* x, - double* jacobian) const { - MatrixRef m(jacobian, constancy_mask_.size(), local_size_); - m.setZero(); - for (int i = 0, j = 0; i < constancy_mask_.size(); ++i) { - if (!constancy_mask_[i]) { - m(i, j++) = 1.0; - } - } - return true; -} - -bool SubsetParameterization::MultiplyByJacobian(const double* x, - const int num_rows, - const double* global_matrix, - double* local_matrix) const { - for (int row = 0; row < num_rows; ++row) { - for (int col = 0, j = 0; col < constancy_mask_.size(); ++col) { - if (!constancy_mask_[col]) { - local_matrix[row * LocalSize() + j++] = - global_matrix[row * GlobalSize() + col]; - } - } - } - return true; -} - -bool QuaternionParameterization::Plus(const double* x, - const double* delta, - double* x_plus_delta) const { - const double norm_delta = - sqrt(delta[0] * delta[0] + delta[1] * delta[1] + delta[2] * delta[2]); - if (norm_delta > 0.0) { - const double sin_delta_by_delta = (sin(norm_delta) / norm_delta); - double q_delta[4]; - q_delta[0] = cos(norm_delta); - q_delta[1] = sin_delta_by_delta * delta[0]; - q_delta[2] = sin_delta_by_delta * delta[1]; - q_delta[3] = sin_delta_by_delta * delta[2]; - QuaternionProduct(q_delta, x, x_plus_delta); - } else { - for (int i = 0; i < 4; ++i) { - x_plus_delta[i] = x[i]; - } - } - return true; -} - -bool QuaternionParameterization::ComputeJacobian(const double* x, - double* jacobian) const { - jacobian[0] = -x[1]; jacobian[1] = -x[2]; jacobian[2] = -x[3]; // NOLINT - jacobian[3] = x[0]; jacobian[4] = x[3]; jacobian[5] = -x[2]; // NOLINT - jacobian[6] = -x[3]; jacobian[7] = x[0]; jacobian[8] = x[1]; // NOLINT - jacobian[9] = x[2]; jacobian[10] = -x[1]; jacobian[11] = x[0]; // NOLINT - return true; -} - -HomogeneousVectorParameterization::HomogeneousVectorParameterization(int size) - : size_(size) { - CHECK_GT(size_, 1) << "The size of the homogeneous vector needs to be " - << "greater than 1."; -} - -bool HomogeneousVectorParameterization::Plus(const double* x_ptr, - const double* delta_ptr, - double* x_plus_delta_ptr) const { - ConstVectorRef x(x_ptr, size_); - ConstVectorRef delta(delta_ptr, size_ - 1); - VectorRef x_plus_delta(x_plus_delta_ptr, size_); - - const double norm_delta = delta.norm(); - - if (norm_delta == 0.0) { - x_plus_delta = x; - return true; - } - - // Map the delta from the minimum representation to the over parameterized - // homogeneous vector. See section A6.9.2 on page 624 of Hartley & Zisserman - // (2nd Edition) for a detailed description. Note there is a typo on Page - // 625, line 4 so check the book errata. - const double norm_delta_div_2 = 0.5 * norm_delta; - const double sin_delta_by_delta = sin(norm_delta_div_2) / - norm_delta_div_2; - - Vector y(size_); - y.head(size_ - 1) = 0.5 * sin_delta_by_delta * delta; - y(size_ - 1) = cos(norm_delta_div_2); - - Vector v(size_); - double beta; - internal::ComputeHouseholderVector<double>(x, &v, &beta); - - // Apply the delta update to remain on the unit sphere. See section A6.9.3 - // on page 625 of Hartley & Zisserman (2nd Edition) for a detailed - // description. - x_plus_delta = x.norm() * (y - v * (beta * (v.transpose() * y))); - - return true; -} - -bool HomogeneousVectorParameterization::ComputeJacobian( - const double* x_ptr, double* jacobian_ptr) const { - ConstVectorRef x(x_ptr, size_); - MatrixRef jacobian(jacobian_ptr, size_, size_ - 1); - - Vector v(size_); - double beta; - internal::ComputeHouseholderVector<double>(x, &v, &beta); - - // The Jacobian is equal to J = 0.5 * H.leftCols(size_ - 1) where H is the - // Householder matrix (H = I - beta * v * v'). - for (int i = 0; i < size_ - 1; ++i) { - jacobian.col(i) = -0.5 * beta * v(i) * v; - jacobian.col(i)(i) += 0.5; - } - jacobian *= x.norm(); - - return true; -} - -ProductParameterization::ProductParameterization( - LocalParameterization* local_param1, - LocalParameterization* local_param2) { - local_params_.push_back(local_param1); - local_params_.push_back(local_param2); - Init(); -} - -ProductParameterization::ProductParameterization( - LocalParameterization* local_param1, - LocalParameterization* local_param2, - LocalParameterization* local_param3) { - local_params_.push_back(local_param1); - local_params_.push_back(local_param2); - local_params_.push_back(local_param3); - Init(); -} - -ProductParameterization::ProductParameterization( - LocalParameterization* local_param1, - LocalParameterization* local_param2, - LocalParameterization* local_param3, - LocalParameterization* local_param4) { - local_params_.push_back(local_param1); - local_params_.push_back(local_param2); - local_params_.push_back(local_param3); - local_params_.push_back(local_param4); - Init(); -} - -ProductParameterization::~ProductParameterization() { - for (int i = 0; i < local_params_.size(); ++i) { - delete local_params_[i]; - } -} - -void ProductParameterization::Init() { - global_size_ = 0; - local_size_ = 0; - buffer_size_ = 0; - for (int i = 0; i < local_params_.size(); ++i) { - const LocalParameterization* param = local_params_[i]; - buffer_size_ = std::max(buffer_size_, - param->LocalSize() * param->GlobalSize()); - global_size_ += param->GlobalSize(); - local_size_ += param->LocalSize(); - } -} - -bool ProductParameterization::Plus(const double* x, - const double* delta, - double* x_plus_delta) const { - int x_cursor = 0; - int delta_cursor = 0; - for (int i = 0; i < local_params_.size(); ++i) { - const LocalParameterization* param = local_params_[i]; - if (!param->Plus(x + x_cursor, - delta + delta_cursor, - x_plus_delta + x_cursor)) { - return false; - } - delta_cursor += param->LocalSize(); - x_cursor += param->GlobalSize(); - } - - return true; -} - -bool ProductParameterization::ComputeJacobian(const double* x, - double* jacobian_ptr) const { - MatrixRef jacobian(jacobian_ptr, GlobalSize(), LocalSize()); - jacobian.setZero(); - internal::FixedArray<double> buffer(buffer_size_); - - int x_cursor = 0; - int delta_cursor = 0; - for (int i = 0; i < local_params_.size(); ++i) { - const LocalParameterization* param = local_params_[i]; - const int local_size = param->LocalSize(); - const int global_size = param->GlobalSize(); - - if (!param->ComputeJacobian(x + x_cursor, buffer.get())) { - return false; - } - - jacobian.block(x_cursor, delta_cursor, global_size, local_size) - = MatrixRef(buffer.get(), global_size, local_size); - delta_cursor += local_size; - x_cursor += global_size; - } - - return true; -} - -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/loss_function.cc b/extern/libmv/third_party/ceres/internal/ceres/loss_function.cc deleted file mode 100644 index eb5026784dd..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/loss_function.cc +++ /dev/null @@ -1,174 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Purpose: See .h file. - -#include "ceres/loss_function.h" - -#include <cmath> -#include <cstddef> -#include <limits> - -namespace ceres { - -void TrivialLoss::Evaluate(double s, double rho[3]) const { - rho[0] = s; - rho[1] = 1.0; - rho[2] = 0.0; -} - -void HuberLoss::Evaluate(double s, double rho[3]) const { - if (s > b_) { - // Outlier region. - // 'r' is always positive. - const double r = sqrt(s); - rho[0] = 2.0 * a_ * r - b_; - rho[1] = std::max(std::numeric_limits<double>::min(), a_ / r); - rho[2] = - rho[1] / (2.0 * s); - } else { - // Inlier region. - rho[0] = s; - rho[1] = 1.0; - rho[2] = 0.0; - } -} - -void SoftLOneLoss::Evaluate(double s, double rho[3]) const { - const double sum = 1.0 + s * c_; - const double tmp = sqrt(sum); - // 'sum' and 'tmp' are always positive, assuming that 's' is. - rho[0] = 2.0 * b_ * (tmp - 1.0); - rho[1] = std::max(std::numeric_limits<double>::min(), 1.0 / tmp); - rho[2] = - (c_ * rho[1]) / (2.0 * sum); -} - -void CauchyLoss::Evaluate(double s, double rho[3]) const { - const double sum = 1.0 + s * c_; - const double inv = 1.0 / sum; - // 'sum' and 'inv' are always positive, assuming that 's' is. - rho[0] = b_ * log(sum); - rho[1] = std::max(std::numeric_limits<double>::min(), inv); - rho[2] = - c_ * (inv * inv); -} - -void ArctanLoss::Evaluate(double s, double rho[3]) const { - const double sum = 1 + s * s * b_; - const double inv = 1 / sum; - // 'sum' and 'inv' are always positive. - rho[0] = a_ * atan2(s, a_); - rho[1] = std::max(std::numeric_limits<double>::min(), inv); - rho[2] = -2.0 * s * b_ * (inv * inv); -} - -TolerantLoss::TolerantLoss(double a, double b) - : a_(a), - b_(b), - c_(b * log(1.0 + exp(-a / b))) { - CHECK_GE(a, 0.0); - CHECK_GT(b, 0.0); -} - -void TolerantLoss::Evaluate(double s, double rho[3]) const { - const double x = (s - a_) / b_; - // The basic equation is rho[0] = b ln(1 + e^x). However, if e^x is too - // large, it will overflow. Since numerically 1 + e^x == e^x when the - // x is greater than about ln(2^53) for doubles, beyond this threshold - // we substitute x for ln(1 + e^x) as a numerically equivalent approximation. - static const double kLog2Pow53 = 36.7; // ln(MathLimits<double>::kEpsilon). - if (x > kLog2Pow53) { - rho[0] = s - a_ - c_; - rho[1] = 1.0; - rho[2] = 0.0; - } else { - const double e_x = exp(x); - rho[0] = b_ * log(1.0 + e_x) - c_; - rho[1] = std::max(std::numeric_limits<double>::min(), e_x / (1.0 + e_x)); - rho[2] = 0.5 / (b_ * (1.0 + cosh(x))); - } -} - -void TukeyLoss::Evaluate(double s, double* rho) const { - if (s <= a_squared_) { - // Inlier region. - const double value = 1.0 - s / a_squared_; - const double value_sq = value * value; - rho[0] = a_squared_ / 6.0 * (1.0 - value_sq * value); - rho[1] = 0.5 * value_sq; - rho[2] = -1.0 / a_squared_ * value; - } else { - // Outlier region. - rho[0] = a_squared_ / 6.0; - rho[1] = 0.0; - rho[2] = 0.0; - } -} - -ComposedLoss::ComposedLoss(const LossFunction* f, Ownership ownership_f, - const LossFunction* g, Ownership ownership_g) - : f_(CHECK_NOTNULL(f)), - g_(CHECK_NOTNULL(g)), - ownership_f_(ownership_f), - ownership_g_(ownership_g) { -} - -ComposedLoss::~ComposedLoss() { - if (ownership_f_ == DO_NOT_TAKE_OWNERSHIP) { - f_.release(); - } - if (ownership_g_ == DO_NOT_TAKE_OWNERSHIP) { - g_.release(); - } -} - -void ComposedLoss::Evaluate(double s, double rho[3]) const { - double rho_f[3], rho_g[3]; - g_->Evaluate(s, rho_g); - f_->Evaluate(rho_g[0], rho_f); - rho[0] = rho_f[0]; - // f'(g(s)) * g'(s). - rho[1] = rho_f[1] * rho_g[1]; - // f''(g(s)) * g'(s) * g'(s) + f'(g(s)) * g''(s). - rho[2] = rho_f[2] * rho_g[1] * rho_g[1] + rho_f[1] * rho_g[2]; -} - -void ScaledLoss::Evaluate(double s, double rho[3]) const { - if (rho_.get() == NULL) { - rho[0] = a_ * s; - rho[1] = a_; - rho[2] = 0.0; - } else { - rho_->Evaluate(s, rho); - rho[0] *= a_; - rho[1] *= a_; - rho[2] *= a_; - } -} - -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/low_rank_inverse_hessian.cc b/extern/libmv/third_party/ceres/internal/ceres/low_rank_inverse_hessian.cc deleted file mode 100644 index 1c6c9925f1c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/low_rank_inverse_hessian.cc +++ /dev/null @@ -1,188 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include <list> - -#include "ceres/internal/eigen.h" -#include "ceres/low_rank_inverse_hessian.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::list; - -// The (L)BFGS algorithm explicitly requires that the secant equation: -// -// B_{k+1} * s_k = y_k -// -// Is satisfied at each iteration, where B_{k+1} is the approximated -// Hessian at the k+1-th iteration, s_k = (x_{k+1} - x_{k}) and -// y_k = (grad_{k+1} - grad_{k}). As the approximated Hessian must be -// positive definite, this is equivalent to the condition: -// -// s_k^T * y_k > 0 [s_k^T * B_{k+1} * s_k = s_k^T * y_k > 0] -// -// This condition would always be satisfied if the function was strictly -// convex, alternatively, it is always satisfied provided that a Wolfe line -// search is used (even if the function is not strictly convex). See [1] -// (p138) for a proof. -// -// Although Ceres will always use a Wolfe line search when using (L)BFGS, -// practical implementation considerations mean that the line search -// may return a point that satisfies only the Armijo condition, and thus -// could violate the Secant equation. As such, we will only use a step -// to update the Hessian approximation if: -// -// s_k^T * y_k > tolerance -// -// It is important that tolerance is very small (and >=0), as otherwise we -// might skip the update too often and fail to capture important curvature -// information in the Hessian. For example going from 1e-10 -> 1e-14 improves -// the NIST benchmark score from 43/54 to 53/54. -// -// [1] Nocedal J., Wright S., Numerical Optimization, 2nd Ed. Springer, 1999. -// -// TODO(alexs.mac): Consider using Damped BFGS update instead of -// skipping update. -const double kLBFGSSecantConditionHessianUpdateTolerance = 1e-14; - -LowRankInverseHessian::LowRankInverseHessian( - int num_parameters, - int max_num_corrections, - bool use_approximate_eigenvalue_scaling) - : num_parameters_(num_parameters), - max_num_corrections_(max_num_corrections), - use_approximate_eigenvalue_scaling_(use_approximate_eigenvalue_scaling), - approximate_eigenvalue_scale_(1.0), - delta_x_history_(num_parameters, max_num_corrections), - delta_gradient_history_(num_parameters, max_num_corrections), - delta_x_dot_delta_gradient_(max_num_corrections) { -} - -bool LowRankInverseHessian::Update(const Vector& delta_x, - const Vector& delta_gradient) { - const double delta_x_dot_delta_gradient = delta_x.dot(delta_gradient); - if (delta_x_dot_delta_gradient <= - kLBFGSSecantConditionHessianUpdateTolerance) { - VLOG(2) << "Skipping L-BFGS Update, delta_x_dot_delta_gradient too " - << "small: " << delta_x_dot_delta_gradient << ", tolerance: " - << kLBFGSSecantConditionHessianUpdateTolerance - << " (Secant condition)."; - return false; - } - - - int next = indices_.size(); - // Once the size of the list reaches max_num_corrections_, simulate - // a circular buffer by removing the first element of the list and - // making it the next position where the LBFGS history is stored. - if (next == max_num_corrections_) { - next = indices_.front(); - indices_.pop_front(); - } - - indices_.push_back(next); - delta_x_history_.col(next) = delta_x; - delta_gradient_history_.col(next) = delta_gradient; - delta_x_dot_delta_gradient_(next) = delta_x_dot_delta_gradient; - approximate_eigenvalue_scale_ = - delta_x_dot_delta_gradient / delta_gradient.squaredNorm(); - return true; -} - -void LowRankInverseHessian::RightMultiply(const double* x_ptr, - double* y_ptr) const { - ConstVectorRef gradient(x_ptr, num_parameters_); - VectorRef search_direction(y_ptr, num_parameters_); - - search_direction = gradient; - - const int num_corrections = indices_.size(); - Vector alpha(num_corrections); - - for (list<int>::const_reverse_iterator it = indices_.rbegin(); - it != indices_.rend(); - ++it) { - const double alpha_i = delta_x_history_.col(*it).dot(search_direction) / - delta_x_dot_delta_gradient_(*it); - search_direction -= alpha_i * delta_gradient_history_.col(*it); - alpha(*it) = alpha_i; - } - - if (use_approximate_eigenvalue_scaling_) { - // Rescale the initial inverse Hessian approximation (H_0) to be iteratively - // updated so that it is of similar 'size' to the true inverse Hessian along - // the most recent search direction. As shown in [1]: - // - // \gamma_k = (delta_gradient_{k-1}' * delta_x_{k-1}) / - // (delta_gradient_{k-1}' * delta_gradient_{k-1}) - // - // Satisfies: - // - // (1 / \lambda_m) <= \gamma_k <= (1 / \lambda_1) - // - // Where \lambda_1 & \lambda_m are the smallest and largest eigenvalues of - // the true Hessian (not the inverse) along the most recent search direction - // respectively. Thus \gamma is an approximate eigenvalue of the true - // inverse Hessian, and choosing: H_0 = I * \gamma will yield a starting - // point that has a similar scale to the true inverse Hessian. This - // technique is widely reported to often improve convergence, however this - // is not universally true, particularly if there are errors in the initial - // jacobians, or if there are significant differences in the sensitivity - // of the problem to the parameters (i.e. the range of the magnitudes of - // the components of the gradient is large). - // - // The original origin of this rescaling trick is somewhat unclear, the - // earliest reference appears to be Oren [1], however it is widely discussed - // without specific attributation in various texts including [2] (p143/178). - // - // [1] Oren S.S., Self-scaling variable metric (SSVM) algorithms Part II: - // Implementation and experiments, Management Science, - // 20(5), 863-874, 1974. - // [2] Nocedal J., Wright S., Numerical Optimization, Springer, 1999. - search_direction *= approximate_eigenvalue_scale_; - - VLOG(4) << "Applying approximate_eigenvalue_scale: " - << approximate_eigenvalue_scale_ << " to initial inverse Hessian " - << "approximation."; - } - - for (list<int>::const_iterator it = indices_.begin(); - it != indices_.end(); - ++it) { - const double beta = delta_gradient_history_.col(*it).dot(search_direction) / - delta_x_dot_delta_gradient_(*it); - search_direction += delta_x_history_.col(*it) * (alpha(*it) - beta); - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/low_rank_inverse_hessian.h b/extern/libmv/third_party/ceres/internal/ceres/low_rank_inverse_hessian.h deleted file mode 100644 index 2c768c2ca53..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/low_rank_inverse_hessian.h +++ /dev/null @@ -1,108 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Limited memory positive definite approximation to the inverse -// Hessian, using the LBFGS algorithm - -#ifndef CERES_INTERNAL_LOW_RANK_INVERSE_HESSIAN_H_ -#define CERES_INTERNAL_LOW_RANK_INVERSE_HESSIAN_H_ - -#include <list> - -#include "ceres/internal/eigen.h" -#include "ceres/linear_operator.h" - -namespace ceres { -namespace internal { - -// LowRankInverseHessian is a positive definite approximation to the -// Hessian using the limited memory variant of the -// Broyden-Fletcher-Goldfarb-Shanno (BFGS)secant formula for -// approximating the Hessian. -// -// Other update rules like the Davidon-Fletcher-Powell (DFP) are -// possible, but the BFGS rule is considered the best performing one. -// -// The limited memory variant was developed by Nocedal and further -// enhanced with scaling rule by Byrd, Nocedal and Schanbel. -// -// Nocedal, J. (1980). "Updating Quasi-Newton Matrices with Limited -// Storage". Mathematics of Computation 35 (151): 773–782. -// -// Byrd, R. H.; Nocedal, J.; Schnabel, R. B. (1994). -// "Representations of Quasi-Newton Matrices and their use in -// Limited Memory Methods". Mathematical Programming 63 (4): -class LowRankInverseHessian : public LinearOperator { - public: - // num_parameters is the row/column size of the Hessian. - // max_num_corrections is the rank of the Hessian approximation. - // use_approximate_eigenvalue_scaling controls whether the initial - // inverse Hessian used during Right/LeftMultiply() is scaled by - // the approximate eigenvalue of the true inverse Hessian at the - // current operating point. - // The approximation uses: - // 2 * max_num_corrections * num_parameters + max_num_corrections - // doubles. - LowRankInverseHessian(int num_parameters, - int max_num_corrections, - bool use_approximate_eigenvalue_scaling); - virtual ~LowRankInverseHessian() {} - - // Update the low rank approximation. delta_x is the change in the - // domain of Hessian, and delta_gradient is the change in the - // gradient. The update copies the delta_x and delta_gradient - // vectors, and gets rid of the oldest delta_x and delta_gradient - // vectors if the number of corrections is already equal to - // max_num_corrections. - bool Update(const Vector& delta_x, const Vector& delta_gradient); - - // LinearOperator interface - virtual void RightMultiply(const double* x, double* y) const; - virtual void LeftMultiply(const double* x, double* y) const { - RightMultiply(x, y); - } - virtual int num_rows() const { return num_parameters_; } - virtual int num_cols() const { return num_parameters_; } - - private: - const int num_parameters_; - const int max_num_corrections_; - const bool use_approximate_eigenvalue_scaling_; - double approximate_eigenvalue_scale_; - ColMajorMatrix delta_x_history_; - ColMajorMatrix delta_gradient_history_; - Vector delta_x_dot_delta_gradient_; - std::list<int> indices_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_LOW_RANK_INVERSE_HESSIAN_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/map_util.h b/extern/libmv/third_party/ceres/internal/ceres/map_util.h deleted file mode 100644 index 61c531f297c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/map_util.h +++ /dev/null @@ -1,130 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// Originally by Anton Carver - -#ifndef CERES_INTERNAL_MAP_UTIL_H_ -#define CERES_INTERNAL_MAP_UTIL_H_ - -#include <utility> -#include "ceres/internal/port.h" -#include "glog/logging.h" - -namespace ceres { - -// Perform a lookup in a map or hash_map, assuming that the key exists. -// Crash if it does not. -// -// This is intended as a replacement for operator[] as an rvalue (for reading) -// when the key is guaranteed to exist. -// -// operator[] is discouraged for several reasons: -// * It has a side-effect of inserting missing keys -// * It is not thread-safe (even when it is not inserting, it can still -// choose to resize the underlying storage) -// * It invalidates iterators (when it chooses to resize) -// * It default constructs a value object even if it doesn't need to -// -// This version assumes the key is printable, and includes it in the fatal log -// message. -template <class Collection> -const typename Collection::value_type::second_type& -FindOrDie(const Collection& collection, - const typename Collection::value_type::first_type& key) { - typename Collection::const_iterator it = collection.find(key); - CHECK(it != collection.end()) << "Map key not found: " << key; - return it->second; -} - -// Perform a lookup in a map or hash_map. -// If the key is present in the map then the value associated with that -// key is returned, otherwise the value passed as a default is returned. -template <class Collection> -const typename Collection::value_type::second_type& -FindWithDefault(const Collection& collection, - const typename Collection::value_type::first_type& key, - const typename Collection::value_type::second_type& value) { - typename Collection::const_iterator it = collection.find(key); - if (it == collection.end()) { - return value; - } - return it->second; -} - -// Insert a new key and value into a map or hash_map. -// If the key is not present in the map the key and value are -// inserted, otherwise nothing happens. True indicates that an insert -// took place, false indicates the key was already present. -template <class Collection> -bool InsertIfNotPresent( - Collection * const collection, - const typename Collection::value_type::first_type& key, - const typename Collection::value_type::second_type& value) { - std::pair<typename Collection::iterator, bool> ret = - collection->insert(typename Collection::value_type(key, value)); - return ret.second; -} - -// Perform a lookup in a map or hash_map. -// Same as above but the returned pointer is not const and can be used to change -// the stored value. -template <class Collection> -typename Collection::value_type::second_type* -FindOrNull(Collection& collection, // NOLINT - const typename Collection::value_type::first_type& key) { - typename Collection::iterator it = collection.find(key); - if (it == collection.end()) { - return 0; - } - return &it->second; -} - -// Test to see if a set, map, hash_set or hash_map contains a particular key. -// Returns true if the key is in the collection. -template <class Collection, class Key> -bool ContainsKey(const Collection& collection, const Key& key) { - typename Collection::const_iterator it = collection.find(key); - return it != collection.end(); -} - -// Inserts a new key/value into a map or hash_map. -// Dies if the key is already present. -template<class Collection> -void InsertOrDie(Collection* const collection, - const typename Collection::value_type::first_type& key, - const typename Collection::value_type::second_type& data) { - typedef typename Collection::value_type value_type; - CHECK(collection->insert(value_type(key, data)).second) - << "duplicate key: " << key; -} - -} // namespace ceres - -#endif // CERES_INTERNAL_MAP_UTIL_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/minimizer.cc b/extern/libmv/third_party/ceres/internal/ceres/minimizer.cc deleted file mode 100644 index f5960336f12..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/minimizer.cc +++ /dev/null @@ -1,87 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/line_search_minimizer.h" -#include "ceres/minimizer.h" -#include "ceres/trust_region_minimizer.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -Minimizer* Minimizer::Create(MinimizerType minimizer_type) { - if (minimizer_type == TRUST_REGION) { - return new TrustRegionMinimizer; - } - - if (minimizer_type == LINE_SEARCH) { - return new LineSearchMinimizer; - } - - LOG(FATAL) << "Unknown minimizer_type: " << minimizer_type; - return NULL; -} - - -Minimizer::~Minimizer() {} - -bool Minimizer::RunCallbacks(const Minimizer::Options& options, - const IterationSummary& iteration_summary, - Solver::Summary* summary) { - const bool is_not_silent = !options.is_silent; - CallbackReturnType status = SOLVER_CONTINUE; - int i = 0; - while (status == SOLVER_CONTINUE && i < options.callbacks.size()) { - status = (*options.callbacks[i])(iteration_summary); - ++i; - } - switch (status) { - case SOLVER_CONTINUE: - return true; - case SOLVER_TERMINATE_SUCCESSFULLY: - summary->termination_type = USER_SUCCESS; - summary->message = - "User callback returned SOLVER_TERMINATE_SUCCESSFULLY."; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - return false; - case SOLVER_ABORT: - summary->termination_type = USER_FAILURE; - summary->message = "User callback returned SOLVER_ABORT."; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - return false; - default: - LOG(FATAL) << "Unknown type of user callback status"; - } - return false; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/minimizer.h b/extern/libmv/third_party/ceres/internal/ceres/minimizer.h deleted file mode 100644 index b59372806e7..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/minimizer.h +++ /dev/null @@ -1,202 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_MINIMIZER_H_ -#define CERES_INTERNAL_MINIMIZER_H_ - -#include <string> -#include <vector> -#include "ceres/internal/port.h" -#include "ceres/iteration_callback.h" -#include "ceres/solver.h" - -namespace ceres { -namespace internal { - -class Evaluator; -class SparseMatrix; -class TrustRegionStrategy; -class CoordinateDescentMinimizer; -class LinearSolver; - -// Interface for non-linear least squares solvers. -class Minimizer { - public: - // Options struct to control the behaviour of the Minimizer. Please - // see solver.h for detailed information about the meaning and - // default values of each of these parameters. - struct Options { - Options() { - Init(Solver::Options()); - } - - explicit Options(const Solver::Options& options) { - Init(options); - } - - void Init(const Solver::Options& options) { - num_threads = options.num_threads; - max_num_iterations = options.max_num_iterations; - max_solver_time_in_seconds = options.max_solver_time_in_seconds; - max_step_solver_retries = 5; - gradient_tolerance = options.gradient_tolerance; - parameter_tolerance = options.parameter_tolerance; - function_tolerance = options.function_tolerance; - min_relative_decrease = options.min_relative_decrease; - eta = options.eta; - jacobi_scaling = options.jacobi_scaling; - use_nonmonotonic_steps = options.use_nonmonotonic_steps; - max_consecutive_nonmonotonic_steps = - options.max_consecutive_nonmonotonic_steps; - trust_region_problem_dump_directory = - options.trust_region_problem_dump_directory; - trust_region_minimizer_iterations_to_dump = - options.trust_region_minimizer_iterations_to_dump; - trust_region_problem_dump_format_type = - options.trust_region_problem_dump_format_type; - max_num_consecutive_invalid_steps = - options.max_num_consecutive_invalid_steps; - min_trust_region_radius = options.min_trust_region_radius; - line_search_direction_type = options.line_search_direction_type; - line_search_type = options.line_search_type; - nonlinear_conjugate_gradient_type = - options.nonlinear_conjugate_gradient_type; - max_lbfgs_rank = options.max_lbfgs_rank; - use_approximate_eigenvalue_bfgs_scaling = - options.use_approximate_eigenvalue_bfgs_scaling; - line_search_interpolation_type = - options.line_search_interpolation_type; - min_line_search_step_size = options.min_line_search_step_size; - line_search_sufficient_function_decrease = - options.line_search_sufficient_function_decrease; - max_line_search_step_contraction = - options.max_line_search_step_contraction; - min_line_search_step_contraction = - options.min_line_search_step_contraction; - max_num_line_search_step_size_iterations = - options.max_num_line_search_step_size_iterations; - max_num_line_search_direction_restarts = - options.max_num_line_search_direction_restarts; - line_search_sufficient_curvature_decrease = - options.line_search_sufficient_curvature_decrease; - max_line_search_step_expansion = - options.max_line_search_step_expansion; - inner_iteration_tolerance = options.inner_iteration_tolerance; - is_silent = (options.logging_type == SILENT); - is_constrained = false; - callbacks = options.callbacks; - } - - int max_num_iterations; - double max_solver_time_in_seconds; - int num_threads; - - // Number of times the linear solver should be retried in case of - // numerical failure. The retries are done by exponentially scaling up - // mu at each retry. This leads to stronger and stronger - // regularization making the linear least squares problem better - // conditioned at each retry. - int max_step_solver_retries; - double gradient_tolerance; - double parameter_tolerance; - double function_tolerance; - double min_relative_decrease; - double eta; - bool jacobi_scaling; - bool use_nonmonotonic_steps; - int max_consecutive_nonmonotonic_steps; - std::vector<int> trust_region_minimizer_iterations_to_dump; - DumpFormatType trust_region_problem_dump_format_type; - std::string trust_region_problem_dump_directory; - int max_num_consecutive_invalid_steps; - double min_trust_region_radius; - LineSearchDirectionType line_search_direction_type; - LineSearchType line_search_type; - NonlinearConjugateGradientType nonlinear_conjugate_gradient_type; - int max_lbfgs_rank; - bool use_approximate_eigenvalue_bfgs_scaling; - LineSearchInterpolationType line_search_interpolation_type; - double min_line_search_step_size; - double line_search_sufficient_function_decrease; - double max_line_search_step_contraction; - double min_line_search_step_contraction; - int max_num_line_search_step_size_iterations; - int max_num_line_search_direction_restarts; - double line_search_sufficient_curvature_decrease; - double max_line_search_step_expansion; - double inner_iteration_tolerance; - - // If true, then all logging is disabled. - bool is_silent; - - // Use a bounds constrained optimization algorithm. - bool is_constrained; - - // List of callbacks that are executed by the Minimizer at the end - // of each iteration. - // - // The Options struct does not own these pointers. - std::vector<IterationCallback*> callbacks; - - // Object responsible for evaluating the cost, residuals and - // Jacobian matrix. - shared_ptr<Evaluator> evaluator; - - // Object responsible for actually computing the trust region - // step, and sizing the trust region radius. - shared_ptr<TrustRegionStrategy> trust_region_strategy; - - // Object holding the Jacobian matrix. It is assumed that the - // sparsity structure of the matrix has already been initialized - // and will remain constant for the life time of the - // optimization. - shared_ptr<SparseMatrix> jacobian; - - shared_ptr<CoordinateDescentMinimizer> inner_iteration_minimizer; - }; - - static Minimizer* Create(MinimizerType minimizer_type); - static bool RunCallbacks(const Options& options, - const IterationSummary& iteration_summary, - Solver::Summary* summary); - - virtual ~Minimizer(); - // Note: The minimizer is expected to update the state of the - // parameters array every iteration. This is required for the - // StateUpdatingCallback to work. - virtual void Minimize(const Options& options, - double* parameters, - Solver::Summary* summary) = 0; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_MINIMIZER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/mutex.h b/extern/libmv/third_party/ceres/internal/ceres/mutex.h deleted file mode 100644 index 2ce97772755..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/mutex.h +++ /dev/null @@ -1,329 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: Craig Silverstein. -// -// A simple mutex wrapper, supporting locks and read-write locks. -// You should assume the locks are *not* re-entrant. -// -// This class is meant to be internal-only and should be wrapped by an -// internal namespace. Before you use this module, please give the -// name of your internal namespace for this module. Or, if you want -// to expose it, you'll want to move it to the Google namespace. We -// cannot put this class in global namespace because there can be some -// problems when we have multiple versions of Mutex in each shared object. -// -// NOTE: by default, we have #ifdef'ed out the TryLock() method. -// This is for two reasons: -// 1) TryLock() under Windows is a bit annoying (it requires a -// #define to be defined very early). -// 2) TryLock() is broken for NO_THREADS mode, at least in NDEBUG -// mode. -// If you need TryLock(), and either these two caveats are not a -// problem for you, or you're willing to work around them, then -// feel free to #define GMUTEX_TRYLOCK, or to remove the #ifdefs -// in the code below. -// -// CYGWIN NOTE: Cygwin support for rwlock seems to be buggy: -// http://www.cygwin.com/ml/cygwin/2008-12/msg00017.html -// Because of that, we might as well use windows locks for -// cygwin. They seem to be more reliable than the cygwin pthreads layer. -// -// TRICKY IMPLEMENTATION NOTE: -// This class is designed to be safe to use during -// dynamic-initialization -- that is, by global constructors that are -// run before main() starts. The issue in this case is that -// dynamic-initialization happens in an unpredictable order, and it -// could be that someone else's dynamic initializer could call a -// function that tries to acquire this mutex -- but that all happens -// before this mutex's constructor has run. (This can happen even if -// the mutex and the function that uses the mutex are in the same .cc -// file.) Basically, because Mutex does non-trivial work in its -// constructor, it's not, in the naive implementation, safe to use -// before dynamic initialization has run on it. -// -// The solution used here is to pair the actual mutex primitive with a -// bool that is set to true when the mutex is dynamically initialized. -// (Before that it's false.) Then we modify all mutex routines to -// look at the bool, and not try to lock/unlock until the bool makes -// it to true (which happens after the Mutex constructor has run.) -// -// This works because before main() starts -- particularly, during -// dynamic initialization -- there are no threads, so a) it's ok that -// the mutex operations are a no-op, since we don't need locking then -// anyway; and b) we can be quite confident our bool won't change -// state between a call to Lock() and a call to Unlock() (that would -// require a global constructor in one translation unit to call Lock() -// and another global constructor in another translation unit to call -// Unlock() later, which is pretty perverse). -// -// That said, it's tricky, and can conceivably fail; it's safest to -// avoid trying to acquire a mutex in a global constructor, if you -// can. One way it can fail is that a really smart compiler might -// initialize the bool to true at static-initialization time (too -// early) rather than at dynamic-initialization time. To discourage -// that, we set is_safe_ to true in code (not the constructor -// colon-initializer) and set it to true via a function that always -// evaluates to true, but that the compiler can't know always -// evaluates to true. This should be good enough. - -#ifndef CERES_INTERNAL_MUTEX_H_ -#define CERES_INTERNAL_MUTEX_H_ - -#include "ceres/internal/port.h" - -#if defined(CERES_NO_THREADS) - typedef int MutexType; // to keep a lock-count -#elif defined(_WIN32) || defined(__CYGWIN32__) || defined(__CYGWIN64__) -# define CERES_WIN32_LEAN_AND_MEAN // We only need minimal includes -# ifdef CERES_GMUTEX_TRYLOCK - // We need Windows NT or later for TryEnterCriticalSection(). If you - // don't need that functionality, you can remove these _WIN32_WINNT - // lines, and change TryLock() to assert(0) or something. -# ifndef _WIN32_WINNT -# define _WIN32_WINNT 0x0400 -# endif -# endif -// Unfortunately, windows.h defines a bunch of macros with common -// names. Two in particular need avoiding: ERROR and min/max. -// To avoid macro definition of ERROR. -# define NOGDI -// To avoid macro definition of min/max. -# ifndef NOMINMAX -# define NOMINMAX -# endif -# include <windows.h> - typedef CRITICAL_SECTION MutexType; -#elif defined(CERES_HAVE_PTHREAD) && defined(CERES_HAVE_RWLOCK) - // Needed for pthread_rwlock_*. If it causes problems, you could take it - // out, but then you'd have to unset CERES_HAVE_RWLOCK (at least on linux -- - // it *does* cause problems for FreeBSD, or MacOSX, but isn't needed for - // locking there.) -# if defined(__linux__) && !defined(_XOPEN_SOURCE) -# define _XOPEN_SOURCE 500 // may be needed to get the rwlock calls -# endif -# include <pthread.h> - typedef pthread_rwlock_t MutexType; -#elif defined(CERES_HAVE_PTHREAD) -# include <pthread.h> - typedef pthread_mutex_t MutexType; -#else -# error Need to implement mutex.h for your architecture, or #define NO_THREADS -#endif - -// We need to include these header files after defining _XOPEN_SOURCE -// as they may define the _XOPEN_SOURCE macro. -#include <assert.h> -#include <stdlib.h> // for abort() - -namespace ceres { -namespace internal { - -class Mutex { - public: - // Create a Mutex that is not held by anybody. This constructor is - // typically used for Mutexes allocated on the heap or the stack. - // See below for a recommendation for constructing global Mutex - // objects. - inline Mutex(); - - // Destructor - inline ~Mutex(); - - inline void Lock(); // Block if needed until free then acquire exclusively - inline void Unlock(); // Release a lock acquired via Lock() -#ifdef CERES_GMUTEX_TRYLOCK - inline bool TryLock(); // If free, Lock() and return true, else return false -#endif - // Note that on systems that don't support read-write locks, these may - // be implemented as synonyms to Lock() and Unlock(). So you can use - // these for efficiency, but don't use them anyplace where being able - // to do shared reads is necessary to avoid deadlock. - inline void ReaderLock(); // Block until free or shared then acquire a share - inline void ReaderUnlock(); // Release a read share of this Mutex - inline void WriterLock() { Lock(); } // Acquire an exclusive lock - inline void WriterUnlock() { Unlock(); } // Release a lock from WriterLock() - - // TODO(hamaji): Do nothing, implement correctly. - inline void AssertHeld() {} - - private: - MutexType mutex_; - // We want to make sure that the compiler sets is_safe_ to true only - // when we tell it to, and never makes assumptions is_safe_ is - // always true. volatile is the most reliable way to do that. - volatile bool is_safe_; - - inline void SetIsSafe() { is_safe_ = true; } - - // Catch the error of writing Mutex when intending MutexLock. - Mutex(Mutex* /*ignored*/) {} - // Disallow "evil" constructors - Mutex(const Mutex&); - void operator=(const Mutex&); -}; - -// Now the implementation of Mutex for various systems -#if defined(CERES_NO_THREADS) - -// When we don't have threads, we can be either reading or writing, -// but not both. We can have lots of readers at once (in no-threads -// mode, that's most likely to happen in recursive function calls), -// but only one writer. We represent this by having mutex_ be -1 when -// writing and a number > 0 when reading (and 0 when no lock is held). -// -// In debug mode, we assert these invariants, while in non-debug mode -// we do nothing, for efficiency. That's why everything is in an -// assert. - -Mutex::Mutex() : mutex_(0) { } -Mutex::~Mutex() { assert(mutex_ == 0); } -void Mutex::Lock() { assert(--mutex_ == -1); } -void Mutex::Unlock() { assert(mutex_++ == -1); } -#ifdef CERES_GMUTEX_TRYLOCK -bool Mutex::TryLock() { if (mutex_) return false; Lock(); return true; } -#endif -void Mutex::ReaderLock() { assert(++mutex_ > 0); } -void Mutex::ReaderUnlock() { assert(mutex_-- > 0); } - -#elif defined(_WIN32) || defined(__CYGWIN32__) || defined(__CYGWIN64__) - -Mutex::Mutex() { InitializeCriticalSection(&mutex_); SetIsSafe(); } -Mutex::~Mutex() { DeleteCriticalSection(&mutex_); } -void Mutex::Lock() { if (is_safe_) EnterCriticalSection(&mutex_); } -void Mutex::Unlock() { if (is_safe_) LeaveCriticalSection(&mutex_); } -#ifdef GMUTEX_TRYLOCK -bool Mutex::TryLock() { return is_safe_ ? - TryEnterCriticalSection(&mutex_) != 0 : true; } -#endif -void Mutex::ReaderLock() { Lock(); } // we don't have read-write locks -void Mutex::ReaderUnlock() { Unlock(); } - -#elif defined(CERES_HAVE_PTHREAD) && defined(CERES_HAVE_RWLOCK) - -#define CERES_SAFE_PTHREAD(fncall) do { /* run fncall if is_safe_ is true */ \ - if (is_safe_ && fncall(&mutex_) != 0) abort(); \ -} while (0) - -Mutex::Mutex() { - SetIsSafe(); - if (is_safe_ && pthread_rwlock_init(&mutex_, NULL) != 0) abort(); -} -Mutex::~Mutex() { CERES_SAFE_PTHREAD(pthread_rwlock_destroy); } -void Mutex::Lock() { CERES_SAFE_PTHREAD(pthread_rwlock_wrlock); } -void Mutex::Unlock() { CERES_SAFE_PTHREAD(pthread_rwlock_unlock); } -#ifdef CERES_GMUTEX_TRYLOCK -bool Mutex::TryLock() { return is_safe_ ? - pthread_rwlock_trywrlock(&mutex_) == 0 : - true; } -#endif -void Mutex::ReaderLock() { CERES_SAFE_PTHREAD(pthread_rwlock_rdlock); } -void Mutex::ReaderUnlock() { CERES_SAFE_PTHREAD(pthread_rwlock_unlock); } -#undef CERES_SAFE_PTHREAD - -#elif defined(CERES_HAVE_PTHREAD) - -#define CERES_SAFE_PTHREAD(fncall) do { /* run fncall if is_safe_ is true */ \ - if (is_safe_ && fncall(&mutex_) != 0) abort(); \ -} while (0) - -Mutex::Mutex() { - SetIsSafe(); - if (is_safe_ && pthread_mutex_init(&mutex_, NULL) != 0) abort(); -} -Mutex::~Mutex() { CERES_SAFE_PTHREAD(pthread_mutex_destroy); } -void Mutex::Lock() { CERES_SAFE_PTHREAD(pthread_mutex_lock); } -void Mutex::Unlock() { CERES_SAFE_PTHREAD(pthread_mutex_unlock); } -#ifdef CERES_GMUTEX_TRYLOCK -bool Mutex::TryLock() { return is_safe_ ? - pthread_mutex_trylock(&mutex_) == 0 : true; } -#endif -void Mutex::ReaderLock() { Lock(); } -void Mutex::ReaderUnlock() { Unlock(); } -#undef CERES_SAFE_PTHREAD - -#endif - -// -------------------------------------------------------------------------- -// Some helper classes - -// Note: The weird "Ceres" prefix for the class is a workaround for having two -// similar mutex.h files included in the same translation unit. This is a -// problem because macros do not respect C++ namespaces, and as a result, this -// does not work well (e.g. inside Chrome). The offending macros are -// "MutexLock(x) COMPILE_ASSERT(false)". To work around this, "Ceres" is -// prefixed to the class names; this permits defining the classes. - -// CeresMutexLock(mu) acquires mu when constructed and releases it -// when destroyed. -class CeresMutexLock { - public: - explicit CeresMutexLock(Mutex *mu) : mu_(mu) { mu_->Lock(); } - ~CeresMutexLock() { mu_->Unlock(); } - private: - Mutex * const mu_; - // Disallow "evil" constructors - CeresMutexLock(const CeresMutexLock&); - void operator=(const CeresMutexLock&); -}; - -// CeresReaderMutexLock and CeresWriterMutexLock do the same, for rwlocks -class CeresReaderMutexLock { - public: - explicit CeresReaderMutexLock(Mutex *mu) : mu_(mu) { mu_->ReaderLock(); } - ~CeresReaderMutexLock() { mu_->ReaderUnlock(); } - private: - Mutex * const mu_; - // Disallow "evil" constructors - CeresReaderMutexLock(const CeresReaderMutexLock&); - void operator=(const CeresReaderMutexLock&); -}; - -class CeresWriterMutexLock { - public: - explicit CeresWriterMutexLock(Mutex *mu) : mu_(mu) { mu_->WriterLock(); } - ~CeresWriterMutexLock() { mu_->WriterUnlock(); } - private: - Mutex * const mu_; - // Disallow "evil" constructors - CeresWriterMutexLock(const CeresWriterMutexLock&); - void operator=(const CeresWriterMutexLock&); -}; - -// Catch bug where variable name is omitted, e.g. MutexLock (&mu); -#define CeresMutexLock(x) \ - COMPILE_ASSERT(0, ceres_mutex_lock_decl_missing_var_name) -#define CeresReaderMutexLock(x) \ - COMPILE_ASSERT(0, ceres_rmutex_lock_decl_missing_var_name) -#define CeresWriterMutexLock(x) \ - COMPILE_ASSERT(0, ceres_wmutex_lock_decl_missing_var_name) - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_MUTEX_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/normal_prior.cc b/extern/libmv/third_party/ceres/internal/ceres/normal_prior.cc deleted file mode 100644 index b3666cd702f..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/normal_prior.cc +++ /dev/null @@ -1,66 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/normal_prior.h" - -#include <cstddef> -#include <vector> -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { - -NormalPrior::NormalPrior(const Matrix& A, const Vector& b) - : A_(A), b_(b) { - CHECK_GT(b_.rows(), 0); - CHECK_GT(A_.rows(), 0); - CHECK_EQ(b_.rows(), A.cols()); - set_num_residuals(A_.rows()); - mutable_parameter_block_sizes()->push_back(b_.rows()); -} - -bool NormalPrior::Evaluate(double const* const* parameters, - double* residuals, - double** jacobians) const { - ConstVectorRef p(parameters[0], parameter_block_sizes()[0]); - VectorRef r(residuals, num_residuals()); - // The following line should read - // r = A_ * (p - b_); - // The extra eval is to get around a bug in the eigen library. - r = A_ * (p - b_).eval(); - if ((jacobians != NULL) && (jacobians[0] != NULL)) { - MatrixRef(jacobians[0], num_residuals(), parameter_block_sizes()[0]) = A_; - } - return true; -} - -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/parameter_block.h b/extern/libmv/third_party/ceres/internal/ceres/parameter_block.h deleted file mode 100644 index cb7140d9582..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/parameter_block.h +++ /dev/null @@ -1,398 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#ifndef CERES_INTERNAL_PARAMETER_BLOCK_H_ -#define CERES_INTERNAL_PARAMETER_BLOCK_H_ - -#include <algorithm> -#include <cstdlib> -#include <limits> -#include <string> -#include "ceres/array_utils.h" -#include "ceres/collections_port.h" -#include "ceres/integral_types.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/local_parameterization.h" -#include "ceres/stringprintf.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -class ProblemImpl; -class ResidualBlock; - -// The parameter block encodes the location of the user's original value, and -// also the "current state" of the parameter. The evaluator uses whatever is in -// the current state of the parameter when evaluating. This is inlined since the -// methods are performance sensitive. -// -// The class is not thread-safe, unless only const methods are called. The -// parameter block may also hold a pointer to a local parameterization; the -// parameter block does not take ownership of this pointer, so the user is -// responsible for the proper disposal of the local parameterization. -class ParameterBlock { - public: - // TODO(keir): Decide what data structure is best here. Should this be a set? - // Probably not, because sets are memory inefficient. However, if it's a - // vector, you can get into pathological linear performance when removing a - // residual block from a problem where all the residual blocks depend on one - // parameter; for example, shared focal length in a bundle adjustment - // problem. It might be worth making a custom structure that is just an array - // when it is small, but transitions to a hash set when it has more elements. - // - // For now, use a hash set. - typedef HashSet<ResidualBlock*> ResidualBlockSet; - - // Create a parameter block with the user state, size, and index specified. - // The size is the size of the parameter block and the index is the position - // of the parameter block inside a Program (if any). - ParameterBlock(double* user_state, int size, int index) { - Init(user_state, size, index, NULL); - } - - ParameterBlock(double* user_state, - int size, - int index, - LocalParameterization* local_parameterization) { - Init(user_state, size, index, local_parameterization); - } - - // The size of the parameter block. - int Size() const { return size_; } - - // Manipulate the parameter state. - bool SetState(const double* x) { - CHECK(x != NULL) - << "Tried to set the state of constant parameter " - << "with user location " << user_state_; - CHECK(!is_constant_) - << "Tried to set the state of constant parameter " - << "with user location " << user_state_; - - state_ = x; - return UpdateLocalParameterizationJacobian(); - } - - // Copy the current parameter state out to x. This is "GetState()" rather than - // simply "state()" since it is actively copying the data into the passed - // pointer. - void GetState(double *x) const { - if (x != state_) { - memcpy(x, state_, sizeof(*state_) * size_); - } - } - - // Direct pointers to the current state. - const double* state() const { return state_; } - const double* user_state() const { return user_state_; } - double* mutable_user_state() { return user_state_; } - LocalParameterization* local_parameterization() const { - return local_parameterization_; - } - LocalParameterization* mutable_local_parameterization() { - return local_parameterization_; - } - - // Set this parameter block to vary or not. - void SetConstant() { is_constant_ = true; } - void SetVarying() { is_constant_ = false; } - bool IsConstant() const { return is_constant_; } - - // This parameter block's index in an array. - int index() const { return index_; } - void set_index(int index) { index_ = index; } - - // This parameter offset inside a larger state vector. - int state_offset() const { return state_offset_; } - void set_state_offset(int state_offset) { state_offset_ = state_offset; } - - // This parameter offset inside a larger delta vector. - int delta_offset() const { return delta_offset_; } - void set_delta_offset(int delta_offset) { delta_offset_ = delta_offset; } - - // Methods relating to the parameter block's parameterization. - - // The local to global jacobian. Returns NULL if there is no local - // parameterization for this parameter block. The returned matrix is row-major - // and has Size() rows and LocalSize() columns. - const double* LocalParameterizationJacobian() const { - return local_parameterization_jacobian_.get(); - } - - int LocalSize() const { - return (local_parameterization_ == NULL) - ? size_ - : local_parameterization_->LocalSize(); - } - - // Set the parameterization. The parameterization can be set exactly once; - // multiple calls to set the parameterization to different values will crash. - // It is an error to pass NULL for the parameterization. The parameter block - // does not take ownership of the parameterization. - void SetParameterization(LocalParameterization* new_parameterization) { - CHECK(new_parameterization != NULL) << "NULL parameterization invalid."; - CHECK(new_parameterization->GlobalSize() == size_) - << "Invalid parameterization for parameter block. The parameter block " - << "has size " << size_ << " while the parameterization has a global " - << "size of " << new_parameterization->GlobalSize() << ". Did you " - << "accidentally use the wrong parameter block or parameterization?"; - if (new_parameterization != local_parameterization_) { - CHECK(local_parameterization_ == NULL) - << "Can't re-set the local parameterization; it leads to " - << "ambiguous ownership."; - local_parameterization_ = new_parameterization; - local_parameterization_jacobian_.reset( - new double[local_parameterization_->GlobalSize() * - local_parameterization_->LocalSize()]); - CHECK(UpdateLocalParameterizationJacobian()) - << "Local parameterization Jacobian computation failed for x: " - << ConstVectorRef(state_, Size()).transpose(); - } else { - // Ignore the case that the parameterizations match. - } - } - - void SetUpperBound(int index, double upper_bound) { - CHECK_LT(index, size_); - - if (upper_bounds_.get() == NULL) { - upper_bounds_.reset(new double[size_]); - std::fill(upper_bounds_.get(), - upper_bounds_.get() + size_, - std::numeric_limits<double>::max()); - } - - upper_bounds_[index] = upper_bound; - } - - void SetLowerBound(int index, double lower_bound) { - CHECK_LT(index, size_); - - if (lower_bounds_.get() == NULL) { - lower_bounds_.reset(new double[size_]); - std::fill(lower_bounds_.get(), - lower_bounds_.get() + size_, - -std::numeric_limits<double>::max()); - } - - lower_bounds_[index] = lower_bound; - } - - // Generalization of the addition operation. This is the same as - // LocalParameterization::Plus() followed by projection onto the - // hyper cube implied by the bounds constraints. - bool Plus(const double *x, const double* delta, double* x_plus_delta) { - if (local_parameterization_ != NULL) { - if (!local_parameterization_->Plus(x, delta, x_plus_delta)) { - return false; - } - } else { - VectorRef(x_plus_delta, size_) = ConstVectorRef(x, size_) + - ConstVectorRef(delta, size_); - } - - // Project onto the box constraints. - if (lower_bounds_.get() != NULL) { - for (int i = 0; i < size_; ++i) { - x_plus_delta[i] = std::max(x_plus_delta[i], lower_bounds_[i]); - } - } - - if (upper_bounds_.get() != NULL) { - for (int i = 0; i < size_; ++i) { - x_plus_delta[i] = std::min(x_plus_delta[i], upper_bounds_[i]); - } - } - - return true; - } - - std::string ToString() const { - return StringPrintf("{ this=%p, user_state=%p, state=%p, size=%d, " - "constant=%d, index=%d, state_offset=%d, " - "delta_offset=%d }", - this, - user_state_, - state_, - size_, - is_constant_, - index_, - state_offset_, - delta_offset_); - } - - void EnableResidualBlockDependencies() { - CHECK(residual_blocks_.get() == NULL) - << "Ceres bug: There is already a residual block collection " - << "for parameter block: " << ToString(); - residual_blocks_.reset(new ResidualBlockSet); - } - - void AddResidualBlock(ResidualBlock* residual_block) { - CHECK(residual_blocks_.get() != NULL) - << "Ceres bug: The residual block collection is null for parameter " - << "block: " << ToString(); - residual_blocks_->insert(residual_block); - } - - void RemoveResidualBlock(ResidualBlock* residual_block) { - CHECK(residual_blocks_.get() != NULL) - << "Ceres bug: The residual block collection is null for parameter " - << "block: " << ToString(); - CHECK(residual_blocks_->find(residual_block) != residual_blocks_->end()) - << "Ceres bug: Missing residual for parameter block: " << ToString(); - residual_blocks_->erase(residual_block); - } - - // This is only intended for iterating; perhaps this should only expose - // .begin() and .end(). - ResidualBlockSet* mutable_residual_blocks() { - return residual_blocks_.get(); - } - - double LowerBoundForParameter(int index) const { - if (lower_bounds_.get() == NULL) { - return -std::numeric_limits<double>::max(); - } else { - return lower_bounds_[index]; - } - } - - double UpperBoundForParameter(int index) const { - if (upper_bounds_.get() == NULL) { - return std::numeric_limits<double>::max(); - } else { - return upper_bounds_[index]; - } - } - - private: - void Init(double* user_state, - int size, - int index, - LocalParameterization* local_parameterization) { - user_state_ = user_state; - size_ = size; - index_ = index; - is_constant_ = false; - state_ = user_state_; - - local_parameterization_ = NULL; - if (local_parameterization != NULL) { - SetParameterization(local_parameterization); - } - - state_offset_ = -1; - delta_offset_ = -1; - } - - bool UpdateLocalParameterizationJacobian() { - if (local_parameterization_ == NULL) { - return true; - } - - // Update the local to global Jacobian. In some cases this is - // wasted effort; if this is a bottleneck, we will find a solution - // at that time. - - const int jacobian_size = Size() * LocalSize(); - InvalidateArray(jacobian_size, - local_parameterization_jacobian_.get()); - if (!local_parameterization_->ComputeJacobian( - state_, - local_parameterization_jacobian_.get())) { - LOG(WARNING) << "Local parameterization Jacobian computation failed" - "for x: " << ConstVectorRef(state_, Size()).transpose(); - return false; - } - - if (!IsArrayValid(jacobian_size, local_parameterization_jacobian_.get())) { - LOG(WARNING) << "Local parameterization Jacobian computation returned" - << "an invalid matrix for x: " - << ConstVectorRef(state_, Size()).transpose() - << "\n Jacobian matrix : " - << ConstMatrixRef(local_parameterization_jacobian_.get(), - Size(), - LocalSize()); - return false; - } - return true; - } - - double* user_state_; - int size_; - bool is_constant_; - LocalParameterization* local_parameterization_; - - // The "state" of the parameter. These fields are only needed while the - // solver is running. While at first glance using mutable is a bad idea, this - // ends up simplifying the internals of Ceres enough to justify the potential - // pitfalls of using "mutable." - mutable const double* state_; - mutable scoped_array<double> local_parameterization_jacobian_; - - // The index of the parameter. This is used by various other parts of Ceres to - // permit switching from a ParameterBlock* to an index in another array. - int32 index_; - - // The offset of this parameter block inside a larger state vector. - int32 state_offset_; - - // The offset of this parameter block inside a larger delta vector. - int32 delta_offset_; - - // If non-null, contains the residual blocks this parameter block is in. - scoped_ptr<ResidualBlockSet> residual_blocks_; - - // Upper and lower bounds for the parameter block. SetUpperBound - // and SetLowerBound lazily initialize the upper_bounds_ and - // lower_bounds_ arrays. If they are never called, then memory for - // these arrays is never allocated. Thus for problems where there - // are no bounds, or only one sided bounds we do not pay the cost of - // allocating memory for the inactive bounds constraints. - // - // Upon initialization these arrays are initialized to - // std::numeric_limits<double>::max() and - // -std::numeric_limits<double>::max() respectively which correspond - // to the parameter block being unconstrained. - scoped_array<double> upper_bounds_; - scoped_array<double> lower_bounds_; - - // Necessary so ProblemImpl can clean up the parameterizations. - friend class ProblemImpl; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_PARAMETER_BLOCK_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/parameter_block_ordering.cc b/extern/libmv/third_party/ceres/internal/ceres/parameter_block_ordering.cc deleted file mode 100644 index efba339977c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/parameter_block_ordering.cc +++ /dev/null @@ -1,173 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/parameter_block_ordering.h" - -#include "ceres/graph.h" -#include "ceres/graph_algorithms.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/map_util.h" -#include "ceres/parameter_block.h" -#include "ceres/program.h" -#include "ceres/residual_block.h" -#include "ceres/wall_time.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::map; -using std::set; -using std::vector; - -int ComputeStableSchurOrdering(const Program& program, - vector<ParameterBlock*>* ordering) { - CHECK_NOTNULL(ordering)->clear(); - EventLogger event_logger("ComputeStableSchurOrdering"); - scoped_ptr<Graph< ParameterBlock*> > graph(CreateHessianGraph(program)); - event_logger.AddEvent("CreateHessianGraph"); - - const vector<ParameterBlock*>& parameter_blocks = program.parameter_blocks(); - const HashSet<ParameterBlock*>& vertices = graph->vertices(); - for (int i = 0; i < parameter_blocks.size(); ++i) { - if (vertices.count(parameter_blocks[i]) > 0) { - ordering->push_back(parameter_blocks[i]); - } - } - event_logger.AddEvent("Preordering"); - - int independent_set_size = StableIndependentSetOrdering(*graph, ordering); - event_logger.AddEvent("StableIndependentSet"); - - // Add the excluded blocks to back of the ordering vector. - for (int i = 0; i < parameter_blocks.size(); ++i) { - ParameterBlock* parameter_block = parameter_blocks[i]; - if (parameter_block->IsConstant()) { - ordering->push_back(parameter_block); - } - } - event_logger.AddEvent("ConstantParameterBlocks"); - - return independent_set_size; -} - -int ComputeSchurOrdering(const Program& program, - vector<ParameterBlock*>* ordering) { - CHECK_NOTNULL(ordering)->clear(); - - scoped_ptr<Graph< ParameterBlock*> > graph(CreateHessianGraph(program)); - int independent_set_size = IndependentSetOrdering(*graph, ordering); - const vector<ParameterBlock*>& parameter_blocks = program.parameter_blocks(); - - // Add the excluded blocks to back of the ordering vector. - for (int i = 0; i < parameter_blocks.size(); ++i) { - ParameterBlock* parameter_block = parameter_blocks[i]; - if (parameter_block->IsConstant()) { - ordering->push_back(parameter_block); - } - } - - return independent_set_size; -} - -void ComputeRecursiveIndependentSetOrdering(const Program& program, - ParameterBlockOrdering* ordering) { - CHECK_NOTNULL(ordering)->Clear(); - const vector<ParameterBlock*> parameter_blocks = program.parameter_blocks(); - scoped_ptr<Graph< ParameterBlock*> > graph(CreateHessianGraph(program)); - - int num_covered = 0; - int round = 0; - while (num_covered < parameter_blocks.size()) { - vector<ParameterBlock*> independent_set_ordering; - const int independent_set_size = - IndependentSetOrdering(*graph, &independent_set_ordering); - for (int i = 0; i < independent_set_size; ++i) { - ParameterBlock* parameter_block = independent_set_ordering[i]; - ordering->AddElementToGroup(parameter_block->mutable_user_state(), round); - graph->RemoveVertex(parameter_block); - } - num_covered += independent_set_size; - ++round; - } -} - -Graph<ParameterBlock*>* CreateHessianGraph(const Program& program) { - Graph<ParameterBlock*>* graph = CHECK_NOTNULL(new Graph<ParameterBlock*>); - const vector<ParameterBlock*>& parameter_blocks = program.parameter_blocks(); - for (int i = 0; i < parameter_blocks.size(); ++i) { - ParameterBlock* parameter_block = parameter_blocks[i]; - if (!parameter_block->IsConstant()) { - graph->AddVertex(parameter_block); - } - } - - const vector<ResidualBlock*>& residual_blocks = program.residual_blocks(); - for (int i = 0; i < residual_blocks.size(); ++i) { - const ResidualBlock* residual_block = residual_blocks[i]; - const int num_parameter_blocks = residual_block->NumParameterBlocks(); - ParameterBlock* const* parameter_blocks = - residual_block->parameter_blocks(); - for (int j = 0; j < num_parameter_blocks; ++j) { - if (parameter_blocks[j]->IsConstant()) { - continue; - } - - for (int k = j + 1; k < num_parameter_blocks; ++k) { - if (parameter_blocks[k]->IsConstant()) { - continue; - } - - graph->AddEdge(parameter_blocks[j], parameter_blocks[k]); - } - } - } - - return graph; -} - -void OrderingToGroupSizes(const ParameterBlockOrdering* ordering, - vector<int>* group_sizes) { - CHECK_NOTNULL(group_sizes)->clear(); - if (ordering == NULL) { - return; - } - - const map<int, set<double*> >& group_to_elements = - ordering->group_to_elements(); - for (map<int, set<double*> >::const_iterator it = group_to_elements.begin(); - it != group_to_elements.end(); - ++it) { - group_sizes->push_back(it->second.size()); - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/parameter_block_ordering.h b/extern/libmv/third_party/ceres/internal/ceres/parameter_block_ordering.h deleted file mode 100644 index f996929f6b3..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/parameter_block_ordering.h +++ /dev/null @@ -1,89 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_PARAMETER_BLOCK_ORDERING_H_ -#define CERES_INTERNAL_PARAMETER_BLOCK_ORDERING_H_ - -#include <vector> -#include "ceres/ordered_groups.h" -#include "ceres/graph.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -class Program; -class ParameterBlock; - -// Uses an approximate independent set ordering to order the parameter -// blocks of a problem so that it is suitable for use with Schur -// complement based solvers. The output variable ordering contains an -// ordering of the parameter blocks and the return value is size of -// the independent set or the number of e_blocks (see -// schur_complement_solver.h for an explanation). Constant parameters -// are added to the end. -// -// The ordering vector has the structure -// -// ordering = [independent set, -// complement of the independent set, -// fixed blocks] -int ComputeSchurOrdering(const Program& program, - std::vector<ParameterBlock* >* ordering); - -// Same as above, except that ties while computing the independent set -// ordering are resolved in favour of the order in which the parameter -// blocks occur in the program. -int ComputeStableSchurOrdering(const Program& program, - std::vector<ParameterBlock* >* ordering); - -// Use an approximate independent set ordering to decompose the -// parameter blocks of a problem in a sequence of independent -// sets. The ordering covers all the non-constant parameter blocks in -// the program. -void ComputeRecursiveIndependentSetOrdering(const Program& program, - ParameterBlockOrdering* ordering); - -// Builds a graph on the parameter blocks of a Problem, whose -// structure reflects the sparsity structure of the Hessian. Each -// vertex corresponds to a parameter block in the Problem except for -// parameter blocks that are marked constant. An edge connects two -// parameter blocks, if they co-occur in a residual block. -Graph<ParameterBlock*>* CreateHessianGraph(const Program& program); - -// Iterate over each of the groups in order of their priority and fill -// summary with their sizes. -void OrderingToGroupSizes(const ParameterBlockOrdering* ordering, - std::vector<int>* group_sizes); - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_PARAMETER_BLOCK_ORDERING_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/partitioned_matrix_view.cc b/extern/libmv/third_party/ceres/internal/ceres/partitioned_matrix_view.cc deleted file mode 100644 index 8054964e039..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/partitioned_matrix_view.cc +++ /dev/null @@ -1,185 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of PartitionedMatrixView. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_partitioned_matrix_view_specializations.py. -// Editing it manually is not recommended. - -#include "ceres/linear_solver.h" -#include "ceres/partitioned_matrix_view.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -PartitionedMatrixViewBase* -PartitionedMatrixViewBase::Create(const LinearSolver::Options& options, - const BlockSparseMatrix& matrix) { -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - if ((options.row_block_size == 2) && - (options.e_block_size == 2) && - (options.f_block_size == 2)) { - return new PartitionedMatrixView<2, 2, 2>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 2) && - (options.f_block_size == 3)) { - return new PartitionedMatrixView<2, 2, 3>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 2) && - (options.f_block_size == 4)) { - return new PartitionedMatrixView<2, 2, 4>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 2) && - (options.f_block_size == Eigen::Dynamic)) { - return new PartitionedMatrixView<2, 2, Eigen::Dynamic>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 3) && - (options.f_block_size == 3)) { - return new PartitionedMatrixView<2, 3, 3>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 3) && - (options.f_block_size == 4)) { - return new PartitionedMatrixView<2, 3, 4>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 3) && - (options.f_block_size == 6)) { - return new PartitionedMatrixView<2, 3, 6>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 3) && - (options.f_block_size == 9)) { - return new PartitionedMatrixView<2, 3, 9>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 3) && - (options.f_block_size == Eigen::Dynamic)) { - return new PartitionedMatrixView<2, 3, Eigen::Dynamic>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 4) && - (options.f_block_size == 3)) { - return new PartitionedMatrixView<2, 4, 3>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 4) && - (options.f_block_size == 4)) { - return new PartitionedMatrixView<2, 4, 4>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 4) && - (options.f_block_size == 8)) { - return new PartitionedMatrixView<2, 4, 8>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 4) && - (options.f_block_size == 9)) { - return new PartitionedMatrixView<2, 4, 9>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 4) && - (options.f_block_size == Eigen::Dynamic)) { - return new PartitionedMatrixView<2, 4, Eigen::Dynamic>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 2) && - (options.e_block_size == Eigen::Dynamic) && - (options.f_block_size == Eigen::Dynamic)) { - return new PartitionedMatrixView<2, Eigen::Dynamic, Eigen::Dynamic>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 4) && - (options.e_block_size == 4) && - (options.f_block_size == 2)) { - return new PartitionedMatrixView<4, 4, 2>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 4) && - (options.e_block_size == 4) && - (options.f_block_size == 3)) { - return new PartitionedMatrixView<4, 4, 3>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 4) && - (options.e_block_size == 4) && - (options.f_block_size == 4)) { - return new PartitionedMatrixView<4, 4, 4>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == 4) && - (options.e_block_size == 4) && - (options.f_block_size == Eigen::Dynamic)) { - return new PartitionedMatrixView<4, 4, Eigen::Dynamic>( - matrix, options.elimination_groups[0]); - } - if ((options.row_block_size == Eigen::Dynamic) && - (options.e_block_size == Eigen::Dynamic) && - (options.f_block_size == Eigen::Dynamic)) { - return new PartitionedMatrixView<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic>( - matrix, options.elimination_groups[0]); - } - -#endif - VLOG(1) << "Template specializations not found for <" - << options.row_block_size << "," - << options.e_block_size << "," - << options.f_block_size << ">"; - return new PartitionedMatrixView<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic>( - matrix, options.elimination_groups[0]); -}; - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/partitioned_matrix_view.h b/extern/libmv/third_party/ceres/internal/ceres/partitioned_matrix_view.h deleted file mode 100644 index 6e75060a47e..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/partitioned_matrix_view.h +++ /dev/null @@ -1,152 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// For generalized bi-partite Jacobian matrices that arise in -// Structure from Motion related problems, it is sometimes useful to -// have access to the two parts of the matrix as linear operators -// themselves. This class provides that functionality. - -#ifndef CERES_INTERNAL_PARTITIONED_MATRIX_VIEW_H_ -#define CERES_INTERNAL_PARTITIONED_MATRIX_VIEW_H_ - -#include <algorithm> -#include <cstring> -#include <vector> - -#include "ceres/block_structure.h" -#include "ceres/internal/eigen.h" -#include "ceres/linear_solver.h" -#include "ceres/small_blas.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -// Given generalized bi-partite matrix A = [E F], with the same block -// structure as required by the Schur complement based solver, found -// in explicit_schur_complement_solver.h, provide access to the -// matrices E and F and their outer products E'E and F'F with -// themselves. -// -// Lack of BlockStructure object will result in a crash and if the -// block structure of the matrix does not satisfy the requirements of -// the Schur complement solver it will result in unpredictable and -// wrong output. -class PartitionedMatrixViewBase { - public: - virtual ~PartitionedMatrixViewBase() {} - - // y += E'x - virtual void LeftMultiplyE(const double* x, double* y) const = 0; - - // y += F'x - virtual void LeftMultiplyF(const double* x, double* y) const = 0; - - // y += Ex - virtual void RightMultiplyE(const double* x, double* y) const = 0; - - // y += Fx - virtual void RightMultiplyF(const double* x, double* y) const = 0; - - // Create and return the block diagonal of the matrix E'E. - virtual BlockSparseMatrix* CreateBlockDiagonalEtE() const = 0; - - // Create and return the block diagonal of the matrix F'F. Caller - // owns the result. - virtual BlockSparseMatrix* CreateBlockDiagonalFtF() const = 0; - - // Compute the block diagonal of the matrix E'E and store it in - // block_diagonal. The matrix block_diagonal is expected to have a - // BlockStructure (preferably created using - // CreateBlockDiagonalMatrixEtE) which is has the same structure as - // the block diagonal of E'E. - virtual void UpdateBlockDiagonalEtE( - BlockSparseMatrix* block_diagonal) const = 0; - - // Compute the block diagonal of the matrix F'F and store it in - // block_diagonal. The matrix block_diagonal is expected to have a - // BlockStructure (preferably created using - // CreateBlockDiagonalMatrixFtF) which is has the same structure as - // the block diagonal of F'F. - virtual void UpdateBlockDiagonalFtF( - BlockSparseMatrix* block_diagonal) const = 0; - - virtual int num_col_blocks_e() const = 0; - virtual int num_col_blocks_f() const = 0; - virtual int num_cols_e() const = 0; - virtual int num_cols_f() const = 0; - virtual int num_rows() const = 0; - virtual int num_cols() const = 0; - - static PartitionedMatrixViewBase* Create(const LinearSolver::Options& options, - const BlockSparseMatrix& matrix); -}; - -template <int kRowBlockSize = Eigen::Dynamic, - int kEBlockSize = Eigen::Dynamic, - int kFBlockSize = Eigen::Dynamic > -class PartitionedMatrixView : public PartitionedMatrixViewBase { - public: - // matrix = [E F], where the matrix E contains the first - // num_col_blocks_a column blocks. - PartitionedMatrixView(const BlockSparseMatrix& matrix, int num_col_blocks_e); - - virtual ~PartitionedMatrixView(); - virtual void LeftMultiplyE(const double* x, double* y) const; - virtual void LeftMultiplyF(const double* x, double* y) const; - virtual void RightMultiplyE(const double* x, double* y) const; - virtual void RightMultiplyF(const double* x, double* y) const; - virtual BlockSparseMatrix* CreateBlockDiagonalEtE() const; - virtual BlockSparseMatrix* CreateBlockDiagonalFtF() const; - virtual void UpdateBlockDiagonalEtE(BlockSparseMatrix* block_diagonal) const; - virtual void UpdateBlockDiagonalFtF(BlockSparseMatrix* block_diagonal) const; - virtual int num_col_blocks_e() const { return num_col_blocks_e_; } - virtual int num_col_blocks_f() const { return num_col_blocks_f_; } - virtual int num_cols_e() const { return num_cols_e_; } - virtual int num_cols_f() const { return num_cols_f_; } - virtual int num_rows() const { return matrix_.num_rows(); } - virtual int num_cols() const { return matrix_.num_cols(); } - - private: - BlockSparseMatrix* CreateBlockDiagonalMatrixLayout(int start_col_block, - int end_col_block) const; - - const BlockSparseMatrix& matrix_; - int num_row_blocks_e_; - int num_col_blocks_e_; - int num_col_blocks_f_; - int num_cols_e_; - int num_cols_f_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_PARTITIONED_MATRIX_VIEW_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/partitioned_matrix_view_impl.h b/extern/libmv/third_party/ceres/internal/ceres/partitioned_matrix_view_impl.h deleted file mode 100644 index 86fb278fa27..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/partitioned_matrix_view_impl.h +++ /dev/null @@ -1,380 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/partitioned_matrix_view.h" - -#include <algorithm> -#include <cstring> -#include <vector> -#include "ceres/block_sparse_matrix.h" -#include "ceres/block_structure.h" -#include "ceres/internal/eigen.h" -#include "ceres/small_blas.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>:: -PartitionedMatrixView( - const BlockSparseMatrix& matrix, - int num_col_blocks_e) - : matrix_(matrix), - num_col_blocks_e_(num_col_blocks_e) { - const CompressedRowBlockStructure* bs = matrix_.block_structure(); - CHECK_NOTNULL(bs); - - num_col_blocks_f_ = bs->cols.size() - num_col_blocks_e_; - - // Compute the number of row blocks in E. The number of row blocks - // in E maybe less than the number of row blocks in the input matrix - // as some of the row blocks at the bottom may not have any - // e_blocks. For a definition of what an e_block is, please see - // explicit_schur_complement_solver.h - num_row_blocks_e_ = 0; - for (int r = 0; r < bs->rows.size(); ++r) { - const std::vector<Cell>& cells = bs->rows[r].cells; - if (cells[0].block_id < num_col_blocks_e_) { - ++num_row_blocks_e_; - } - } - - // Compute the number of columns in E and F. - num_cols_e_ = 0; - num_cols_f_ = 0; - - for (int c = 0; c < bs->cols.size(); ++c) { - const Block& block = bs->cols[c]; - if (c < num_col_blocks_e_) { - num_cols_e_ += block.size; - } else { - num_cols_f_ += block.size; - } - } - - CHECK_EQ(num_cols_e_ + num_cols_f_, matrix_.num_cols()); -} - -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>:: -~PartitionedMatrixView() { -} - -// The next four methods don't seem to be particularly cache -// friendly. This is an artifact of how the BlockStructure of the -// input matrix is constructed. These methods will benefit from -// multithreading as well as improved data layout. - -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>:: -RightMultiplyE(const double* x, double* y) const { - const CompressedRowBlockStructure* bs = matrix_.block_structure(); - - // Iterate over the first num_row_blocks_e_ row blocks, and multiply - // by the first cell in each row block. - const double* values = matrix_.values(); - for (int r = 0; r < num_row_blocks_e_; ++r) { - const Cell& cell = bs->rows[r].cells[0]; - const int row_block_pos = bs->rows[r].block.position; - const int row_block_size = bs->rows[r].block.size; - const int col_block_id = cell.block_id; - const int col_block_pos = bs->cols[col_block_id].position; - const int col_block_size = bs->cols[col_block_id].size; - MatrixVectorMultiply<kRowBlockSize, kEBlockSize, 1>( - values + cell.position, row_block_size, col_block_size, - x + col_block_pos, - y + row_block_pos); - } -} - -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>:: -RightMultiplyF(const double* x, double* y) const { - const CompressedRowBlockStructure* bs = matrix_.block_structure(); - - // Iterate over row blocks, and if the row block is in E, then - // multiply by all the cells except the first one which is of type - // E. If the row block is not in E (i.e its in the bottom - // num_row_blocks - num_row_blocks_e row blocks), then all the cells - // are of type F and multiply by them all. - const double* values = matrix_.values(); - for (int r = 0; r < num_row_blocks_e_; ++r) { - const int row_block_pos = bs->rows[r].block.position; - const int row_block_size = bs->rows[r].block.size; - const std::vector<Cell>& cells = bs->rows[r].cells; - for (int c = 1; c < cells.size(); ++c) { - const int col_block_id = cells[c].block_id; - const int col_block_pos = bs->cols[col_block_id].position; - const int col_block_size = bs->cols[col_block_id].size; - MatrixVectorMultiply<kRowBlockSize, kFBlockSize, 1>( - values + cells[c].position, row_block_size, col_block_size, - x + col_block_pos - num_cols_e_, - y + row_block_pos); - } - } - - for (int r = num_row_blocks_e_; r < bs->rows.size(); ++r) { - const int row_block_pos = bs->rows[r].block.position; - const int row_block_size = bs->rows[r].block.size; - const std::vector<Cell>& cells = bs->rows[r].cells; - for (int c = 0; c < cells.size(); ++c) { - const int col_block_id = cells[c].block_id; - const int col_block_pos = bs->cols[col_block_id].position; - const int col_block_size = bs->cols[col_block_id].size; - MatrixVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>( - values + cells[c].position, row_block_size, col_block_size, - x + col_block_pos - num_cols_e_, - y + row_block_pos); - } - } -} - -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>:: -LeftMultiplyE(const double* x, double* y) const { - const CompressedRowBlockStructure* bs = matrix_.block_structure(); - - // Iterate over the first num_row_blocks_e_ row blocks, and multiply - // by the first cell in each row block. - const double* values = matrix_.values(); - for (int r = 0; r < num_row_blocks_e_; ++r) { - const Cell& cell = bs->rows[r].cells[0]; - const int row_block_pos = bs->rows[r].block.position; - const int row_block_size = bs->rows[r].block.size; - const int col_block_id = cell.block_id; - const int col_block_pos = bs->cols[col_block_id].position; - const int col_block_size = bs->cols[col_block_id].size; - MatrixTransposeVectorMultiply<kRowBlockSize, kEBlockSize, 1>( - values + cell.position, row_block_size, col_block_size, - x + row_block_pos, - y + col_block_pos); - } -} - -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>:: -LeftMultiplyF(const double* x, double* y) const { - const CompressedRowBlockStructure* bs = matrix_.block_structure(); - - // Iterate over row blocks, and if the row block is in E, then - // multiply by all the cells except the first one which is of type - // E. If the row block is not in E (i.e its in the bottom - // num_row_blocks - num_row_blocks_e row blocks), then all the cells - // are of type F and multiply by them all. - const double* values = matrix_.values(); - for (int r = 0; r < num_row_blocks_e_; ++r) { - const int row_block_pos = bs->rows[r].block.position; - const int row_block_size = bs->rows[r].block.size; - const std::vector<Cell>& cells = bs->rows[r].cells; - for (int c = 1; c < cells.size(); ++c) { - const int col_block_id = cells[c].block_id; - const int col_block_pos = bs->cols[col_block_id].position; - const int col_block_size = bs->cols[col_block_id].size; - MatrixTransposeVectorMultiply<kRowBlockSize, kFBlockSize, 1>( - values + cells[c].position, row_block_size, col_block_size, - x + row_block_pos, - y + col_block_pos - num_cols_e_); - } - } - - for (int r = num_row_blocks_e_; r < bs->rows.size(); ++r) { - const int row_block_pos = bs->rows[r].block.position; - const int row_block_size = bs->rows[r].block.size; - const std::vector<Cell>& cells = bs->rows[r].cells; - for (int c = 0; c < cells.size(); ++c) { - const int col_block_id = cells[c].block_id; - const int col_block_pos = bs->cols[col_block_id].position; - const int col_block_size = bs->cols[col_block_id].size; - MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>( - values + cells[c].position, row_block_size, col_block_size, - x + row_block_pos, - y + col_block_pos - num_cols_e_); - } - } -} - -// Given a range of columns blocks of a matrix m, compute the block -// structure of the block diagonal of the matrix m(:, -// start_col_block:end_col_block)'m(:, start_col_block:end_col_block) -// and return a BlockSparseMatrix with the this block structure. The -// caller owns the result. -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -BlockSparseMatrix* -PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>:: -CreateBlockDiagonalMatrixLayout(int start_col_block, int end_col_block) const { - const CompressedRowBlockStructure* bs = matrix_.block_structure(); - CompressedRowBlockStructure* block_diagonal_structure = - new CompressedRowBlockStructure; - - int block_position = 0; - int diagonal_cell_position = 0; - - // Iterate over the column blocks, creating a new diagonal block for - // each column block. - for (int c = start_col_block; c < end_col_block; ++c) { - const Block& block = bs->cols[c]; - block_diagonal_structure->cols.push_back(Block()); - Block& diagonal_block = block_diagonal_structure->cols.back(); - diagonal_block.size = block.size; - diagonal_block.position = block_position; - - block_diagonal_structure->rows.push_back(CompressedRow()); - CompressedRow& row = block_diagonal_structure->rows.back(); - row.block = diagonal_block; - - row.cells.push_back(Cell()); - Cell& cell = row.cells.back(); - cell.block_id = c - start_col_block; - cell.position = diagonal_cell_position; - - block_position += block.size; - diagonal_cell_position += block.size * block.size; - } - - // Build a BlockSparseMatrix with the just computed block - // structure. - return new BlockSparseMatrix(block_diagonal_structure); -} - -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -BlockSparseMatrix* -PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>:: -CreateBlockDiagonalEtE() const { - BlockSparseMatrix* block_diagonal = - CreateBlockDiagonalMatrixLayout(0, num_col_blocks_e_); - UpdateBlockDiagonalEtE(block_diagonal); - return block_diagonal; -} - -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -BlockSparseMatrix* -PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>:: -CreateBlockDiagonalFtF() const { - BlockSparseMatrix* block_diagonal = - CreateBlockDiagonalMatrixLayout( - num_col_blocks_e_, num_col_blocks_e_ + num_col_blocks_f_); - UpdateBlockDiagonalFtF(block_diagonal); - return block_diagonal; -} - -// Similar to the code in RightMultiplyE, except instead of the matrix -// vector multiply its an outer product. -// -// block_diagonal = block_diagonal(E'E) -// -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>:: -UpdateBlockDiagonalEtE( - BlockSparseMatrix* block_diagonal) const { - const CompressedRowBlockStructure* bs = matrix_.block_structure(); - const CompressedRowBlockStructure* block_diagonal_structure = - block_diagonal->block_structure(); - - block_diagonal->SetZero(); - const double* values = matrix_.values(); - for (int r = 0; r < num_row_blocks_e_ ; ++r) { - const Cell& cell = bs->rows[r].cells[0]; - const int row_block_size = bs->rows[r].block.size; - const int block_id = cell.block_id; - const int col_block_size = bs->cols[block_id].size; - const int cell_position = - block_diagonal_structure->rows[block_id].cells[0].position; - - MatrixTransposeMatrixMultiply - <kRowBlockSize, kEBlockSize, kRowBlockSize, kEBlockSize, 1>( - values + cell.position, row_block_size, col_block_size, - values + cell.position, row_block_size, col_block_size, - block_diagonal->mutable_values() + cell_position, - 0, 0, col_block_size, col_block_size); - } -} - -// Similar to the code in RightMultiplyF, except instead of the matrix -// vector multiply its an outer product. -// -// block_diagonal = block_diagonal(F'F) -// -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -PartitionedMatrixView<kRowBlockSize, kEBlockSize, kFBlockSize>:: -UpdateBlockDiagonalFtF(BlockSparseMatrix* block_diagonal) const { - const CompressedRowBlockStructure* bs = matrix_.block_structure(); - const CompressedRowBlockStructure* block_diagonal_structure = - block_diagonal->block_structure(); - - block_diagonal->SetZero(); - const double* values = matrix_.values(); - for (int r = 0; r < num_row_blocks_e_; ++r) { - const int row_block_size = bs->rows[r].block.size; - const std::vector<Cell>& cells = bs->rows[r].cells; - for (int c = 1; c < cells.size(); ++c) { - const int col_block_id = cells[c].block_id; - const int col_block_size = bs->cols[col_block_id].size; - const int diagonal_block_id = col_block_id - num_col_blocks_e_; - const int cell_position = - block_diagonal_structure->rows[diagonal_block_id].cells[0].position; - - MatrixTransposeMatrixMultiply - <kRowBlockSize, kFBlockSize, kRowBlockSize, kFBlockSize, 1>( - values + cells[c].position, row_block_size, col_block_size, - values + cells[c].position, row_block_size, col_block_size, - block_diagonal->mutable_values() + cell_position, - 0, 0, col_block_size, col_block_size); - } - } - - for (int r = num_row_blocks_e_; r < bs->rows.size(); ++r) { - const int row_block_size = bs->rows[r].block.size; - const std::vector<Cell>& cells = bs->rows[r].cells; - for (int c = 0; c < cells.size(); ++c) { - const int col_block_id = cells[c].block_id; - const int col_block_size = bs->cols[col_block_id].size; - const int diagonal_block_id = col_block_id - num_col_blocks_e_; - const int cell_position = - block_diagonal_structure->rows[diagonal_block_id].cells[0].position; - - MatrixTransposeMatrixMultiply - <Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, 1>( - values + cells[c].position, row_block_size, col_block_size, - values + cells[c].position, row_block_size, col_block_size, - block_diagonal->mutable_values() + cell_position, - 0, 0, col_block_size, col_block_size); - } - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/polynomial.cc b/extern/libmv/third_party/ceres/internal/ceres/polynomial.cc deleted file mode 100644 index 13bf8edeee6..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/polynomial.cc +++ /dev/null @@ -1,398 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: moll.markus@arcor.de (Markus Moll) -// sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/polynomial.h" - -#include <cmath> -#include <cstddef> -#include <vector> - -#include "Eigen/Dense" -#include "ceres/internal/port.h" -#include "ceres/stringprintf.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::string; -using std::vector; - -namespace { - -// Balancing function as described by B. N. Parlett and C. Reinsch, -// "Balancing a Matrix for Calculation of Eigenvalues and Eigenvectors". -// In: Numerische Mathematik, Volume 13, Number 4 (1969), 293-304, -// Springer Berlin / Heidelberg. DOI: 10.1007/BF02165404 -void BalanceCompanionMatrix(Matrix* companion_matrix_ptr) { - CHECK_NOTNULL(companion_matrix_ptr); - Matrix& companion_matrix = *companion_matrix_ptr; - Matrix companion_matrix_offdiagonal = companion_matrix; - companion_matrix_offdiagonal.diagonal().setZero(); - - const int degree = companion_matrix.rows(); - - // gamma <= 1 controls how much a change in the scaling has to - // lower the 1-norm of the companion matrix to be accepted. - // - // gamma = 1 seems to lead to cycles (numerical issues?), so - // we set it slightly lower. - const double gamma = 0.9; - - // Greedily scale row/column pairs until there is no change. - bool scaling_has_changed; - do { - scaling_has_changed = false; - - for (int i = 0; i < degree; ++i) { - const double row_norm = companion_matrix_offdiagonal.row(i).lpNorm<1>(); - const double col_norm = companion_matrix_offdiagonal.col(i).lpNorm<1>(); - - // Decompose row_norm/col_norm into mantissa * 2^exponent, - // where 0.5 <= mantissa < 1. Discard mantissa (return value - // of frexp), as only the exponent is needed. - int exponent = 0; - std::frexp(row_norm / col_norm, &exponent); - exponent /= 2; - - if (exponent != 0) { - const double scaled_col_norm = std::ldexp(col_norm, exponent); - const double scaled_row_norm = std::ldexp(row_norm, -exponent); - if (scaled_col_norm + scaled_row_norm < gamma * (col_norm + row_norm)) { - // Accept the new scaling. (Multiplication by powers of 2 should not - // introduce rounding errors (ignoring non-normalized numbers and - // over- or underflow)) - scaling_has_changed = true; - companion_matrix_offdiagonal.row(i) *= std::ldexp(1.0, -exponent); - companion_matrix_offdiagonal.col(i) *= std::ldexp(1.0, exponent); - } - } - } - } while (scaling_has_changed); - - companion_matrix_offdiagonal.diagonal() = companion_matrix.diagonal(); - companion_matrix = companion_matrix_offdiagonal; - VLOG(3) << "Balanced companion matrix is\n" << companion_matrix; -} - -void BuildCompanionMatrix(const Vector& polynomial, - Matrix* companion_matrix_ptr) { - CHECK_NOTNULL(companion_matrix_ptr); - Matrix& companion_matrix = *companion_matrix_ptr; - - const int degree = polynomial.size() - 1; - - companion_matrix.resize(degree, degree); - companion_matrix.setZero(); - companion_matrix.diagonal(-1).setOnes(); - companion_matrix.col(degree - 1) = -polynomial.reverse().head(degree); -} - -// Remove leading terms with zero coefficients. -Vector RemoveLeadingZeros(const Vector& polynomial_in) { - int i = 0; - while (i < (polynomial_in.size() - 1) && polynomial_in(i) == 0.0) { - ++i; - } - return polynomial_in.tail(polynomial_in.size() - i); -} - -void FindLinearPolynomialRoots(const Vector& polynomial, - Vector* real, - Vector* imaginary) { - CHECK_EQ(polynomial.size(), 2); - if (real != NULL) { - real->resize(1); - (*real)(0) = -polynomial(1) / polynomial(0); - } - - if (imaginary != NULL) { - imaginary->setZero(1); - } -} - -void FindQuadraticPolynomialRoots(const Vector& polynomial, - Vector* real, - Vector* imaginary) { - CHECK_EQ(polynomial.size(), 3); - const double a = polynomial(0); - const double b = polynomial(1); - const double c = polynomial(2); - const double D = b * b - 4 * a * c; - const double sqrt_D = sqrt(fabs(D)); - if (real != NULL) { - real->setZero(2); - } - if (imaginary != NULL) { - imaginary->setZero(2); - } - - // Real roots. - if (D >= 0) { - if (real != NULL) { - // Stable quadratic roots according to BKP Horn. - // http://people.csail.mit.edu/bkph/articles/Quadratics.pdf - if (b >= 0) { - (*real)(0) = (-b - sqrt_D) / (2.0 * a); - (*real)(1) = (2.0 * c) / (-b - sqrt_D); - } else { - (*real)(0) = (2.0 * c) / (-b + sqrt_D); - (*real)(1) = (-b + sqrt_D) / (2.0 * a); - } - } - return; - } - - // Use the normal quadratic formula for the complex case. - if (real != NULL) { - (*real)(0) = -b / (2.0 * a); - (*real)(1) = -b / (2.0 * a); - } - if (imaginary != NULL) { - (*imaginary)(0) = sqrt_D / (2.0 * a); - (*imaginary)(1) = -sqrt_D / (2.0 * a); - } -} -} // namespace - -bool FindPolynomialRoots(const Vector& polynomial_in, - Vector* real, - Vector* imaginary) { - if (polynomial_in.size() == 0) { - LOG(ERROR) << "Invalid polynomial of size 0 passed to FindPolynomialRoots"; - return false; - } - - Vector polynomial = RemoveLeadingZeros(polynomial_in); - const int degree = polynomial.size() - 1; - - VLOG(3) << "Input polynomial: " << polynomial_in.transpose(); - if (polynomial.size() != polynomial_in.size()) { - VLOG(3) << "Trimmed polynomial: " << polynomial.transpose(); - } - - // Is the polynomial constant? - if (degree == 0) { - LOG(WARNING) << "Trying to extract roots from a constant " - << "polynomial in FindPolynomialRoots"; - // We return true with no roots, not false, as if the polynomial is constant - // it is correct that there are no roots. It is not the case that they were - // there, but that we have failed to extract them. - return true; - } - - // Linear - if (degree == 1) { - FindLinearPolynomialRoots(polynomial, real, imaginary); - return true; - } - - // Quadratic - if (degree == 2) { - FindQuadraticPolynomialRoots(polynomial, real, imaginary); - return true; - } - - // The degree is now known to be at least 3. For cubic or higher - // roots we use the method of companion matrices. - - // Divide by leading term - const double leading_term = polynomial(0); - polynomial /= leading_term; - - // Build and balance the companion matrix to the polynomial. - Matrix companion_matrix(degree, degree); - BuildCompanionMatrix(polynomial, &companion_matrix); - BalanceCompanionMatrix(&companion_matrix); - - // Find its (complex) eigenvalues. - Eigen::EigenSolver<Matrix> solver(companion_matrix, false); - if (solver.info() != Eigen::Success) { - LOG(ERROR) << "Failed to extract eigenvalues from companion matrix."; - return false; - } - - // Output roots - if (real != NULL) { - *real = solver.eigenvalues().real(); - } else { - LOG(WARNING) << "NULL pointer passed as real argument to " - << "FindPolynomialRoots. Real parts of the roots will not " - << "be returned."; - } - if (imaginary != NULL) { - *imaginary = solver.eigenvalues().imag(); - } - return true; -} - -Vector DifferentiatePolynomial(const Vector& polynomial) { - const int degree = polynomial.rows() - 1; - CHECK_GE(degree, 0); - - // Degree zero polynomials are constants, and their derivative does - // not result in a smaller degree polynomial, just a degree zero - // polynomial with value zero. - if (degree == 0) { - return Eigen::VectorXd::Zero(1); - } - - Vector derivative(degree); - for (int i = 0; i < degree; ++i) { - derivative(i) = (degree - i) * polynomial(i); - } - - return derivative; -} - -void MinimizePolynomial(const Vector& polynomial, - const double x_min, - const double x_max, - double* optimal_x, - double* optimal_value) { - // Find the minimum of the polynomial at the two ends. - // - // We start by inspecting the middle of the interval. Technically - // this is not needed, but we do this to make this code as close to - // the minFunc package as possible. - *optimal_x = (x_min + x_max) / 2.0; - *optimal_value = EvaluatePolynomial(polynomial, *optimal_x); - - const double x_min_value = EvaluatePolynomial(polynomial, x_min); - if (x_min_value < *optimal_value) { - *optimal_value = x_min_value; - *optimal_x = x_min; - } - - const double x_max_value = EvaluatePolynomial(polynomial, x_max); - if (x_max_value < *optimal_value) { - *optimal_value = x_max_value; - *optimal_x = x_max; - } - - // If the polynomial is linear or constant, we are done. - if (polynomial.rows() <= 2) { - return; - } - - const Vector derivative = DifferentiatePolynomial(polynomial); - Vector roots_real; - if (!FindPolynomialRoots(derivative, &roots_real, NULL)) { - LOG(WARNING) << "Unable to find the critical points of " - << "the interpolating polynomial."; - return; - } - - // This is a bit of an overkill, as some of the roots may actually - // have a complex part, but its simpler to just check these values. - for (int i = 0; i < roots_real.rows(); ++i) { - const double root = roots_real(i); - if ((root < x_min) || (root > x_max)) { - continue; - } - - const double value = EvaluatePolynomial(polynomial, root); - if (value < *optimal_value) { - *optimal_value = value; - *optimal_x = root; - } - } -} - -string FunctionSample::ToDebugString() const { - return StringPrintf("[x: %.8e, value: %.8e, gradient: %.8e, " - "value_is_valid: %d, gradient_is_valid: %d]", - x, value, gradient, value_is_valid, gradient_is_valid); -} - -Vector FindInterpolatingPolynomial(const vector<FunctionSample>& samples) { - const int num_samples = samples.size(); - int num_constraints = 0; - for (int i = 0; i < num_samples; ++i) { - if (samples[i].value_is_valid) { - ++num_constraints; - } - if (samples[i].gradient_is_valid) { - ++num_constraints; - } - } - - const int degree = num_constraints - 1; - - Matrix lhs = Matrix::Zero(num_constraints, num_constraints); - Vector rhs = Vector::Zero(num_constraints); - - int row = 0; - for (int i = 0; i < num_samples; ++i) { - const FunctionSample& sample = samples[i]; - if (sample.value_is_valid) { - for (int j = 0; j <= degree; ++j) { - lhs(row, j) = pow(sample.x, degree - j); - } - rhs(row) = sample.value; - ++row; - } - - if (sample.gradient_is_valid) { - for (int j = 0; j < degree; ++j) { - lhs(row, j) = (degree - j) * pow(sample.x, degree - j - 1); - } - rhs(row) = sample.gradient; - ++row; - } - } - - return lhs.fullPivLu().solve(rhs); -} - -void MinimizeInterpolatingPolynomial(const vector<FunctionSample>& samples, - double x_min, - double x_max, - double* optimal_x, - double* optimal_value) { - const Vector polynomial = FindInterpolatingPolynomial(samples); - MinimizePolynomial(polynomial, x_min, x_max, optimal_x, optimal_value); - for (int i = 0; i < samples.size(); ++i) { - const FunctionSample& sample = samples[i]; - if ((sample.x < x_min) || (sample.x > x_max)) { - continue; - } - - const double value = EvaluatePolynomial(polynomial, sample.x); - if (value < *optimal_value) { - *optimal_x = sample.x; - *optimal_value = value; - } - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/polynomial.h b/extern/libmv/third_party/ceres/internal/ceres/polynomial.h deleted file mode 100644 index 09a64c577f5..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/polynomial.h +++ /dev/null @@ -1,136 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: moll.markus@arcor.de (Markus Moll) -// sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_POLYNOMIAL_SOLVER_H_ -#define CERES_INTERNAL_POLYNOMIAL_SOLVER_H_ - -#include <string> -#include <vector> -#include "ceres/internal/eigen.h" -#include "ceres/internal/port.h" - -namespace ceres { -namespace internal { - -// All polynomials are assumed to be the form -// -// sum_{i=0}^N polynomial(i) x^{N-i}. -// -// and are given by a vector of coefficients of size N + 1. - -// Evaluate the polynomial at x using the Horner scheme. -inline double EvaluatePolynomial(const Vector& polynomial, double x) { - double v = 0.0; - for (int i = 0; i < polynomial.size(); ++i) { - v = v * x + polynomial(i); - } - return v; -} - -// Use the companion matrix eigenvalues to determine the roots of the -// polynomial. -// -// This function returns true on success, false otherwise. -// Failure indicates that the polynomial is invalid (of size 0) or -// that the eigenvalues of the companion matrix could not be computed. -// On failure, a more detailed message will be written to LOG(ERROR). -// If real is not NULL, the real parts of the roots will be returned in it. -// Likewise, if imaginary is not NULL, imaginary parts will be returned in it. -bool FindPolynomialRoots(const Vector& polynomial, - Vector* real, - Vector* imaginary); - -// Return the derivative of the given polynomial. It is assumed that -// the input polynomial is at least of degree zero. -Vector DifferentiatePolynomial(const Vector& polynomial); - -// Find the minimum value of the polynomial in the interval [x_min, -// x_max]. The minimum is obtained by computing all the roots of the -// derivative of the input polynomial. All real roots within the -// interval [x_min, x_max] are considered as well as the end points -// x_min and x_max. Since polynomials are differentiable functions, -// this ensures that the true minimum is found. -void MinimizePolynomial(const Vector& polynomial, - double x_min, - double x_max, - double* optimal_x, - double* optimal_value); - -// Structure for storing sample values of a function. -// -// Clients can use this struct to communicate the value of the -// function and or its gradient at a given point x. -struct FunctionSample { - FunctionSample() - : x(0.0), - value(0.0), - value_is_valid(false), - gradient(0.0), - gradient_is_valid(false) { - } - std::string ToDebugString() const; - - double x; - double value; // value = f(x) - bool value_is_valid; - double gradient; // gradient = f'(x) - bool gradient_is_valid; -}; - -// Given a set of function value and/or gradient samples, find a -// polynomial whose value and gradients are exactly equal to the ones -// in samples. -// -// Generally speaking, -// -// degree = # values + # gradients - 1 -// -// Of course its possible to sample a polynomial any number of times, -// in which case, generally speaking the spurious higher order -// coefficients will be zero. -Vector FindInterpolatingPolynomial(const std::vector<FunctionSample>& samples); - -// Interpolate the function described by samples with a polynomial, -// and minimize it on the interval [x_min, x_max]. Depending on the -// input samples, it is possible that the interpolation or the root -// finding algorithms may fail due to numerical difficulties. But the -// function is guaranteed to return its best guess of an answer, by -// considering the samples and the end points as possible solutions. -void MinimizeInterpolatingPolynomial(const std::vector<FunctionSample>& samples, - double x_min, - double x_max, - double* optimal_x, - double* optimal_value); - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_POLYNOMIAL_SOLVER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/preconditioner.cc b/extern/libmv/third_party/ceres/internal/ceres/preconditioner.cc deleted file mode 100644 index 82621dae50c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/preconditioner.cc +++ /dev/null @@ -1,73 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/preconditioner.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -Preconditioner::~Preconditioner() { -} - -PreconditionerType Preconditioner::PreconditionerForZeroEBlocks( - PreconditionerType preconditioner_type) { - if (preconditioner_type == SCHUR_JACOBI || - preconditioner_type == CLUSTER_JACOBI || - preconditioner_type == CLUSTER_TRIDIAGONAL) { - return JACOBI; - } - return preconditioner_type; -} - -SparseMatrixPreconditionerWrapper::SparseMatrixPreconditionerWrapper( - const SparseMatrix* matrix) - : matrix_(CHECK_NOTNULL(matrix)) { -} - -SparseMatrixPreconditionerWrapper::~SparseMatrixPreconditionerWrapper() { -} - -bool SparseMatrixPreconditionerWrapper::UpdateImpl(const SparseMatrix& A, - const double* D) { - return true; -} - -void SparseMatrixPreconditionerWrapper::RightMultiply(const double* x, - double* y) const { - matrix_->RightMultiply(x, y); -} - -int SparseMatrixPreconditionerWrapper::num_rows() const { - return matrix_->num_rows(); -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/preconditioner.h b/extern/libmv/third_party/ceres/internal/ceres/preconditioner.h deleted file mode 100644 index a248eae060d..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/preconditioner.h +++ /dev/null @@ -1,177 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_PRECONDITIONER_H_ -#define CERES_INTERNAL_PRECONDITIONER_H_ - -#include <vector> -#include "ceres/casts.h" -#include "ceres/compressed_row_sparse_matrix.h" -#include "ceres/linear_operator.h" -#include "ceres/sparse_matrix.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -class BlockSparseMatrix; -class SparseMatrix; - -class Preconditioner : public LinearOperator { - public: - struct Options { - Options() - : type(JACOBI), - visibility_clustering_type(CANONICAL_VIEWS), - sparse_linear_algebra_library_type(SUITE_SPARSE), - num_threads(1), - row_block_size(Eigen::Dynamic), - e_block_size(Eigen::Dynamic), - f_block_size(Eigen::Dynamic) { - } - - PreconditionerType type; - VisibilityClusteringType visibility_clustering_type; - SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type; - - // If possible, how many threads the preconditioner can use. - int num_threads; - - // Hints about the order in which the parameter blocks should be - // eliminated by the linear solver. - // - // For example if elimination_groups is a vector of size k, then - // the linear solver is informed that it should eliminate the - // parameter blocks 0 ... elimination_groups[0] - 1 first, and - // then elimination_groups[0] ... elimination_groups[1] - 1 and so - // on. Within each elimination group, the linear solver is free to - // choose how the parameter blocks are ordered. Different linear - // solvers have differing requirements on elimination_groups. - // - // The most common use is for Schur type solvers, where there - // should be at least two elimination groups and the first - // elimination group must form an independent set in the normal - // equations. The first elimination group corresponds to the - // num_eliminate_blocks in the Schur type solvers. - std::vector<int> elimination_groups; - - // If the block sizes in a BlockSparseMatrix are fixed, then in - // some cases the Schur complement based solvers can detect and - // specialize on them. - // - // It is expected that these parameters are set programmatically - // rather than manually. - // - // Please see schur_complement_solver.h and schur_eliminator.h for - // more details. - int row_block_size; - int e_block_size; - int f_block_size; - }; - - // If the optimization problem is such that there are no remaining - // e-blocks, ITERATIVE_SCHUR with a Schur type preconditioner cannot - // be used. This function returns JACOBI if a preconditioner for - // ITERATIVE_SCHUR is used. The input preconditioner_type is - // returned otherwise. - static PreconditionerType PreconditionerForZeroEBlocks( - PreconditionerType preconditioner_type); - - virtual ~Preconditioner(); - - // Update the numerical value of the preconditioner for the linear - // system: - // - // | A | x = |b| - // |diag(D)| |0| - // - // for some vector b. It is important that the matrix A have the - // same block structure as the one used to construct this object. - // - // D can be NULL, in which case its interpreted as a diagonal matrix - // of size zero. - virtual bool Update(const LinearOperator& A, const double* D) = 0; - - // LinearOperator interface. Since the operator is symmetric, - // LeftMultiply and num_cols are just calls to RightMultiply and - // num_rows respectively. Update() must be called before - // RightMultiply can be called. - virtual void RightMultiply(const double* x, double* y) const = 0; - virtual void LeftMultiply(const double* x, double* y) const { - return RightMultiply(x, y); - } - - virtual int num_rows() const = 0; - virtual int num_cols() const { - return num_rows(); - } -}; - -// This templated subclass of Preconditioner serves as a base class for -// other preconditioners that depend on the particular matrix layout of -// the underlying linear operator. -template <typename MatrixType> -class TypedPreconditioner : public Preconditioner { - public: - virtual ~TypedPreconditioner() {} - virtual bool Update(const LinearOperator& A, const double* D) { - return UpdateImpl(*down_cast<const MatrixType*>(&A), D); - } - - private: - virtual bool UpdateImpl(const MatrixType& A, const double* D) = 0; -}; - -// Preconditioners that depend on acccess to the low level structure -// of a SparseMatrix. -typedef TypedPreconditioner<SparseMatrix> SparseMatrixPreconditioner; // NOLINT -typedef TypedPreconditioner<BlockSparseMatrix> BlockSparseMatrixPreconditioner; // NOLINT -typedef TypedPreconditioner<CompressedRowSparseMatrix> CompressedRowSparseMatrixPreconditioner; // NOLINT - -// Wrap a SparseMatrix object as a preconditioner. -class SparseMatrixPreconditionerWrapper : public SparseMatrixPreconditioner { - public: - // Wrapper does NOT take ownership of the matrix pointer. - explicit SparseMatrixPreconditionerWrapper(const SparseMatrix* matrix); - virtual ~SparseMatrixPreconditionerWrapper(); - - // Preconditioner interface - virtual void RightMultiply(const double* x, double* y) const; - virtual int num_rows() const; - - private: - virtual bool UpdateImpl(const SparseMatrix& A, const double* D); - const SparseMatrix* matrix_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_PRECONDITIONER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/preprocessor.cc b/extern/libmv/third_party/ceres/internal/ceres/preprocessor.cc deleted file mode 100644 index 4aba6a39ce8..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/preprocessor.cc +++ /dev/null @@ -1,113 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameragarwal@google.com (Sameer Agarwal) - -#include "ceres/callbacks.h" -#include "ceres/gradient_checking_cost_function.h" -#include "ceres/line_search_preprocessor.h" -#include "ceres/preprocessor.h" -#include "ceres/problem_impl.h" -#include "ceres/solver.h" -#include "ceres/trust_region_preprocessor.h" - -namespace ceres { -namespace internal { - -Preprocessor* Preprocessor::Create(MinimizerType minimizer_type) { - if (minimizer_type == TRUST_REGION) { - return new TrustRegionPreprocessor; - } - - if (minimizer_type == LINE_SEARCH) { - return new LineSearchPreprocessor; - } - - LOG(FATAL) << "Unknown minimizer_type: " << minimizer_type; - return NULL; -} - -Preprocessor::~Preprocessor() { -} - -void ChangeNumThreadsIfNeeded(Solver::Options* options) { -#ifndef CERES_USE_OPENMP - if (options->num_threads > 1) { - LOG(WARNING) - << "OpenMP support is not compiled into this binary; " - << "only options.num_threads = 1 is supported. Switching " - << "to single threaded mode."; - options->num_threads = 1; - } - - // Only the Trust Region solver currently uses a linear solver. - if (options->minimizer_type == TRUST_REGION && - options->num_linear_solver_threads > 1) { - LOG(WARNING) - << "OpenMP support is not compiled into this binary; " - << "only options.num_linear_solver_threads=1 is supported. Switching " - << "to single threaded mode."; - options->num_linear_solver_threads = 1; - } -#endif // CERES_USE_OPENMP -} - -void SetupCommonMinimizerOptions(PreprocessedProblem* pp) { - const Solver::Options& options = pp->options; - Program* program = pp->reduced_program.get(); - - // Assuming that the parameter blocks in the program have been - // reordered as needed, extract them into a contiguous vector. - pp->reduced_parameters.resize(program->NumParameters()); - double* reduced_parameters = pp->reduced_parameters.data(); - program->ParameterBlocksToStateVector(reduced_parameters); - - Minimizer::Options& minimizer_options = pp->minimizer_options; - minimizer_options = Minimizer::Options(options); - minimizer_options.evaluator = pp->evaluator; - - if (options.logging_type != SILENT) { - pp->logging_callback.reset( - new LoggingCallback(options.minimizer_type, - options.minimizer_progress_to_stdout)); - minimizer_options.callbacks.insert(minimizer_options.callbacks.begin(), - pp->logging_callback.get()); - } - - if (options.update_state_every_iteration) { - pp->state_updating_callback.reset( - new StateUpdatingCallback(program, reduced_parameters)); - // This must get pushed to the front of the callbacks so that it - // is run before any of the user callbacks. - minimizer_options.callbacks.insert(minimizer_options.callbacks.begin(), - pp->state_updating_callback.get()); - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/preprocessor.h b/extern/libmv/third_party/ceres/internal/ceres/preprocessor.h deleted file mode 100644 index ff53d6f0d3f..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/preprocessor.h +++ /dev/null @@ -1,122 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_PREPROCESSOR_H_ -#define CERES_INTERNAL_PREPROCESSOR_H_ - -#include <string> -#include <vector> - -#include "ceres/coordinate_descent_minimizer.h" -#include "ceres/evaluator.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/iteration_callback.h" -#include "ceres/linear_solver.h" -#include "ceres/minimizer.h" -#include "ceres/problem_impl.h" -#include "ceres/program.h" -#include "ceres/solver.h" - -namespace ceres { -namespace internal { - -struct PreprocessedProblem; - -// Given a Problem object and a Solver::Options object indicating the -// configuration of the solver, the job of the Preprocessor is to -// analyze the Problem and perform the setup needed to solve it using -// the desired Minimization algorithm. The setup involves removing -// redundancies in the input problem (inactive parameter and residual -// blocks), finding fill reducing orderings as needed, configuring and -// creating various objects needed by the Minimizer to solve the -// problem such as an evaluator, a linear solver etc. -// -// Each Minimizer (LineSearchMinimizer and TrustRegionMinimizer) comes -// with a corresponding Preprocessor (LineSearchPreprocessor and -// TrustRegionPreprocessor) that knows about its needs and performs -// the preprocessing needed. -// -// The output of the Preprocessor is stored in a PreprocessedProblem -// object. -class Preprocessor { - public: - // Factory. - static Preprocessor* Create(MinimizerType minimizer_type); - virtual ~Preprocessor(); - virtual bool Preprocess(const Solver::Options& options, - ProblemImpl* problem, - PreprocessedProblem* pp) = 0; -}; - -// A PreprocessedProblem is the result of running the Preprocessor on -// a Problem and Solver::Options object. -struct PreprocessedProblem { - PreprocessedProblem() - : fixed_cost(0.0) { - } - - std::string error; - Solver::Options options; - LinearSolver::Options linear_solver_options; - Evaluator::Options evaluator_options; - Minimizer::Options minimizer_options; - - ProblemImpl* problem; - scoped_ptr<ProblemImpl> gradient_checking_problem; - scoped_ptr<Program> reduced_program; - scoped_ptr<LinearSolver> linear_solver; - scoped_ptr<IterationCallback> logging_callback; - scoped_ptr<IterationCallback> state_updating_callback; - - shared_ptr<Evaluator> evaluator; - shared_ptr<CoordinateDescentMinimizer> inner_iteration_minimizer; - - std::vector<double*> removed_parameter_blocks; - Vector reduced_parameters; - double fixed_cost; -}; - -// Common functions used by various preprocessors. - -// If OpenMP support is not available and user has requested more than -// one thread, then set the *_num_threads options as needed to 1. -void ChangeNumThreadsIfNeeded(Solver::Options* options); - -// Extract the effective parameter vector from the preprocessed -// problem and setup bits of the Minimizer::Options object that are -// common to all Preprocessors. -void SetupCommonMinimizerOptions(PreprocessedProblem* pp); - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_PREPROCESSOR_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/problem.cc b/extern/libmv/third_party/ceres/internal/ceres/problem.cc deleted file mode 100644 index 03b7d6afa48..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/problem.cc +++ /dev/null @@ -1,273 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// keir@google.com (Keir Mierle) - -#include "ceres/problem.h" - -#include <vector> -#include "ceres/crs_matrix.h" -#include "ceres/problem_impl.h" - -namespace ceres { - -using std::vector; - -Problem::Problem() : problem_impl_(new internal::ProblemImpl) {} -Problem::Problem(const Problem::Options& options) - : problem_impl_(new internal::ProblemImpl(options)) {} -Problem::~Problem() {} - -ResidualBlockId Problem::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - const vector<double*>& parameter_blocks) { - return problem_impl_->AddResidualBlock(cost_function, - loss_function, - parameter_blocks); -} - -ResidualBlockId Problem::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0) { - return problem_impl_->AddResidualBlock(cost_function, - loss_function, - x0); -} - -ResidualBlockId Problem::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1) { - return problem_impl_->AddResidualBlock(cost_function, - loss_function, - x0, x1); -} - -ResidualBlockId Problem::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2) { - return problem_impl_->AddResidualBlock(cost_function, - loss_function, - x0, x1, x2); -} - -ResidualBlockId Problem::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3) { - return problem_impl_->AddResidualBlock(cost_function, - loss_function, - x0, x1, x2, x3); -} - -ResidualBlockId Problem::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3, double* x4) { - return problem_impl_->AddResidualBlock(cost_function, - loss_function, - x0, x1, x2, x3, x4); -} - -ResidualBlockId Problem::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3, double* x4, double* x5) { - return problem_impl_->AddResidualBlock(cost_function, - loss_function, - x0, x1, x2, x3, x4, x5); -} - -ResidualBlockId Problem::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3, double* x4, double* x5, - double* x6) { - return problem_impl_->AddResidualBlock(cost_function, - loss_function, - x0, x1, x2, x3, x4, x5, x6); -} - -ResidualBlockId Problem::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3, double* x4, double* x5, - double* x6, double* x7) { - return problem_impl_->AddResidualBlock(cost_function, - loss_function, - x0, x1, x2, x3, x4, x5, x6, x7); -} - -ResidualBlockId Problem::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3, double* x4, double* x5, - double* x6, double* x7, double* x8) { - return problem_impl_->AddResidualBlock(cost_function, - loss_function, - x0, x1, x2, x3, x4, x5, x6, x7, x8); -} - -ResidualBlockId Problem::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3, double* x4, double* x5, - double* x6, double* x7, double* x8, double* x9) { - return problem_impl_->AddResidualBlock( - cost_function, - loss_function, - x0, x1, x2, x3, x4, x5, x6, x7, x8, x9); -} - -void Problem::AddParameterBlock(double* values, int size) { - problem_impl_->AddParameterBlock(values, size); -} - -void Problem::AddParameterBlock(double* values, - int size, - LocalParameterization* local_parameterization) { - problem_impl_->AddParameterBlock(values, size, local_parameterization); -} - -void Problem::RemoveResidualBlock(ResidualBlockId residual_block) { - problem_impl_->RemoveResidualBlock(residual_block); -} - -void Problem::RemoveParameterBlock(double* values) { - problem_impl_->RemoveParameterBlock(values); -} - -void Problem::SetParameterBlockConstant(double* values) { - problem_impl_->SetParameterBlockConstant(values); -} - -void Problem::SetParameterBlockVariable(double* values) { - problem_impl_->SetParameterBlockVariable(values); -} - -void Problem::SetParameterization( - double* values, - LocalParameterization* local_parameterization) { - problem_impl_->SetParameterization(values, local_parameterization); -} - -const LocalParameterization* Problem::GetParameterization( - double* values) const { - return problem_impl_->GetParameterization(values); -} - -void Problem::SetParameterLowerBound(double* values, - int index, - double lower_bound) { - problem_impl_->SetParameterLowerBound(values, index, lower_bound); -} - -void Problem::SetParameterUpperBound(double* values, - int index, - double upper_bound) { - problem_impl_->SetParameterUpperBound(values, index, upper_bound); -} - -bool Problem::Evaluate(const EvaluateOptions& evaluate_options, - double* cost, - vector<double>* residuals, - vector<double>* gradient, - CRSMatrix* jacobian) { - return problem_impl_->Evaluate(evaluate_options, - cost, - residuals, - gradient, - jacobian); -} - -int Problem::NumParameterBlocks() const { - return problem_impl_->NumParameterBlocks(); -} - -int Problem::NumParameters() const { - return problem_impl_->NumParameters(); -} - -int Problem::NumResidualBlocks() const { - return problem_impl_->NumResidualBlocks(); -} - -int Problem::NumResiduals() const { - return problem_impl_->NumResiduals(); -} - -int Problem::ParameterBlockSize(const double* parameter_block) const { - return problem_impl_->ParameterBlockSize(parameter_block); -} - -int Problem::ParameterBlockLocalSize(const double* parameter_block) const { - return problem_impl_->ParameterBlockLocalSize(parameter_block); -} - -bool Problem::HasParameterBlock(const double* values) const { - return problem_impl_->HasParameterBlock(values); -} - -void Problem::GetParameterBlocks(vector<double*>* parameter_blocks) const { - problem_impl_->GetParameterBlocks(parameter_blocks); -} - -void Problem::GetResidualBlocks( - vector<ResidualBlockId>* residual_blocks) const { - problem_impl_->GetResidualBlocks(residual_blocks); -} - -void Problem::GetParameterBlocksForResidualBlock( - const ResidualBlockId residual_block, - vector<double*>* parameter_blocks) const { - problem_impl_->GetParameterBlocksForResidualBlock(residual_block, - parameter_blocks); -} - -const CostFunction* Problem::GetCostFunctionForResidualBlock( - const ResidualBlockId residual_block) const { - return problem_impl_->GetCostFunctionForResidualBlock(residual_block); -} - -const LossFunction* Problem::GetLossFunctionForResidualBlock( - const ResidualBlockId residual_block) const { - return problem_impl_->GetLossFunctionForResidualBlock(residual_block); -} - -void Problem::GetResidualBlocksForParameterBlock( - const double* values, - vector<ResidualBlockId>* residual_blocks) const { - problem_impl_->GetResidualBlocksForParameterBlock(values, - residual_blocks); -} - -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/problem_impl.cc b/extern/libmv/third_party/ceres/internal/ceres/problem_impl.cc deleted file mode 100644 index 8547d5d3f77..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/problem_impl.cc +++ /dev/null @@ -1,945 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// mierle@gmail.com (Keir Mierle) - -#include "ceres/problem_impl.h" - -#include <algorithm> -#include <cstddef> -#include <iterator> -#include <set> -#include <string> -#include <utility> -#include <vector> -#include "ceres/casts.h" -#include "ceres/compressed_row_sparse_matrix.h" -#include "ceres/cost_function.h" -#include "ceres/crs_matrix.h" -#include "ceres/evaluator.h" -#include "ceres/loss_function.h" -#include "ceres/map_util.h" -#include "ceres/parameter_block.h" -#include "ceres/program.h" -#include "ceres/residual_block.h" -#include "ceres/stl_util.h" -#include "ceres/stringprintf.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::map; -using std::string; -using std::vector; -typedef std::map<double*, internal::ParameterBlock*> ParameterMap; - -namespace { -// Returns true if two regions of memory, a and b, with sizes size_a and size_b -// respectively, overlap. -bool RegionsAlias(const double* a, int size_a, - const double* b, int size_b) { - return (a < b) ? b < (a + size_a) - : a < (b + size_b); -} - -void CheckForNoAliasing(double* existing_block, - int existing_block_size, - double* new_block, - int new_block_size) { - CHECK(!RegionsAlias(existing_block, existing_block_size, - new_block, new_block_size)) - << "Aliasing detected between existing parameter block at memory " - << "location " << existing_block - << " and has size " << existing_block_size << " with new parameter " - << "block that has memory address " << new_block << " and would have " - << "size " << new_block_size << "."; -} - -} // namespace - -ParameterBlock* ProblemImpl::InternalAddParameterBlock(double* values, - int size) { - CHECK(values != NULL) << "Null pointer passed to AddParameterBlock " - << "for a parameter with size " << size; - - // Ignore the request if there is a block for the given pointer already. - ParameterMap::iterator it = parameter_block_map_.find(values); - if (it != parameter_block_map_.end()) { - if (!options_.disable_all_safety_checks) { - int existing_size = it->second->Size(); - CHECK(size == existing_size) - << "Tried adding a parameter block with the same double pointer, " - << values << ", twice, but with different block sizes. Original " - << "size was " << existing_size << " but new size is " - << size; - } - return it->second; - } - - if (!options_.disable_all_safety_checks) { - // Before adding the parameter block, also check that it doesn't alias any - // other parameter blocks. - if (!parameter_block_map_.empty()) { - ParameterMap::iterator lb = parameter_block_map_.lower_bound(values); - - // If lb is not the first block, check the previous block for aliasing. - if (lb != parameter_block_map_.begin()) { - ParameterMap::iterator previous = lb; - --previous; - CheckForNoAliasing(previous->first, - previous->second->Size(), - values, - size); - } - - // If lb is not off the end, check lb for aliasing. - if (lb != parameter_block_map_.end()) { - CheckForNoAliasing(lb->first, - lb->second->Size(), - values, - size); - } - } - } - - // Pass the index of the new parameter block as well to keep the index in - // sync with the position of the parameter in the program's parameter vector. - ParameterBlock* new_parameter_block = - new ParameterBlock(values, size, program_->parameter_blocks_.size()); - - // For dynamic problems, add the list of dependent residual blocks, which is - // empty to start. - if (options_.enable_fast_removal) { - new_parameter_block->EnableResidualBlockDependencies(); - } - parameter_block_map_[values] = new_parameter_block; - program_->parameter_blocks_.push_back(new_parameter_block); - return new_parameter_block; -} - -void ProblemImpl::InternalRemoveResidualBlock(ResidualBlock* residual_block) { - CHECK_NOTNULL(residual_block); - // Perform no check on the validity of residual_block, that is handled in - // the public method: RemoveResidualBlock(). - - // If needed, remove the parameter dependencies on this residual block. - if (options_.enable_fast_removal) { - const int num_parameter_blocks_for_residual = - residual_block->NumParameterBlocks(); - for (int i = 0; i < num_parameter_blocks_for_residual; ++i) { - residual_block->parameter_blocks()[i] - ->RemoveResidualBlock(residual_block); - } - - ResidualBlockSet::iterator it = residual_block_set_.find(residual_block); - residual_block_set_.erase(it); - } - DeleteBlockInVector(program_->mutable_residual_blocks(), residual_block); -} - -// Deletes the residual block in question, assuming there are no other -// references to it inside the problem (e.g. by another parameter). Referenced -// cost and loss functions are tucked away for future deletion, since it is not -// possible to know whether other parts of the problem depend on them without -// doing a full scan. -void ProblemImpl::DeleteBlock(ResidualBlock* residual_block) { - // The const casts here are legit, since ResidualBlock holds these - // pointers as const pointers but we have ownership of them and - // have the right to destroy them when the destructor is called. - if (options_.cost_function_ownership == TAKE_OWNERSHIP && - residual_block->cost_function() != NULL) { - cost_functions_to_delete_.push_back( - const_cast<CostFunction*>(residual_block->cost_function())); - } - if (options_.loss_function_ownership == TAKE_OWNERSHIP && - residual_block->loss_function() != NULL) { - loss_functions_to_delete_.push_back( - const_cast<LossFunction*>(residual_block->loss_function())); - } - delete residual_block; -} - -// Deletes the parameter block in question, assuming there are no other -// references to it inside the problem (e.g. by any residual blocks). -// Referenced parameterizations are tucked away for future deletion, since it -// is not possible to know whether other parts of the problem depend on them -// without doing a full scan. -void ProblemImpl::DeleteBlock(ParameterBlock* parameter_block) { - if (options_.local_parameterization_ownership == TAKE_OWNERSHIP && - parameter_block->local_parameterization() != NULL) { - local_parameterizations_to_delete_.push_back( - parameter_block->mutable_local_parameterization()); - } - parameter_block_map_.erase(parameter_block->mutable_user_state()); - delete parameter_block; -} - -ProblemImpl::ProblemImpl() : program_(new internal::Program) {} -ProblemImpl::ProblemImpl(const Problem::Options& options) - : options_(options), - program_(new internal::Program) {} - -ProblemImpl::~ProblemImpl() { - // Collect the unique cost/loss functions and delete the residuals. - const int num_residual_blocks = program_->residual_blocks_.size(); - cost_functions_to_delete_.reserve(num_residual_blocks); - loss_functions_to_delete_.reserve(num_residual_blocks); - for (int i = 0; i < program_->residual_blocks_.size(); ++i) { - DeleteBlock(program_->residual_blocks_[i]); - } - - // Collect the unique parameterizations and delete the parameters. - for (int i = 0; i < program_->parameter_blocks_.size(); ++i) { - DeleteBlock(program_->parameter_blocks_[i]); - } - - // Delete the owned cost/loss functions and parameterizations. - STLDeleteUniqueContainerPointers(local_parameterizations_to_delete_.begin(), - local_parameterizations_to_delete_.end()); - STLDeleteUniqueContainerPointers(cost_functions_to_delete_.begin(), - cost_functions_to_delete_.end()); - STLDeleteUniqueContainerPointers(loss_functions_to_delete_.begin(), - loss_functions_to_delete_.end()); -} - -ResidualBlock* ProblemImpl::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - const vector<double*>& parameter_blocks) { - CHECK_NOTNULL(cost_function); - CHECK_EQ(parameter_blocks.size(), - cost_function->parameter_block_sizes().size()); - - // Check the sizes match. - const vector<int32>& parameter_block_sizes = - cost_function->parameter_block_sizes(); - - if (!options_.disable_all_safety_checks) { - CHECK_EQ(parameter_block_sizes.size(), parameter_blocks.size()) - << "Number of blocks input is different than the number of blocks " - << "that the cost function expects."; - - // Check for duplicate parameter blocks. - vector<double*> sorted_parameter_blocks(parameter_blocks); - sort(sorted_parameter_blocks.begin(), sorted_parameter_blocks.end()); - vector<double*>::const_iterator duplicate_items = - unique(sorted_parameter_blocks.begin(), - sorted_parameter_blocks.end()); - if (duplicate_items != sorted_parameter_blocks.end()) { - string blocks; - for (int i = 0; i < parameter_blocks.size(); ++i) { - blocks += StringPrintf(" %p ", parameter_blocks[i]); - } - - LOG(FATAL) << "Duplicate parameter blocks in a residual parameter " - << "are not allowed. Parameter block pointers: [" - << blocks << "]"; - } - } - - // Add parameter blocks and convert the double*'s to parameter blocks. - vector<ParameterBlock*> parameter_block_ptrs(parameter_blocks.size()); - for (int i = 0; i < parameter_blocks.size(); ++i) { - parameter_block_ptrs[i] = - InternalAddParameterBlock(parameter_blocks[i], - parameter_block_sizes[i]); - } - - if (!options_.disable_all_safety_checks) { - // Check that the block sizes match the block sizes expected by the - // cost_function. - for (int i = 0; i < parameter_block_ptrs.size(); ++i) { - CHECK_EQ(cost_function->parameter_block_sizes()[i], - parameter_block_ptrs[i]->Size()) - << "The cost function expects parameter block " << i - << " of size " << cost_function->parameter_block_sizes()[i] - << " but was given a block of size " - << parameter_block_ptrs[i]->Size(); - } - } - - ResidualBlock* new_residual_block = - new ResidualBlock(cost_function, - loss_function, - parameter_block_ptrs, - program_->residual_blocks_.size()); - - // Add dependencies on the residual to the parameter blocks. - if (options_.enable_fast_removal) { - for (int i = 0; i < parameter_blocks.size(); ++i) { - parameter_block_ptrs[i]->AddResidualBlock(new_residual_block); - } - } - - program_->residual_blocks_.push_back(new_residual_block); - - if (options_.enable_fast_removal) { - residual_block_set_.insert(new_residual_block); - } - - return new_residual_block; -} - -// Unfortunately, macros don't help much to reduce this code, and var args don't -// work because of the ambiguous case that there is no loss function. -ResidualBlock* ProblemImpl::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0) { - vector<double*> residual_parameters; - residual_parameters.push_back(x0); - return AddResidualBlock(cost_function, loss_function, residual_parameters); -} - -ResidualBlock* ProblemImpl::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1) { - vector<double*> residual_parameters; - residual_parameters.push_back(x0); - residual_parameters.push_back(x1); - return AddResidualBlock(cost_function, loss_function, residual_parameters); -} - -ResidualBlock* ProblemImpl::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2) { - vector<double*> residual_parameters; - residual_parameters.push_back(x0); - residual_parameters.push_back(x1); - residual_parameters.push_back(x2); - return AddResidualBlock(cost_function, loss_function, residual_parameters); -} - -ResidualBlock* ProblemImpl::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3) { - vector<double*> residual_parameters; - residual_parameters.push_back(x0); - residual_parameters.push_back(x1); - residual_parameters.push_back(x2); - residual_parameters.push_back(x3); - return AddResidualBlock(cost_function, loss_function, residual_parameters); -} - -ResidualBlock* ProblemImpl::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3, double* x4) { - vector<double*> residual_parameters; - residual_parameters.push_back(x0); - residual_parameters.push_back(x1); - residual_parameters.push_back(x2); - residual_parameters.push_back(x3); - residual_parameters.push_back(x4); - return AddResidualBlock(cost_function, loss_function, residual_parameters); -} - -ResidualBlock* ProblemImpl::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3, double* x4, double* x5) { - vector<double*> residual_parameters; - residual_parameters.push_back(x0); - residual_parameters.push_back(x1); - residual_parameters.push_back(x2); - residual_parameters.push_back(x3); - residual_parameters.push_back(x4); - residual_parameters.push_back(x5); - return AddResidualBlock(cost_function, loss_function, residual_parameters); -} - -ResidualBlock* ProblemImpl::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3, double* x4, double* x5, - double* x6) { - vector<double*> residual_parameters; - residual_parameters.push_back(x0); - residual_parameters.push_back(x1); - residual_parameters.push_back(x2); - residual_parameters.push_back(x3); - residual_parameters.push_back(x4); - residual_parameters.push_back(x5); - residual_parameters.push_back(x6); - return AddResidualBlock(cost_function, loss_function, residual_parameters); -} - -ResidualBlock* ProblemImpl::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3, double* x4, double* x5, - double* x6, double* x7) { - vector<double*> residual_parameters; - residual_parameters.push_back(x0); - residual_parameters.push_back(x1); - residual_parameters.push_back(x2); - residual_parameters.push_back(x3); - residual_parameters.push_back(x4); - residual_parameters.push_back(x5); - residual_parameters.push_back(x6); - residual_parameters.push_back(x7); - return AddResidualBlock(cost_function, loss_function, residual_parameters); -} - -ResidualBlock* ProblemImpl::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3, double* x4, double* x5, - double* x6, double* x7, double* x8) { - vector<double*> residual_parameters; - residual_parameters.push_back(x0); - residual_parameters.push_back(x1); - residual_parameters.push_back(x2); - residual_parameters.push_back(x3); - residual_parameters.push_back(x4); - residual_parameters.push_back(x5); - residual_parameters.push_back(x6); - residual_parameters.push_back(x7); - residual_parameters.push_back(x8); - return AddResidualBlock(cost_function, loss_function, residual_parameters); -} - -ResidualBlock* ProblemImpl::AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, double* x3, double* x4, double* x5, - double* x6, double* x7, double* x8, double* x9) { - vector<double*> residual_parameters; - residual_parameters.push_back(x0); - residual_parameters.push_back(x1); - residual_parameters.push_back(x2); - residual_parameters.push_back(x3); - residual_parameters.push_back(x4); - residual_parameters.push_back(x5); - residual_parameters.push_back(x6); - residual_parameters.push_back(x7); - residual_parameters.push_back(x8); - residual_parameters.push_back(x9); - return AddResidualBlock(cost_function, loss_function, residual_parameters); -} - -void ProblemImpl::AddParameterBlock(double* values, int size) { - InternalAddParameterBlock(values, size); -} - -void ProblemImpl::AddParameterBlock( - double* values, - int size, - LocalParameterization* local_parameterization) { - ParameterBlock* parameter_block = - InternalAddParameterBlock(values, size); - if (local_parameterization != NULL) { - parameter_block->SetParameterization(local_parameterization); - } -} - -// Delete a block from a vector of blocks, maintaining the indexing invariant. -// This is done in constant time by moving an element from the end of the -// vector over the element to remove, then popping the last element. It -// destroys the ordering in the interest of speed. -template<typename Block> -void ProblemImpl::DeleteBlockInVector(vector<Block*>* mutable_blocks, - Block* block_to_remove) { - CHECK_EQ((*mutable_blocks)[block_to_remove->index()], block_to_remove) - << "You found a Ceres bug! \n" - << "Block requested: " - << block_to_remove->ToString() << "\n" - << "Block present: " - << (*mutable_blocks)[block_to_remove->index()]->ToString(); - - // Prepare the to-be-moved block for the new, lower-in-index position by - // setting the index to the blocks final location. - Block* tmp = mutable_blocks->back(); - tmp->set_index(block_to_remove->index()); - - // Overwrite the to-be-deleted residual block with the one at the end. - (*mutable_blocks)[block_to_remove->index()] = tmp; - - DeleteBlock(block_to_remove); - - // The block is gone so shrink the vector of blocks accordingly. - mutable_blocks->pop_back(); -} - -void ProblemImpl::RemoveResidualBlock(ResidualBlock* residual_block) { - CHECK_NOTNULL(residual_block); - - // Verify that residual_block identifies a residual in the current problem. - const string residual_not_found_message = - StringPrintf("Residual block to remove: %p not found. This usually means " - "one of three things have happened:\n" - " 1) residual_block is uninitialised and points to a random " - "area in memory.\n" - " 2) residual_block represented a residual that was added to" - " the problem, but referred to a parameter block which has " - "since been removed, which removes all residuals which " - "depend on that parameter block, and was thus removed.\n" - " 3) residual_block referred to a residual that has already " - "been removed from the problem (by the user).", - residual_block); - if (options_.enable_fast_removal) { - CHECK(residual_block_set_.find(residual_block) != - residual_block_set_.end()) - << residual_not_found_message; - } else { - // Perform a full search over all current residuals. - CHECK(std::find(program_->residual_blocks().begin(), - program_->residual_blocks().end(), - residual_block) != program_->residual_blocks().end()) - << residual_not_found_message; - } - - InternalRemoveResidualBlock(residual_block); -} - -void ProblemImpl::RemoveParameterBlock(double* values) { - ParameterBlock* parameter_block = - FindWithDefault(parameter_block_map_, values, NULL); - if (parameter_block == NULL) { - LOG(FATAL) << "Parameter block not found: " << values - << ". You must add the parameter block to the problem before " - << "it can be removed."; - } - - if (options_.enable_fast_removal) { - // Copy the dependent residuals from the parameter block because the set of - // dependents will change after each call to RemoveResidualBlock(). - vector<ResidualBlock*> residual_blocks_to_remove( - parameter_block->mutable_residual_blocks()->begin(), - parameter_block->mutable_residual_blocks()->end()); - for (int i = 0; i < residual_blocks_to_remove.size(); ++i) { - InternalRemoveResidualBlock(residual_blocks_to_remove[i]); - } - } else { - // Scan all the residual blocks to remove ones that depend on the parameter - // block. Do the scan backwards since the vector changes while iterating. - const int num_residual_blocks = NumResidualBlocks(); - for (int i = num_residual_blocks - 1; i >= 0; --i) { - ResidualBlock* residual_block = - (*(program_->mutable_residual_blocks()))[i]; - const int num_parameter_blocks = residual_block->NumParameterBlocks(); - for (int j = 0; j < num_parameter_blocks; ++j) { - if (residual_block->parameter_blocks()[j] == parameter_block) { - InternalRemoveResidualBlock(residual_block); - // The parameter blocks are guaranteed unique. - break; - } - } - } - } - DeleteBlockInVector(program_->mutable_parameter_blocks(), parameter_block); -} - -void ProblemImpl::SetParameterBlockConstant(double* values) { - ParameterBlock* parameter_block = - FindWithDefault(parameter_block_map_, values, NULL); - if (parameter_block == NULL) { - LOG(FATAL) << "Parameter block not found: " << values - << ". You must add the parameter block to the problem before " - << "it can be set constant."; - } - - parameter_block->SetConstant(); -} - -void ProblemImpl::SetParameterBlockVariable(double* values) { - ParameterBlock* parameter_block = - FindWithDefault(parameter_block_map_, values, NULL); - if (parameter_block == NULL) { - LOG(FATAL) << "Parameter block not found: " << values - << ". You must add the parameter block to the problem before " - << "it can be set varying."; - } - - parameter_block->SetVarying(); -} - -void ProblemImpl::SetParameterization( - double* values, - LocalParameterization* local_parameterization) { - ParameterBlock* parameter_block = - FindWithDefault(parameter_block_map_, values, NULL); - if (parameter_block == NULL) { - LOG(FATAL) << "Parameter block not found: " << values - << ". You must add the parameter block to the problem before " - << "you can set its local parameterization."; - } - - parameter_block->SetParameterization(local_parameterization); -} - -const LocalParameterization* ProblemImpl::GetParameterization( - double* values) const { - ParameterBlock* parameter_block = - FindWithDefault(parameter_block_map_, values, NULL); - if (parameter_block == NULL) { - LOG(FATAL) << "Parameter block not found: " << values - << ". You must add the parameter block to the problem before " - << "you can get its local parameterization."; - } - - return parameter_block->local_parameterization(); -} - -void ProblemImpl::SetParameterLowerBound(double* values, - int index, - double lower_bound) { - ParameterBlock* parameter_block = - FindWithDefault(parameter_block_map_, values, NULL); - if (parameter_block == NULL) { - LOG(FATAL) << "Parameter block not found: " << values - << ". You must add the parameter block to the problem before " - << "you can set a lower bound on one of its components."; - } - - parameter_block->SetLowerBound(index, lower_bound); -} - -void ProblemImpl::SetParameterUpperBound(double* values, - int index, - double upper_bound) { - ParameterBlock* parameter_block = - FindWithDefault(parameter_block_map_, values, NULL); - if (parameter_block == NULL) { - LOG(FATAL) << "Parameter block not found: " << values - << ". You must add the parameter block to the problem before " - << "you can set an upper bound on one of its components."; - } - parameter_block->SetUpperBound(index, upper_bound); -} - -bool ProblemImpl::Evaluate(const Problem::EvaluateOptions& evaluate_options, - double* cost, - vector<double>* residuals, - vector<double>* gradient, - CRSMatrix* jacobian) { - if (cost == NULL && - residuals == NULL && - gradient == NULL && - jacobian == NULL) { - LOG(INFO) << "Nothing to do."; - return true; - } - - // If the user supplied residual blocks, then use them, otherwise - // take the residual blocks from the underlying program. - Program program; - *program.mutable_residual_blocks() = - ((evaluate_options.residual_blocks.size() > 0) - ? evaluate_options.residual_blocks : program_->residual_blocks()); - - const vector<double*>& parameter_block_ptrs = - evaluate_options.parameter_blocks; - - vector<ParameterBlock*> variable_parameter_blocks; - vector<ParameterBlock*>& parameter_blocks = - *program.mutable_parameter_blocks(); - - if (parameter_block_ptrs.size() == 0) { - // The user did not provide any parameter blocks, so default to - // using all the parameter blocks in the order that they are in - // the underlying program object. - parameter_blocks = program_->parameter_blocks(); - } else { - // The user supplied a vector of parameter blocks. Using this list - // requires a number of steps. - - // 1. Convert double* into ParameterBlock* - parameter_blocks.resize(parameter_block_ptrs.size()); - for (int i = 0; i < parameter_block_ptrs.size(); ++i) { - parameter_blocks[i] = FindWithDefault(parameter_block_map_, - parameter_block_ptrs[i], - NULL); - if (parameter_blocks[i] == NULL) { - LOG(FATAL) << "No known parameter block for " - << "Problem::Evaluate::Options.parameter_blocks[" << i << "]" - << " = " << parameter_block_ptrs[i]; - } - } - - // 2. The user may have only supplied a subset of parameter - // blocks, so identify the ones that are not supplied by the user - // and are NOT constant. These parameter blocks are stored in - // variable_parameter_blocks. - // - // To ensure that the parameter blocks are not included in the - // columns of the jacobian, we need to make sure that they are - // constant during evaluation and then make them variable again - // after we are done. - vector<ParameterBlock*> all_parameter_blocks(program_->parameter_blocks()); - vector<ParameterBlock*> included_parameter_blocks( - program.parameter_blocks()); - - vector<ParameterBlock*> excluded_parameter_blocks; - sort(all_parameter_blocks.begin(), all_parameter_blocks.end()); - sort(included_parameter_blocks.begin(), included_parameter_blocks.end()); - set_difference(all_parameter_blocks.begin(), - all_parameter_blocks.end(), - included_parameter_blocks.begin(), - included_parameter_blocks.end(), - back_inserter(excluded_parameter_blocks)); - - variable_parameter_blocks.reserve(excluded_parameter_blocks.size()); - for (int i = 0; i < excluded_parameter_blocks.size(); ++i) { - ParameterBlock* parameter_block = excluded_parameter_blocks[i]; - if (!parameter_block->IsConstant()) { - variable_parameter_blocks.push_back(parameter_block); - parameter_block->SetConstant(); - } - } - } - - // Setup the Parameter indices and offsets before an evaluator can - // be constructed and used. - program.SetParameterOffsetsAndIndex(); - - Evaluator::Options evaluator_options; - - // Even though using SPARSE_NORMAL_CHOLESKY requires SuiteSparse or - // CXSparse, here it just being used for telling the evaluator to - // use a SparseRowCompressedMatrix for the jacobian. This is because - // the Evaluator decides the storage for the Jacobian based on the - // type of linear solver being used. - evaluator_options.linear_solver_type = SPARSE_NORMAL_CHOLESKY; -#ifndef CERES_USE_OPENMP - LOG_IF(WARNING, evaluate_options.num_threads > 1) - << "OpenMP support is not compiled into this binary; " - << "only evaluate_options.num_threads = 1 is supported. Switching " - << "to single threaded mode."; - evaluator_options.num_threads = 1; -#else - evaluator_options.num_threads = evaluate_options.num_threads; -#endif // CERES_USE_OPENMP - - string error; - scoped_ptr<Evaluator> evaluator( - Evaluator::Create(evaluator_options, &program, &error)); - if (evaluator.get() == NULL) { - LOG(ERROR) << "Unable to create an Evaluator object. " - << "Error: " << error - << "This is a Ceres bug; please contact the developers!"; - - // Make the parameter blocks that were temporarily marked - // constant, variable again. - for (int i = 0; i < variable_parameter_blocks.size(); ++i) { - variable_parameter_blocks[i]->SetVarying(); - } - - program_->SetParameterBlockStatePtrsToUserStatePtrs(); - program_->SetParameterOffsetsAndIndex(); - return false; - } - - if (residuals !=NULL) { - residuals->resize(evaluator->NumResiduals()); - } - - if (gradient != NULL) { - gradient->resize(evaluator->NumEffectiveParameters()); - } - - scoped_ptr<CompressedRowSparseMatrix> tmp_jacobian; - if (jacobian != NULL) { - tmp_jacobian.reset( - down_cast<CompressedRowSparseMatrix*>(evaluator->CreateJacobian())); - } - - // Point the state pointers to the user state pointers. This is - // needed so that we can extract a parameter vector which is then - // passed to Evaluator::Evaluate. - program.SetParameterBlockStatePtrsToUserStatePtrs(); - - // Copy the value of the parameter blocks into a vector, since the - // Evaluate::Evaluate method needs its input as such. The previous - // call to SetParameterBlockStatePtrsToUserStatePtrs ensures that - // these values are the ones corresponding to the actual state of - // the parameter blocks, rather than the temporary state pointer - // used for evaluation. - Vector parameters(program.NumParameters()); - program.ParameterBlocksToStateVector(parameters.data()); - - double tmp_cost = 0; - - Evaluator::EvaluateOptions evaluator_evaluate_options; - evaluator_evaluate_options.apply_loss_function = - evaluate_options.apply_loss_function; - bool status = evaluator->Evaluate(evaluator_evaluate_options, - parameters.data(), - &tmp_cost, - residuals != NULL ? &(*residuals)[0] : NULL, - gradient != NULL ? &(*gradient)[0] : NULL, - tmp_jacobian.get()); - - // Make the parameter blocks that were temporarily marked constant, - // variable again. - for (int i = 0; i < variable_parameter_blocks.size(); ++i) { - variable_parameter_blocks[i]->SetVarying(); - } - - if (status) { - if (cost != NULL) { - *cost = tmp_cost; - } - if (jacobian != NULL) { - tmp_jacobian->ToCRSMatrix(jacobian); - } - } - - program_->SetParameterBlockStatePtrsToUserStatePtrs(); - program_->SetParameterOffsetsAndIndex(); - return status; -} - -int ProblemImpl::NumParameterBlocks() const { - return program_->NumParameterBlocks(); -} - -int ProblemImpl::NumParameters() const { - return program_->NumParameters(); -} - -int ProblemImpl::NumResidualBlocks() const { - return program_->NumResidualBlocks(); -} - -int ProblemImpl::NumResiduals() const { - return program_->NumResiduals(); -} - -int ProblemImpl::ParameterBlockSize(const double* values) const { - ParameterBlock* parameter_block = - FindWithDefault(parameter_block_map_, const_cast<double*>(values), NULL); - if (parameter_block == NULL) { - LOG(FATAL) << "Parameter block not found: " << values - << ". You must add the parameter block to the problem before " - << "you can get its size."; - } - - return parameter_block->Size(); -} - -int ProblemImpl::ParameterBlockLocalSize(const double* values) const { - ParameterBlock* parameter_block = - FindWithDefault(parameter_block_map_, const_cast<double*>(values), NULL); - if (parameter_block == NULL) { - LOG(FATAL) << "Parameter block not found: " << values - << ". You must add the parameter block to the problem before " - << "you can get its local size."; - } - - return parameter_block->LocalSize(); -} - -bool ProblemImpl::HasParameterBlock(const double* parameter_block) const { - return (parameter_block_map_.find(const_cast<double*>(parameter_block)) != - parameter_block_map_.end()); -} - -void ProblemImpl::GetParameterBlocks(vector<double*>* parameter_blocks) const { - CHECK_NOTNULL(parameter_blocks); - parameter_blocks->resize(0); - for (ParameterMap::const_iterator it = parameter_block_map_.begin(); - it != parameter_block_map_.end(); - ++it) { - parameter_blocks->push_back(it->first); - } -} - -void ProblemImpl::GetResidualBlocks( - vector<ResidualBlockId>* residual_blocks) const { - CHECK_NOTNULL(residual_blocks); - *residual_blocks = program().residual_blocks(); -} - -void ProblemImpl::GetParameterBlocksForResidualBlock( - const ResidualBlockId residual_block, - vector<double*>* parameter_blocks) const { - int num_parameter_blocks = residual_block->NumParameterBlocks(); - CHECK_NOTNULL(parameter_blocks)->resize(num_parameter_blocks); - for (int i = 0; i < num_parameter_blocks; ++i) { - (*parameter_blocks)[i] = - residual_block->parameter_blocks()[i]->mutable_user_state(); - } -} - -const CostFunction* ProblemImpl::GetCostFunctionForResidualBlock( - const ResidualBlockId residual_block) const { - return residual_block->cost_function(); -} - -const LossFunction* ProblemImpl::GetLossFunctionForResidualBlock( - const ResidualBlockId residual_block) const { - return residual_block->loss_function(); -} - -void ProblemImpl::GetResidualBlocksForParameterBlock( - const double* values, - vector<ResidualBlockId>* residual_blocks) const { - ParameterBlock* parameter_block = - FindWithDefault(parameter_block_map_, const_cast<double*>(values), NULL); - if (parameter_block == NULL) { - LOG(FATAL) << "Parameter block not found: " << values - << ". You must add the parameter block to the problem before " - << "you can get the residual blocks that depend on it."; - } - - if (options_.enable_fast_removal) { - // In this case the residual blocks that depend on the parameter block are - // stored in the parameter block already, so just copy them out. - CHECK_NOTNULL(residual_blocks)->resize( - parameter_block->mutable_residual_blocks()->size()); - std::copy(parameter_block->mutable_residual_blocks()->begin(), - parameter_block->mutable_residual_blocks()->end(), - residual_blocks->begin()); - return; - } - - // Find residual blocks that depend on the parameter block. - CHECK_NOTNULL(residual_blocks)->clear(); - const int num_residual_blocks = NumResidualBlocks(); - for (int i = 0; i < num_residual_blocks; ++i) { - ResidualBlock* residual_block = - (*(program_->mutable_residual_blocks()))[i]; - const int num_parameter_blocks = residual_block->NumParameterBlocks(); - for (int j = 0; j < num_parameter_blocks; ++j) { - if (residual_block->parameter_blocks()[j] == parameter_block) { - residual_blocks->push_back(residual_block); - // The parameter blocks are guaranteed unique. - break; - } - } - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/problem_impl.h b/extern/libmv/third_party/ceres/internal/ceres/problem_impl.h deleted file mode 100644 index f42bde6c793..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/problem_impl.h +++ /dev/null @@ -1,226 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// This is the implementation of the public Problem API. The pointer to -// implementation (PIMPL) idiom makes it possible for Ceres internal code to -// refer to the private data members without needing to exposing it to the -// world. An alternative to PIMPL is to have a factory which returns instances -// of a virtual base class; while that approach would work, it requires clients -// to always put a Problem object into a scoped pointer; this needlessly muddies -// client code for little benefit. Therefore, the PIMPL comprise was chosen. - -#ifndef CERES_PUBLIC_PROBLEM_IMPL_H_ -#define CERES_PUBLIC_PROBLEM_IMPL_H_ - -#include <map> -#include <vector> - -#include "ceres/internal/macros.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/collections_port.h" -#include "ceres/problem.h" -#include "ceres/types.h" - -namespace ceres { - -class CostFunction; -class LossFunction; -class LocalParameterization; -struct CRSMatrix; - -namespace internal { - -class Program; -class ResidualBlock; - -class ProblemImpl { - public: - typedef std::map<double*, ParameterBlock*> ParameterMap; - typedef HashSet<ResidualBlock*> ResidualBlockSet; - - ProblemImpl(); - explicit ProblemImpl(const Problem::Options& options); - - ~ProblemImpl(); - - // See the public problem.h file for description of these methods. - ResidualBlockId AddResidualBlock( - CostFunction* cost_function, - LossFunction* loss_function, - const std::vector<double*>& parameter_blocks); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3, double* x4); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3, double* x4, double* x5); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3, double* x4, double* x5, - double* x6); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3, double* x4, double* x5, - double* x6, double* x7); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3, double* x4, double* x5, - double* x6, double* x7, double* x8); - ResidualBlockId AddResidualBlock(CostFunction* cost_function, - LossFunction* loss_function, - double* x0, double* x1, double* x2, - double* x3, double* x4, double* x5, - double* x6, double* x7, double* x8, - double* x9); - void AddParameterBlock(double* values, int size); - void AddParameterBlock(double* values, - int size, - LocalParameterization* local_parameterization); - - void RemoveResidualBlock(ResidualBlock* residual_block); - void RemoveParameterBlock(double* values); - - void SetParameterBlockConstant(double* values); - void SetParameterBlockVariable(double* values); - void SetParameterization(double* values, - LocalParameterization* local_parameterization); - const LocalParameterization* GetParameterization(double* values) const; - - void SetParameterLowerBound(double* values, int index, double lower_bound); - void SetParameterUpperBound(double* values, int index, double upper_bound); - - bool Evaluate(const Problem::EvaluateOptions& options, - double* cost, - std::vector<double>* residuals, - std::vector<double>* gradient, - CRSMatrix* jacobian); - - int NumParameterBlocks() const; - int NumParameters() const; - int NumResidualBlocks() const; - int NumResiduals() const; - - int ParameterBlockSize(const double* parameter_block) const; - int ParameterBlockLocalSize(const double* parameter_block) const; - - bool HasParameterBlock(const double* parameter_block) const; - - void GetParameterBlocks(std::vector<double*>* parameter_blocks) const; - void GetResidualBlocks(std::vector<ResidualBlockId>* residual_blocks) const; - - void GetParameterBlocksForResidualBlock( - const ResidualBlockId residual_block, - std::vector<double*>* parameter_blocks) const; - - const CostFunction* GetCostFunctionForResidualBlock( - const ResidualBlockId residual_block) const; - const LossFunction* GetLossFunctionForResidualBlock( - const ResidualBlockId residual_block) const; - - void GetResidualBlocksForParameterBlock( - const double* values, - std::vector<ResidualBlockId>* residual_blocks) const; - - const Program& program() const { return *program_; } - Program* mutable_program() { return program_.get(); } - - const ParameterMap& parameter_map() const { return parameter_block_map_; } - const ResidualBlockSet& residual_block_set() const { - CHECK(options_.enable_fast_removal) - << "Fast removal not enabled, residual_block_set is not maintained."; - return residual_block_set_; - } - - private: - ParameterBlock* InternalAddParameterBlock(double* values, int size); - void InternalRemoveResidualBlock(ResidualBlock* residual_block); - - bool InternalEvaluate(Program* program, - double* cost, - std::vector<double>* residuals, - std::vector<double>* gradient, - CRSMatrix* jacobian); - - // Delete the arguments in question. These differ from the Remove* functions - // in that they do not clean up references to the block to delete; they - // merely delete them. - template<typename Block> - void DeleteBlockInVector(std::vector<Block*>* mutable_blocks, - Block* block_to_remove); - void DeleteBlock(ResidualBlock* residual_block); - void DeleteBlock(ParameterBlock* parameter_block); - - const Problem::Options options_; - - // The mapping from user pointers to parameter blocks. - std::map<double*, ParameterBlock*> parameter_block_map_; - - // Iff enable_fast_removal is enabled, contains the current residual blocks. - ResidualBlockSet residual_block_set_; - - // The actual parameter and residual blocks. - internal::scoped_ptr<internal::Program> program_; - - // When removing residual and parameter blocks, cost/loss functions and - // parameterizations have ambiguous ownership. Instead of scanning the entire - // problem to see if the cost/loss/parameterization is shared with other - // residual or parameter blocks, buffer them until destruction. - // - // TODO(keir): See if it makes sense to use sets instead. - std::vector<CostFunction*> cost_functions_to_delete_; - std::vector<LossFunction*> loss_functions_to_delete_; - std::vector<LocalParameterization*> local_parameterizations_to_delete_; - - CERES_DISALLOW_COPY_AND_ASSIGN(ProblemImpl); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_PUBLIC_PROBLEM_IMPL_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/program.cc b/extern/libmv/third_party/ceres/internal/ceres/program.cc deleted file mode 100644 index 8e97f072113..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/program.cc +++ /dev/null @@ -1,524 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#include "ceres/program.h" - -#include <map> -#include <vector> -#include "ceres/array_utils.h" -#include "ceres/casts.h" -#include "ceres/compressed_row_sparse_matrix.h" -#include "ceres/cost_function.h" -#include "ceres/evaluator.h" -#include "ceres/internal/port.h" -#include "ceres/local_parameterization.h" -#include "ceres/loss_function.h" -#include "ceres/map_util.h" -#include "ceres/parameter_block.h" -#include "ceres/problem.h" -#include "ceres/residual_block.h" -#include "ceres/stl_util.h" -#include "ceres/triplet_sparse_matrix.h" - -namespace ceres { -namespace internal { - -using std::max; -using std::set; -using std::string; -using std::vector; - -Program::Program() {} - -Program::Program(const Program& program) - : parameter_blocks_(program.parameter_blocks_), - residual_blocks_(program.residual_blocks_) { -} - -const vector<ParameterBlock*>& Program::parameter_blocks() const { - return parameter_blocks_; -} - -const vector<ResidualBlock*>& Program::residual_blocks() const { - return residual_blocks_; -} - -vector<ParameterBlock*>* Program::mutable_parameter_blocks() { - return ¶meter_blocks_; -} - -vector<ResidualBlock*>* Program::mutable_residual_blocks() { - return &residual_blocks_; -} - -bool Program::StateVectorToParameterBlocks(const double *state) { - for (int i = 0; i < parameter_blocks_.size(); ++i) { - if (!parameter_blocks_[i]->IsConstant() && - !parameter_blocks_[i]->SetState(state)) { - return false; - } - state += parameter_blocks_[i]->Size(); - } - return true; -} - -void Program::ParameterBlocksToStateVector(double *state) const { - for (int i = 0; i < parameter_blocks_.size(); ++i) { - parameter_blocks_[i]->GetState(state); - state += parameter_blocks_[i]->Size(); - } -} - -void Program::CopyParameterBlockStateToUserState() { - for (int i = 0; i < parameter_blocks_.size(); ++i) { - parameter_blocks_[i]->GetState(parameter_blocks_[i]->mutable_user_state()); - } -} - -bool Program::SetParameterBlockStatePtrsToUserStatePtrs() { - for (int i = 0; i < parameter_blocks_.size(); ++i) { - if (!parameter_blocks_[i]->IsConstant() && - !parameter_blocks_[i]->SetState(parameter_blocks_[i]->user_state())) { - return false; - } - } - return true; -} - -bool Program::Plus(const double* state, - const double* delta, - double* state_plus_delta) const { - for (int i = 0; i < parameter_blocks_.size(); ++i) { - if (!parameter_blocks_[i]->Plus(state, delta, state_plus_delta)) { - return false; - } - state += parameter_blocks_[i]->Size(); - delta += parameter_blocks_[i]->LocalSize(); - state_plus_delta += parameter_blocks_[i]->Size(); - } - return true; -} - -void Program::SetParameterOffsetsAndIndex() { - // Set positions for all parameters appearing as arguments to residuals to one - // past the end of the parameter block array. - for (int i = 0; i < residual_blocks_.size(); ++i) { - ResidualBlock* residual_block = residual_blocks_[i]; - for (int j = 0; j < residual_block->NumParameterBlocks(); ++j) { - residual_block->parameter_blocks()[j]->set_index(-1); - } - } - // For parameters that appear in the program, set their position and offset. - int state_offset = 0; - int delta_offset = 0; - for (int i = 0; i < parameter_blocks_.size(); ++i) { - parameter_blocks_[i]->set_index(i); - parameter_blocks_[i]->set_state_offset(state_offset); - parameter_blocks_[i]->set_delta_offset(delta_offset); - state_offset += parameter_blocks_[i]->Size(); - delta_offset += parameter_blocks_[i]->LocalSize(); - } -} - -bool Program::IsValid() const { - for (int i = 0; i < residual_blocks_.size(); ++i) { - const ResidualBlock* residual_block = residual_blocks_[i]; - if (residual_block->index() != i) { - LOG(WARNING) << "Residual block: " << i - << " has incorrect index: " << residual_block->index(); - return false; - } - } - - int state_offset = 0; - int delta_offset = 0; - for (int i = 0; i < parameter_blocks_.size(); ++i) { - const ParameterBlock* parameter_block = parameter_blocks_[i]; - if (parameter_block->index() != i || - parameter_block->state_offset() != state_offset || - parameter_block->delta_offset() != delta_offset) { - LOG(WARNING) << "Parameter block: " << i - << "has incorrect indexing information: " - << parameter_block->ToString(); - return false; - } - - state_offset += parameter_blocks_[i]->Size(); - delta_offset += parameter_blocks_[i]->LocalSize(); - } - - return true; -} - -bool Program::ParameterBlocksAreFinite(string* message) const { - CHECK_NOTNULL(message); - for (int i = 0; i < parameter_blocks_.size(); ++i) { - const ParameterBlock* parameter_block = parameter_blocks_[i]; - const double* array = parameter_block->user_state(); - const int size = parameter_block->Size(); - const int invalid_index = FindInvalidValue(size, array); - if (invalid_index != size) { - *message = StringPrintf( - "ParameterBlock: %p with size %d has at least one invalid value.\n" - "First invalid value is at index: %d.\n" - "Parameter block values: ", - array, size, invalid_index); - AppendArrayToString(size, array, message); - return false; - } - } - return true; -} - -bool Program::IsBoundsConstrained() const { - for (int i = 0; i < parameter_blocks_.size(); ++i) { - const ParameterBlock* parameter_block = parameter_blocks_[i]; - if (parameter_block->IsConstant()) { - continue; - } - const int size = parameter_block->Size(); - for (int j = 0; j < size; ++j) { - const double lower_bound = parameter_block->LowerBoundForParameter(j); - const double upper_bound = parameter_block->UpperBoundForParameter(j); - if (lower_bound > -std::numeric_limits<double>::max() || - upper_bound < std::numeric_limits<double>::max()) { - return true; - } - } - } - return false; -} - -bool Program::IsFeasible(string* message) const { - CHECK_NOTNULL(message); - for (int i = 0; i < parameter_blocks_.size(); ++i) { - const ParameterBlock* parameter_block = parameter_blocks_[i]; - const double* parameters = parameter_block->user_state(); - const int size = parameter_block->Size(); - if (parameter_block->IsConstant()) { - // Constant parameter blocks must start in the feasible region - // to ultimately produce a feasible solution, since Ceres cannot - // change them. - for (int j = 0; j < size; ++j) { - const double lower_bound = parameter_block->LowerBoundForParameter(j); - const double upper_bound = parameter_block->UpperBoundForParameter(j); - if (parameters[j] < lower_bound || parameters[j] > upper_bound) { - *message = StringPrintf( - "ParameterBlock: %p with size %d has at least one infeasible " - "value." - "\nFirst infeasible value is at index: %d." - "\nLower bound: %e, value: %e, upper bound: %e" - "\nParameter block values: ", - parameters, size, j, lower_bound, parameters[j], upper_bound); - AppendArrayToString(size, parameters, message); - return false; - } - } - } else { - // Variable parameter blocks must have non-empty feasible - // regions, otherwise there is no way to produce a feasible - // solution. - for (int j = 0; j < size; ++j) { - const double lower_bound = parameter_block->LowerBoundForParameter(j); - const double upper_bound = parameter_block->UpperBoundForParameter(j); - if (lower_bound >= upper_bound) { - *message = StringPrintf( - "ParameterBlock: %p with size %d has at least one infeasible " - "bound." - "\nFirst infeasible bound is at index: %d." - "\nLower bound: %e, upper bound: %e" - "\nParameter block values: ", - parameters, size, j, lower_bound, upper_bound); - AppendArrayToString(size, parameters, message); - return false; - } - } - } - } - - return true; -} - -Program* Program::CreateReducedProgram( - vector<double*>* removed_parameter_blocks, - double* fixed_cost, - string* error) const { - CHECK_NOTNULL(removed_parameter_blocks); - CHECK_NOTNULL(fixed_cost); - CHECK_NOTNULL(error); - - scoped_ptr<Program> reduced_program(new Program(*this)); - if (!reduced_program->RemoveFixedBlocks(removed_parameter_blocks, - fixed_cost, - error)) { - return NULL; - } - - reduced_program->SetParameterOffsetsAndIndex(); - return reduced_program.release(); -} - -bool Program::RemoveFixedBlocks(vector<double*>* removed_parameter_blocks, - double* fixed_cost, - string* error) { - CHECK_NOTNULL(removed_parameter_blocks); - CHECK_NOTNULL(fixed_cost); - CHECK_NOTNULL(error); - - scoped_array<double> residual_block_evaluate_scratch; - residual_block_evaluate_scratch.reset( - new double[MaxScratchDoublesNeededForEvaluate()]); - *fixed_cost = 0.0; - - // Mark all the parameters as unused. Abuse the index member of the - // parameter blocks for the marking. - for (int i = 0; i < parameter_blocks_.size(); ++i) { - parameter_blocks_[i]->set_index(-1); - } - - // Filter out residual that have all-constant parameters, and mark - // all the parameter blocks that appear in residuals. - int num_active_residual_blocks = 0; - for (int i = 0; i < residual_blocks_.size(); ++i) { - ResidualBlock* residual_block = residual_blocks_[i]; - int num_parameter_blocks = residual_block->NumParameterBlocks(); - - // Determine if the residual block is fixed, and also mark varying - // parameters that appear in the residual block. - bool all_constant = true; - for (int k = 0; k < num_parameter_blocks; k++) { - ParameterBlock* parameter_block = residual_block->parameter_blocks()[k]; - if (!parameter_block->IsConstant()) { - all_constant = false; - parameter_block->set_index(1); - } - } - - if (!all_constant) { - residual_blocks_[num_active_residual_blocks++] = residual_block; - continue; - } - - // The residual is constant and will be removed, so its cost is - // added to the variable fixed_cost. - double cost = 0.0; - if (!residual_block->Evaluate(true, - &cost, - NULL, - NULL, - residual_block_evaluate_scratch.get())) { - *error = StringPrintf("Evaluation of the residual %d failed during " - "removal of fixed residual blocks.", i); - return false; - } - *fixed_cost += cost; - } - residual_blocks_.resize(num_active_residual_blocks); - - // Filter out unused or fixed parameter blocks. - int num_active_parameter_blocks = 0; - removed_parameter_blocks->clear(); - for (int i = 0; i < parameter_blocks_.size(); ++i) { - ParameterBlock* parameter_block = parameter_blocks_[i]; - if (parameter_block->index() == -1) { - removed_parameter_blocks->push_back( - parameter_block->mutable_user_state()); - } else { - parameter_blocks_[num_active_parameter_blocks++] = parameter_block; - } - } - parameter_blocks_.resize(num_active_parameter_blocks); - - if (!(((NumResidualBlocks() == 0) && - (NumParameterBlocks() == 0)) || - ((NumResidualBlocks() != 0) && - (NumParameterBlocks() != 0)))) { - *error = "Congratulations, you found a bug in Ceres. Please report it."; - return false; - } - - return true; -} - -bool Program::IsParameterBlockSetIndependent( - const set<double*>& independent_set) const { - // Loop over each residual block and ensure that no two parameter - // blocks in the same residual block are part of - // parameter_block_ptrs as that would violate the assumption that it - // is an independent set in the Hessian matrix. - for (vector<ResidualBlock*>::const_iterator it = residual_blocks_.begin(); - it != residual_blocks_.end(); - ++it) { - ParameterBlock* const* parameter_blocks = (*it)->parameter_blocks(); - const int num_parameter_blocks = (*it)->NumParameterBlocks(); - int count = 0; - for (int i = 0; i < num_parameter_blocks; ++i) { - count += independent_set.count( - parameter_blocks[i]->mutable_user_state()); - } - if (count > 1) { - return false; - } - } - return true; -} - -TripletSparseMatrix* Program::CreateJacobianBlockSparsityTranspose() const { - // Matrix to store the block sparsity structure of the Jacobian. - TripletSparseMatrix* tsm = - new TripletSparseMatrix(NumParameterBlocks(), - NumResidualBlocks(), - 10 * NumResidualBlocks()); - int num_nonzeros = 0; - int* rows = tsm->mutable_rows(); - int* cols = tsm->mutable_cols(); - double* values = tsm->mutable_values(); - - for (int c = 0; c < residual_blocks_.size(); ++c) { - const ResidualBlock* residual_block = residual_blocks_[c]; - const int num_parameter_blocks = residual_block->NumParameterBlocks(); - ParameterBlock* const* parameter_blocks = - residual_block->parameter_blocks(); - - for (int j = 0; j < num_parameter_blocks; ++j) { - if (parameter_blocks[j]->IsConstant()) { - continue; - } - - // Re-size the matrix if needed. - if (num_nonzeros >= tsm->max_num_nonzeros()) { - tsm->set_num_nonzeros(num_nonzeros); - tsm->Reserve(2 * num_nonzeros); - rows = tsm->mutable_rows(); - cols = tsm->mutable_cols(); - values = tsm->mutable_values(); - } - - const int r = parameter_blocks[j]->index(); - rows[num_nonzeros] = r; - cols[num_nonzeros] = c; - values[num_nonzeros] = 1.0; - ++num_nonzeros; - } - } - - tsm->set_num_nonzeros(num_nonzeros); - return tsm; -} - -int Program::NumResidualBlocks() const { - return residual_blocks_.size(); -} - -int Program::NumParameterBlocks() const { - return parameter_blocks_.size(); -} - -int Program::NumResiduals() const { - int num_residuals = 0; - for (int i = 0; i < residual_blocks_.size(); ++i) { - num_residuals += residual_blocks_[i]->NumResiduals(); - } - return num_residuals; -} - -int Program::NumParameters() const { - int num_parameters = 0; - for (int i = 0; i < parameter_blocks_.size(); ++i) { - num_parameters += parameter_blocks_[i]->Size(); - } - return num_parameters; -} - -int Program::NumEffectiveParameters() const { - int num_parameters = 0; - for (int i = 0; i < parameter_blocks_.size(); ++i) { - num_parameters += parameter_blocks_[i]->LocalSize(); - } - return num_parameters; -} - -int Program::MaxScratchDoublesNeededForEvaluate() const { - // Compute the scratch space needed for evaluate. - int max_scratch_bytes_for_evaluate = 0; - for (int i = 0; i < residual_blocks_.size(); ++i) { - max_scratch_bytes_for_evaluate = - max(max_scratch_bytes_for_evaluate, - residual_blocks_[i]->NumScratchDoublesForEvaluate()); - } - return max_scratch_bytes_for_evaluate; -} - -int Program::MaxDerivativesPerResidualBlock() const { - int max_derivatives = 0; - for (int i = 0; i < residual_blocks_.size(); ++i) { - int derivatives = 0; - ResidualBlock* residual_block = residual_blocks_[i]; - int num_parameters = residual_block->NumParameterBlocks(); - for (int j = 0; j < num_parameters; ++j) { - derivatives += residual_block->NumResiduals() * - residual_block->parameter_blocks()[j]->LocalSize(); - } - max_derivatives = max(max_derivatives, derivatives); - } - return max_derivatives; -} - -int Program::MaxParametersPerResidualBlock() const { - int max_parameters = 0; - for (int i = 0; i < residual_blocks_.size(); ++i) { - max_parameters = max(max_parameters, - residual_blocks_[i]->NumParameterBlocks()); - } - return max_parameters; -} - -int Program::MaxResidualsPerResidualBlock() const { - int max_residuals = 0; - for (int i = 0; i < residual_blocks_.size(); ++i) { - max_residuals = max(max_residuals, residual_blocks_[i]->NumResiduals()); - } - return max_residuals; -} - -string Program::ToString() const { - string ret = "Program dump\n"; - ret += StringPrintf("Number of parameter blocks: %d\n", NumParameterBlocks()); - ret += StringPrintf("Number of parameters: %d\n", NumParameters()); - ret += "Parameters:\n"; - for (int i = 0; i < parameter_blocks_.size(); ++i) { - ret += StringPrintf("%d: %s\n", - i, parameter_blocks_[i]->ToString().c_str()); - } - return ret; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/program.h b/extern/libmv/third_party/ceres/internal/ceres/program.h deleted file mode 100644 index 38c958fe34a..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/program.h +++ /dev/null @@ -1,192 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#ifndef CERES_INTERNAL_PROGRAM_H_ -#define CERES_INTERNAL_PROGRAM_H_ - -#include <set> -#include <string> -#include <vector> -#include "ceres/internal/port.h" - -namespace ceres { -namespace internal { - -class ParameterBlock; -class ProblemImpl; -class ResidualBlock; -class TripletSparseMatrix; - -// A nonlinear least squares optimization problem. This is different from the -// similarly-named "Problem" object, which offers a mutation interface for -// adding and modifying parameters and residuals. The Program contains the core -// part of the Problem, which is the parameters and the residuals, stored in a -// particular ordering. The ordering is critical, since it defines the mapping -// between (residual, parameter) pairs and a position in the jacobian of the -// objective function. Various parts of Ceres transform one Program into -// another; for example, the first stage of solving involves stripping all -// constant parameters and residuals. This is in contrast with Problem, which is -// not built for transformation. -class Program { - public: - Program(); - explicit Program(const Program& program); - - // The ordered parameter and residual blocks for the program. - const std::vector<ParameterBlock*>& parameter_blocks() const; - const std::vector<ResidualBlock*>& residual_blocks() const; - std::vector<ParameterBlock*>* mutable_parameter_blocks(); - std::vector<ResidualBlock*>* mutable_residual_blocks(); - - // Serialize to/from the program and update states. - // - // NOTE: Setting the state of a parameter block can trigger the - // computation of the Jacobian of its local parameterization. If - // this computation fails for some reason, then this method returns - // false and the state of the parameter blocks cannot be trusted. - bool StateVectorToParameterBlocks(const double *state); - void ParameterBlocksToStateVector(double *state) const; - - // Copy internal state to the user's parameters. - void CopyParameterBlockStateToUserState(); - - // Set the parameter block pointers to the user pointers. Since this - // runs parameter block set state internally, which may call local - // parameterizations, this can fail. False is returned on failure. - bool SetParameterBlockStatePtrsToUserStatePtrs(); - - // Update a state vector for the program given a delta. - bool Plus(const double* state, - const double* delta, - double* state_plus_delta) const; - - // Set the parameter indices and offsets. This permits mapping backward - // from a ParameterBlock* to an index in the parameter_blocks() vector. For - // any parameter block p, after calling SetParameterOffsetsAndIndex(), it - // is true that - // - // parameter_blocks()[p->index()] == p - // - // If a parameter appears in a residual but not in the parameter block, then - // it will have an index of -1. - // - // This also updates p->state_offset() and p->delta_offset(), which are the - // position of the parameter in the state and delta vector respectively. - void SetParameterOffsetsAndIndex(); - - // Check if the internal state of the program (the indexing and the - // offsets) are correct. - bool IsValid() const; - - bool ParameterBlocksAreFinite(std::string* message) const; - - // Returns true if the program has any non-constant parameter blocks - // which have non-trivial bounds constraints. - bool IsBoundsConstrained() const; - - // Returns false, if the program has any constant parameter blocks - // which are not feasible, or any variable parameter blocks which - // have a lower bound greater than or equal to the upper bound. - bool IsFeasible(std::string* message) const; - - // Loop over each residual block and ensure that no two parameter - // blocks in the same residual block are part of - // parameter_blocks as that would violate the assumption that it - // is an independent set in the Hessian matrix. - bool IsParameterBlockSetIndependent( - const std::set<double*>& independent_set) const; - - // Create a TripletSparseMatrix which contains the zero-one - // structure corresponding to the block sparsity of the transpose of - // the Jacobian matrix. - // - // Caller owns the result. - TripletSparseMatrix* CreateJacobianBlockSparsityTranspose() const; - - // Create a copy of this program and removes constant parameter - // blocks and residual blocks with no varying parameter blocks while - // preserving their relative order. - // - // removed_parameter_blocks on exit will contain the list of - // parameter blocks that were removed. - // - // fixed_cost will be equal to the sum of the costs of the residual - // blocks that were removed. - // - // If there was a problem, then the function will return a NULL - // pointer and error will contain a human readable description of - // the problem. - Program* CreateReducedProgram(std::vector<double*>* removed_parameter_blocks, - double* fixed_cost, - std::string* error) const; - - // See problem.h for what these do. - int NumParameterBlocks() const; - int NumParameters() const; - int NumEffectiveParameters() const; - int NumResidualBlocks() const; - int NumResiduals() const; - - int MaxScratchDoublesNeededForEvaluate() const; - int MaxDerivativesPerResidualBlock() const; - int MaxParametersPerResidualBlock() const; - int MaxResidualsPerResidualBlock() const; - - // A human-readable dump of the parameter blocks for debugging. - // TODO(keir): If necessary, also dump the residual blocks. - std::string ToString() const; - - private: - // Remove constant parameter blocks and residual blocks with no - // varying parameter blocks while preserving their relative order. - // - // removed_parameter_blocks on exit will contain the list of - // parameter blocks that were removed. - // - // fixed_cost will be equal to the sum of the costs of the residual - // blocks that were removed. - // - // If there was a problem, then the function will return false and - // error will contain a human readable description of the problem. - bool RemoveFixedBlocks(std::vector<double*>* removed_parameter_blocks, - double* fixed_cost, - std::string* message); - - // The Program does not own the ParameterBlock or ResidualBlock objects. - std::vector<ParameterBlock*> parameter_blocks_; - std::vector<ResidualBlock*> residual_blocks_; - - friend class ProblemImpl; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_PROGRAM_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/program_evaluator.h b/extern/libmv/third_party/ceres/internal/ceres/program_evaluator.h deleted file mode 100644 index 74a812adeef..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/program_evaluator.h +++ /dev/null @@ -1,384 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// The ProgramEvaluator runs the cost functions contained in each residual block -// and stores the result into a jacobian. The particular type of jacobian is -// abstracted out using two template parameters: -// -// - An "EvaluatePreparer" that is responsible for creating the array with -// pointers to the jacobian blocks where the cost function evaluates to. -// - A "JacobianWriter" that is responsible for storing the resulting -// jacobian blocks in the passed sparse matrix. -// -// This abstraction affords an efficient evaluator implementation while still -// supporting writing to multiple sparse matrix formats. For example, when the -// ProgramEvaluator is parameterized for writing to block sparse matrices, the -// residual jacobians are written directly into their final position in the -// block sparse matrix by the user's CostFunction; there is no copying. -// -// The evaluation is threaded with OpenMP. -// -// The EvaluatePreparer and JacobianWriter interfaces are as follows: -// -// class EvaluatePreparer { -// // Prepare the jacobians array for use as the destination of a call to -// // a cost function's evaluate method. -// void Prepare(const ResidualBlock* residual_block, -// int residual_block_index, -// SparseMatrix* jacobian, -// double** jacobians); -// } -// -// class JacobianWriter { -// // Create a jacobian that this writer can write. Same as -// // Evaluator::CreateJacobian. -// SparseMatrix* CreateJacobian() const; -// -// // Create num_threads evaluate preparers. Caller owns result which must -// // be freed with delete[]. Resulting preparers are valid while *this is. -// EvaluatePreparer* CreateEvaluatePreparers(int num_threads); -// -// // Write the block jacobians from a residual block evaluation to the -// // larger sparse jacobian. -// void Write(int residual_id, -// int residual_offset, -// double** jacobians, -// SparseMatrix* jacobian); -// } -// -// Note: The ProgramEvaluator is not thread safe, since internally it maintains -// some per-thread scratch space. - -#ifndef CERES_INTERNAL_PROGRAM_EVALUATOR_H_ -#define CERES_INTERNAL_PROGRAM_EVALUATOR_H_ - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifdef CERES_USE_OPENMP -#include <omp.h> -#endif - -#include <map> -#include <string> -#include <vector> -#include "ceres/execution_summary.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/parameter_block.h" -#include "ceres/program.h" -#include "ceres/residual_block.h" -#include "ceres/small_blas.h" - -namespace ceres { -namespace internal { - -struct NullJacobianFinalizer { - void operator()(SparseMatrix* jacobian, int num_parameters) {} -}; - -template<typename EvaluatePreparer, - typename JacobianWriter, - typename JacobianFinalizer = NullJacobianFinalizer> -class ProgramEvaluator : public Evaluator { - public: - ProgramEvaluator(const Evaluator::Options &options, Program* program) - : options_(options), - program_(program), - jacobian_writer_(options, program), - evaluate_preparers_( - jacobian_writer_.CreateEvaluatePreparers(options.num_threads)) { -#ifndef CERES_USE_OPENMP - if (options_.num_threads > 1) { - LOG(WARNING) - << "OpenMP support is not compiled into this binary; " - << "only options.num_threads = 1 is supported. Switching " - << "to single threaded mode."; - options_.num_threads = 1; - } -#endif - - BuildResidualLayout(*program, &residual_layout_); - evaluate_scratch_.reset(CreateEvaluatorScratch(*program, - options.num_threads)); - } - - // Implementation of Evaluator interface. - SparseMatrix* CreateJacobian() const { - return jacobian_writer_.CreateJacobian(); - } - - bool Evaluate(const Evaluator::EvaluateOptions& evaluate_options, - const double* state, - double* cost, - double* residuals, - double* gradient, - SparseMatrix* jacobian) { - ScopedExecutionTimer total_timer("Evaluator::Total", &execution_summary_); - ScopedExecutionTimer call_type_timer(gradient == NULL && jacobian == NULL - ? "Evaluator::Residual" - : "Evaluator::Jacobian", - &execution_summary_); - - // The parameters are stateful, so set the state before evaluating. - if (!program_->StateVectorToParameterBlocks(state)) { - return false; - } - - if (residuals != NULL) { - VectorRef(residuals, program_->NumResiduals()).setZero(); - } - - if (jacobian != NULL) { - jacobian->SetZero(); - } - - // Each thread gets it's own cost and evaluate scratch space. - for (int i = 0; i < options_.num_threads; ++i) { - evaluate_scratch_[i].cost = 0.0; - if (gradient != NULL) { - VectorRef(evaluate_scratch_[i].gradient.get(), - program_->NumEffectiveParameters()).setZero(); - } - } - - // This bool is used to disable the loop if an error is encountered - // without breaking out of it. The remaining loop iterations are still run, - // but with an empty body, and so will finish quickly. - bool abort = false; - int num_residual_blocks = program_->NumResidualBlocks(); -#pragma omp parallel for num_threads(options_.num_threads) - for (int i = 0; i < num_residual_blocks; ++i) { -// Disable the loop instead of breaking, as required by OpenMP. -#pragma omp flush(abort) - if (abort) { - continue; - } - -#ifdef CERES_USE_OPENMP - int thread_id = omp_get_thread_num(); -#else - int thread_id = 0; -#endif - EvaluatePreparer* preparer = &evaluate_preparers_[thread_id]; - EvaluateScratch* scratch = &evaluate_scratch_[thread_id]; - - // Prepare block residuals if requested. - const ResidualBlock* residual_block = program_->residual_blocks()[i]; - double* block_residuals = NULL; - if (residuals != NULL) { - block_residuals = residuals + residual_layout_[i]; - } else if (gradient != NULL) { - block_residuals = scratch->residual_block_residuals.get(); - } - - // Prepare block jacobians if requested. - double** block_jacobians = NULL; - if (jacobian != NULL || gradient != NULL) { - preparer->Prepare(residual_block, - i, - jacobian, - scratch->jacobian_block_ptrs.get()); - block_jacobians = scratch->jacobian_block_ptrs.get(); - } - - // Evaluate the cost, residuals, and jacobians. - double block_cost; - if (!residual_block->Evaluate( - evaluate_options.apply_loss_function, - &block_cost, - block_residuals, - block_jacobians, - scratch->residual_block_evaluate_scratch.get())) { - abort = true; -// This ensures that the OpenMP threads have a consistent view of 'abort'. Do -// the flush inside the failure case so that there is usually only one -// synchronization point per loop iteration instead of two. -#pragma omp flush(abort) - continue; - } - - scratch->cost += block_cost; - - // Store the jacobians, if they were requested. - if (jacobian != NULL) { - jacobian_writer_.Write(i, - residual_layout_[i], - block_jacobians, - jacobian); - } - - // Compute and store the gradient, if it was requested. - if (gradient != NULL) { - int num_residuals = residual_block->NumResiduals(); - int num_parameter_blocks = residual_block->NumParameterBlocks(); - for (int j = 0; j < num_parameter_blocks; ++j) { - const ParameterBlock* parameter_block = - residual_block->parameter_blocks()[j]; - if (parameter_block->IsConstant()) { - continue; - } - - MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>( - block_jacobians[j], - num_residuals, - parameter_block->LocalSize(), - block_residuals, - scratch->gradient.get() + parameter_block->delta_offset()); - } - } - } - - if (!abort) { - const int num_parameters = program_->NumEffectiveParameters(); - - // Sum the cost and gradient (if requested) from each thread. - (*cost) = 0.0; - if (gradient != NULL) { - VectorRef(gradient, num_parameters).setZero(); - } - for (int i = 0; i < options_.num_threads; ++i) { - (*cost) += evaluate_scratch_[i].cost; - if (gradient != NULL) { - VectorRef(gradient, num_parameters) += - VectorRef(evaluate_scratch_[i].gradient.get(), num_parameters); - } - } - - // Finalize the Jacobian if it is available. - // `num_parameters` is passed to the finalizer so that additional - // storage can be reserved for additional diagonal elements if - // necessary. - if (jacobian != NULL) { - JacobianFinalizer f; - f(jacobian, num_parameters); - } - } - return !abort; - } - - bool Plus(const double* state, - const double* delta, - double* state_plus_delta) const { - return program_->Plus(state, delta, state_plus_delta); - } - - int NumParameters() const { - return program_->NumParameters(); - } - int NumEffectiveParameters() const { - return program_->NumEffectiveParameters(); - } - - int NumResiduals() const { - return program_->NumResiduals(); - } - - virtual std::map<std::string, int> CallStatistics() const { - return execution_summary_.calls(); - } - - virtual std::map<std::string, double> TimeStatistics() const { - return execution_summary_.times(); - } - - private: - // Per-thread scratch space needed to evaluate and store each residual block. - struct EvaluateScratch { - void Init(int max_parameters_per_residual_block, - int max_scratch_doubles_needed_for_evaluate, - int max_residuals_per_residual_block, - int num_parameters) { - residual_block_evaluate_scratch.reset( - new double[max_scratch_doubles_needed_for_evaluate]); - gradient.reset(new double[num_parameters]); - VectorRef(gradient.get(), num_parameters).setZero(); - residual_block_residuals.reset( - new double[max_residuals_per_residual_block]); - jacobian_block_ptrs.reset( - new double*[max_parameters_per_residual_block]); - } - - double cost; - scoped_array<double> residual_block_evaluate_scratch; - // The gradient in the local parameterization. - scoped_array<double> gradient; - // Enough space to store the residual for the largest residual block. - scoped_array<double> residual_block_residuals; - scoped_array<double*> jacobian_block_ptrs; - }; - - static void BuildResidualLayout(const Program& program, - std::vector<int>* residual_layout) { - const std::vector<ResidualBlock*>& residual_blocks = - program.residual_blocks(); - residual_layout->resize(program.NumResidualBlocks()); - int residual_pos = 0; - for (int i = 0; i < residual_blocks.size(); ++i) { - const int num_residuals = residual_blocks[i]->NumResiduals(); - (*residual_layout)[i] = residual_pos; - residual_pos += num_residuals; - } - } - - // Create scratch space for each thread evaluating the program. - static EvaluateScratch* CreateEvaluatorScratch(const Program& program, - int num_threads) { - int max_parameters_per_residual_block = - program.MaxParametersPerResidualBlock(); - int max_scratch_doubles_needed_for_evaluate = - program.MaxScratchDoublesNeededForEvaluate(); - int max_residuals_per_residual_block = - program.MaxResidualsPerResidualBlock(); - int num_parameters = program.NumEffectiveParameters(); - - EvaluateScratch* evaluate_scratch = new EvaluateScratch[num_threads]; - for (int i = 0; i < num_threads; i++) { - evaluate_scratch[i].Init(max_parameters_per_residual_block, - max_scratch_doubles_needed_for_evaluate, - max_residuals_per_residual_block, - num_parameters); - } - return evaluate_scratch; - } - - Evaluator::Options options_; - Program* program_; - JacobianWriter jacobian_writer_; - scoped_array<EvaluatePreparer> evaluate_preparers_; - scoped_array<EvaluateScratch> evaluate_scratch_; - std::vector<int> residual_layout_; - ::ceres::internal::ExecutionSummary execution_summary_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_PROGRAM_EVALUATOR_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/random.h b/extern/libmv/third_party/ceres/internal/ceres/random.h deleted file mode 100644 index 2a025600609..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/random.h +++ /dev/null @@ -1,70 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_RANDOM_H_ -#define CERES_INTERNAL_RANDOM_H_ - -#include <cmath> -#include <cstdlib> -#include "ceres/internal/port.h" - -namespace ceres { - -inline void SetRandomState(int state) { - srand(state); -} - -inline int Uniform(int n) { - return rand() % n; -} - -inline double RandDouble() { - double r = static_cast<double>(rand()); - return r / RAND_MAX; -} - -// Box-Muller algorithm for normal random number generation. -// http://en.wikipedia.org/wiki/Box-Muller_transform -inline double RandNormal() { - double x1, x2, w; - do { - x1 = 2.0 * RandDouble() - 1.0; - x2 = 2.0 * RandDouble() - 1.0; - w = x1 * x1 + x2 * x2; - } while ( w >= 1.0 || w == 0.0 ); - - w = sqrt((-2.0 * log(w)) / w); - return x1 * w; -} - -} // namespace ceres - -#endif // CERES_INTERNAL_RANDOM_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/reorder_program.cc b/extern/libmv/third_party/ceres/internal/ceres/reorder_program.cc deleted file mode 100644 index d0e8f32b3b7..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/reorder_program.cc +++ /dev/null @@ -1,596 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/reorder_program.h" - -#include <algorithm> -#include <numeric> -#include <vector> - -#include "ceres/cxsparse.h" -#include "ceres/internal/port.h" -#include "ceres/ordered_groups.h" -#include "ceres/parameter_block.h" -#include "ceres/parameter_block_ordering.h" -#include "ceres/problem_impl.h" -#include "ceres/program.h" -#include "ceres/residual_block.h" -#include "ceres/solver.h" -#include "ceres/suitesparse.h" -#include "ceres/triplet_sparse_matrix.h" -#include "ceres/types.h" -#include "Eigen/SparseCore" - -#ifdef CERES_USE_EIGEN_SPARSE -#include "Eigen/OrderingMethods" -#endif - -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::map; -using std::set; -using std::string; -using std::vector; - -namespace { - -// Find the minimum index of any parameter block to the given -// residual. Parameter blocks that have indices greater than -// size_of_first_elimination_group are considered to have an index -// equal to size_of_first_elimination_group. -static int MinParameterBlock(const ResidualBlock* residual_block, - int size_of_first_elimination_group) { - int min_parameter_block_position = size_of_first_elimination_group; - for (int i = 0; i < residual_block->NumParameterBlocks(); ++i) { - ParameterBlock* parameter_block = residual_block->parameter_blocks()[i]; - if (!parameter_block->IsConstant()) { - CHECK_NE(parameter_block->index(), -1) - << "Did you forget to call Program::SetParameterOffsetsAndIndex()? " - << "This is a Ceres bug; please contact the developers!"; - min_parameter_block_position = std::min(parameter_block->index(), - min_parameter_block_position); - } - } - return min_parameter_block_position; -} - -#if EIGEN_VERSION_AT_LEAST(3, 2, 2) && defined(CERES_USE_EIGEN_SPARSE) -Eigen::SparseMatrix<int> CreateBlockJacobian( - const TripletSparseMatrix& block_jacobian_transpose) { - typedef Eigen::SparseMatrix<int> SparseMatrix; - typedef Eigen::Triplet<int> Triplet; - - const int* rows = block_jacobian_transpose.rows(); - const int* cols = block_jacobian_transpose.cols(); - int num_nonzeros = block_jacobian_transpose.num_nonzeros(); - vector<Triplet> triplets; - triplets.reserve(num_nonzeros); - for (int i = 0; i < num_nonzeros; ++i) { - triplets.push_back(Triplet(cols[i], rows[i], 1)); - } - - SparseMatrix block_jacobian(block_jacobian_transpose.num_cols(), - block_jacobian_transpose.num_rows()); - block_jacobian.setFromTriplets(triplets.begin(), triplets.end()); - return block_jacobian; -} -#endif - -void OrderingForSparseNormalCholeskyUsingSuiteSparse( - const TripletSparseMatrix& tsm_block_jacobian_transpose, - const vector<ParameterBlock*>& parameter_blocks, - const ParameterBlockOrdering& parameter_block_ordering, - int* ordering) { -#ifdef CERES_NO_SUITESPARSE - LOG(FATAL) << "Congratulations, you found a Ceres bug! " - << "Please report this error to the developers."; -#else - SuiteSparse ss; - cholmod_sparse* block_jacobian_transpose = - ss.CreateSparseMatrix( - const_cast<TripletSparseMatrix*>(&tsm_block_jacobian_transpose)); - - // No CAMD or the user did not supply a useful ordering, then just - // use regular AMD. - if (parameter_block_ordering.NumGroups() <= 1 || - !SuiteSparse::IsConstrainedApproximateMinimumDegreeOrderingAvailable()) { - ss.ApproximateMinimumDegreeOrdering(block_jacobian_transpose, &ordering[0]); - } else { - vector<int> constraints; - for (int i = 0; i < parameter_blocks.size(); ++i) { - constraints.push_back( - parameter_block_ordering.GroupId( - parameter_blocks[i]->mutable_user_state())); - } - - // Renumber the entries of constraints to be contiguous integers - // as CAMD requires that the group ids be in the range [0, - // parameter_blocks.size() - 1]. - MapValuesToContiguousRange(constraints.size(), &constraints[0]); - ss.ConstrainedApproximateMinimumDegreeOrdering(block_jacobian_transpose, - &constraints[0], - ordering); - } - - ss.Free(block_jacobian_transpose); -#endif // CERES_NO_SUITESPARSE -} - -void OrderingForSparseNormalCholeskyUsingCXSparse( - const TripletSparseMatrix& tsm_block_jacobian_transpose, - int* ordering) { -#ifdef CERES_NO_CXSPARSE - LOG(FATAL) << "Congratulations, you found a Ceres bug! " - << "Please report this error to the developers."; -#else // CERES_NO_CXSPARSE - // CXSparse works with J'J instead of J'. So compute the block - // sparsity for J'J and compute an approximate minimum degree - // ordering. - CXSparse cxsparse; - cs_di* block_jacobian_transpose; - block_jacobian_transpose = - cxsparse.CreateSparseMatrix( - const_cast<TripletSparseMatrix*>(&tsm_block_jacobian_transpose)); - cs_di* block_jacobian = cxsparse.TransposeMatrix(block_jacobian_transpose); - cs_di* block_hessian = - cxsparse.MatrixMatrixMultiply(block_jacobian_transpose, block_jacobian); - cxsparse.Free(block_jacobian); - cxsparse.Free(block_jacobian_transpose); - - cxsparse.ApproximateMinimumDegreeOrdering(block_hessian, ordering); - cxsparse.Free(block_hessian); -#endif // CERES_NO_CXSPARSE -} - - -#if EIGEN_VERSION_AT_LEAST(3, 2, 2) -void OrderingForSparseNormalCholeskyUsingEigenSparse( - const TripletSparseMatrix& tsm_block_jacobian_transpose, - int* ordering) { -#ifndef CERES_USE_EIGEN_SPARSE - LOG(FATAL) << - "SPARSE_NORMAL_CHOLESKY cannot be used with EIGEN_SPARSE " - "because Ceres was not built with support for " - "Eigen's SimplicialLDLT decomposition. " - "This requires enabling building with -DEIGENSPARSE=ON."; -#else - - // This conversion from a TripletSparseMatrix to a Eigen::Triplet - // matrix is unfortunate, but unavoidable for now. It is not a - // significant performance penalty in the grand scheme of - // things. The right thing to do here would be to get a compressed - // row sparse matrix representation of the jacobian and go from - // there. But that is a project for another day. - typedef Eigen::SparseMatrix<int> SparseMatrix; - - const SparseMatrix block_jacobian = - CreateBlockJacobian(tsm_block_jacobian_transpose); - const SparseMatrix block_hessian = - block_jacobian.transpose() * block_jacobian; - - Eigen::AMDOrdering<int> amd_ordering; - Eigen::PermutationMatrix<Eigen::Dynamic, Eigen::Dynamic, int> perm; - amd_ordering(block_hessian, perm); - for (int i = 0; i < block_hessian.rows(); ++i) { - ordering[i] = perm.indices()[i]; - } -#endif // CERES_USE_EIGEN_SPARSE -} -#endif - -} // namespace - -bool ApplyOrdering(const ProblemImpl::ParameterMap& parameter_map, - const ParameterBlockOrdering& ordering, - Program* program, - string* error) { - const int num_parameter_blocks = program->NumParameterBlocks(); - if (ordering.NumElements() != num_parameter_blocks) { - *error = StringPrintf("User specified ordering does not have the same " - "number of parameters as the problem. The problem" - "has %d blocks while the ordering has %d blocks.", - num_parameter_blocks, - ordering.NumElements()); - return false; - } - - vector<ParameterBlock*>* parameter_blocks = - program->mutable_parameter_blocks(); - parameter_blocks->clear(); - - const map<int, set<double*> >& groups = ordering.group_to_elements(); - for (map<int, set<double*> >::const_iterator group_it = groups.begin(); - group_it != groups.end(); - ++group_it) { - const set<double*>& group = group_it->second; - for (set<double*>::const_iterator parameter_block_ptr_it = group.begin(); - parameter_block_ptr_it != group.end(); - ++parameter_block_ptr_it) { - ProblemImpl::ParameterMap::const_iterator parameter_block_it = - parameter_map.find(*parameter_block_ptr_it); - if (parameter_block_it == parameter_map.end()) { - *error = StringPrintf("User specified ordering contains a pointer " - "to a double that is not a parameter block in " - "the problem. The invalid double is in group: %d", - group_it->first); - return false; - } - parameter_blocks->push_back(parameter_block_it->second); - } - } - return true; -} - -bool LexicographicallyOrderResidualBlocks( - const int size_of_first_elimination_group, - Program* program, - string* error) { - CHECK_GE(size_of_first_elimination_group, 1) - << "Congratulations, you found a Ceres bug! Please report this error " - << "to the developers."; - - // Create a histogram of the number of residuals for each E block. There is an - // extra bucket at the end to catch all non-eliminated F blocks. - vector<int> residual_blocks_per_e_block(size_of_first_elimination_group + 1); - vector<ResidualBlock*>* residual_blocks = program->mutable_residual_blocks(); - vector<int> min_position_per_residual(residual_blocks->size()); - for (int i = 0; i < residual_blocks->size(); ++i) { - ResidualBlock* residual_block = (*residual_blocks)[i]; - int position = MinParameterBlock(residual_block, - size_of_first_elimination_group); - min_position_per_residual[i] = position; - DCHECK_LE(position, size_of_first_elimination_group); - residual_blocks_per_e_block[position]++; - } - - // Run a cumulative sum on the histogram, to obtain offsets to the start of - // each histogram bucket (where each bucket is for the residuals for that - // E-block). - vector<int> offsets(size_of_first_elimination_group + 1); - std::partial_sum(residual_blocks_per_e_block.begin(), - residual_blocks_per_e_block.end(), - offsets.begin()); - CHECK_EQ(offsets.back(), residual_blocks->size()) - << "Congratulations, you found a Ceres bug! Please report this error " - << "to the developers."; - - CHECK(find(residual_blocks_per_e_block.begin(), - residual_blocks_per_e_block.end() - 1, 0) != - residual_blocks_per_e_block.end()) - << "Congratulations, you found a Ceres bug! Please report this error " - << "to the developers."; - - // Fill in each bucket with the residual blocks for its corresponding E block. - // Each bucket is individually filled from the back of the bucket to the front - // of the bucket. The filling order among the buckets is dictated by the - // residual blocks. This loop uses the offsets as counters; subtracting one - // from each offset as a residual block is placed in the bucket. When the - // filling is finished, the offset pointerts should have shifted down one - // entry (this is verified below). - vector<ResidualBlock*> reordered_residual_blocks( - (*residual_blocks).size(), static_cast<ResidualBlock*>(NULL)); - for (int i = 0; i < residual_blocks->size(); ++i) { - int bucket = min_position_per_residual[i]; - - // Decrement the cursor, which should now point at the next empty position. - offsets[bucket]--; - - // Sanity. - CHECK(reordered_residual_blocks[offsets[bucket]] == NULL) - << "Congratulations, you found a Ceres bug! Please report this error " - << "to the developers."; - - reordered_residual_blocks[offsets[bucket]] = (*residual_blocks)[i]; - } - - // Sanity check #1: The difference in bucket offsets should match the - // histogram sizes. - for (int i = 0; i < size_of_first_elimination_group; ++i) { - CHECK_EQ(residual_blocks_per_e_block[i], offsets[i + 1] - offsets[i]) - << "Congratulations, you found a Ceres bug! Please report this error " - << "to the developers."; - } - // Sanity check #2: No NULL's left behind. - for (int i = 0; i < reordered_residual_blocks.size(); ++i) { - CHECK(reordered_residual_blocks[i] != NULL) - << "Congratulations, you found a Ceres bug! Please report this error " - << "to the developers."; - } - - // Now that the residuals are collected by E block, swap them in place. - swap(*program->mutable_residual_blocks(), reordered_residual_blocks); - return true; -} - -// Pre-order the columns corresponding to the schur complement if -// possible. -void MaybeReorderSchurComplementColumnsUsingSuiteSparse( - const ParameterBlockOrdering& parameter_block_ordering, - Program* program) { -#ifndef CERES_NO_SUITESPARSE - SuiteSparse ss; - if (!SuiteSparse::IsConstrainedApproximateMinimumDegreeOrderingAvailable()) { - return; - } - - vector<int> constraints; - vector<ParameterBlock*>& parameter_blocks = - *(program->mutable_parameter_blocks()); - - for (int i = 0; i < parameter_blocks.size(); ++i) { - constraints.push_back( - parameter_block_ordering.GroupId( - parameter_blocks[i]->mutable_user_state())); - } - - // Renumber the entries of constraints to be contiguous integers as - // CAMD requires that the group ids be in the range [0, - // parameter_blocks.size() - 1]. - MapValuesToContiguousRange(constraints.size(), &constraints[0]); - - // Compute a block sparse presentation of J'. - scoped_ptr<TripletSparseMatrix> tsm_block_jacobian_transpose( - program->CreateJacobianBlockSparsityTranspose()); - - cholmod_sparse* block_jacobian_transpose = - ss.CreateSparseMatrix(tsm_block_jacobian_transpose.get()); - - vector<int> ordering(parameter_blocks.size(), 0); - ss.ConstrainedApproximateMinimumDegreeOrdering(block_jacobian_transpose, - &constraints[0], - &ordering[0]); - ss.Free(block_jacobian_transpose); - - const vector<ParameterBlock*> parameter_blocks_copy(parameter_blocks); - for (int i = 0; i < program->NumParameterBlocks(); ++i) { - parameter_blocks[i] = parameter_blocks_copy[ordering[i]]; - } - - program->SetParameterOffsetsAndIndex(); -#endif -} - -void MaybeReorderSchurComplementColumnsUsingEigen( - const int size_of_first_elimination_group, - const ProblemImpl::ParameterMap& parameter_map, - Program* program) { -#if !EIGEN_VERSION_AT_LEAST(3, 2, 2) || !defined(CERES_USE_EIGEN_SPARSE) - return; -#else - - scoped_ptr<TripletSparseMatrix> tsm_block_jacobian_transpose( - program->CreateJacobianBlockSparsityTranspose()); - - typedef Eigen::SparseMatrix<int> SparseMatrix; - const SparseMatrix block_jacobian = - CreateBlockJacobian(*tsm_block_jacobian_transpose); - const int num_rows = block_jacobian.rows(); - const int num_cols = block_jacobian.cols(); - - // Vertically partition the jacobian in parameter blocks of type E - // and F. - const SparseMatrix E = - block_jacobian.block(0, - 0, - num_rows, - size_of_first_elimination_group); - const SparseMatrix F = - block_jacobian.block(0, - size_of_first_elimination_group, - num_rows, - num_cols - size_of_first_elimination_group); - - // Block sparsity pattern of the schur complement. - const SparseMatrix block_schur_complement = - F.transpose() * F - F.transpose() * E * E.transpose() * F; - - Eigen::AMDOrdering<int> amd_ordering; - Eigen::PermutationMatrix<Eigen::Dynamic, Eigen::Dynamic, int> perm; - amd_ordering(block_schur_complement, perm); - - const vector<ParameterBlock*>& parameter_blocks = program->parameter_blocks(); - vector<ParameterBlock*> ordering(num_cols); - - // The ordering of the first size_of_first_elimination_group does - // not matter, so we preserve the existing ordering. - for (int i = 0; i < size_of_first_elimination_group; ++i) { - ordering[i] = parameter_blocks[i]; - } - - // For the rest of the blocks, use the ordering computed using AMD. - for (int i = 0; i < block_schur_complement.cols(); ++i) { - ordering[size_of_first_elimination_group + i] = - parameter_blocks[size_of_first_elimination_group + perm.indices()[i]]; - } - - swap(*program->mutable_parameter_blocks(), ordering); - program->SetParameterOffsetsAndIndex(); -#endif -} - -bool ReorderProgramForSchurTypeLinearSolver( - const LinearSolverType linear_solver_type, - const SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type, - const ProblemImpl::ParameterMap& parameter_map, - ParameterBlockOrdering* parameter_block_ordering, - Program* program, - string* error) { - if (parameter_block_ordering->NumElements() != - program->NumParameterBlocks()) { - *error = StringPrintf( - "The program has %d parameter blocks, but the parameter block " - "ordering has %d parameter blocks.", - program->NumParameterBlocks(), - parameter_block_ordering->NumElements()); - return false; - } - - if (parameter_block_ordering->NumGroups() == 1) { - // If the user supplied an parameter_block_ordering with just one - // group, it is equivalent to the user supplying NULL as an - // parameter_block_ordering. Ceres is completely free to choose the - // parameter block ordering as it sees fit. For Schur type solvers, - // this means that the user wishes for Ceres to identify the - // e_blocks, which we do by computing a maximal independent set. - vector<ParameterBlock*> schur_ordering; - const int size_of_first_elimination_group = - ComputeStableSchurOrdering(*program, &schur_ordering); - - CHECK_EQ(schur_ordering.size(), program->NumParameterBlocks()) - << "Congratulations, you found a Ceres bug! Please report this error " - << "to the developers."; - - // Update the parameter_block_ordering object. - for (int i = 0; i < schur_ordering.size(); ++i) { - double* parameter_block = schur_ordering[i]->mutable_user_state(); - const int group_id = (i < size_of_first_elimination_group) ? 0 : 1; - parameter_block_ordering->AddElementToGroup(parameter_block, group_id); - } - - // We could call ApplyOrdering but this is cheaper and - // simpler. - swap(*program->mutable_parameter_blocks(), schur_ordering); - } else { - // The user provided an ordering with more than one elimination - // group. - - // Verify that the first elimination group is an independent set. - const set<double*>& first_elimination_group = - parameter_block_ordering - ->group_to_elements() - .begin() - ->second; - if (!program->IsParameterBlockSetIndependent(first_elimination_group)) { - *error = - StringPrintf("The first elimination group in the parameter block " - "ordering of size %zd is not an independent set", - first_elimination_group.size()); - return false; - } - - if (!ApplyOrdering(parameter_map, - *parameter_block_ordering, - program, - error)) { - return false; - } - } - - program->SetParameterOffsetsAndIndex(); - - const int size_of_first_elimination_group = - parameter_block_ordering->group_to_elements().begin()->second.size(); - - if (linear_solver_type == SPARSE_SCHUR) { - if (sparse_linear_algebra_library_type == SUITE_SPARSE) { - MaybeReorderSchurComplementColumnsUsingSuiteSparse( - *parameter_block_ordering, - program); - } else if (sparse_linear_algebra_library_type == EIGEN_SPARSE) { - MaybeReorderSchurComplementColumnsUsingEigen( - size_of_first_elimination_group, - parameter_map, - program); - } - } - - // Schur type solvers also require that their residual blocks be - // lexicographically ordered. - if (!LexicographicallyOrderResidualBlocks(size_of_first_elimination_group, - program, - error)) { - return false; - } - - return true; -} - -bool ReorderProgramForSparseNormalCholesky( - const SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type, - const ParameterBlockOrdering& parameter_block_ordering, - Program* program, - string* error) { - if (parameter_block_ordering.NumElements() != program->NumParameterBlocks()) { - *error = StringPrintf( - "The program has %d parameter blocks, but the parameter block " - "ordering has %d parameter blocks.", - program->NumParameterBlocks(), - parameter_block_ordering.NumElements()); - return false; - } - - // Compute a block sparse presentation of J'. - scoped_ptr<TripletSparseMatrix> tsm_block_jacobian_transpose( - program->CreateJacobianBlockSparsityTranspose()); - - vector<int> ordering(program->NumParameterBlocks(), 0); - vector<ParameterBlock*>& parameter_blocks = - *(program->mutable_parameter_blocks()); - - if (sparse_linear_algebra_library_type == SUITE_SPARSE) { - OrderingForSparseNormalCholeskyUsingSuiteSparse( - *tsm_block_jacobian_transpose, - parameter_blocks, - parameter_block_ordering, - &ordering[0]); - } else if (sparse_linear_algebra_library_type == CX_SPARSE) { - OrderingForSparseNormalCholeskyUsingCXSparse( - *tsm_block_jacobian_transpose, - &ordering[0]); - } else if (sparse_linear_algebra_library_type == EIGEN_SPARSE) { -#if EIGEN_VERSION_AT_LEAST(3, 2, 2) - OrderingForSparseNormalCholeskyUsingEigenSparse( - *tsm_block_jacobian_transpose, - &ordering[0]); -#else - // For Eigen versions less than 3.2.2, there is nothing to do as - // older versions of Eigen do not expose a method for doing - // symbolic analysis on pre-ordered matrices, so a block - // pre-ordering is a bit pointless. - - return true; -#endif - } - - // Apply ordering. - const vector<ParameterBlock*> parameter_blocks_copy(parameter_blocks); - for (int i = 0; i < program->NumParameterBlocks(); ++i) { - parameter_blocks[i] = parameter_blocks_copy[ordering[i]]; - } - - program->SetParameterOffsetsAndIndex(); - return true; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/reorder_program.h b/extern/libmv/third_party/ceres/internal/ceres/reorder_program.h deleted file mode 100644 index 36e5d1637a9..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/reorder_program.h +++ /dev/null @@ -1,101 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_REORDER_PROGRAM_H_ -#define CERES_INTERNAL_REORDER_PROGRAM_H_ - -#include <string> -#include "ceres/internal/port.h" -#include "ceres/parameter_block_ordering.h" -#include "ceres/problem_impl.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -class Program; - -// Reorder the parameter blocks in program using the ordering -bool ApplyOrdering(const ProblemImpl::ParameterMap& parameter_map, - const ParameterBlockOrdering& ordering, - Program* program, - std::string* error); - -// Reorder the residuals for program, if necessary, so that the residuals -// involving each E block occur together. This is a necessary condition for the -// Schur eliminator, which works on these "row blocks" in the jacobian. -bool LexicographicallyOrderResidualBlocks(int size_of_first_elimination_group, - Program* program, - std::string* error); - -// Schur type solvers require that all parameter blocks eliminated -// by the Schur eliminator occur before others and the residuals be -// sorted in lexicographic order of their parameter blocks. -// -// If the parameter_block_ordering only contains one elimination -// group then a maximal independent set is computed and used as the -// first elimination group, otherwise the user's ordering is used. -// -// If the linear solver type is SPARSE_SCHUR and support for -// constrained fill-reducing ordering is available in the sparse -// linear algebra library (SuiteSparse version >= 4.2.0) then -// columns of the schur complement matrix are ordered to reduce the -// fill-in the Cholesky factorization. -// -// Upon return, ordering contains the parameter block ordering that -// was used to order the program. -bool ReorderProgramForSchurTypeLinearSolver( - LinearSolverType linear_solver_type, - SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type, - const ProblemImpl::ParameterMap& parameter_map, - ParameterBlockOrdering* parameter_block_ordering, - Program* program, - std::string* error); - -// Sparse cholesky factorization routines when doing the sparse -// cholesky factorization of the Jacobian matrix, reorders its -// columns to reduce the fill-in. Compute this permutation and -// re-order the parameter blocks. -// -// When using SuiteSparse, if the parameter_block_ordering contains -// more than one elimination group and support for constrained -// fill-reducing ordering is available in the sparse linear algebra -// library (SuiteSparse version >= 4.2.0) then the fill reducing -// ordering will take it into account, otherwise it will be ignored. -bool ReorderProgramForSparseNormalCholesky( - SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type, - const ParameterBlockOrdering& parameter_block_ordering, - Program* program, - std::string* error); - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_REORDER_PROGRAM_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/residual_block.cc b/extern/libmv/third_party/ceres/internal/ceres/residual_block.cc deleted file mode 100644 index 9a123cf132e..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/residual_block.cc +++ /dev/null @@ -1,219 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/residual_block.h" - -#include <algorithm> -#include <cstddef> -#include <vector> -#include "ceres/corrector.h" -#include "ceres/parameter_block.h" -#include "ceres/residual_block_utils.h" -#include "ceres/cost_function.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/fixed_array.h" -#include "ceres/local_parameterization.h" -#include "ceres/loss_function.h" -#include "ceres/small_blas.h" - -using Eigen::Dynamic; - -namespace ceres { -namespace internal { - -ResidualBlock::ResidualBlock( - const CostFunction* cost_function, - const LossFunction* loss_function, - const std::vector<ParameterBlock*>& parameter_blocks, - int index) - : cost_function_(cost_function), - loss_function_(loss_function), - parameter_blocks_( - new ParameterBlock* [ - cost_function->parameter_block_sizes().size()]), - index_(index) { - std::copy(parameter_blocks.begin(), - parameter_blocks.end(), - parameter_blocks_.get()); -} - -bool ResidualBlock::Evaluate(const bool apply_loss_function, - double* cost, - double* residuals, - double** jacobians, - double* scratch) const { - const int num_parameter_blocks = NumParameterBlocks(); - const int num_residuals = cost_function_->num_residuals(); - - // Collect the parameters from their blocks. This will rarely allocate, since - // residuals taking more than 8 parameter block arguments are rare. - FixedArray<const double*, 8> parameters(num_parameter_blocks); - for (int i = 0; i < num_parameter_blocks; ++i) { - parameters[i] = parameter_blocks_[i]->state(); - } - - // Put pointers into the scratch space into global_jacobians as appropriate. - FixedArray<double*, 8> global_jacobians(num_parameter_blocks); - if (jacobians != NULL) { - for (int i = 0; i < num_parameter_blocks; ++i) { - const ParameterBlock* parameter_block = parameter_blocks_[i]; - if (jacobians[i] != NULL && - parameter_block->LocalParameterizationJacobian() != NULL) { - global_jacobians[i] = scratch; - scratch += num_residuals * parameter_block->Size(); - } else { - global_jacobians[i] = jacobians[i]; - } - } - } - - // If the caller didn't request residuals, use the scratch space for them. - bool outputting_residuals = (residuals != NULL); - if (!outputting_residuals) { - residuals = scratch; - } - - // Invalidate the evaluation buffers so that we can check them after - // the CostFunction::Evaluate call, to see if all the return values - // that were required were written to and that they are finite. - double** eval_jacobians = (jacobians != NULL) ? global_jacobians.get() : NULL; - - InvalidateEvaluation(*this, cost, residuals, eval_jacobians); - - if (!cost_function_->Evaluate(parameters.get(), residuals, eval_jacobians)) { - return false; - } - - if (!IsEvaluationValid(*this, - parameters.get(), - cost, - residuals, - eval_jacobians)) { - std::string message = - "\n\n" - "Error in evaluating the ResidualBlock.\n\n" - "There are two possible reasons. Either the CostFunction did not evaluate and fill all \n" // NOLINT - "residual and jacobians that were requested or there was a non-finite value (nan/infinite)\n" // NOLINT - "generated during the or jacobian computation. \n\n" + - EvaluationToString(*this, - parameters.get(), - cost, - residuals, - eval_jacobians); - LOG(WARNING) << message; - return false; - } - - double squared_norm = VectorRef(residuals, num_residuals).squaredNorm(); - - // Update the jacobians with the local parameterizations. - if (jacobians != NULL) { - for (int i = 0; i < num_parameter_blocks; ++i) { - if (jacobians[i] != NULL) { - const ParameterBlock* parameter_block = parameter_blocks_[i]; - - // Apply local reparameterization to the jacobians. - if (parameter_block->LocalParameterizationJacobian() != NULL) { - // jacobians[i] = global_jacobians[i] * global_to_local_jacobian. - MatrixMatrixMultiply<Dynamic, Dynamic, Dynamic, Dynamic, 0>( - global_jacobians[i], - num_residuals, - parameter_block->Size(), - parameter_block->LocalParameterizationJacobian(), - parameter_block->Size(), - parameter_block->LocalSize(), - jacobians[i], 0, 0, num_residuals, parameter_block->LocalSize()); - } - } - } - } - - if (loss_function_ == NULL || !apply_loss_function) { - *cost = 0.5 * squared_norm; - return true; - } - - double rho[3]; - loss_function_->Evaluate(squared_norm, rho); - *cost = 0.5 * rho[0]; - - // No jacobians and not outputting residuals? All done. Doing an early exit - // here avoids constructing the "Corrector" object below in a common case. - if (jacobians == NULL && !outputting_residuals) { - return true; - } - - // Correct for the effects of the loss function. The jacobians need to be - // corrected before the residuals, since they use the uncorrected residuals. - Corrector correct(squared_norm, rho); - if (jacobians != NULL) { - for (int i = 0; i < num_parameter_blocks; ++i) { - if (jacobians[i] != NULL) { - const ParameterBlock* parameter_block = parameter_blocks_[i]; - - // Correct the jacobians for the loss function. - correct.CorrectJacobian(num_residuals, - parameter_block->LocalSize(), - residuals, - jacobians[i]); - } - } - } - - // Correct the residuals with the loss function. - if (outputting_residuals) { - correct.CorrectResiduals(num_residuals, residuals); - } - return true; -} - -int ResidualBlock::NumScratchDoublesForEvaluate() const { - // Compute the amount of scratch space needed to store the full-sized - // jacobians. For parameters that have no local parameterization no storage - // is needed and the passed-in jacobian array is used directly. Also include - // space to store the residuals, which is needed for cost-only evaluations. - // This is slightly pessimistic, since both won't be needed all the time, but - // the amount of excess should not cause problems for the caller. - int num_parameters = NumParameterBlocks(); - int scratch_doubles = 1; - for (int i = 0; i < num_parameters; ++i) { - const ParameterBlock* parameter_block = parameter_blocks_[i]; - if (!parameter_block->IsConstant() && - parameter_block->LocalParameterizationJacobian() != NULL) { - scratch_doubles += parameter_block->Size(); - } - } - scratch_doubles *= NumResiduals(); - return scratch_doubles; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/residual_block.h b/extern/libmv/third_party/ceres/internal/ceres/residual_block.h deleted file mode 100644 index 05e6d1f81e5..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/residual_block.h +++ /dev/null @@ -1,148 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// keir@google.com (Keir Mierle) -// -// Purpose : Class and struct definitions for parameter and residual blocks. - -#ifndef CERES_INTERNAL_RESIDUAL_BLOCK_H_ -#define CERES_INTERNAL_RESIDUAL_BLOCK_H_ - -#include <string> -#include <vector> - -#include "ceres/cost_function.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/stringprintf.h" -#include "ceres/types.h" - -namespace ceres { - -class LossFunction; - -namespace internal { - -class ParameterBlock; - -// A term in the least squares problem. The mathematical form of each term in -// the overall least-squares cost function is: -// -// 1 -// --- loss_function( || cost_function(block1, block2, ...) ||^2 ), -// 2 -// -// Storing the cost function and the loss function separately permits optimizing -// the problem with standard non-linear least techniques, without requiring a -// more general non-linear solver. -// -// The residual block stores pointers to but does not own the cost functions, -// loss functions, and parameter blocks. -class ResidualBlock { - public: - // Construct the residual block with the given cost/loss functions. Loss may - // be null. The index is the index of the residual block in the Program's - // residual_blocks array. - ResidualBlock(const CostFunction* cost_function, - const LossFunction* loss_function, - const std::vector<ParameterBlock*>& parameter_blocks, - int index); - - // Evaluates the residual term, storing the scalar cost in *cost, the residual - // components in *residuals, and the jacobians between the parameters and - // residuals in jacobians[i], in row-major order. If residuals is NULL, the - // residuals are not computed. If jacobians is NULL, no jacobians are - // computed. If jacobians[i] is NULL, then the jacobian for that parameter is - // not computed. - // - // Evaluate needs scratch space which must be supplied by the caller via - // scratch. The array should have at least NumScratchDoublesForEvaluate() - // space available. - // - // The return value indicates the success or failure. If the function returns - // false, the caller should expect the the output memory locations to have - // been modified. - // - // The returned cost and jacobians have had robustification and local - // parameterizations applied already; for example, the jacobian for a - // 4-dimensional quaternion parameter using the "QuaternionParameterization" - // is num_residuals by 3 instead of num_residuals by 4. - // - // apply_loss_function as the name implies allows the user to switch - // the application of the loss function on and off. - bool Evaluate(bool apply_loss_function, - double* cost, - double* residuals, - double** jacobians, - double* scratch) const; - - - const CostFunction* cost_function() const { return cost_function_; } - const LossFunction* loss_function() const { return loss_function_; } - - // Access the parameter blocks for this residual. The array has size - // NumParameterBlocks(). - ParameterBlock* const* parameter_blocks() const { - return parameter_blocks_.get(); - } - - // Number of variable blocks that this residual term depends on. - int NumParameterBlocks() const { - return cost_function_->parameter_block_sizes().size(); - } - - // The size of the residual vector returned by this residual function. - int NumResiduals() const { return cost_function_->num_residuals(); } - - // The minimum amount of scratch space needed to pass to Evaluate(). - int NumScratchDoublesForEvaluate() const; - - // This residual block's index in an array. - int index() const { return index_; } - void set_index(int index) { index_ = index; } - - std::string ToString() { - return StringPrintf("{residual block; index=%d}", index_); - } - - private: - const CostFunction* cost_function_; - const LossFunction* loss_function_; - scoped_array<ParameterBlock*> parameter_blocks_; - - // The index of the residual, typically in a Program. This is only to permit - // switching from a ResidualBlock* to an index in the Program's array, needed - // to do efficient removals. - int32 index_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_RESIDUAL_BLOCK_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.cc b/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.cc deleted file mode 100644 index dd2bd73a6ac..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.cc +++ /dev/null @@ -1,142 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/residual_block_utils.h" - -#include <cmath> -#include <cstddef> -#include <limits> -#include "ceres/array_utils.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/port.h" -#include "ceres/parameter_block.h" -#include "ceres/residual_block.h" -#include "ceres/stringprintf.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -using std::string; - -void InvalidateEvaluation(const ResidualBlock& block, - double* cost, - double* residuals, - double** jacobians) { - const int num_parameter_blocks = block.NumParameterBlocks(); - const int num_residuals = block.NumResiduals(); - - InvalidateArray(1, cost); - InvalidateArray(num_residuals, residuals); - if (jacobians != NULL) { - for (int i = 0; i < num_parameter_blocks; ++i) { - const int parameter_block_size = block.parameter_blocks()[i]->Size(); - InvalidateArray(num_residuals * parameter_block_size, jacobians[i]); - } - } -} - -string EvaluationToString(const ResidualBlock& block, - double const* const* parameters, - double* cost, - double* residuals, - double** jacobians) { - CHECK_NOTNULL(cost); - CHECK_NOTNULL(residuals); - - const int num_parameter_blocks = block.NumParameterBlocks(); - const int num_residuals = block.NumResiduals(); - string result = ""; - - StringAppendF(&result, - "Residual Block size: %d parameter blocks x %d residuals\n\n", - num_parameter_blocks, num_residuals); - result += - "For each parameter block, the value of the parameters are printed in the first column \n" // NOLINT - "and the value of the jacobian under the corresponding residual. If a ParameterBlock was \n" // NOLINT - "held constant then the corresponding jacobian is printed as 'Not Computed'. If an entry \n" // NOLINT - "of the Jacobian/residual array was requested but was not written to by user code, it is \n" // NOLINT - "indicated by 'Uninitialized'. This is an error. Residuals or Jacobian values evaluating \n" // NOLINT - "to Inf or NaN is also an error. \n\n"; // NOLINT - - string space = "Residuals: "; - result += space; - AppendArrayToString(num_residuals, residuals, &result); - StringAppendF(&result, "\n\n"); - - for (int i = 0; i < num_parameter_blocks; ++i) { - const int parameter_block_size = block.parameter_blocks()[i]->Size(); - StringAppendF( - &result, "Parameter Block %d, size: %d\n", i, parameter_block_size); - StringAppendF(&result, "\n"); - for (int j = 0; j < parameter_block_size; ++j) { - AppendArrayToString(1, parameters[i] + j, &result); - StringAppendF(&result, "| "); - for (int k = 0; k < num_residuals; ++k) { - AppendArrayToString(1, - (jacobians != NULL && jacobians[i] != NULL) - ? jacobians[i] + k * parameter_block_size + j - : NULL, - &result); - } - StringAppendF(&result, "\n"); - } - StringAppendF(&result, "\n"); - } - StringAppendF(&result, "\n"); - return result; -} - -bool IsEvaluationValid(const ResidualBlock& block, - double const* const* parameters, - double* cost, - double* residuals, - double** jacobians) { - const int num_parameter_blocks = block.NumParameterBlocks(); - const int num_residuals = block.NumResiduals(); - - if (!IsArrayValid(num_residuals, residuals)) { - return false; - } - - if (jacobians != NULL) { - for (int i = 0; i < num_parameter_blocks; ++i) { - const int parameter_block_size = block.parameter_blocks()[i]->Size(); - if (!IsArrayValid(num_residuals * parameter_block_size, jacobians[i])) { - return false; - } - } - } - - return true; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.h b/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.h deleted file mode 100644 index 627337f743c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.h +++ /dev/null @@ -1,80 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Utility routines for ResidualBlock evaluation. -// -// These are useful for detecting two common class of errors. -// -// 1. Uninitialized memory - where the user for some reason did not -// compute part of a cost/residual/jacobian. -// -// 2. Numerical failure while computing the cost/residual/jacobian, -// e.g. NaN, infinities etc. This is particularly useful since the -// automatic differentiation code does computations that are not -// evident to the user and can silently generate hard to debug errors. - -#ifndef CERES_INTERNAL_RESIDUAL_BLOCK_UTILS_H_ -#define CERES_INTERNAL_RESIDUAL_BLOCK_UTILS_H_ - -#include <string> -#include "ceres/internal/port.h" - -namespace ceres { -namespace internal { - -class ResidualBlock; - -// Invalidate cost, resdual and jacobian arrays (if not NULL). -void InvalidateEvaluation(const ResidualBlock& block, - double* cost, - double* residuals, - double** jacobians); - -// Check if any of the arrays cost, residuals or jacobians contains an -// NaN, return true if it does. -bool IsEvaluationValid(const ResidualBlock& block, - double const* const* parameters, - double* cost, - double* residuals, - double** jacobians); - -// Create a string representation of the Residual block containing the -// value of the parameters, residuals and jacobians if present. -// Useful for debugging output. -std::string EvaluationToString(const ResidualBlock& block, - double const* const* parameters, - double* cost, - double* residuals, - double** jacobians); - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_RESIDUAL_BLOCK_UTILS_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.cc deleted file mode 100644 index 2491060dcdc..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.cc +++ /dev/null @@ -1,670 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/internal/port.h" - -#include <algorithm> -#include <ctime> -#include <set> -#include <vector> - -#include "ceres/block_random_access_dense_matrix.h" -#include "ceres/block_random_access_matrix.h" -#include "ceres/block_random_access_sparse_matrix.h" -#include "ceres/block_sparse_matrix.h" -#include "ceres/block_structure.h" -#include "ceres/conjugate_gradients_solver.h" -#include "ceres/cxsparse.h" -#include "ceres/detect_structure.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/lapack.h" -#include "ceres/linear_solver.h" -#include "ceres/schur_complement_solver.h" -#include "ceres/suitesparse.h" -#include "ceres/triplet_sparse_matrix.h" -#include "ceres/types.h" -#include "ceres/wall_time.h" -#include "Eigen/Dense" -#include "Eigen/SparseCore" - -namespace ceres { -namespace internal { - -using std::make_pair; -using std::pair; -using std::set; -using std::vector; - -namespace { - -class BlockRandomAccessSparseMatrixAdapter : public LinearOperator { - public: - explicit BlockRandomAccessSparseMatrixAdapter( - const BlockRandomAccessSparseMatrix& m) - : m_(m) { - } - - virtual ~BlockRandomAccessSparseMatrixAdapter() {} - - // y = y + Ax; - virtual void RightMultiply(const double* x, double* y) const { - m_.SymmetricRightMultiply(x, y); - } - - // y = y + A'x; - virtual void LeftMultiply(const double* x, double* y) const { - m_.SymmetricRightMultiply(x, y); - } - - virtual int num_rows() const { return m_.num_rows(); } - virtual int num_cols() const { return m_.num_rows(); } - - private: - const BlockRandomAccessSparseMatrix& m_; -}; - -class BlockRandomAccessDiagonalMatrixAdapter : public LinearOperator { - public: - explicit BlockRandomAccessDiagonalMatrixAdapter( - const BlockRandomAccessDiagonalMatrix& m) - : m_(m) { - } - - virtual ~BlockRandomAccessDiagonalMatrixAdapter() {} - - // y = y + Ax; - virtual void RightMultiply(const double* x, double* y) const { - m_.RightMultiply(x, y); - } - - // y = y + A'x; - virtual void LeftMultiply(const double* x, double* y) const { - m_.RightMultiply(x, y); - } - - virtual int num_rows() const { return m_.num_rows(); } - virtual int num_cols() const { return m_.num_rows(); } - - private: - const BlockRandomAccessDiagonalMatrix& m_; -}; - -} // namespace - -LinearSolver::Summary SchurComplementSolver::SolveImpl( - BlockSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x) { - EventLogger event_logger("SchurComplementSolver::Solve"); - - if (eliminator_.get() == NULL) { - InitStorage(A->block_structure()); - DetectStructure(*A->block_structure(), - options_.elimination_groups[0], - &options_.row_block_size, - &options_.e_block_size, - &options_.f_block_size); - eliminator_.reset(CHECK_NOTNULL(SchurEliminatorBase::Create(options_))); - eliminator_->Init(options_.elimination_groups[0], A->block_structure()); - }; - std::fill(x, x + A->num_cols(), 0.0); - event_logger.AddEvent("Setup"); - - eliminator_->Eliminate(A, b, per_solve_options.D, lhs_.get(), rhs_.get()); - event_logger.AddEvent("Eliminate"); - - double* reduced_solution = x + A->num_cols() - lhs_->num_cols(); - const LinearSolver::Summary summary = - SolveReducedLinearSystem(per_solve_options, reduced_solution); - event_logger.AddEvent("ReducedSolve"); - - if (summary.termination_type == LINEAR_SOLVER_SUCCESS) { - eliminator_->BackSubstitute(A, b, per_solve_options.D, reduced_solution, x); - event_logger.AddEvent("BackSubstitute"); - } - - return summary; -} - -// Initialize a BlockRandomAccessDenseMatrix to store the Schur -// complement. -void DenseSchurComplementSolver::InitStorage( - const CompressedRowBlockStructure* bs) { - const int num_eliminate_blocks = options().elimination_groups[0]; - const int num_col_blocks = bs->cols.size(); - - vector<int> blocks(num_col_blocks - num_eliminate_blocks, 0); - for (int i = num_eliminate_blocks, j = 0; - i < num_col_blocks; - ++i, ++j) { - blocks[j] = bs->cols[i].size; - } - - set_lhs(new BlockRandomAccessDenseMatrix(blocks)); - set_rhs(new double[lhs()->num_rows()]); -} - -// Solve the system Sx = r, assuming that the matrix S is stored in a -// BlockRandomAccessDenseMatrix. The linear system is solved using -// Eigen's Cholesky factorization. -LinearSolver::Summary -DenseSchurComplementSolver::SolveReducedLinearSystem( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution) { - LinearSolver::Summary summary; - summary.num_iterations = 0; - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = "Success."; - - const BlockRandomAccessDenseMatrix* m = - down_cast<const BlockRandomAccessDenseMatrix*>(lhs()); - const int num_rows = m->num_rows(); - - // The case where there are no f blocks, and the system is block - // diagonal. - if (num_rows == 0) { - return summary; - } - - summary.num_iterations = 1; - - if (options().dense_linear_algebra_library_type == EIGEN) { - Eigen::LLT<Matrix, Eigen::Upper> llt = - ConstMatrixRef(m->values(), num_rows, num_rows) - .selfadjointView<Eigen::Upper>() - .llt(); - if (llt.info() != Eigen::Success) { - summary.termination_type = LINEAR_SOLVER_FAILURE; - summary.message = - "Eigen failure. Unable to perform dense Cholesky factorization."; - return summary; - } - - VectorRef(solution, num_rows) = llt.solve(ConstVectorRef(rhs(), num_rows)); - } else { - VectorRef(solution, num_rows) = ConstVectorRef(rhs(), num_rows); - summary.termination_type = - LAPACK::SolveInPlaceUsingCholesky(num_rows, - m->values(), - solution, - &summary.message); - } - - return summary; -} - -SparseSchurComplementSolver::SparseSchurComplementSolver( - const LinearSolver::Options& options) - : SchurComplementSolver(options), - factor_(NULL), - cxsparse_factor_(NULL) { -} - -SparseSchurComplementSolver::~SparseSchurComplementSolver() { - if (factor_ != NULL) { - ss_.Free(factor_); - factor_ = NULL; - } - - if (cxsparse_factor_ != NULL) { - cxsparse_.Free(cxsparse_factor_); - cxsparse_factor_ = NULL; - } -} - -// Determine the non-zero blocks in the Schur Complement matrix, and -// initialize a BlockRandomAccessSparseMatrix object. -void SparseSchurComplementSolver::InitStorage( - const CompressedRowBlockStructure* bs) { - const int num_eliminate_blocks = options().elimination_groups[0]; - const int num_col_blocks = bs->cols.size(); - const int num_row_blocks = bs->rows.size(); - - blocks_.resize(num_col_blocks - num_eliminate_blocks, 0); - for (int i = num_eliminate_blocks; i < num_col_blocks; ++i) { - blocks_[i - num_eliminate_blocks] = bs->cols[i].size; - } - - set<pair<int, int> > block_pairs; - for (int i = 0; i < blocks_.size(); ++i) { - block_pairs.insert(make_pair(i, i)); - } - - int r = 0; - while (r < num_row_blocks) { - int e_block_id = bs->rows[r].cells.front().block_id; - if (e_block_id >= num_eliminate_blocks) { - break; - } - vector<int> f_blocks; - - // Add to the chunk until the first block in the row is - // different than the one in the first row for the chunk. - for (; r < num_row_blocks; ++r) { - const CompressedRow& row = bs->rows[r]; - if (row.cells.front().block_id != e_block_id) { - break; - } - - // Iterate over the blocks in the row, ignoring the first - // block since it is the one to be eliminated. - for (int c = 1; c < row.cells.size(); ++c) { - const Cell& cell = row.cells[c]; - f_blocks.push_back(cell.block_id - num_eliminate_blocks); - } - } - - sort(f_blocks.begin(), f_blocks.end()); - f_blocks.erase(unique(f_blocks.begin(), f_blocks.end()), f_blocks.end()); - for (int i = 0; i < f_blocks.size(); ++i) { - for (int j = i + 1; j < f_blocks.size(); ++j) { - block_pairs.insert(make_pair(f_blocks[i], f_blocks[j])); - } - } - } - - // Remaing rows do not contribute to the chunks and directly go - // into the schur complement via an outer product. - for (; r < num_row_blocks; ++r) { - const CompressedRow& row = bs->rows[r]; - CHECK_GE(row.cells.front().block_id, num_eliminate_blocks); - for (int i = 0; i < row.cells.size(); ++i) { - int r_block1_id = row.cells[i].block_id - num_eliminate_blocks; - for (int j = 0; j < row.cells.size(); ++j) { - int r_block2_id = row.cells[j].block_id - num_eliminate_blocks; - if (r_block1_id <= r_block2_id) { - block_pairs.insert(make_pair(r_block1_id, r_block2_id)); - } - } - } - } - - set_lhs(new BlockRandomAccessSparseMatrix(blocks_, block_pairs)); - set_rhs(new double[lhs()->num_rows()]); -} - -LinearSolver::Summary -SparseSchurComplementSolver::SolveReducedLinearSystem( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution) { - if (options().type == ITERATIVE_SCHUR) { - CHECK(options().use_explicit_schur_complement); - return SolveReducedLinearSystemUsingConjugateGradients(per_solve_options, - solution); - } - - switch (options().sparse_linear_algebra_library_type) { - case SUITE_SPARSE: - return SolveReducedLinearSystemUsingSuiteSparse(per_solve_options, - solution); - case CX_SPARSE: - return SolveReducedLinearSystemUsingCXSparse(per_solve_options, - solution); - case EIGEN_SPARSE: - return SolveReducedLinearSystemUsingEigen(per_solve_options, - solution); - default: - LOG(FATAL) << "Unknown sparse linear algebra library : " - << options().sparse_linear_algebra_library_type; - } - - return LinearSolver::Summary(); -} - -// Solve the system Sx = r, assuming that the matrix S is stored in a -// BlockRandomAccessSparseMatrix. The linear system is solved using -// CHOLMOD's sparse cholesky factorization routines. -LinearSolver::Summary -SparseSchurComplementSolver::SolveReducedLinearSystemUsingSuiteSparse( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution) { -#ifdef CERES_NO_SUITESPARSE - - LinearSolver::Summary summary; - summary.num_iterations = 0; - summary.termination_type = LINEAR_SOLVER_FATAL_ERROR; - summary.message = "Ceres was not built with SuiteSparse support. " - "Therefore, SPARSE_SCHUR cannot be used with SUITE_SPARSE"; - return summary; - -#else - - LinearSolver::Summary summary; - summary.num_iterations = 0; - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = "Success."; - - TripletSparseMatrix* tsm = - const_cast<TripletSparseMatrix*>( - down_cast<const BlockRandomAccessSparseMatrix*>(lhs())->matrix()); - const int num_rows = tsm->num_rows(); - - // The case where there are no f blocks, and the system is block - // diagonal. - if (num_rows == 0) { - return summary; - } - - summary.num_iterations = 1; - cholmod_sparse* cholmod_lhs = NULL; - if (options().use_postordering) { - // If we are going to do a full symbolic analysis of the schur - // complement matrix from scratch and not rely on the - // pre-ordering, then the fastest path in cholmod_factorize is the - // one corresponding to upper triangular matrices. - - // Create a upper triangular symmetric matrix. - cholmod_lhs = ss_.CreateSparseMatrix(tsm); - cholmod_lhs->stype = 1; - - if (factor_ == NULL) { - factor_ = ss_.BlockAnalyzeCholesky(cholmod_lhs, - blocks_, - blocks_, - &summary.message); - } - } else { - // If we are going to use the natural ordering (i.e. rely on the - // pre-ordering computed by solver_impl.cc), then the fastest - // path in cholmod_factorize is the one corresponding to lower - // triangular matrices. - - // Create a upper triangular symmetric matrix. - cholmod_lhs = ss_.CreateSparseMatrixTranspose(tsm); - cholmod_lhs->stype = -1; - - if (factor_ == NULL) { - factor_ = ss_.AnalyzeCholeskyWithNaturalOrdering(cholmod_lhs, - &summary.message); - } - } - - if (factor_ == NULL) { - ss_.Free(cholmod_lhs); - summary.termination_type = LINEAR_SOLVER_FATAL_ERROR; - // No need to set message as it has already been set by the - // symbolic analysis routines above. - return summary; - } - - summary.termination_type = - ss_.Cholesky(cholmod_lhs, factor_, &summary.message); - - ss_.Free(cholmod_lhs); - - if (summary.termination_type != LINEAR_SOLVER_SUCCESS) { - // No need to set message as it has already been set by the - // numeric factorization routine above. - return summary; - } - - cholmod_dense* cholmod_rhs = - ss_.CreateDenseVector(const_cast<double*>(rhs()), num_rows, num_rows); - cholmod_dense* cholmod_solution = ss_.Solve(factor_, - cholmod_rhs, - &summary.message); - ss_.Free(cholmod_rhs); - - if (cholmod_solution == NULL) { - summary.message = - "SuiteSparse failure. Unable to perform triangular solve."; - summary.termination_type = LINEAR_SOLVER_FAILURE; - return summary; - } - - VectorRef(solution, num_rows) - = VectorRef(static_cast<double*>(cholmod_solution->x), num_rows); - ss_.Free(cholmod_solution); - return summary; -#endif // CERES_NO_SUITESPARSE -} - -// Solve the system Sx = r, assuming that the matrix S is stored in a -// BlockRandomAccessSparseMatrix. The linear system is solved using -// CXSparse's sparse cholesky factorization routines. -LinearSolver::Summary -SparseSchurComplementSolver::SolveReducedLinearSystemUsingCXSparse( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution) { -#ifdef CERES_NO_CXSPARSE - - LinearSolver::Summary summary; - summary.num_iterations = 0; - summary.termination_type = LINEAR_SOLVER_FATAL_ERROR; - summary.message = "Ceres was not built with CXSparse support. " - "Therefore, SPARSE_SCHUR cannot be used with CX_SPARSE"; - return summary; - -#else - - LinearSolver::Summary summary; - summary.num_iterations = 0; - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = "Success."; - - // Extract the TripletSparseMatrix that is used for actually storing S. - TripletSparseMatrix* tsm = - const_cast<TripletSparseMatrix*>( - down_cast<const BlockRandomAccessSparseMatrix*>(lhs())->matrix()); - const int num_rows = tsm->num_rows(); - - // The case where there are no f blocks, and the system is block - // diagonal. - if (num_rows == 0) { - return summary; - } - - cs_di* lhs = CHECK_NOTNULL(cxsparse_.CreateSparseMatrix(tsm)); - VectorRef(solution, num_rows) = ConstVectorRef(rhs(), num_rows); - - // Compute symbolic factorization if not available. - if (cxsparse_factor_ == NULL) { - cxsparse_factor_ = cxsparse_.BlockAnalyzeCholesky(lhs, blocks_, blocks_); - } - - if (cxsparse_factor_ == NULL) { - summary.termination_type = LINEAR_SOLVER_FATAL_ERROR; - summary.message = - "CXSparse failure. Unable to find symbolic factorization."; - } else if (!cxsparse_.SolveCholesky(lhs, cxsparse_factor_, solution)) { - summary.termination_type = LINEAR_SOLVER_FAILURE; - summary.message = "CXSparse::SolveCholesky failed."; - } - - cxsparse_.Free(lhs); - return summary; -#endif // CERES_NO_CXPARSE -} - -// Solve the system Sx = r, assuming that the matrix S is stored in a -// BlockRandomAccessSparseMatrix. The linear system is solved using -// Eigen's sparse cholesky factorization routines. -LinearSolver::Summary -SparseSchurComplementSolver::SolveReducedLinearSystemUsingEigen( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution) { -#ifndef CERES_USE_EIGEN_SPARSE - - LinearSolver::Summary summary; - summary.num_iterations = 0; - summary.termination_type = LINEAR_SOLVER_FATAL_ERROR; - summary.message = - "SPARSE_SCHUR cannot be used with EIGEN_SPARSE. " - "Ceres was not built with support for " - "Eigen's SimplicialLDLT decomposition. " - "This requires enabling building with -DEIGENSPARSE=ON."; - return summary; - -#else - EventLogger event_logger("SchurComplementSolver::EigenSolve"); - LinearSolver::Summary summary; - summary.num_iterations = 0; - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = "Success."; - - // Extract the TripletSparseMatrix that is used for actually storing S. - TripletSparseMatrix* tsm = - const_cast<TripletSparseMatrix*>( - down_cast<const BlockRandomAccessSparseMatrix*>(lhs())->matrix()); - const int num_rows = tsm->num_rows(); - - // The case where there are no f blocks, and the system is block - // diagonal. - if (num_rows == 0) { - return summary; - } - - // This is an upper triangular matrix. - CompressedRowSparseMatrix crsm(*tsm); - // Map this to a column major, lower triangular matrix. - Eigen::MappedSparseMatrix<double, Eigen::ColMajor> eigen_lhs( - crsm.num_rows(), - crsm.num_rows(), - crsm.num_nonzeros(), - crsm.mutable_rows(), - crsm.mutable_cols(), - crsm.mutable_values()); - event_logger.AddEvent("ToCompressedRowSparseMatrix"); - - // Compute symbolic factorization if one does not exist. - if (simplicial_ldlt_.get() == NULL) { - simplicial_ldlt_.reset(new SimplicialLDLT); - // This ordering is quite bad. The scalar ordering produced by the - // AMD algorithm is quite bad and can be an order of magnitude - // worse than the one computed using the block version of the - // algorithm. - simplicial_ldlt_->analyzePattern(eigen_lhs); - event_logger.AddEvent("Analysis"); - if (simplicial_ldlt_->info() != Eigen::Success) { - summary.termination_type = LINEAR_SOLVER_FATAL_ERROR; - summary.message = - "Eigen failure. Unable to find symbolic factorization."; - return summary; - } - } - - simplicial_ldlt_->factorize(eigen_lhs); - event_logger.AddEvent("Factorize"); - if (simplicial_ldlt_->info() != Eigen::Success) { - summary.termination_type = LINEAR_SOLVER_FAILURE; - summary.message = "Eigen failure. Unable to find numeric factoriztion."; - return summary; - } - - VectorRef(solution, num_rows) = - simplicial_ldlt_->solve(ConstVectorRef(rhs(), num_rows)); - event_logger.AddEvent("Solve"); - if (simplicial_ldlt_->info() != Eigen::Success) { - summary.termination_type = LINEAR_SOLVER_FAILURE; - summary.message = "Eigen failure. Unable to do triangular solve."; - } - - return summary; -#endif // CERES_USE_EIGEN_SPARSE -} - -LinearSolver::Summary -SparseSchurComplementSolver::SolveReducedLinearSystemUsingConjugateGradients( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution) { - const int num_rows = lhs()->num_rows(); - // The case where there are no f blocks, and the system is block - // diagonal. - if (num_rows == 0) { - LinearSolver::Summary summary; - summary.num_iterations = 0; - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = "Success."; - return summary; - } - - // Only SCHUR_JACOBI is supported over here right now. - CHECK_EQ(options().preconditioner_type, SCHUR_JACOBI); - - if (preconditioner_.get() == NULL) { - preconditioner_.reset(new BlockRandomAccessDiagonalMatrix(blocks_)); - } - - BlockRandomAccessSparseMatrix* sc = - down_cast<BlockRandomAccessSparseMatrix*>( - const_cast<BlockRandomAccessMatrix*>(lhs())); - - // Extract block diagonal from the Schur complement to construct the - // schur_jacobi preconditioner. - for (int i = 0; i < blocks_.size(); ++i) { - const int block_size = blocks_[i]; - - int sc_r, sc_c, sc_row_stride, sc_col_stride; - CellInfo* sc_cell_info = - CHECK_NOTNULL(sc->GetCell(i, i, - &sc_r, &sc_c, - &sc_row_stride, &sc_col_stride)); - MatrixRef sc_m(sc_cell_info->values, sc_row_stride, sc_col_stride); - - int pre_r, pre_c, pre_row_stride, pre_col_stride; - CellInfo* pre_cell_info = CHECK_NOTNULL( - preconditioner_->GetCell(i, i, - &pre_r, &pre_c, - &pre_row_stride, &pre_col_stride)); - MatrixRef pre_m(pre_cell_info->values, pre_row_stride, pre_col_stride); - - pre_m.block(pre_r, pre_c, block_size, block_size) = - sc_m.block(sc_r, sc_c, block_size, block_size); - } - preconditioner_->Invert(); - - VectorRef(solution, num_rows).setZero(); - - scoped_ptr<LinearOperator> lhs_adapter( - new BlockRandomAccessSparseMatrixAdapter(*sc)); - scoped_ptr<LinearOperator> preconditioner_adapter( - new BlockRandomAccessDiagonalMatrixAdapter(*preconditioner_)); - - - LinearSolver::Options cg_options; - cg_options.min_num_iterations = options().min_num_iterations; - cg_options.max_num_iterations = options().max_num_iterations; - ConjugateGradientsSolver cg_solver(cg_options); - - LinearSolver::PerSolveOptions cg_per_solve_options; - cg_per_solve_options.r_tolerance = per_solve_options.r_tolerance; - cg_per_solve_options.q_tolerance = per_solve_options.q_tolerance; - cg_per_solve_options.preconditioner = preconditioner_adapter.get(); - - return cg_solver.Solve(lhs_adapter.get(), - rhs(), - cg_per_solve_options, - solution); -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.h b/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.h deleted file mode 100644 index 714dafc5b0c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.h +++ /dev/null @@ -1,226 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_SCHUR_COMPLEMENT_SOLVER_H_ -#define CERES_INTERNAL_SCHUR_COMPLEMENT_SOLVER_H_ - -#include <set> -#include <utility> -#include <vector> - -#include "ceres/internal/port.h" - -#include "ceres/block_random_access_matrix.h" -#include "ceres/block_sparse_matrix.h" -#include "ceres/block_structure.h" -#include "ceres/cxsparse.h" -#include "ceres/linear_solver.h" -#include "ceres/schur_eliminator.h" -#include "ceres/suitesparse.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/types.h" -#include "ceres/block_random_access_diagonal_matrix.h" - -#ifdef CERES_USE_EIGEN_SPARSE -#include "Eigen/SparseCholesky" -#include "Eigen/OrderingMethods" -#endif - -namespace ceres { -namespace internal { - -class BlockSparseMatrix; - -// Base class for Schur complement based linear least squares -// solvers. It assumes that the input linear system Ax = b can be -// partitioned into -// -// E y + F z = b -// -// Where x = [y;z] is a partition of the variables. The paritioning -// of the variables is such that, E'E is a block diagonal -// matrix. Further, the rows of A are ordered so that for every -// variable block in y, all the rows containing that variable block -// occur as a vertically contiguous block. i.e the matrix A looks like -// -// E F -// A = [ y1 0 0 0 | z1 0 0 0 z5] -// [ y1 0 0 0 | z1 z2 0 0 0] -// [ 0 y2 0 0 | 0 0 z3 0 0] -// [ 0 0 y3 0 | z1 z2 z3 z4 z5] -// [ 0 0 y3 0 | z1 0 0 0 z5] -// [ 0 0 0 y4 | 0 0 0 0 z5] -// [ 0 0 0 y4 | 0 z2 0 0 0] -// [ 0 0 0 y4 | 0 0 0 0 0] -// [ 0 0 0 0 | z1 0 0 0 0] -// [ 0 0 0 0 | 0 0 z3 z4 z5] -// -// This structure should be reflected in the corresponding -// CompressedRowBlockStructure object associated with A. The linear -// system Ax = b should either be well posed or the array D below -// should be non-null and the diagonal matrix corresponding to it -// should be non-singular. -// -// SchurComplementSolver has two sub-classes. -// -// DenseSchurComplementSolver: For problems where the Schur complement -// matrix is small and dense, or if CHOLMOD/SuiteSparse is not -// installed. For structure from motion problems, this is solver can -// be used for problems with upto a few hundred cameras. -// -// SparseSchurComplementSolver: For problems where the Schur -// complement matrix is large and sparse. It requires that -// CHOLMOD/SuiteSparse be installed, as it uses CHOLMOD to find a -// sparse Cholesky factorization of the Schur complement. This solver -// can be used for solving structure from motion problems with tens of -// thousands of cameras, though depending on the exact sparsity -// structure, it maybe better to use an iterative solver. -// -// The two solvers can be instantiated by calling -// LinearSolver::CreateLinearSolver with LinearSolver::Options::type -// set to DENSE_SCHUR and SPARSE_SCHUR -// respectively. LinearSolver::Options::elimination_groups[0] should be -// at least 1. -class SchurComplementSolver : public BlockSparseMatrixSolver { - public: - explicit SchurComplementSolver(const LinearSolver::Options& options) - : options_(options) { - CHECK_GT(options.elimination_groups.size(), 1); - CHECK_GT(options.elimination_groups[0], 0); - } - - // LinearSolver methods - virtual ~SchurComplementSolver() {} - virtual LinearSolver::Summary SolveImpl( - BlockSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double* x); - - protected: - const LinearSolver::Options& options() const { return options_; } - - const BlockRandomAccessMatrix* lhs() const { return lhs_.get(); } - void set_lhs(BlockRandomAccessMatrix* lhs) { lhs_.reset(lhs); } - const double* rhs() const { return rhs_.get(); } - void set_rhs(double* rhs) { rhs_.reset(rhs); } - - private: - virtual void InitStorage(const CompressedRowBlockStructure* bs) = 0; - virtual LinearSolver::Summary SolveReducedLinearSystem( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution) = 0; - - LinearSolver::Options options_; - - scoped_ptr<SchurEliminatorBase> eliminator_; - scoped_ptr<BlockRandomAccessMatrix> lhs_; - scoped_array<double> rhs_; - - CERES_DISALLOW_COPY_AND_ASSIGN(SchurComplementSolver); -}; - -// Dense Cholesky factorization based solver. -class DenseSchurComplementSolver : public SchurComplementSolver { - public: - explicit DenseSchurComplementSolver(const LinearSolver::Options& options) - : SchurComplementSolver(options) {} - virtual ~DenseSchurComplementSolver() {} - - private: - virtual void InitStorage(const CompressedRowBlockStructure* bs); - virtual LinearSolver::Summary SolveReducedLinearSystem( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution); - - CERES_DISALLOW_COPY_AND_ASSIGN(DenseSchurComplementSolver); -}; - -// Sparse Cholesky factorization based solver. -class SparseSchurComplementSolver : public SchurComplementSolver { - public: - explicit SparseSchurComplementSolver(const LinearSolver::Options& options); - virtual ~SparseSchurComplementSolver(); - - private: - virtual void InitStorage(const CompressedRowBlockStructure* bs); - virtual LinearSolver::Summary SolveReducedLinearSystem( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution); - LinearSolver::Summary SolveReducedLinearSystemUsingSuiteSparse( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution); - LinearSolver::Summary SolveReducedLinearSystemUsingCXSparse( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution); - LinearSolver::Summary SolveReducedLinearSystemUsingEigen( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution); - LinearSolver::Summary SolveReducedLinearSystemUsingConjugateGradients( - const LinearSolver::PerSolveOptions& per_solve_options, - double* solution); - - // Size of the blocks in the Schur complement. - std::vector<int> blocks_; - - SuiteSparse ss_; - // Symbolic factorization of the reduced linear system. Precomputed - // once and reused in subsequent calls. - cholmod_factor* factor_; - - CXSparse cxsparse_; - // Cached factorization - cs_dis* cxsparse_factor_; - -#ifdef CERES_USE_EIGEN_SPARSE - - // The preprocessor gymnastics here are dealing with the fact that - // before version 3.2.2, Eigen did not support a third template - // parameter to specify the ordering. -#if EIGEN_VERSION_AT_LEAST(3,2,2) - typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>, Eigen::Lower, - Eigen::NaturalOrdering<int> > - SimplicialLDLT; -#else - typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>, Eigen::Lower> - SimplicialLDLT; -#endif - - scoped_ptr<SimplicialLDLT> simplicial_ldlt_; -#endif - - scoped_ptr<BlockRandomAccessDiagonalMatrix> preconditioner_; - CERES_DISALLOW_COPY_AND_ASSIGN(SparseSchurComplementSolver); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_SCHUR_COMPLEMENT_SOLVER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/schur_eliminator.cc b/extern/libmv/third_party/ceres/internal/ceres/schur_eliminator.cc deleted file mode 100644 index ec0e2a020e5..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/schur_eliminator.cc +++ /dev/null @@ -1,163 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Template specialization of SchurEliminator. -// -// ======================================== -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -// THIS FILE IS AUTOGENERATED. DO NOT EDIT. -//========================================= -// -// This file is generated using generate_eliminator_specialization.py. -// Editing it manually is not recommended. - -#include "ceres/linear_solver.h" -#include "ceres/schur_eliminator.h" -#include "ceres/internal/eigen.h" - -namespace ceres { -namespace internal { - -SchurEliminatorBase* -SchurEliminatorBase::Create(const LinearSolver::Options& options) { -#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION - if ((options.row_block_size == 2) && - (options.e_block_size == 2) && - (options.f_block_size == 2)) { - return new SchurEliminator<2, 2, 2>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 2) && - (options.f_block_size == 3)) { - return new SchurEliminator<2, 2, 3>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 2) && - (options.f_block_size == 4)) { - return new SchurEliminator<2, 2, 4>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 2) && - (options.f_block_size == Eigen::Dynamic)) { - return new SchurEliminator<2, 2, Eigen::Dynamic>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 3) && - (options.f_block_size == 3)) { - return new SchurEliminator<2, 3, 3>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 3) && - (options.f_block_size == 4)) { - return new SchurEliminator<2, 3, 4>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 3) && - (options.f_block_size == 6)) { - return new SchurEliminator<2, 3, 6>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 3) && - (options.f_block_size == 9)) { - return new SchurEliminator<2, 3, 9>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 3) && - (options.f_block_size == Eigen::Dynamic)) { - return new SchurEliminator<2, 3, Eigen::Dynamic>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 4) && - (options.f_block_size == 3)) { - return new SchurEliminator<2, 4, 3>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 4) && - (options.f_block_size == 4)) { - return new SchurEliminator<2, 4, 4>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 4) && - (options.f_block_size == 8)) { - return new SchurEliminator<2, 4, 8>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 4) && - (options.f_block_size == 9)) { - return new SchurEliminator<2, 4, 9>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == 4) && - (options.f_block_size == Eigen::Dynamic)) { - return new SchurEliminator<2, 4, Eigen::Dynamic>(options); - } - if ((options.row_block_size == 2) && - (options.e_block_size == Eigen::Dynamic) && - (options.f_block_size == Eigen::Dynamic)) { - return new SchurEliminator<2, Eigen::Dynamic, Eigen::Dynamic>(options); - } - if ((options.row_block_size == 4) && - (options.e_block_size == 4) && - (options.f_block_size == 2)) { - return new SchurEliminator<4, 4, 2>(options); - } - if ((options.row_block_size == 4) && - (options.e_block_size == 4) && - (options.f_block_size == 3)) { - return new SchurEliminator<4, 4, 3>(options); - } - if ((options.row_block_size == 4) && - (options.e_block_size == 4) && - (options.f_block_size == 4)) { - return new SchurEliminator<4, 4, 4>(options); - } - if ((options.row_block_size == 4) && - (options.e_block_size == 4) && - (options.f_block_size == Eigen::Dynamic)) { - return new SchurEliminator<4, 4, Eigen::Dynamic>(options); - } - if ((options.row_block_size == Eigen::Dynamic) && - (options.e_block_size == Eigen::Dynamic) && - (options.f_block_size == Eigen::Dynamic)) { - return new SchurEliminator<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic>(options); - } - -#endif - VLOG(1) << "Template specializations not found for <" - << options.row_block_size << "," - << options.e_block_size << "," - << options.f_block_size << ">"; - return new SchurEliminator<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic>(options); -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/schur_eliminator.h b/extern/libmv/third_party/ceres/internal/ceres/schur_eliminator.h deleted file mode 100644 index 761b58adc7f..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/schur_eliminator.h +++ /dev/null @@ -1,355 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_SCHUR_ELIMINATOR_H_ -#define CERES_INTERNAL_SCHUR_ELIMINATOR_H_ - -#include <map> -#include <vector> -#include "ceres/mutex.h" -#include "ceres/block_random_access_matrix.h" -#include "ceres/block_sparse_matrix.h" -#include "ceres/block_structure.h" -#include "ceres/linear_solver.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" - -namespace ceres { -namespace internal { - -// Classes implementing the SchurEliminatorBase interface implement -// variable elimination for linear least squares problems. Assuming -// that the input linear system Ax = b can be partitioned into -// -// E y + F z = b -// -// Where x = [y;z] is a partition of the variables. The paritioning -// of the variables is such that, E'E is a block diagonal matrix. Or -// in other words, the parameter blocks in E form an independent set -// of the of the graph implied by the block matrix A'A. Then, this -// class provides the functionality to compute the Schur complement -// system -// -// S z = r -// -// where -// -// S = F'F - F'E (E'E)^{-1} E'F and r = F'b - F'E(E'E)^(-1) E'b -// -// This is the Eliminate operation, i.e., construct the linear system -// obtained by eliminating the variables in E. -// -// The eliminator also provides the reverse functionality, i.e. given -// values for z it can back substitute for the values of y, by solving the -// linear system -// -// Ey = b - F z -// -// which is done by observing that -// -// y = (E'E)^(-1) [E'b - E'F z] -// -// The eliminator has a number of requirements. -// -// The rows of A are ordered so that for every variable block in y, -// all the rows containing that variable block occur as a vertically -// contiguous block. i.e the matrix A looks like -// -// E F chunk -// A = [ y1 0 0 0 | z1 0 0 0 z5] 1 -// [ y1 0 0 0 | z1 z2 0 0 0] 1 -// [ 0 y2 0 0 | 0 0 z3 0 0] 2 -// [ 0 0 y3 0 | z1 z2 z3 z4 z5] 3 -// [ 0 0 y3 0 | z1 0 0 0 z5] 3 -// [ 0 0 0 y4 | 0 0 0 0 z5] 4 -// [ 0 0 0 y4 | 0 z2 0 0 0] 4 -// [ 0 0 0 y4 | 0 0 0 0 0] 4 -// [ 0 0 0 0 | z1 0 0 0 0] non chunk blocks -// [ 0 0 0 0 | 0 0 z3 z4 z5] non chunk blocks -// -// This structure should be reflected in the corresponding -// CompressedRowBlockStructure object associated with A. The linear -// system Ax = b should either be well posed or the array D below -// should be non-null and the diagonal matrix corresponding to it -// should be non-singular. For simplicity of exposition only the case -// with a null D is described. -// -// The usual way to do the elimination is as follows. Starting with -// -// E y + F z = b -// -// we can form the normal equations, -// -// E'E y + E'F z = E'b -// F'E y + F'F z = F'b -// -// multiplying both sides of the first equation by (E'E)^(-1) and then -// by F'E we get -// -// F'E y + F'E (E'E)^(-1) E'F z = F'E (E'E)^(-1) E'b -// F'E y + F'F z = F'b -// -// now subtracting the two equations we get -// -// [FF' - F'E (E'E)^(-1) E'F] z = F'b - F'E(E'E)^(-1) E'b -// -// Instead of forming the normal equations and operating on them as -// general sparse matrices, the algorithm here deals with one -// parameter block in y at a time. The rows corresponding to a single -// parameter block yi are known as a chunk, and the algorithm operates -// on one chunk at a time. The mathematics remains the same since the -// reduced linear system can be shown to be the sum of the reduced -// linear systems for each chunk. This can be seen by observing two -// things. -// -// 1. E'E is a block diagonal matrix. -// -// 2. When E'F is computed, only the terms within a single chunk -// interact, i.e for y1 column blocks when transposed and multiplied -// with F, the only non-zero contribution comes from the blocks in -// chunk1. -// -// Thus, the reduced linear system -// -// FF' - F'E (E'E)^(-1) E'F -// -// can be re-written as -// -// sum_k F_k F_k' - F_k'E_k (E_k'E_k)^(-1) E_k' F_k -// -// Where the sum is over chunks and E_k'E_k is dense matrix of size y1 -// x y1. -// -// Advanced usage. Uptil now it has been assumed that the user would -// be interested in all of the Schur Complement S. However, it is also -// possible to use this eliminator to obtain an arbitrary submatrix of -// the full Schur complement. When the eliminator is generating the -// blocks of S, it asks the RandomAccessBlockMatrix instance passed to -// it if it has storage for that block. If it does, the eliminator -// computes/updates it, if not it is skipped. This is useful when one -// is interested in constructing a preconditioner based on the Schur -// Complement, e.g., computing the block diagonal of S so that it can -// be used as a preconditioner for an Iterative Substructuring based -// solver [See Agarwal et al, Bundle Adjustment in the Large, ECCV -// 2008 for an example of such use]. -// -// Example usage: Please see schur_complement_solver.cc -class SchurEliminatorBase { - public: - virtual ~SchurEliminatorBase() {} - - // Initialize the eliminator. It is the user's responsibilty to call - // this function before calling Eliminate or BackSubstitute. It is - // also the caller's responsibilty to ensure that the - // CompressedRowBlockStructure object passed to this method is the - // same one (or is equivalent to) the one associated with the - // BlockSparseMatrix objects below. - virtual void Init(int num_eliminate_blocks, - const CompressedRowBlockStructure* bs) = 0; - - // Compute the Schur complement system from the augmented linear - // least squares problem [A;D] x = [b;0]. The left hand side and the - // right hand side of the reduced linear system are returned in lhs - // and rhs respectively. - // - // It is the caller's responsibility to construct and initialize - // lhs. Depending upon the structure of the lhs object passed here, - // the full or a submatrix of the Schur complement will be computed. - // - // Since the Schur complement is a symmetric matrix, only the upper - // triangular part of the Schur complement is computed. - virtual void Eliminate(const BlockSparseMatrix* A, - const double* b, - const double* D, - BlockRandomAccessMatrix* lhs, - double* rhs) = 0; - - // Given values for the variables z in the F block of A, solve for - // the optimal values of the variables y corresponding to the E - // block in A. - virtual void BackSubstitute(const BlockSparseMatrix* A, - const double* b, - const double* D, - const double* z, - double* y) = 0; - // Factory - static SchurEliminatorBase* Create(const LinearSolver::Options& options); -}; - -// Templated implementation of the SchurEliminatorBase interface. The -// templating is on the sizes of the row, e and f blocks sizes in the -// input matrix. In many problems, the sizes of one or more of these -// blocks are constant, in that case, its worth passing these -// parameters as template arguments so that they are visible to the -// compiler and can be used for compile time optimization of the low -// level linear algebra routines. -// -// This implementation is mulithreaded using OpenMP. The level of -// parallelism is controlled by LinearSolver::Options::num_threads. -template <int kRowBlockSize = Eigen::Dynamic, - int kEBlockSize = Eigen::Dynamic, - int kFBlockSize = Eigen::Dynamic > -class SchurEliminator : public SchurEliminatorBase { - public: - explicit SchurEliminator(const LinearSolver::Options& options) - : num_threads_(options.num_threads) { - } - - // SchurEliminatorBase Interface - virtual ~SchurEliminator(); - virtual void Init(int num_eliminate_blocks, - const CompressedRowBlockStructure* bs); - virtual void Eliminate(const BlockSparseMatrix* A, - const double* b, - const double* D, - BlockRandomAccessMatrix* lhs, - double* rhs); - virtual void BackSubstitute(const BlockSparseMatrix* A, - const double* b, - const double* D, - const double* z, - double* y); - - private: - // Chunk objects store combinatorial information needed to - // efficiently eliminate a whole chunk out of the least squares - // problem. Consider the first chunk in the example matrix above. - // - // [ y1 0 0 0 | z1 0 0 0 z5] - // [ y1 0 0 0 | z1 z2 0 0 0] - // - // One of the intermediate quantities that needs to be calculated is - // for each row the product of the y block transposed with the - // non-zero z block, and the sum of these blocks across rows. A - // temporary array "buffer_" is used for computing and storing them - // and the buffer_layout maps the indices of the z-blocks to - // position in the buffer_ array. The size of the chunk is the - // number of row blocks/residual blocks for the particular y block - // being considered. - // - // For the example chunk shown above, - // - // size = 2 - // - // The entries of buffer_layout will be filled in the following order. - // - // buffer_layout[z1] = 0 - // buffer_layout[z5] = y1 * z1 - // buffer_layout[z2] = y1 * z1 + y1 * z5 - typedef std::map<int, int> BufferLayoutType; - struct Chunk { - Chunk() : size(0) {} - int size; - int start; - BufferLayoutType buffer_layout; - }; - - void ChunkDiagonalBlockAndGradient( - const Chunk& chunk, - const BlockSparseMatrix* A, - const double* b, - int row_block_counter, - typename EigenTypes<kEBlockSize, kEBlockSize>::Matrix* eet, - double* g, - double* buffer, - BlockRandomAccessMatrix* lhs); - - void UpdateRhs(const Chunk& chunk, - const BlockSparseMatrix* A, - const double* b, - int row_block_counter, - const double* inverse_ete_g, - double* rhs); - - void ChunkOuterProduct(const CompressedRowBlockStructure* bs, - const Matrix& inverse_eet, - const double* buffer, - const BufferLayoutType& buffer_layout, - BlockRandomAccessMatrix* lhs); - void EBlockRowOuterProduct(const BlockSparseMatrix* A, - int row_block_index, - BlockRandomAccessMatrix* lhs); - - - void NoEBlockRowsUpdate(const BlockSparseMatrix* A, - const double* b, - int row_block_counter, - BlockRandomAccessMatrix* lhs, - double* rhs); - - void NoEBlockRowOuterProduct(const BlockSparseMatrix* A, - int row_block_index, - BlockRandomAccessMatrix* lhs); - - int num_eliminate_blocks_; - - // Block layout of the columns of the reduced linear system. Since - // the f blocks can be of varying size, this vector stores the - // position of each f block in the row/col of the reduced linear - // system. Thus lhs_row_layout_[i] is the row/col position of the - // i^th f block. - std::vector<int> lhs_row_layout_; - - // Combinatorial structure of the chunks in A. For more information - // see the documentation of the Chunk object above. - std::vector<Chunk> chunks_; - - // TODO(sameeragarwal): The following two arrays contain per-thread - // storage. They should be refactored into a per thread struct. - - // Buffer to store the products of the y and z blocks generated - // during the elimination phase. buffer_ is of size num_threads * - // buffer_size_. Each thread accesses the chunk - // - // [thread_id * buffer_size_ , (thread_id + 1) * buffer_size_] - // - scoped_array<double> buffer_; - - // Buffer to store per thread matrix matrix products used by - // ChunkOuterProduct. Like buffer_ it is of size num_threads * - // buffer_size_. Each thread accesses the chunk - // - // [thread_id * buffer_size_ , (thread_id + 1) * buffer_size_ -1] - // - scoped_array<double> chunk_outer_product_buffer_; - - int buffer_size_; - int num_threads_; - int uneliminated_row_begins_; - - // Locks for the blocks in the right hand side of the reduced linear - // system. - std::vector<Mutex*> rhs_locks_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_SCHUR_ELIMINATOR_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/schur_eliminator_impl.h b/extern/libmv/third_party/ceres/internal/ceres/schur_eliminator_impl.h deleted file mode 100644 index f2535880f15..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/schur_eliminator_impl.h +++ /dev/null @@ -1,698 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// TODO(sameeragarwal): row_block_counter can perhaps be replaced by -// Chunk::start ? - -#ifndef CERES_INTERNAL_SCHUR_ELIMINATOR_IMPL_H_ -#define CERES_INTERNAL_SCHUR_ELIMINATOR_IMPL_H_ - -// Eigen has an internal threshold switching between different matrix -// multiplication algorithms. In particular for matrices larger than -// EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD it uses a cache friendly -// matrix matrix product algorithm that has a higher setup cost. For -// matrix sizes close to this threshold, especially when the matrices -// are thin and long, the default choice may not be optimal. This is -// the case for us, as the default choice causes a 30% performance -// regression when we moved from Eigen2 to Eigen3. - -#define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD 10 - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifdef CERES_USE_OPENMP -#include <omp.h> -#endif - -#include <algorithm> -#include <map> -#include "ceres/block_random_access_matrix.h" -#include "ceres/block_sparse_matrix.h" -#include "ceres/block_structure.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/fixed_array.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/map_util.h" -#include "ceres/schur_eliminator.h" -#include "ceres/small_blas.h" -#include "ceres/stl_util.h" -#include "Eigen/Dense" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>::~SchurEliminator() { - STLDeleteElements(&rhs_locks_); -} - -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>:: -Init(int num_eliminate_blocks, const CompressedRowBlockStructure* bs) { - CHECK_GT(num_eliminate_blocks, 0) - << "SchurComplementSolver cannot be initialized with " - << "num_eliminate_blocks = 0."; - - num_eliminate_blocks_ = num_eliminate_blocks; - - const int num_col_blocks = bs->cols.size(); - const int num_row_blocks = bs->rows.size(); - - buffer_size_ = 1; - chunks_.clear(); - lhs_row_layout_.clear(); - - int lhs_num_rows = 0; - // Add a map object for each block in the reduced linear system - // and build the row/column block structure of the reduced linear - // system. - lhs_row_layout_.resize(num_col_blocks - num_eliminate_blocks_); - for (int i = num_eliminate_blocks_; i < num_col_blocks; ++i) { - lhs_row_layout_[i - num_eliminate_blocks_] = lhs_num_rows; - lhs_num_rows += bs->cols[i].size; - } - - int r = 0; - // Iterate over the row blocks of A, and detect the chunks. The - // matrix should already have been ordered so that all rows - // containing the same y block are vertically contiguous. Along - // the way also compute the amount of space each chunk will need - // to perform the elimination. - while (r < num_row_blocks) { - const int chunk_block_id = bs->rows[r].cells.front().block_id; - if (chunk_block_id >= num_eliminate_blocks_) { - break; - } - - chunks_.push_back(Chunk()); - Chunk& chunk = chunks_.back(); - chunk.size = 0; - chunk.start = r; - int buffer_size = 0; - const int e_block_size = bs->cols[chunk_block_id].size; - - // Add to the chunk until the first block in the row is - // different than the one in the first row for the chunk. - while (r + chunk.size < num_row_blocks) { - const CompressedRow& row = bs->rows[r + chunk.size]; - if (row.cells.front().block_id != chunk_block_id) { - break; - } - - // Iterate over the blocks in the row, ignoring the first - // block since it is the one to be eliminated. - for (int c = 1; c < row.cells.size(); ++c) { - const Cell& cell = row.cells[c]; - if (InsertIfNotPresent( - &(chunk.buffer_layout), cell.block_id, buffer_size)) { - buffer_size += e_block_size * bs->cols[cell.block_id].size; - } - } - - buffer_size_ = std::max(buffer_size, buffer_size_); - ++chunk.size; - } - - CHECK_GT(chunk.size, 0); - r += chunk.size; - } - const Chunk& chunk = chunks_.back(); - - uneliminated_row_begins_ = chunk.start + chunk.size; - if (num_threads_ > 1) { - random_shuffle(chunks_.begin(), chunks_.end()); - } - - buffer_.reset(new double[buffer_size_ * num_threads_]); - - // chunk_outer_product_buffer_ only needs to store e_block_size * - // f_block_size, which is always less than buffer_size_, so we just - // allocate buffer_size_ per thread. - chunk_outer_product_buffer_.reset(new double[buffer_size_ * num_threads_]); - - STLDeleteElements(&rhs_locks_); - rhs_locks_.resize(num_col_blocks - num_eliminate_blocks_); - for (int i = 0; i < num_col_blocks - num_eliminate_blocks_; ++i) { - rhs_locks_[i] = new Mutex; - } -} - -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>:: -Eliminate(const BlockSparseMatrix* A, - const double* b, - const double* D, - BlockRandomAccessMatrix* lhs, - double* rhs) { - if (lhs->num_rows() > 0) { - lhs->SetZero(); - VectorRef(rhs, lhs->num_rows()).setZero(); - } - - const CompressedRowBlockStructure* bs = A->block_structure(); - const int num_col_blocks = bs->cols.size(); - - // Add the diagonal to the schur complement. - if (D != NULL) { -#pragma omp parallel for num_threads(num_threads_) schedule(dynamic) - for (int i = num_eliminate_blocks_; i < num_col_blocks; ++i) { - const int block_id = i - num_eliminate_blocks_; - int r, c, row_stride, col_stride; - CellInfo* cell_info = lhs->GetCell(block_id, block_id, - &r, &c, - &row_stride, &col_stride); - if (cell_info != NULL) { - const int block_size = bs->cols[i].size; - typename EigenTypes<Eigen::Dynamic>::ConstVectorRef - diag(D + bs->cols[i].position, block_size); - - CeresMutexLock l(&cell_info->m); - MatrixRef m(cell_info->values, row_stride, col_stride); - m.block(r, c, block_size, block_size).diagonal() - += diag.array().square().matrix(); - } - } - } - - // Eliminate y blocks one chunk at a time. For each chunk, compute - // the entries of the normal equations and the gradient vector block - // corresponding to the y block and then apply Gaussian elimination - // to them. The matrix ete stores the normal matrix corresponding to - // the block being eliminated and array buffer_ contains the - // non-zero blocks in the row corresponding to this y block in the - // normal equations. This computation is done in - // ChunkDiagonalBlockAndGradient. UpdateRhs then applies gaussian - // elimination to the rhs of the normal equations, updating the rhs - // of the reduced linear system by modifying rhs blocks for all the - // z blocks that share a row block/residual term with the y - // block. EliminateRowOuterProduct does the corresponding operation - // for the lhs of the reduced linear system. -#pragma omp parallel for num_threads(num_threads_) schedule(dynamic) - for (int i = 0; i < chunks_.size(); ++i) { -#ifdef CERES_USE_OPENMP - int thread_id = omp_get_thread_num(); -#else - int thread_id = 0; -#endif - double* buffer = buffer_.get() + thread_id * buffer_size_; - const Chunk& chunk = chunks_[i]; - const int e_block_id = bs->rows[chunk.start].cells.front().block_id; - const int e_block_size = bs->cols[e_block_id].size; - - VectorRef(buffer, buffer_size_).setZero(); - - typename EigenTypes<kEBlockSize, kEBlockSize>::Matrix - ete(e_block_size, e_block_size); - - if (D != NULL) { - const typename EigenTypes<kEBlockSize>::ConstVectorRef - diag(D + bs->cols[e_block_id].position, e_block_size); - ete = diag.array().square().matrix().asDiagonal(); - } else { - ete.setZero(); - } - - FixedArray<double, 8> g(e_block_size); - typename EigenTypes<kEBlockSize>::VectorRef gref(g.get(), e_block_size); - gref.setZero(); - - // We are going to be computing - // - // S += F'F - F'E(E'E)^{-1}E'F - // - // for each Chunk. The computation is broken down into a number of - // function calls as below. - - // Compute the outer product of the e_blocks with themselves (ete - // = E'E). Compute the product of the e_blocks with the - // corresonding f_blocks (buffer = E'F), the gradient of the terms - // in this chunk (g) and add the outer product of the f_blocks to - // Schur complement (S += F'F). - ChunkDiagonalBlockAndGradient( - chunk, A, b, chunk.start, &ete, g.get(), buffer, lhs); - - // Normally one wouldn't compute the inverse explicitly, but - // e_block_size will typically be a small number like 3, in - // which case its much faster to compute the inverse once and - // use it to multiply other matrices/vectors instead of doing a - // Solve call over and over again. - typename EigenTypes<kEBlockSize, kEBlockSize>::Matrix inverse_ete = - ete - .template selfadjointView<Eigen::Upper>() - .llt() - .solve(Matrix::Identity(e_block_size, e_block_size)); - - // For the current chunk compute and update the rhs of the reduced - // linear system. - // - // rhs = F'b - F'E(E'E)^(-1) E'b - - FixedArray<double, 8> inverse_ete_g(e_block_size); - MatrixVectorMultiply<kEBlockSize, kEBlockSize, 0>( - inverse_ete.data(), - e_block_size, - e_block_size, - g.get(), - inverse_ete_g.get()); - - UpdateRhs(chunk, A, b, chunk.start, inverse_ete_g.get(), rhs); - - // S -= F'E(E'E)^{-1}E'F - ChunkOuterProduct(bs, inverse_ete, buffer, chunk.buffer_layout, lhs); - } - - // For rows with no e_blocks, the schur complement update reduces to - // S += F'F. - NoEBlockRowsUpdate(A, b, uneliminated_row_begins_, lhs, rhs); -} - -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>:: -BackSubstitute(const BlockSparseMatrix* A, - const double* b, - const double* D, - const double* z, - double* y) { - const CompressedRowBlockStructure* bs = A->block_structure(); -#pragma omp parallel for num_threads(num_threads_) schedule(dynamic) - for (int i = 0; i < chunks_.size(); ++i) { - const Chunk& chunk = chunks_[i]; - const int e_block_id = bs->rows[chunk.start].cells.front().block_id; - const int e_block_size = bs->cols[e_block_id].size; - - double* y_ptr = y + bs->cols[e_block_id].position; - typename EigenTypes<kEBlockSize>::VectorRef y_block(y_ptr, e_block_size); - - typename EigenTypes<kEBlockSize, kEBlockSize>::Matrix - ete(e_block_size, e_block_size); - if (D != NULL) { - const typename EigenTypes<kEBlockSize>::ConstVectorRef - diag(D + bs->cols[e_block_id].position, e_block_size); - ete = diag.array().square().matrix().asDiagonal(); - } else { - ete.setZero(); - } - - const double* values = A->values(); - for (int j = 0; j < chunk.size; ++j) { - const CompressedRow& row = bs->rows[chunk.start + j]; - const Cell& e_cell = row.cells.front(); - DCHECK_EQ(e_block_id, e_cell.block_id); - - FixedArray<double, 8> sj(row.block.size); - - typename EigenTypes<kRowBlockSize>::VectorRef(sj.get(), row.block.size) = - typename EigenTypes<kRowBlockSize>::ConstVectorRef - (b + bs->rows[chunk.start + j].block.position, row.block.size); - - for (int c = 1; c < row.cells.size(); ++c) { - const int f_block_id = row.cells[c].block_id; - const int f_block_size = bs->cols[f_block_id].size; - const int r_block = f_block_id - num_eliminate_blocks_; - - MatrixVectorMultiply<kRowBlockSize, kFBlockSize, -1>( - values + row.cells[c].position, row.block.size, f_block_size, - z + lhs_row_layout_[r_block], - sj.get()); - } - - MatrixTransposeVectorMultiply<kRowBlockSize, kEBlockSize, 1>( - values + e_cell.position, row.block.size, e_block_size, - sj.get(), - y_ptr); - - MatrixTransposeMatrixMultiply - <kRowBlockSize, kEBlockSize, kRowBlockSize, kEBlockSize, 1>( - values + e_cell.position, row.block.size, e_block_size, - values + e_cell.position, row.block.size, e_block_size, - ete.data(), 0, 0, e_block_size, e_block_size); - } - - ete.llt().solveInPlace(y_block); - } -} - -// Update the rhs of the reduced linear system. Compute -// -// F'b - F'E(E'E)^(-1) E'b -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>:: -UpdateRhs(const Chunk& chunk, - const BlockSparseMatrix* A, - const double* b, - int row_block_counter, - const double* inverse_ete_g, - double* rhs) { - const CompressedRowBlockStructure* bs = A->block_structure(); - const int e_block_id = bs->rows[chunk.start].cells.front().block_id; - const int e_block_size = bs->cols[e_block_id].size; - - int b_pos = bs->rows[row_block_counter].block.position; - const double* values = A->values(); - for (int j = 0; j < chunk.size; ++j) { - const CompressedRow& row = bs->rows[row_block_counter + j]; - const Cell& e_cell = row.cells.front(); - - typename EigenTypes<kRowBlockSize>::Vector sj = - typename EigenTypes<kRowBlockSize>::ConstVectorRef - (b + b_pos, row.block.size); - - MatrixVectorMultiply<kRowBlockSize, kEBlockSize, -1>( - values + e_cell.position, row.block.size, e_block_size, - inverse_ete_g, sj.data()); - - for (int c = 1; c < row.cells.size(); ++c) { - const int block_id = row.cells[c].block_id; - const int block_size = bs->cols[block_id].size; - const int block = block_id - num_eliminate_blocks_; - CeresMutexLock l(rhs_locks_[block]); - MatrixTransposeVectorMultiply<kRowBlockSize, kFBlockSize, 1>( - values + row.cells[c].position, - row.block.size, block_size, - sj.data(), rhs + lhs_row_layout_[block]); - } - b_pos += row.block.size; - } -} - -// Given a Chunk - set of rows with the same e_block, e.g. in the -// following Chunk with two rows. -// -// E F -// [ y11 0 0 0 | z11 0 0 0 z51] -// [ y12 0 0 0 | z12 z22 0 0 0] -// -// this function computes twp matrices. The diagonal block matrix -// -// ete = y11 * y11' + y12 * y12' -// -// and the off diagonal blocks in the Guass Newton Hessian. -// -// buffer = [y11'(z11 + z12), y12' * z22, y11' * z51] -// -// which are zero compressed versions of the block sparse matrices E'E -// and E'F. -// -// and the gradient of the e_block, E'b. -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>:: -ChunkDiagonalBlockAndGradient( - const Chunk& chunk, - const BlockSparseMatrix* A, - const double* b, - int row_block_counter, - typename EigenTypes<kEBlockSize, kEBlockSize>::Matrix* ete, - double* g, - double* buffer, - BlockRandomAccessMatrix* lhs) { - const CompressedRowBlockStructure* bs = A->block_structure(); - - int b_pos = bs->rows[row_block_counter].block.position; - const int e_block_size = ete->rows(); - - // Iterate over the rows in this chunk, for each row, compute the - // contribution of its F blocks to the Schur complement, the - // contribution of its E block to the matrix EE' (ete), and the - // corresponding block in the gradient vector. - const double* values = A->values(); - for (int j = 0; j < chunk.size; ++j) { - const CompressedRow& row = bs->rows[row_block_counter + j]; - - if (row.cells.size() > 1) { - EBlockRowOuterProduct(A, row_block_counter + j, lhs); - } - - // Extract the e_block, ETE += E_i' E_i - const Cell& e_cell = row.cells.front(); - MatrixTransposeMatrixMultiply - <kRowBlockSize, kEBlockSize, kRowBlockSize, kEBlockSize, 1>( - values + e_cell.position, row.block.size, e_block_size, - values + e_cell.position, row.block.size, e_block_size, - ete->data(), 0, 0, e_block_size, e_block_size); - - // g += E_i' b_i - MatrixTransposeVectorMultiply<kRowBlockSize, kEBlockSize, 1>( - values + e_cell.position, row.block.size, e_block_size, - b + b_pos, - g); - - - // buffer = E'F. This computation is done by iterating over the - // f_blocks for each row in the chunk. - for (int c = 1; c < row.cells.size(); ++c) { - const int f_block_id = row.cells[c].block_id; - const int f_block_size = bs->cols[f_block_id].size; - double* buffer_ptr = - buffer + FindOrDie(chunk.buffer_layout, f_block_id); - MatrixTransposeMatrixMultiply - <kRowBlockSize, kEBlockSize, kRowBlockSize, kFBlockSize, 1>( - values + e_cell.position, row.block.size, e_block_size, - values + row.cells[c].position, row.block.size, f_block_size, - buffer_ptr, 0, 0, e_block_size, f_block_size); - } - b_pos += row.block.size; - } -} - -// Compute the outer product F'E(E'E)^{-1}E'F and subtract it from the -// Schur complement matrix, i.e -// -// S -= F'E(E'E)^{-1}E'F. -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>:: -ChunkOuterProduct(const CompressedRowBlockStructure* bs, - const Matrix& inverse_ete, - const double* buffer, - const BufferLayoutType& buffer_layout, - BlockRandomAccessMatrix* lhs) { - // This is the most computationally expensive part of this - // code. Profiling experiments reveal that the bottleneck is not the - // computation of the right-hand matrix product, but memory - // references to the left hand side. - const int e_block_size = inverse_ete.rows(); - BufferLayoutType::const_iterator it1 = buffer_layout.begin(); - -#ifdef CERES_USE_OPENMP - int thread_id = omp_get_thread_num(); -#else - int thread_id = 0; -#endif - double* b1_transpose_inverse_ete = - chunk_outer_product_buffer_.get() + thread_id * buffer_size_; - - // S(i,j) -= bi' * ete^{-1} b_j - for (; it1 != buffer_layout.end(); ++it1) { - const int block1 = it1->first - num_eliminate_blocks_; - const int block1_size = bs->cols[it1->first].size; - MatrixTransposeMatrixMultiply - <kEBlockSize, kFBlockSize, kEBlockSize, kEBlockSize, 0>( - buffer + it1->second, e_block_size, block1_size, - inverse_ete.data(), e_block_size, e_block_size, - b1_transpose_inverse_ete, 0, 0, block1_size, e_block_size); - - BufferLayoutType::const_iterator it2 = it1; - for (; it2 != buffer_layout.end(); ++it2) { - const int block2 = it2->first - num_eliminate_blocks_; - - int r, c, row_stride, col_stride; - CellInfo* cell_info = lhs->GetCell(block1, block2, - &r, &c, - &row_stride, &col_stride); - if (cell_info != NULL) { - const int block2_size = bs->cols[it2->first].size; - CeresMutexLock l(&cell_info->m); - MatrixMatrixMultiply - <kFBlockSize, kEBlockSize, kEBlockSize, kFBlockSize, -1>( - b1_transpose_inverse_ete, block1_size, e_block_size, - buffer + it2->second, e_block_size, block2_size, - cell_info->values, r, c, row_stride, col_stride); - } - } - } -} - -// For rows with no e_blocks, the schur complement update reduces to S -// += F'F. This function iterates over the rows of A with no e_block, -// and calls NoEBlockRowOuterProduct on each row. -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>:: -NoEBlockRowsUpdate(const BlockSparseMatrix* A, - const double* b, - int row_block_counter, - BlockRandomAccessMatrix* lhs, - double* rhs) { - const CompressedRowBlockStructure* bs = A->block_structure(); - const double* values = A->values(); - for (; row_block_counter < bs->rows.size(); ++row_block_counter) { - const CompressedRow& row = bs->rows[row_block_counter]; - for (int c = 0; c < row.cells.size(); ++c) { - const int block_id = row.cells[c].block_id; - const int block_size = bs->cols[block_id].size; - const int block = block_id - num_eliminate_blocks_; - MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>( - values + row.cells[c].position, row.block.size, block_size, - b + row.block.position, - rhs + lhs_row_layout_[block]); - } - NoEBlockRowOuterProduct(A, row_block_counter, lhs); - } -} - - -// A row r of A, which has no e_blocks gets added to the Schur -// Complement as S += r r'. This function is responsible for computing -// the contribution of a single row r to the Schur complement. It is -// very similar in structure to EBlockRowOuterProduct except for -// one difference. It does not use any of the template -// parameters. This is because the algorithm used for detecting the -// static structure of the matrix A only pays attention to rows with -// e_blocks. This is becase rows without e_blocks are rare and -// typically arise from regularization terms in the original -// optimization problem, and have a very different structure than the -// rows with e_blocks. Including them in the static structure -// detection will lead to most template parameters being set to -// dynamic. Since the number of rows without e_blocks is small, the -// lack of templating is not an issue. -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>:: -NoEBlockRowOuterProduct(const BlockSparseMatrix* A, - int row_block_index, - BlockRandomAccessMatrix* lhs) { - const CompressedRowBlockStructure* bs = A->block_structure(); - const CompressedRow& row = bs->rows[row_block_index]; - const double* values = A->values(); - for (int i = 0; i < row.cells.size(); ++i) { - const int block1 = row.cells[i].block_id - num_eliminate_blocks_; - DCHECK_GE(block1, 0); - - const int block1_size = bs->cols[row.cells[i].block_id].size; - int r, c, row_stride, col_stride; - CellInfo* cell_info = lhs->GetCell(block1, block1, - &r, &c, - &row_stride, &col_stride); - if (cell_info != NULL) { - CeresMutexLock l(&cell_info->m); - // This multiply currently ignores the fact that this is a - // symmetric outer product. - MatrixTransposeMatrixMultiply - <Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, 1>( - values + row.cells[i].position, row.block.size, block1_size, - values + row.cells[i].position, row.block.size, block1_size, - cell_info->values, r, c, row_stride, col_stride); - } - - for (int j = i + 1; j < row.cells.size(); ++j) { - const int block2 = row.cells[j].block_id - num_eliminate_blocks_; - DCHECK_GE(block2, 0); - DCHECK_LT(block1, block2); - int r, c, row_stride, col_stride; - CellInfo* cell_info = lhs->GetCell(block1, block2, - &r, &c, - &row_stride, &col_stride); - if (cell_info != NULL) { - const int block2_size = bs->cols[row.cells[j].block_id].size; - CeresMutexLock l(&cell_info->m); - MatrixTransposeMatrixMultiply - <Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, 1>( - values + row.cells[i].position, row.block.size, block1_size, - values + row.cells[j].position, row.block.size, block2_size, - cell_info->values, r, c, row_stride, col_stride); - } - } - } -} - -// For a row with an e_block, compute the contribition S += F'F. This -// function has the same structure as NoEBlockRowOuterProduct, except -// that this function uses the template parameters. -template <int kRowBlockSize, int kEBlockSize, int kFBlockSize> -void -SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>:: -EBlockRowOuterProduct(const BlockSparseMatrix* A, - int row_block_index, - BlockRandomAccessMatrix* lhs) { - const CompressedRowBlockStructure* bs = A->block_structure(); - const CompressedRow& row = bs->rows[row_block_index]; - const double* values = A->values(); - for (int i = 1; i < row.cells.size(); ++i) { - const int block1 = row.cells[i].block_id - num_eliminate_blocks_; - DCHECK_GE(block1, 0); - - const int block1_size = bs->cols[row.cells[i].block_id].size; - int r, c, row_stride, col_stride; - CellInfo* cell_info = lhs->GetCell(block1, block1, - &r, &c, - &row_stride, &col_stride); - if (cell_info != NULL) { - CeresMutexLock l(&cell_info->m); - // block += b1.transpose() * b1; - MatrixTransposeMatrixMultiply - <kRowBlockSize, kFBlockSize, kRowBlockSize, kFBlockSize, 1>( - values + row.cells[i].position, row.block.size, block1_size, - values + row.cells[i].position, row.block.size, block1_size, - cell_info->values, r, c, row_stride, col_stride); - } - - for (int j = i + 1; j < row.cells.size(); ++j) { - const int block2 = row.cells[j].block_id - num_eliminate_blocks_; - DCHECK_GE(block2, 0); - DCHECK_LT(block1, block2); - const int block2_size = bs->cols[row.cells[j].block_id].size; - int r, c, row_stride, col_stride; - CellInfo* cell_info = lhs->GetCell(block1, block2, - &r, &c, - &row_stride, &col_stride); - if (cell_info != NULL) { - // block += b1.transpose() * b2; - CeresMutexLock l(&cell_info->m); - MatrixTransposeMatrixMultiply - <kRowBlockSize, kFBlockSize, kRowBlockSize, kFBlockSize, 1>( - values + row.cells[i].position, row.block.size, block1_size, - values + row.cells[j].position, row.block.size, block2_size, - cell_info->values, r, c, row_stride, col_stride); - } - } - } -} - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_SCHUR_ELIMINATOR_IMPL_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/schur_jacobi_preconditioner.cc b/extern/libmv/third_party/ceres/internal/ceres/schur_jacobi_preconditioner.cc deleted file mode 100644 index 3e6cc90f63c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/schur_jacobi_preconditioner.cc +++ /dev/null @@ -1,115 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/schur_jacobi_preconditioner.h" - -#include <utility> -#include <vector> -#include "ceres/block_random_access_diagonal_matrix.h" -#include "ceres/block_sparse_matrix.h" -#include "ceres/collections_port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/linear_solver.h" -#include "ceres/schur_eliminator.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -SchurJacobiPreconditioner::SchurJacobiPreconditioner( - const CompressedRowBlockStructure& bs, - const Preconditioner::Options& options) - : options_(options) { - CHECK_GT(options_.elimination_groups.size(), 1); - CHECK_GT(options_.elimination_groups[0], 0); - const int num_blocks = bs.cols.size() - options_.elimination_groups[0]; - CHECK_GT(num_blocks, 0) - << "Jacobian should have atleast 1 f_block for " - << "SCHUR_JACOBI preconditioner."; - - std::vector<int> blocks(num_blocks); - for (int i = 0; i < num_blocks; ++i) { - blocks[i] = bs.cols[i + options_.elimination_groups[0]].size; - } - - m_.reset(new BlockRandomAccessDiagonalMatrix(blocks)); - InitEliminator(bs); -} - -SchurJacobiPreconditioner::~SchurJacobiPreconditioner() { -} - -// Initialize the SchurEliminator. -void SchurJacobiPreconditioner::InitEliminator( - const CompressedRowBlockStructure& bs) { - LinearSolver::Options eliminator_options; - eliminator_options.elimination_groups = options_.elimination_groups; - eliminator_options.num_threads = options_.num_threads; - eliminator_options.e_block_size = options_.e_block_size; - eliminator_options.f_block_size = options_.f_block_size; - eliminator_options.row_block_size = options_.row_block_size; - eliminator_.reset(SchurEliminatorBase::Create(eliminator_options)); - eliminator_->Init(eliminator_options.elimination_groups[0], &bs); -} - -// Update the values of the preconditioner matrix and factorize it. -bool SchurJacobiPreconditioner::UpdateImpl(const BlockSparseMatrix& A, - const double* D) { - const int num_rows = m_->num_rows(); - CHECK_GT(num_rows, 0); - - // We need a dummy rhs vector and a dummy b vector since the Schur - // eliminator combines the computation of the reduced camera matrix - // with the computation of the right hand side of that linear - // system. - // - // TODO(sameeragarwal): Perhaps its worth refactoring the - // SchurEliminator::Eliminate function to allow NULL for the rhs. As - // of now it does not seem to be worth the effort. - Vector rhs = Vector::Zero(m_->num_rows()); - Vector b = Vector::Zero(A.num_rows()); - - // Compute a subset of the entries of the Schur complement. - eliminator_->Eliminate(&A, b.data(), D, m_.get(), rhs.data()); - m_->Invert(); - return true; -} - -void SchurJacobiPreconditioner::RightMultiply(const double* x, - double* y) const { - m_->RightMultiply(x, y); -} - -int SchurJacobiPreconditioner::num_rows() const { - return m_->num_rows(); -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/schur_jacobi_preconditioner.h b/extern/libmv/third_party/ceres/internal/ceres/schur_jacobi_preconditioner.h deleted file mode 100644 index 5398f3ff35d..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/schur_jacobi_preconditioner.h +++ /dev/null @@ -1,106 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Detailed descriptions of these preconditions beyond what is -// documented here can be found in -// -// Bundle Adjustment in the Large -// S. Agarwal, N. Snavely, S. Seitz & R. Szeliski, ECCV 2010 -// http://www.cs.washington.edu/homes/sagarwal/bal.pdf - -#ifndef CERES_INTERNAL_SCHUR_JACOBI_PRECONDITIONER_H_ -#define CERES_INTERNAL_SCHUR_JACOBI_PRECONDITIONER_H_ - -#include <set> -#include <vector> -#include <utility> -#include "ceres/collections_port.h" -#include "ceres/internal/macros.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/preconditioner.h" - -namespace ceres { -namespace internal { - -class BlockRandomAccessDiagonalMatrix; -class BlockSparseMatrix; -struct CompressedRowBlockStructure; -class SchurEliminatorBase; - -// This class implements the SCHUR_JACOBI preconditioner for Structure -// from Motion/Bundle Adjustment problems. Full mathematical details -// can be found in -// -// Bundle Adjustment in the Large -// S. Agarwal, N. Snavely, S. Seitz & R. Szeliski, ECCV 2010 -// http://www.cs.washington.edu/homes/sagarwal/bal.pdf -// -// Example usage: -// -// Preconditioner::Options options; -// options.preconditioner_type = SCHUR_JACOBI; -// options.elimination_groups.push_back(num_points); -// options.elimination_groups.push_back(num_cameras); -// SchurJacobiPreconditioner preconditioner( -// *A.block_structure(), options); -// preconditioner.Update(A, NULL); -// preconditioner.RightMultiply(x, y); -// -class SchurJacobiPreconditioner : public BlockSparseMatrixPreconditioner { - public: - // Initialize the symbolic structure of the preconditioner. bs is - // the block structure of the linear system to be solved. It is used - // to determine the sparsity structure of the preconditioner matrix. - // - // It has the same structural requirement as other Schur complement - // based solvers. Please see schur_eliminator.h for more details. - SchurJacobiPreconditioner(const CompressedRowBlockStructure& bs, - const Preconditioner::Options& options); - virtual ~SchurJacobiPreconditioner(); - - // Preconditioner interface. - virtual void RightMultiply(const double* x, double* y) const; - virtual int num_rows() const; - - private: - void InitEliminator(const CompressedRowBlockStructure& bs); - virtual bool UpdateImpl(const BlockSparseMatrix& A, const double* D); - - Preconditioner::Options options_; - scoped_ptr<SchurEliminatorBase> eliminator_; - // Preconditioner matrix. - scoped_ptr<BlockRandomAccessDiagonalMatrix> m_; - CERES_DISALLOW_COPY_AND_ASSIGN(SchurJacobiPreconditioner); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_SCHUR_JACOBI_PRECONDITIONER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/scratch_evaluate_preparer.cc b/extern/libmv/third_party/ceres/internal/ceres/scratch_evaluate_preparer.cc deleted file mode 100644 index f01ef11c26f..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/scratch_evaluate_preparer.cc +++ /dev/null @@ -1,78 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#include "ceres/scratch_evaluate_preparer.h" - -#include "ceres/parameter_block.h" -#include "ceres/program.h" -#include "ceres/residual_block.h" - -namespace ceres { -namespace internal { - -ScratchEvaluatePreparer* ScratchEvaluatePreparer::Create( - const Program &program, - int num_threads) { - ScratchEvaluatePreparer* preparers = new ScratchEvaluatePreparer[num_threads]; - int max_derivatives_per_residual_block = - program.MaxDerivativesPerResidualBlock(); - for (int i = 0; i < num_threads; i++) { - preparers[i].Init(max_derivatives_per_residual_block); - } - return preparers; -} - -void ScratchEvaluatePreparer::Init(int max_derivatives_per_residual_block) { - jacobian_scratch_.reset( - new double[max_derivatives_per_residual_block]); -} - -// Point the jacobian blocks into the scratch area of this evaluate preparer. -void ScratchEvaluatePreparer::Prepare(const ResidualBlock* residual_block, - int /* residual_block_index */, - SparseMatrix* /* jacobian */, - double** jacobians) { - double* jacobian_block_cursor = jacobian_scratch_.get(); - int num_residuals = residual_block->NumResiduals(); - int num_parameter_blocks = residual_block->NumParameterBlocks(); - for (int j = 0; j < num_parameter_blocks; ++j) { - const ParameterBlock* parameter_block = - residual_block->parameter_blocks()[j]; - if (parameter_block->IsConstant()) { - jacobians[j] = NULL; - } else { - jacobians[j] = jacobian_block_cursor; - jacobian_block_cursor += num_residuals * parameter_block->LocalSize(); - } - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/scratch_evaluate_preparer.h b/extern/libmv/third_party/ceres/internal/ceres/scratch_evaluate_preparer.h deleted file mode 100644 index fa9ebd0e50e..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/scratch_evaluate_preparer.h +++ /dev/null @@ -1,69 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// -// A scratch evaluate preparer provides temporary storage for the jacobians that -// are created when running user-provided cost functions. The evaluator takes -// care to avoid evaluating the jacobian for fixed parameters. - -#ifndef CERES_INTERNAL_SCRATCH_EVALUATE_PREPARER_H_ -#define CERES_INTERNAL_SCRATCH_EVALUATE_PREPARER_H_ - -#include "ceres/internal/scoped_ptr.h" - -namespace ceres { -namespace internal { - -class Program; -class ResidualBlock; -class SparseMatrix; - -class ScratchEvaluatePreparer { - public: - // Create num_threads ScratchEvaluatePreparers. - static ScratchEvaluatePreparer* Create(const Program &program, - int num_threads); - - // EvaluatePreparer interface - void Init(int max_derivatives_per_residual_block); - void Prepare(const ResidualBlock* residual_block, - int residual_block_index, - SparseMatrix* jacobian, - double** jacobians); - - private: - // Scratch space for the jacobians; each jacobian is packed one after another. - // There is enough scratch to hold all the jacobians for the largest residual. - scoped_array<double> jacobian_scratch_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_SCRATCH_EVALUATE_PREPARER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/small_blas.h b/extern/libmv/third_party/ceres/internal/ceres/small_blas.h deleted file mode 100644 index 264ac53047d..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/small_blas.h +++ /dev/null @@ -1,381 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Simple blas functions for use in the Schur Eliminator. These are -// fairly basic implementations which already yield a significant -// speedup in the eliminator performance. - -#ifndef CERES_INTERNAL_SMALL_BLAS_H_ -#define CERES_INTERNAL_SMALL_BLAS_H_ - -#include "ceres/internal/port.h" -#include "ceres/internal/eigen.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -// The following three macros are used to share code and reduce -// template junk across the various GEMM variants. -#define CERES_GEMM_BEGIN(name) \ - template<int kRowA, int kColA, int kRowB, int kColB, int kOperation> \ - inline void name(const double* A, \ - const int num_row_a, \ - const int num_col_a, \ - const double* B, \ - const int num_row_b, \ - const int num_col_b, \ - double* C, \ - const int start_row_c, \ - const int start_col_c, \ - const int row_stride_c, \ - const int col_stride_c) - -#define CERES_GEMM_NAIVE_HEADER \ - DCHECK_GT(num_row_a, 0); \ - DCHECK_GT(num_col_a, 0); \ - DCHECK_GT(num_row_b, 0); \ - DCHECK_GT(num_col_b, 0); \ - DCHECK_GE(start_row_c, 0); \ - DCHECK_GE(start_col_c, 0); \ - DCHECK_GT(row_stride_c, 0); \ - DCHECK_GT(col_stride_c, 0); \ - DCHECK((kRowA == Eigen::Dynamic) || (kRowA == num_row_a)); \ - DCHECK((kColA == Eigen::Dynamic) || (kColA == num_col_a)); \ - DCHECK((kRowB == Eigen::Dynamic) || (kRowB == num_row_b)); \ - DCHECK((kColB == Eigen::Dynamic) || (kColB == num_col_b)); \ - const int NUM_ROW_A = (kRowA != Eigen::Dynamic ? kRowA : num_row_a); \ - const int NUM_COL_A = (kColA != Eigen::Dynamic ? kColA : num_col_a); \ - const int NUM_ROW_B = (kRowB != Eigen::Dynamic ? kRowB : num_row_b); \ - const int NUM_COL_B = (kColB != Eigen::Dynamic ? kColB : num_col_b); - -#define CERES_GEMM_EIGEN_HEADER \ - const typename EigenTypes<kRowA, kColA>::ConstMatrixRef \ - Aref(A, num_row_a, num_col_a); \ - const typename EigenTypes<kRowB, kColB>::ConstMatrixRef \ - Bref(B, num_row_b, num_col_b); \ - MatrixRef Cref(C, row_stride_c, col_stride_c); \ - -#define CERES_CALL_GEMM(name) \ - name<kRowA, kColA, kRowB, kColB, kOperation>( \ - A, num_row_a, num_col_a, \ - B, num_row_b, num_col_b, \ - C, start_row_c, start_col_c, row_stride_c, col_stride_c); - - -// For the matrix-matrix functions below, there are three variants for -// each functionality. Foo, FooNaive and FooEigen. Foo is the one to -// be called by the user. FooNaive is a basic loop based -// implementation and FooEigen uses Eigen's implementation. Foo -// chooses between FooNaive and FooEigen depending on how many of the -// template arguments are fixed at compile time. Currently, FooEigen -// is called if all matrix dimensions are compile time -// constants. FooNaive is called otherwise. This leads to the best -// performance currently. -// -// The MatrixMatrixMultiply variants compute: -// -// C op A * B; -// -// The MatrixTransposeMatrixMultiply variants compute: -// -// C op A' * B -// -// where op can be +=, -=, or =. -// -// The template parameters (kRowA, kColA, kRowB, kColB) allow -// specialization of the loop at compile time. If this information is -// not available, then Eigen::Dynamic should be used as the template -// argument. -// -// kOperation = 1 -> C += A * B -// kOperation = -1 -> C -= A * B -// kOperation = 0 -> C = A * B -// -// The functions can write into matrices C which are larger than the -// matrix A * B. This is done by specifying the true size of C via -// row_stride_c and col_stride_c, and then indicating where A * B -// should be written into by start_row_c and start_col_c. -// -// Graphically if row_stride_c = 10, col_stride_c = 12, start_row_c = -// 4 and start_col_c = 5, then if A = 3x2 and B = 2x4, we get -// -// ------------ -// ------------ -// ------------ -// ------------ -// -----xxxx--- -// -----xxxx--- -// -----xxxx--- -// ------------ -// ------------ -// ------------ -// -CERES_GEMM_BEGIN(MatrixMatrixMultiplyEigen) { - CERES_GEMM_EIGEN_HEADER - Eigen::Block<MatrixRef, kRowA, kColB> - block(Cref, start_row_c, start_col_c, num_row_a, num_col_b); - - if (kOperation > 0) { - block.noalias() += Aref * Bref; - } else if (kOperation < 0) { - block.noalias() -= Aref * Bref; - } else { - block.noalias() = Aref * Bref; - } -} - -CERES_GEMM_BEGIN(MatrixMatrixMultiplyNaive) { - CERES_GEMM_NAIVE_HEADER - DCHECK_EQ(NUM_COL_A, NUM_ROW_B); - - const int NUM_ROW_C = NUM_ROW_A; - const int NUM_COL_C = NUM_COL_B; - DCHECK_LE(start_row_c + NUM_ROW_C, row_stride_c); - DCHECK_LE(start_col_c + NUM_COL_C, col_stride_c); - - for (int row = 0; row < NUM_ROW_C; ++row) { - for (int col = 0; col < NUM_COL_C; ++col) { - double tmp = 0.0; - for (int k = 0; k < NUM_COL_A; ++k) { - tmp += A[row * NUM_COL_A + k] * B[k * NUM_COL_B + col]; - } - - const int index = (row + start_row_c) * col_stride_c + start_col_c + col; - if (kOperation > 0) { - C[index] += tmp; - } else if (kOperation < 0) { - C[index] -= tmp; - } else { - C[index] = tmp; - } - } - } -} - -CERES_GEMM_BEGIN(MatrixMatrixMultiply) { -#ifdef CERES_NO_CUSTOM_BLAS - - CERES_CALL_GEMM(MatrixMatrixMultiplyEigen) - return; - -#else - - if (kRowA != Eigen::Dynamic && kColA != Eigen::Dynamic && - kRowB != Eigen::Dynamic && kColB != Eigen::Dynamic) { - CERES_CALL_GEMM(MatrixMatrixMultiplyEigen) - } else { - CERES_CALL_GEMM(MatrixMatrixMultiplyNaive) - } - -#endif -} - -CERES_GEMM_BEGIN(MatrixTransposeMatrixMultiplyEigen) { - CERES_GEMM_EIGEN_HEADER - Eigen::Block<MatrixRef, kColA, kColB> block(Cref, - start_row_c, start_col_c, - num_col_a, num_col_b); - if (kOperation > 0) { - block.noalias() += Aref.transpose() * Bref; - } else if (kOperation < 0) { - block.noalias() -= Aref.transpose() * Bref; - } else { - block.noalias() = Aref.transpose() * Bref; - } -} - -CERES_GEMM_BEGIN(MatrixTransposeMatrixMultiplyNaive) { - CERES_GEMM_NAIVE_HEADER - DCHECK_EQ(NUM_ROW_A, NUM_ROW_B); - - const int NUM_ROW_C = NUM_COL_A; - const int NUM_COL_C = NUM_COL_B; - DCHECK_LE(start_row_c + NUM_ROW_C, row_stride_c); - DCHECK_LE(start_col_c + NUM_COL_C, col_stride_c); - - for (int row = 0; row < NUM_ROW_C; ++row) { - for (int col = 0; col < NUM_COL_C; ++col) { - double tmp = 0.0; - for (int k = 0; k < NUM_ROW_A; ++k) { - tmp += A[k * NUM_COL_A + row] * B[k * NUM_COL_B + col]; - } - - const int index = (row + start_row_c) * col_stride_c + start_col_c + col; - if (kOperation > 0) { - C[index]+= tmp; - } else if (kOperation < 0) { - C[index]-= tmp; - } else { - C[index]= tmp; - } - } - } -} - -CERES_GEMM_BEGIN(MatrixTransposeMatrixMultiply) { -#ifdef CERES_NO_CUSTOM_BLAS - - CERES_CALL_GEMM(MatrixTransposeMatrixMultiplyEigen) - return; - -#else - - if (kRowA != Eigen::Dynamic && kColA != Eigen::Dynamic && - kRowB != Eigen::Dynamic && kColB != Eigen::Dynamic) { - CERES_CALL_GEMM(MatrixTransposeMatrixMultiplyEigen) - } else { - CERES_CALL_GEMM(MatrixTransposeMatrixMultiplyNaive) - } - -#endif -} - -// Matrix-Vector multiplication -// -// c op A * b; -// -// where op can be +=, -=, or =. -// -// The template parameters (kRowA, kColA) allow specialization of the -// loop at compile time. If this information is not available, then -// Eigen::Dynamic should be used as the template argument. -// -// kOperation = 1 -> c += A' * b -// kOperation = -1 -> c -= A' * b -// kOperation = 0 -> c = A' * b -template<int kRowA, int kColA, int kOperation> -inline void MatrixVectorMultiply(const double* A, - const int num_row_a, - const int num_col_a, - const double* b, - double* c) { -#ifdef CERES_NO_CUSTOM_BLAS - const typename EigenTypes<kRowA, kColA>::ConstMatrixRef - Aref(A, num_row_a, num_col_a); - const typename EigenTypes<kColA>::ConstVectorRef bref(b, num_col_a); - typename EigenTypes<kRowA>::VectorRef cref(c, num_row_a); - - // lazyProduct works better than .noalias() for matrix-vector - // products. - if (kOperation > 0) { - cref += Aref.lazyProduct(bref); - } else if (kOperation < 0) { - cref -= Aref.lazyProduct(bref); - } else { - cref = Aref.lazyProduct(bref); - } -#else - - DCHECK_GT(num_row_a, 0); - DCHECK_GT(num_col_a, 0); - DCHECK((kRowA == Eigen::Dynamic) || (kRowA == num_row_a)); - DCHECK((kColA == Eigen::Dynamic) || (kColA == num_col_a)); - - const int NUM_ROW_A = (kRowA != Eigen::Dynamic ? kRowA : num_row_a); - const int NUM_COL_A = (kColA != Eigen::Dynamic ? kColA : num_col_a); - - for (int row = 0; row < NUM_ROW_A; ++row) { - double tmp = 0.0; - for (int col = 0; col < NUM_COL_A; ++col) { - tmp += A[row * NUM_COL_A + col] * b[col]; - } - - if (kOperation > 0) { - c[row] += tmp; - } else if (kOperation < 0) { - c[row] -= tmp; - } else { - c[row] = tmp; - } - } -#endif // CERES_NO_CUSTOM_BLAS -} - -// Similar to MatrixVectorMultiply, except that A is transposed, i.e., -// -// c op A' * b; -template<int kRowA, int kColA, int kOperation> -inline void MatrixTransposeVectorMultiply(const double* A, - const int num_row_a, - const int num_col_a, - const double* b, - double* c) { -#ifdef CERES_NO_CUSTOM_BLAS - const typename EigenTypes<kRowA, kColA>::ConstMatrixRef - Aref(A, num_row_a, num_col_a); - const typename EigenTypes<kRowA>::ConstVectorRef bref(b, num_row_a); - typename EigenTypes<kColA>::VectorRef cref(c, num_col_a); - - // lazyProduct works better than .noalias() for matrix-vector - // products. - if (kOperation > 0) { - cref += Aref.transpose().lazyProduct(bref); - } else if (kOperation < 0) { - cref -= Aref.transpose().lazyProduct(bref); - } else { - cref = Aref.transpose().lazyProduct(bref); - } -#else - - DCHECK_GT(num_row_a, 0); - DCHECK_GT(num_col_a, 0); - DCHECK((kRowA == Eigen::Dynamic) || (kRowA == num_row_a)); - DCHECK((kColA == Eigen::Dynamic) || (kColA == num_col_a)); - - const int NUM_ROW_A = (kRowA != Eigen::Dynamic ? kRowA : num_row_a); - const int NUM_COL_A = (kColA != Eigen::Dynamic ? kColA : num_col_a); - - for (int row = 0; row < NUM_COL_A; ++row) { - double tmp = 0.0; - for (int col = 0; col < NUM_ROW_A; ++col) { - tmp += A[col * NUM_COL_A + row] * b[col]; - } - - if (kOperation > 0) { - c[row] += tmp; - } else if (kOperation < 0) { - c[row] -= tmp; - } else { - c[row] = tmp; - } - } -#endif // CERES_NO_CUSTOM_BLAS -} - -#undef CERES_GEMM_BEGIN -#undef CERES_GEMM_EIGEN_HEADER -#undef CERES_GEMM_NAIVE_HEADER -#undef CERES_CALL_GEMM - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_SMALL_BLAS_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/solver.cc b/extern/libmv/third_party/ceres/internal/ceres/solver.cc deleted file mode 100644 index 9f3228bb0be..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/solver.cc +++ /dev/null @@ -1,841 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) -// sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/solver.h" - -#include <algorithm> -#include <sstream> // NOLINT -#include <vector> -#include "ceres/gradient_checking_cost_function.h" -#include "ceres/internal/port.h" -#include "ceres/parameter_block_ordering.h" -#include "ceres/preprocessor.h" -#include "ceres/problem.h" -#include "ceres/problem_impl.h" -#include "ceres/program.h" -#include "ceres/solver_utils.h" -#include "ceres/stringprintf.h" -#include "ceres/types.h" -#include "ceres/wall_time.h" - -namespace ceres { -namespace { - -using std::map; -using std::string; -using std::vector; - -#define OPTION_OP(x, y, OP) \ - if (!(options.x OP y)) { \ - std::stringstream ss; \ - ss << "Invalid configuration. "; \ - ss << string("Solver::Options::" #x " = ") << options.x << ". "; \ - ss << "Violated constraint: "; \ - ss << string("Solver::Options::" #x " " #OP " "#y); \ - *error = ss.str(); \ - return false; \ - } - -#define OPTION_OP_OPTION(x, y, OP) \ - if (!(options.x OP options.y)) { \ - std::stringstream ss; \ - ss << "Invalid configuration. "; \ - ss << string("Solver::Options::" #x " = ") << options.x << ". "; \ - ss << string("Solver::Options::" #y " = ") << options.y << ". "; \ - ss << "Violated constraint: "; \ - ss << string("Solver::Options::" #x); \ - ss << string(#OP " Solver::Options::" #y "."); \ - *error = ss.str(); \ - return false; \ - } - -#define OPTION_GE(x, y) OPTION_OP(x, y, >=); -#define OPTION_GT(x, y) OPTION_OP(x, y, >); -#define OPTION_LE(x, y) OPTION_OP(x, y, <=); -#define OPTION_LT(x, y) OPTION_OP(x, y, <); -#define OPTION_LE_OPTION(x, y) OPTION_OP_OPTION(x, y, <=) -#define OPTION_LT_OPTION(x, y) OPTION_OP_OPTION(x, y, <) - -bool CommonOptionsAreValid(const Solver::Options& options, string* error) { - OPTION_GE(max_num_iterations, 0); - OPTION_GE(max_solver_time_in_seconds, 0.0); - OPTION_GE(function_tolerance, 0.0); - OPTION_GE(gradient_tolerance, 0.0); - OPTION_GE(parameter_tolerance, 0.0); - OPTION_GT(num_threads, 0); - OPTION_GT(num_linear_solver_threads, 0); - if (options.check_gradients) { - OPTION_GT(gradient_check_relative_precision, 0.0); - OPTION_GT(numeric_derivative_relative_step_size, 0.0); - } - return true; -} - -bool TrustRegionOptionsAreValid(const Solver::Options& options, string* error) { - OPTION_GT(initial_trust_region_radius, 0.0); - OPTION_GT(min_trust_region_radius, 0.0); - OPTION_GT(max_trust_region_radius, 0.0); - OPTION_LE_OPTION(min_trust_region_radius, max_trust_region_radius); - OPTION_LE_OPTION(min_trust_region_radius, initial_trust_region_radius); - OPTION_LE_OPTION(initial_trust_region_radius, max_trust_region_radius); - OPTION_GE(min_relative_decrease, 0.0); - OPTION_GE(min_lm_diagonal, 0.0); - OPTION_GE(max_lm_diagonal, 0.0); - OPTION_LE_OPTION(min_lm_diagonal, max_lm_diagonal); - OPTION_GE(max_num_consecutive_invalid_steps, 0); - OPTION_GT(eta, 0.0); - OPTION_GE(min_linear_solver_iterations, 0); - OPTION_GE(max_linear_solver_iterations, 1); - OPTION_LE_OPTION(min_linear_solver_iterations, max_linear_solver_iterations); - - if (options.use_inner_iterations) { - OPTION_GE(inner_iteration_tolerance, 0.0); - } - - if (options.use_nonmonotonic_steps) { - OPTION_GT(max_consecutive_nonmonotonic_steps, 0); - } - - if (options.linear_solver_type == ITERATIVE_SCHUR && - options.use_explicit_schur_complement && - options.preconditioner_type != SCHUR_JACOBI) { - *error = "use_explicit_schur_complement only supports " - "SCHUR_JACOBI as the preconditioner."; - return false; - } - - if (options.preconditioner_type == CLUSTER_JACOBI && - options.sparse_linear_algebra_library_type != SUITE_SPARSE) { - *error = "CLUSTER_JACOBI requires " - "Solver::Options::sparse_linear_algebra_library_type to be " - "SUITE_SPARSE"; - return false; - } - - if (options.preconditioner_type == CLUSTER_TRIDIAGONAL && - options.sparse_linear_algebra_library_type != SUITE_SPARSE) { - *error = "CLUSTER_TRIDIAGONAL requires " - "Solver::Options::sparse_linear_algebra_library_type to be " - "SUITE_SPARSE"; - return false; - } - -#ifdef CERES_NO_LAPACK - if (options.dense_linear_algebra_library_type == LAPACK) { - if (options.linear_solver_type == DENSE_NORMAL_CHOLESKY) { - *error = "Can't use DENSE_NORMAL_CHOLESKY with LAPACK because " - "LAPACK was not enabled when Ceres was built."; - return false; - } else if (options.linear_solver_type == DENSE_QR) { - *error = "Can't use DENSE_QR with LAPACK because " - "LAPACK was not enabled when Ceres was built."; - return false; - } else if (options.linear_solver_type == DENSE_SCHUR) { - *error = "Can't use DENSE_SCHUR with LAPACK because " - "LAPACK was not enabled when Ceres was built."; - return false; - } - } -#endif - -#ifdef CERES_NO_SUITESPARSE - if (options.sparse_linear_algebra_library_type == SUITE_SPARSE) { - if (options.linear_solver_type == SPARSE_NORMAL_CHOLESKY) { - *error = "Can't use SPARSE_NORMAL_CHOLESKY with SUITESPARSE because " - "SuiteSparse was not enabled when Ceres was built."; - return false; - } else if (options.linear_solver_type == SPARSE_SCHUR) { - *error = "Can't use SPARSE_SCHUR with SUITESPARSE because " - "SuiteSparse was not enabled when Ceres was built."; - return false; - } else if (options.preconditioner_type == CLUSTER_JACOBI) { - *error = "CLUSTER_JACOBI preconditioner not supported. " - "SuiteSparse was not enabled when Ceres was built."; - return false; - } else if (options.preconditioner_type == CLUSTER_TRIDIAGONAL) { - *error = "CLUSTER_TRIDIAGONAL preconditioner not supported. " - "SuiteSparse was not enabled when Ceres was built."; - return false; - } - } -#endif - -#ifdef CERES_NO_CXSPARSE - if (options.sparse_linear_algebra_library_type == CX_SPARSE) { - if (options.linear_solver_type == SPARSE_NORMAL_CHOLESKY) { - *error = "Can't use SPARSE_NORMAL_CHOLESKY with CX_SPARSE because " - "CXSparse was not enabled when Ceres was built."; - return false; - } else if (options.linear_solver_type == SPARSE_SCHUR) { - *error = "Can't use SPARSE_SCHUR with CX_SPARSE because " - "CXSparse was not enabled when Ceres was built."; - return false; - } - } -#endif - -#ifndef CERES_USE_EIGEN_SPARSE - if (options.sparse_linear_algebra_library_type == EIGEN_SPARSE) { - if (options.linear_solver_type == SPARSE_NORMAL_CHOLESKY) { - *error = "Can't use SPARSE_NORMAL_CHOLESKY with EIGEN_SPARSE because " - "Eigen's sparse linear algebra was not enabled when Ceres was " - "built."; - return false; - } else if (options.linear_solver_type == SPARSE_SCHUR) { - *error = "Can't use SPARSE_SCHUR with EIGEN_SPARSE because " - "Eigen's sparse linear algebra was not enabled when Ceres was " - "built."; - return false; - } - } -#endif - - if (options.sparse_linear_algebra_library_type == NO_SPARSE) { - if (options.linear_solver_type == SPARSE_NORMAL_CHOLESKY) { - *error = "Can't use SPARSE_NORMAL_CHOLESKY as " - "sparse_linear_algebra_library_type is NO_SPARSE."; - return false; - } else if (options.linear_solver_type == SPARSE_SCHUR) { - *error = "Can't use SPARSE_SCHUR as " - "sparse_linear_algebra_library_type is NO_SPARSE."; - return false; - } - } - - if (options.trust_region_strategy_type == DOGLEG) { - if (options.linear_solver_type == ITERATIVE_SCHUR || - options.linear_solver_type == CGNR) { - *error = "DOGLEG only supports exact factorization based linear " - "solvers. If you want to use an iterative solver please " - "use LEVENBERG_MARQUARDT as the trust_region_strategy_type"; - return false; - } - } - - if (options.trust_region_minimizer_iterations_to_dump.size() > 0 && - options.trust_region_problem_dump_format_type != CONSOLE && - options.trust_region_problem_dump_directory.empty()) { - *error = "Solver::Options::trust_region_problem_dump_directory is empty."; - return false; - } - - if (options.dynamic_sparsity && - options.linear_solver_type != SPARSE_NORMAL_CHOLESKY) { - *error = "Dynamic sparsity is only supported with SPARSE_NORMAL_CHOLESKY."; - return false; - } - - return true; -} - -bool LineSearchOptionsAreValid(const Solver::Options& options, string* error) { - OPTION_GT(max_lbfgs_rank, 0); - OPTION_GT(min_line_search_step_size, 0.0); - OPTION_GT(max_line_search_step_contraction, 0.0); - OPTION_LT(max_line_search_step_contraction, 1.0); - OPTION_LT_OPTION(max_line_search_step_contraction, - min_line_search_step_contraction); - OPTION_LE(min_line_search_step_contraction, 1.0); - OPTION_GT(max_num_line_search_step_size_iterations, 0); - OPTION_GT(line_search_sufficient_function_decrease, 0.0); - OPTION_LT_OPTION(line_search_sufficient_function_decrease, - line_search_sufficient_curvature_decrease); - OPTION_LT(line_search_sufficient_curvature_decrease, 1.0); - OPTION_GT(max_line_search_step_expansion, 1.0); - - if ((options.line_search_direction_type == ceres::BFGS || - options.line_search_direction_type == ceres::LBFGS) && - options.line_search_type != ceres::WOLFE) { - *error = - string("Invalid configuration: Solver::Options::line_search_type = ") - + string(LineSearchTypeToString(options.line_search_type)) - + string(". When using (L)BFGS, " - "Solver::Options::line_search_type must be set to WOLFE."); - return false; - } - - // Warn user if they have requested BISECTION interpolation, but constraints - // on max/min step size change during line search prevent bisection scaling - // from occurring. Warn only, as this is likely a user mistake, but one which - // does not prevent us from continuing. - LOG_IF(WARNING, - (options.line_search_interpolation_type == ceres::BISECTION && - (options.max_line_search_step_contraction > 0.5 || - options.min_line_search_step_contraction < 0.5))) - << "Line search interpolation type is BISECTION, but specified " - << "max_line_search_step_contraction: " - << options.max_line_search_step_contraction << ", and " - << "min_line_search_step_contraction: " - << options.min_line_search_step_contraction - << ", prevent bisection (0.5) scaling, continuing with solve regardless."; - - return true; -} - -#undef OPTION_OP -#undef OPTION_OP_OPTION -#undef OPTION_GT -#undef OPTION_GE -#undef OPTION_LE -#undef OPTION_LT -#undef OPTION_LE_OPTION -#undef OPTION_LT_OPTION - -void StringifyOrdering(const vector<int>& ordering, string* report) { - if (ordering.size() == 0) { - internal::StringAppendF(report, "AUTOMATIC"); - return; - } - - for (int i = 0; i < ordering.size() - 1; ++i) { - internal::StringAppendF(report, "%d, ", ordering[i]); - } - internal::StringAppendF(report, "%d", ordering.back()); -} - -void SummarizeGivenProgram(const internal::Program& program, - Solver::Summary* summary) { - summary->num_parameter_blocks = program.NumParameterBlocks(); - summary->num_parameters = program.NumParameters(); - summary->num_effective_parameters = program.NumEffectiveParameters(); - summary->num_residual_blocks = program.NumResidualBlocks(); - summary->num_residuals = program.NumResiduals(); -} - -void SummarizeReducedProgram(const internal::Program& program, - Solver::Summary* summary) { - summary->num_parameter_blocks_reduced = program.NumParameterBlocks(); - summary->num_parameters_reduced = program.NumParameters(); - summary->num_effective_parameters_reduced = program.NumEffectiveParameters(); - summary->num_residual_blocks_reduced = program.NumResidualBlocks(); - summary->num_residuals_reduced = program.NumResiduals(); -} - -void PreSolveSummarize(const Solver::Options& options, - const internal::ProblemImpl* problem, - Solver::Summary* summary) { - SummarizeGivenProgram(problem->program(), summary); - internal::OrderingToGroupSizes(options.linear_solver_ordering.get(), - &(summary->linear_solver_ordering_given)); - internal::OrderingToGroupSizes(options.inner_iteration_ordering.get(), - &(summary->inner_iteration_ordering_given)); - - summary->dense_linear_algebra_library_type = options.dense_linear_algebra_library_type; // NOLINT - summary->dogleg_type = options.dogleg_type; - summary->inner_iteration_time_in_seconds = 0.0; - summary->line_search_cost_evaluation_time_in_seconds = 0.0; - summary->line_search_gradient_evaluation_time_in_seconds = 0.0; - summary->line_search_polynomial_minimization_time_in_seconds = 0.0; - summary->line_search_total_time_in_seconds = 0.0; - summary->inner_iterations_given = options.use_inner_iterations; - summary->line_search_direction_type = options.line_search_direction_type; // NOLINT - summary->line_search_interpolation_type = options.line_search_interpolation_type; // NOLINT - summary->line_search_type = options.line_search_type; - summary->linear_solver_type_given = options.linear_solver_type; - summary->max_lbfgs_rank = options.max_lbfgs_rank; - summary->minimizer_type = options.minimizer_type; - summary->nonlinear_conjugate_gradient_type = options.nonlinear_conjugate_gradient_type; // NOLINT - summary->num_linear_solver_threads_given = options.num_linear_solver_threads; // NOLINT - summary->num_threads_given = options.num_threads; - summary->preconditioner_type_given = options.preconditioner_type; - summary->sparse_linear_algebra_library_type = options.sparse_linear_algebra_library_type; // NOLINT - summary->trust_region_strategy_type = options.trust_region_strategy_type; // NOLINT - summary->visibility_clustering_type = options.visibility_clustering_type; // NOLINT -} - -void PostSolveSummarize(const internal::PreprocessedProblem& pp, - Solver::Summary* summary) { - internal::OrderingToGroupSizes(pp.options.linear_solver_ordering.get(), - &(summary->linear_solver_ordering_used)); - internal::OrderingToGroupSizes(pp.options.inner_iteration_ordering.get(), - &(summary->inner_iteration_ordering_used)); - - summary->inner_iterations_used = pp.inner_iteration_minimizer.get() != NULL; // NOLINT - summary->linear_solver_type_used = pp.options.linear_solver_type; - summary->num_linear_solver_threads_used = pp.options.num_linear_solver_threads; // NOLINT - summary->num_threads_used = pp.options.num_threads; - summary->preconditioner_type_used = pp.options.preconditioner_type; // NOLINT - - internal::SetSummaryFinalCost(summary); - - if (pp.reduced_program.get() != NULL) { - SummarizeReducedProgram(*pp.reduced_program, summary); - } - - // It is possible that no evaluator was created. This would be the - // case if the preprocessor failed, or if the reduced problem did - // not contain any parameter blocks. Thus, only extract the - // evaluator statistics if one exists. - if (pp.evaluator.get() != NULL) { - const map<string, double>& evaluator_time_statistics = - pp.evaluator->TimeStatistics(); - summary->residual_evaluation_time_in_seconds = - FindWithDefault(evaluator_time_statistics, "Evaluator::Residual", 0.0); - summary->jacobian_evaluation_time_in_seconds = - FindWithDefault(evaluator_time_statistics, "Evaluator::Jacobian", 0.0); - } - - // Again, like the evaluator, there may or may not be a linear - // solver from which we can extract run time statistics. In - // particular the line search solver does not use a linear solver. - if (pp.linear_solver.get() != NULL) { - const map<string, double>& linear_solver_time_statistics = - pp.linear_solver->TimeStatistics(); - summary->linear_solver_time_in_seconds = - FindWithDefault(linear_solver_time_statistics, - "LinearSolver::Solve", - 0.0); - } -} - -void Minimize(internal::PreprocessedProblem* pp, - Solver::Summary* summary) { - using internal::Program; - using internal::scoped_ptr; - using internal::Minimizer; - - Program* program = pp->reduced_program.get(); - if (pp->reduced_program->NumParameterBlocks() == 0) { - summary->message = "Function tolerance reached. " - "No non-constant parameter blocks found."; - summary->termination_type = CONVERGENCE; - VLOG_IF(1, pp->options.logging_type != SILENT) << summary->message; - summary->initial_cost = summary->fixed_cost; - summary->final_cost = summary->fixed_cost; - return; - } - - scoped_ptr<Minimizer> minimizer( - Minimizer::Create(pp->options.minimizer_type)); - minimizer->Minimize(pp->minimizer_options, - pp->reduced_parameters.data(), - summary); - - if (summary->IsSolutionUsable()) { - program->StateVectorToParameterBlocks(pp->reduced_parameters.data()); - program->CopyParameterBlockStateToUserState(); - } -} - -} // namespace - -bool Solver::Options::IsValid(string* error) const { - if (!CommonOptionsAreValid(*this, error)) { - return false; - } - - if (minimizer_type == TRUST_REGION && - !TrustRegionOptionsAreValid(*this, error)) { - return false; - } - - // We do not know if the problem is bounds constrained or not, if it - // is then the trust region solver will also use the line search - // solver to do a projection onto the box constraints, so make sure - // that the line search options are checked independent of what - // minimizer algorithm is being used. - return LineSearchOptionsAreValid(*this, error); -} - -Solver::~Solver() {} - -void Solver::Solve(const Solver::Options& options, - Problem* problem, - Solver::Summary* summary) { - using internal::PreprocessedProblem; - using internal::Preprocessor; - using internal::ProblemImpl; - using internal::Program; - using internal::scoped_ptr; - using internal::WallTimeInSeconds; - - CHECK_NOTNULL(problem); - CHECK_NOTNULL(summary); - - double start_time = WallTimeInSeconds(); - *summary = Summary(); - if (!options.IsValid(&summary->message)) { - LOG(ERROR) << "Terminating: " << summary->message; - return; - } - - ProblemImpl* problem_impl = problem->problem_impl_.get(); - Program* program = problem_impl->mutable_program(); - PreSolveSummarize(options, problem_impl, summary); - - // Make sure that all the parameter blocks states are set to the - // values provided by the user. - program->SetParameterBlockStatePtrsToUserStatePtrs(); - - scoped_ptr<internal::ProblemImpl> gradient_checking_problem; - if (options.check_gradients) { - gradient_checking_problem.reset( - CreateGradientCheckingProblemImpl( - problem_impl, - options.numeric_derivative_relative_step_size, - options.gradient_check_relative_precision)); - problem_impl = gradient_checking_problem.get(); - program = problem_impl->mutable_program(); - } - - scoped_ptr<Preprocessor> preprocessor( - Preprocessor::Create(options.minimizer_type)); - PreprocessedProblem pp; - const bool status = preprocessor->Preprocess(options, problem_impl, &pp); - summary->fixed_cost = pp.fixed_cost; - summary->preprocessor_time_in_seconds = WallTimeInSeconds() - start_time; - - if (status) { - const double minimizer_start_time = WallTimeInSeconds(); - Minimize(&pp, summary); - summary->minimizer_time_in_seconds = - WallTimeInSeconds() - minimizer_start_time; - } else { - summary->message = pp.error; - } - - const double postprocessor_start_time = WallTimeInSeconds(); - problem_impl = problem->problem_impl_.get(); - program = problem_impl->mutable_program(); - // On exit, ensure that the parameter blocks again point at the user - // provided values and the parameter blocks are numbered according - // to their position in the original user provided program. - program->SetParameterBlockStatePtrsToUserStatePtrs(); - program->SetParameterOffsetsAndIndex(); - PostSolveSummarize(pp, summary); - summary->postprocessor_time_in_seconds = - WallTimeInSeconds() - postprocessor_start_time; - - summary->total_time_in_seconds = WallTimeInSeconds() - start_time; -} - -void Solve(const Solver::Options& options, - Problem* problem, - Solver::Summary* summary) { - Solver solver; - solver.Solve(options, problem, summary); -} - -Solver::Summary::Summary() - // Invalid values for most fields, to ensure that we are not - // accidentally reporting default values. - : minimizer_type(TRUST_REGION), - termination_type(FAILURE), - message("ceres::Solve was not called."), - initial_cost(-1.0), - final_cost(-1.0), - fixed_cost(-1.0), - num_successful_steps(-1), - num_unsuccessful_steps(-1), - num_inner_iteration_steps(-1), - preprocessor_time_in_seconds(-1.0), - minimizer_time_in_seconds(-1.0), - postprocessor_time_in_seconds(-1.0), - total_time_in_seconds(-1.0), - linear_solver_time_in_seconds(-1.0), - residual_evaluation_time_in_seconds(-1.0), - jacobian_evaluation_time_in_seconds(-1.0), - inner_iteration_time_in_seconds(-1.0), - line_search_cost_evaluation_time_in_seconds(-1.0), - line_search_gradient_evaluation_time_in_seconds(-1.0), - line_search_polynomial_minimization_time_in_seconds(-1.0), - line_search_total_time_in_seconds(-1.0), - num_parameter_blocks(-1), - num_parameters(-1), - num_effective_parameters(-1), - num_residual_blocks(-1), - num_residuals(-1), - num_parameter_blocks_reduced(-1), - num_parameters_reduced(-1), - num_effective_parameters_reduced(-1), - num_residual_blocks_reduced(-1), - num_residuals_reduced(-1), - is_constrained(false), - num_threads_given(-1), - num_threads_used(-1), - num_linear_solver_threads_given(-1), - num_linear_solver_threads_used(-1), - linear_solver_type_given(SPARSE_NORMAL_CHOLESKY), - linear_solver_type_used(SPARSE_NORMAL_CHOLESKY), - inner_iterations_given(false), - inner_iterations_used(false), - preconditioner_type_given(IDENTITY), - preconditioner_type_used(IDENTITY), - visibility_clustering_type(CANONICAL_VIEWS), - trust_region_strategy_type(LEVENBERG_MARQUARDT), - dense_linear_algebra_library_type(EIGEN), - sparse_linear_algebra_library_type(SUITE_SPARSE), - line_search_direction_type(LBFGS), - line_search_type(ARMIJO), - line_search_interpolation_type(BISECTION), - nonlinear_conjugate_gradient_type(FLETCHER_REEVES), - max_lbfgs_rank(-1) { -} - -using internal::StringAppendF; -using internal::StringPrintf; - -string Solver::Summary::BriefReport() const { - return StringPrintf("Ceres Solver Report: " - "Iterations: %d, " - "Initial cost: %e, " - "Final cost: %e, " - "Termination: %s", - num_successful_steps + num_unsuccessful_steps, - initial_cost, - final_cost, - TerminationTypeToString(termination_type)); -} - -string Solver::Summary::FullReport() const { - using internal::VersionString; - - string report = string("\nSolver Summary (v " + VersionString() + ")\n\n"); - - StringAppendF(&report, "%45s %21s\n", "Original", "Reduced"); - StringAppendF(&report, "Parameter blocks % 25d% 25d\n", - num_parameter_blocks, num_parameter_blocks_reduced); - StringAppendF(&report, "Parameters % 25d% 25d\n", - num_parameters, num_parameters_reduced); - if (num_effective_parameters_reduced != num_parameters_reduced) { - StringAppendF(&report, "Effective parameters% 25d% 25d\n", - num_effective_parameters, num_effective_parameters_reduced); - } - StringAppendF(&report, "Residual blocks % 25d% 25d\n", - num_residual_blocks, num_residual_blocks_reduced); - StringAppendF(&report, "Residual % 25d% 25d\n", - num_residuals, num_residuals_reduced); - - if (minimizer_type == TRUST_REGION) { - // TRUST_SEARCH HEADER - StringAppendF(&report, "\nMinimizer %19s\n", - "TRUST_REGION"); - - if (linear_solver_type_used == DENSE_NORMAL_CHOLESKY || - linear_solver_type_used == DENSE_SCHUR || - linear_solver_type_used == DENSE_QR) { - StringAppendF(&report, "\nDense linear algebra library %15s\n", - DenseLinearAlgebraLibraryTypeToString( - dense_linear_algebra_library_type)); - } - - if (linear_solver_type_used == SPARSE_NORMAL_CHOLESKY || - linear_solver_type_used == SPARSE_SCHUR || - (linear_solver_type_used == ITERATIVE_SCHUR && - (preconditioner_type_used == CLUSTER_JACOBI || - preconditioner_type_used == CLUSTER_TRIDIAGONAL))) { - StringAppendF(&report, "\nSparse linear algebra library %15s\n", - SparseLinearAlgebraLibraryTypeToString( - sparse_linear_algebra_library_type)); - } - - StringAppendF(&report, "Trust region strategy %19s", - TrustRegionStrategyTypeToString( - trust_region_strategy_type)); - if (trust_region_strategy_type == DOGLEG) { - if (dogleg_type == TRADITIONAL_DOGLEG) { - StringAppendF(&report, " (TRADITIONAL)"); - } else { - StringAppendF(&report, " (SUBSPACE)"); - } - } - StringAppendF(&report, "\n"); - StringAppendF(&report, "\n"); - - StringAppendF(&report, "%45s %21s\n", "Given", "Used"); - StringAppendF(&report, "Linear solver %25s%25s\n", - LinearSolverTypeToString(linear_solver_type_given), - LinearSolverTypeToString(linear_solver_type_used)); - - if (linear_solver_type_given == CGNR || - linear_solver_type_given == ITERATIVE_SCHUR) { - StringAppendF(&report, "Preconditioner %25s%25s\n", - PreconditionerTypeToString(preconditioner_type_given), - PreconditionerTypeToString(preconditioner_type_used)); - } - - if (preconditioner_type_used == CLUSTER_JACOBI || - preconditioner_type_used == CLUSTER_TRIDIAGONAL) { - StringAppendF(&report, "Visibility clustering%24s%25s\n", - VisibilityClusteringTypeToString( - visibility_clustering_type), - VisibilityClusteringTypeToString( - visibility_clustering_type)); - } - StringAppendF(&report, "Threads % 25d% 25d\n", - num_threads_given, num_threads_used); - StringAppendF(&report, "Linear solver threads % 23d% 25d\n", - num_linear_solver_threads_given, - num_linear_solver_threads_used); - - if (IsSchurType(linear_solver_type_used)) { - string given; - StringifyOrdering(linear_solver_ordering_given, &given); - string used; - StringifyOrdering(linear_solver_ordering_used, &used); - StringAppendF(&report, - "Linear solver ordering %22s %24s\n", - given.c_str(), - used.c_str()); - } - - if (inner_iterations_given) { - StringAppendF(&report, - "Use inner iterations %20s %20s\n", - inner_iterations_given ? "True" : "False", - inner_iterations_used ? "True" : "False"); - } - - if (inner_iterations_used) { - string given; - StringifyOrdering(inner_iteration_ordering_given, &given); - string used; - StringifyOrdering(inner_iteration_ordering_used, &used); - StringAppendF(&report, - "Inner iteration ordering %20s %24s\n", - given.c_str(), - used.c_str()); - } - } else { - // LINE_SEARCH HEADER - StringAppendF(&report, "\nMinimizer %19s\n", "LINE_SEARCH"); - - - string line_search_direction_string; - if (line_search_direction_type == LBFGS) { - line_search_direction_string = StringPrintf("LBFGS (%d)", max_lbfgs_rank); - } else if (line_search_direction_type == NONLINEAR_CONJUGATE_GRADIENT) { - line_search_direction_string = - NonlinearConjugateGradientTypeToString( - nonlinear_conjugate_gradient_type); - } else { - line_search_direction_string = - LineSearchDirectionTypeToString(line_search_direction_type); - } - - StringAppendF(&report, "Line search direction %19s\n", - line_search_direction_string.c_str()); - - const string line_search_type_string = - StringPrintf("%s %s", - LineSearchInterpolationTypeToString( - line_search_interpolation_type), - LineSearchTypeToString(line_search_type)); - StringAppendF(&report, "Line search type %19s\n", - line_search_type_string.c_str()); - StringAppendF(&report, "\n"); - - StringAppendF(&report, "%45s %21s\n", "Given", "Used"); - StringAppendF(&report, "Threads % 25d% 25d\n", - num_threads_given, num_threads_used); - } - - StringAppendF(&report, "\nCost:\n"); - StringAppendF(&report, "Initial % 30e\n", initial_cost); - if (termination_type != FAILURE && - termination_type != USER_FAILURE) { - StringAppendF(&report, "Final % 30e\n", final_cost); - StringAppendF(&report, "Change % 30e\n", - initial_cost - final_cost); - } - - StringAppendF(&report, "\nMinimizer iterations % 16d\n", - num_successful_steps + num_unsuccessful_steps); - - // Successful/Unsuccessful steps only matter in the case of the - // trust region solver. Line search terminates when it encounters - // the first unsuccessful step. - if (minimizer_type == TRUST_REGION) { - StringAppendF(&report, "Successful steps % 14d\n", - num_successful_steps); - StringAppendF(&report, "Unsuccessful steps % 14d\n", - num_unsuccessful_steps); - } - if (inner_iterations_used) { - StringAppendF(&report, "Steps with inner iterations % 14d\n", - num_inner_iteration_steps); - } - - const bool print_line_search_timing_information = - minimizer_type == LINE_SEARCH || - (minimizer_type == TRUST_REGION && is_constrained); - - StringAppendF(&report, "\nTime (in seconds):\n"); - StringAppendF(&report, "Preprocessor %25.4f\n", - preprocessor_time_in_seconds); - - StringAppendF(&report, "\n Residual evaluation %23.4f\n", - residual_evaluation_time_in_seconds); - if (print_line_search_timing_information) { - StringAppendF(&report, " Line search cost evaluation %10.4f\n", - line_search_cost_evaluation_time_in_seconds); - } - StringAppendF(&report, " Jacobian evaluation %23.4f\n", - jacobian_evaluation_time_in_seconds); - if (print_line_search_timing_information) { - StringAppendF(&report, " Line search gradient evaluation %6.4f\n", - line_search_gradient_evaluation_time_in_seconds); - } - - if (minimizer_type == TRUST_REGION) { - StringAppendF(&report, " Linear solver %23.4f\n", - linear_solver_time_in_seconds); - } - - if (inner_iterations_used) { - StringAppendF(&report, " Inner iterations %23.4f\n", - inner_iteration_time_in_seconds); - } - - if (print_line_search_timing_information) { - StringAppendF(&report, " Line search polynomial minimization %.4f\n", - line_search_polynomial_minimization_time_in_seconds); - } - - StringAppendF(&report, "Minimizer %25.4f\n\n", - minimizer_time_in_seconds); - - StringAppendF(&report, "Postprocessor %24.4f\n", - postprocessor_time_in_seconds); - - StringAppendF(&report, "Total %25.4f\n\n", - total_time_in_seconds); - - StringAppendF(&report, "Termination: %25s (%s)\n", - TerminationTypeToString(termination_type), message.c_str()); - return report; -} - -bool Solver::Summary::IsSolutionUsable() const { - return internal::IsSolutionUsable(*this); -} - -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/solver_utils.cc b/extern/libmv/third_party/ceres/internal/ceres/solver_utils.cc deleted file mode 100644 index 7f4ff7eb940..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/solver_utils.cc +++ /dev/null @@ -1,86 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include <string> - -#include "Eigen/Core" -#include "ceres/internal/port.h" -#include "ceres/solver_utils.h" -#include "ceres/version.h" - -namespace ceres { -namespace internal { - -#define CERES_EIGEN_VERSION \ - CERES_TO_STRING(EIGEN_WORLD_VERSION) "." \ - CERES_TO_STRING(EIGEN_MAJOR_VERSION) "." \ - CERES_TO_STRING(EIGEN_MINOR_VERSION) - -std::string VersionString() { - std::string value = std::string(CERES_VERSION_STRING); - value += "-eigen-(" + std::string(CERES_EIGEN_VERSION) + ")"; - -#ifdef CERES_NO_LAPACK - value += "-no_lapack"; -#else - value += "-lapack"; -#endif - -#ifndef CERES_NO_SUITESPARSE - value += "-suitesparse-(" + std::string(CERES_SUITESPARSE_VERSION) + ")"; -#endif - -#ifndef CERES_NO_CXSPARSE - value += "-cxsparse-(" + std::string(CERES_CXSPARSE_VERSION) + ")"; -#endif - -#ifdef CERES_USE_EIGEN_SPARSE - value += "-eigensparse"; -#endif - -#ifdef CERES_RESTRUCT_SCHUR_SPECIALIZATIONS - value += "-no_schur_specializations"; -#endif - -#ifdef CERES_USE_OPENMP - value += "-openmp"; -#else - value += "-no_openmp"; -#endif - -#ifdef CERES_NO_CUSTOM_BLAS - value += "-no_custom_blas"; -#endif - - return value; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/solver_utils.h b/extern/libmv/third_party/ceres/internal/ceres/solver_utils.h deleted file mode 100644 index 85fbf3776ab..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/solver_utils.h +++ /dev/null @@ -1,61 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include <algorithm> -#include <string> - -#include "ceres/iteration_callback.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -template <typename SummaryType> -bool IsSolutionUsable(const SummaryType& summary) { - return (summary.termination_type == CONVERGENCE || - summary.termination_type == NO_CONVERGENCE || - summary.termination_type == USER_SUCCESS); -} - -template <typename SummaryType> -void SetSummaryFinalCost(SummaryType* summary) { - summary->final_cost = summary->initial_cost; - // We need the loop here, instead of just looking at the last - // iteration because the minimizer maybe making non-monotonic steps. - for (int i = 0; i < summary->iterations.size(); ++i) { - const IterationSummary& iteration_summary = summary->iterations[i]; - summary->final_cost = std::min(iteration_summary.cost, summary->final_cost); - } -} - -std::string VersionString(); - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/sparse_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/sparse_matrix.cc deleted file mode 100644 index f95ff3220bd..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/sparse_matrix.cc +++ /dev/null @@ -1,40 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/sparse_matrix.h" - -namespace ceres { -namespace internal { - -SparseMatrix::~SparseMatrix() { -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/sparse_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/sparse_matrix.h deleted file mode 100644 index b3af1d06440..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/sparse_matrix.h +++ /dev/null @@ -1,107 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Interface definition for sparse matrices. - -#ifndef CERES_INTERNAL_SPARSE_MATRIX_H_ -#define CERES_INTERNAL_SPARSE_MATRIX_H_ - -#include <cstdio> -#include "ceres/linear_operator.h" -#include "ceres/internal/eigen.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -// This class defines the interface for storing and manipulating -// sparse matrices. The key property that differentiates different -// sparse matrices is how they are organized in memory and how the -// information about the sparsity structure of the matrix is -// stored. This has significant implications for linear solvers -// operating on these matrices. -// -// To deal with the different kinds of layouts, we will assume that a -// sparse matrix will have a two part representation. A values array -// that will be used to store the entries of the sparse matrix and -// some sort of a layout object that tells the user the sparsity -// structure and layout of the values array. For example in case of -// the TripletSparseMatrix, this information is carried in the rows -// and cols arrays and for the BlockSparseMatrix, this information is -// carried in the CompressedRowBlockStructure object. -// -// This interface deliberately does not contain any information about -// the structure of the sparse matrix as that seems to be highly -// matrix type dependent and we are at this stage unable to come up -// with an efficient high level interface that spans multiple sparse -// matrix types. -class SparseMatrix : public LinearOperator { - public: - virtual ~SparseMatrix(); - - // y += Ax; - virtual void RightMultiply(const double* x, double* y) const = 0; - // y += A'x; - virtual void LeftMultiply(const double* x, double* y) const = 0; - - // In MATLAB notation sum(A.*A, 1) - virtual void SquaredColumnNorm(double* x) const = 0; - // A = A * diag(scale) - virtual void ScaleColumns(const double* scale) = 0; - - // A = 0. A->num_nonzeros() == 0 is true after this call. The - // sparsity pattern is preserved. - virtual void SetZero() = 0; - - // Resize and populate dense_matrix with a dense version of the - // sparse matrix. - virtual void ToDenseMatrix(Matrix* dense_matrix) const = 0; - - // Write out the matrix as a sequence of (i,j,s) triplets. This - // format is useful for loading the matrix into MATLAB/octave as a - // sparse matrix. - virtual void ToTextFile(FILE* file) const = 0; - - // Accessors for the values array that stores the entries of the - // sparse matrix. The exact interpreptation of the values of this - // array depends on the particular kind of SparseMatrix being - // accessed. - virtual double* mutable_values() = 0; - virtual const double* values() const = 0; - - virtual int num_rows() const = 0; - virtual int num_cols() const = 0; - virtual int num_nonzeros() const = 0; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_SPARSE_MATRIX_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.cc deleted file mode 100644 index ed00879b47a..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.cc +++ /dev/null @@ -1,486 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/sparse_normal_cholesky_solver.h" - -#include <algorithm> -#include <cstring> -#include <ctime> - -#include "ceres/compressed_row_sparse_matrix.h" -#include "ceres/cxsparse.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/linear_solver.h" -#include "ceres/suitesparse.h" -#include "ceres/triplet_sparse_matrix.h" -#include "ceres/types.h" -#include "ceres/wall_time.h" -#include "Eigen/SparseCore" - -#ifdef CERES_USE_EIGEN_SPARSE -#include "Eigen/SparseCholesky" -#endif - -namespace ceres { -namespace internal { -namespace { - -#ifdef CERES_USE_EIGEN_SPARSE -// A templated factorized and solve function, which allows us to use -// the same code independent of whether a AMD or a Natural ordering is -// used. -template <typename SimplicialCholeskySolver, typename SparseMatrixType> -LinearSolver::Summary SimplicialLDLTSolve( - const SparseMatrixType& lhs, - const bool do_symbolic_analysis, - SimplicialCholeskySolver* solver, - double* rhs_and_solution, - EventLogger* event_logger) { - LinearSolver::Summary summary; - summary.num_iterations = 1; - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = "Success."; - - if (do_symbolic_analysis) { - solver->analyzePattern(lhs); - event_logger->AddEvent("Analyze"); - if (solver->info() != Eigen::Success) { - summary.termination_type = LINEAR_SOLVER_FATAL_ERROR; - summary.message = - "Eigen failure. Unable to find symbolic factorization."; - return summary; - } - } - - solver->factorize(lhs); - event_logger->AddEvent("Factorize"); - if (solver->info() != Eigen::Success) { - summary.termination_type = LINEAR_SOLVER_FAILURE; - summary.message = "Eigen failure. Unable to find numeric factorization."; - return summary; - } - - const Vector rhs = VectorRef(rhs_and_solution, lhs.cols()); - - VectorRef(rhs_and_solution, lhs.cols()) = solver->solve(rhs); - event_logger->AddEvent("Solve"); - if (solver->info() != Eigen::Success) { - summary.termination_type = LINEAR_SOLVER_FAILURE; - summary.message = "Eigen failure. Unable to do triangular solve."; - return summary; - } - - return summary; -} - -#endif // CERES_USE_EIGEN_SPARSE - -#ifndef CERES_NO_CXSPARSE -LinearSolver::Summary ComputeNormalEquationsAndSolveUsingCXSparse( - CompressedRowSparseMatrix* A, - double * rhs_and_solution, - EventLogger* event_logger) { - LinearSolver::Summary summary; - summary.num_iterations = 1; - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = "Success."; - - CXSparse cxsparse; - - // Wrap the augmented Jacobian in a compressed sparse column matrix. - cs_di a_transpose = cxsparse.CreateSparseMatrixTransposeView(A); - - // Compute the normal equations. J'J delta = J'f and solve them - // using a sparse Cholesky factorization. Notice that when compared - // to SuiteSparse we have to explicitly compute the transpose of Jt, - // and then the normal equations before they can be - // factorized. CHOLMOD/SuiteSparse on the other hand can just work - // off of Jt to compute the Cholesky factorization of the normal - // equations. - cs_di* a = cxsparse.TransposeMatrix(&a_transpose); - cs_di* lhs = cxsparse.MatrixMatrixMultiply(&a_transpose, a); - cxsparse.Free(a); - event_logger->AddEvent("NormalEquations"); - - cs_dis* factor = cxsparse.AnalyzeCholesky(lhs); - event_logger->AddEvent("Analysis"); - - if (factor == NULL) { - summary.termination_type = LINEAR_SOLVER_FATAL_ERROR; - summary.message = "CXSparse::AnalyzeCholesky failed."; - } else if (!cxsparse.SolveCholesky(lhs, factor, rhs_and_solution)) { - summary.termination_type = LINEAR_SOLVER_FAILURE; - summary.message = "CXSparse::SolveCholesky failed."; - } - event_logger->AddEvent("Solve"); - - cxsparse.Free(lhs); - cxsparse.Free(factor); - event_logger->AddEvent("TearDown"); - return summary; -} - -#endif // CERES_NO_CXSPARSE - -} // namespace - -SparseNormalCholeskySolver::SparseNormalCholeskySolver( - const LinearSolver::Options& options) - : factor_(NULL), - cxsparse_factor_(NULL), - options_(options) { -} - -void SparseNormalCholeskySolver::FreeFactorization() { - if (factor_ != NULL) { - ss_.Free(factor_); - factor_ = NULL; - } - - if (cxsparse_factor_ != NULL) { - cxsparse_.Free(cxsparse_factor_); - cxsparse_factor_ = NULL; - } -} - -SparseNormalCholeskySolver::~SparseNormalCholeskySolver() { - FreeFactorization(); -} - -LinearSolver::Summary SparseNormalCholeskySolver::SolveImpl( - CompressedRowSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& per_solve_options, - double * x) { - - const int num_cols = A->num_cols(); - VectorRef(x, num_cols).setZero(); - A->LeftMultiply(b, x); - - if (per_solve_options.D != NULL) { - // Temporarily append a diagonal block to the A matrix, but undo - // it before returning the matrix to the user. - scoped_ptr<CompressedRowSparseMatrix> regularizer; - if (A->col_blocks().size() > 0) { - regularizer.reset(CompressedRowSparseMatrix::CreateBlockDiagonalMatrix( - per_solve_options.D, A->col_blocks())); - } else { - regularizer.reset(new CompressedRowSparseMatrix( - per_solve_options.D, num_cols)); - } - A->AppendRows(*regularizer); - } - - LinearSolver::Summary summary; - switch (options_.sparse_linear_algebra_library_type) { - case SUITE_SPARSE: - summary = SolveImplUsingSuiteSparse(A, x); - break; - case CX_SPARSE: - summary = SolveImplUsingCXSparse(A, x); - break; - case EIGEN_SPARSE: - summary = SolveImplUsingEigen(A, x); - break; - default: - LOG(FATAL) << "Unknown sparse linear algebra library : " - << options_.sparse_linear_algebra_library_type; - } - - if (per_solve_options.D != NULL) { - A->DeleteRows(num_cols); - } - - return summary; -} - -LinearSolver::Summary SparseNormalCholeskySolver::SolveImplUsingEigen( - CompressedRowSparseMatrix* A, - double * rhs_and_solution) { -#ifndef CERES_USE_EIGEN_SPARSE - - LinearSolver::Summary summary; - summary.num_iterations = 0; - summary.termination_type = LINEAR_SOLVER_FATAL_ERROR; - summary.message = - "SPARSE_NORMAL_CHOLESKY cannot be used with EIGEN_SPARSE " - "because Ceres was not built with support for " - "Eigen's SimplicialLDLT decomposition. " - "This requires enabling building with -DEIGENSPARSE=ON."; - return summary; - -#else - - EventLogger event_logger("SparseNormalCholeskySolver::Eigen::Solve"); - // Compute the normal equations. J'J delta = J'f and solve them - // using a sparse Cholesky factorization. Notice that when compared - // to SuiteSparse we have to explicitly compute the normal equations - // before they can be factorized. CHOLMOD/SuiteSparse on the other - // hand can just work off of Jt to compute the Cholesky - // factorization of the normal equations. - - if (options_.dynamic_sparsity) { - // In the case where the problem has dynamic sparsity, it is not - // worth using the ComputeOuterProduct routine, as the setup cost - // is not amortized over multiple calls to Solve. - Eigen::MappedSparseMatrix<double, Eigen::RowMajor> a( - A->num_rows(), - A->num_cols(), - A->num_nonzeros(), - A->mutable_rows(), - A->mutable_cols(), - A->mutable_values()); - - Eigen::SparseMatrix<double> lhs = a.transpose() * a; - Eigen::SimplicialLDLT<Eigen::SparseMatrix<double> > solver; - return SimplicialLDLTSolve(lhs, - true, - &solver, - rhs_and_solution, - &event_logger); - } - - if (outer_product_.get() == NULL) { - outer_product_.reset( - CompressedRowSparseMatrix::CreateOuterProductMatrixAndProgram( - *A, &pattern_)); - } - - CompressedRowSparseMatrix::ComputeOuterProduct( - *A, pattern_, outer_product_.get()); - - // Map to an upper triangular column major matrix. - // - // outer_product_ is a compressed row sparse matrix and in lower - // triangular form, when mapped to a compressed column sparse - // matrix, it becomes an upper triangular matrix. - Eigen::MappedSparseMatrix<double, Eigen::ColMajor> lhs( - outer_product_->num_rows(), - outer_product_->num_rows(), - outer_product_->num_nonzeros(), - outer_product_->mutable_rows(), - outer_product_->mutable_cols(), - outer_product_->mutable_values()); - - bool do_symbolic_analysis = false; - - // If using post ordering or an old version of Eigen, we cannot - // depend on a preordered jacobian, so we work with a SimplicialLDLT - // decomposition with AMD ordering. - if (options_.use_postordering || - !EIGEN_VERSION_AT_LEAST(3, 2, 2)) { - if (amd_ldlt_.get() == NULL) { - amd_ldlt_.reset(new SimplicialLDLTWithAMDOrdering); - do_symbolic_analysis = true; - } - - return SimplicialLDLTSolve(lhs, - do_symbolic_analysis, - amd_ldlt_.get(), - rhs_and_solution, - &event_logger); - } - -#if EIGEN_VERSION_AT_LEAST(3,2,2) - // The common case - if (natural_ldlt_.get() == NULL) { - natural_ldlt_.reset(new SimplicialLDLTWithNaturalOrdering); - do_symbolic_analysis = true; - } - - return SimplicialLDLTSolve(lhs, - do_symbolic_analysis, - natural_ldlt_.get(), - rhs_and_solution, - &event_logger); -#endif - -#endif // EIGEN_USE_EIGEN_SPARSE -} - -LinearSolver::Summary SparseNormalCholeskySolver::SolveImplUsingCXSparse( - CompressedRowSparseMatrix* A, - double * rhs_and_solution) { -#ifdef CERES_NO_CXSPARSE - - LinearSolver::Summary summary; - summary.num_iterations = 0; - summary.termination_type = LINEAR_SOLVER_FATAL_ERROR; - summary.message = - "SPARSE_NORMAL_CHOLESKY cannot be used with CX_SPARSE " - "because Ceres was not built with support for CXSparse. " - "This requires enabling building with -DCXSPARSE=ON."; - - return summary; - -#else - - EventLogger event_logger("SparseNormalCholeskySolver::CXSparse::Solve"); - if (options_.dynamic_sparsity) { - return ComputeNormalEquationsAndSolveUsingCXSparse(A, - rhs_and_solution, - &event_logger); - } - - LinearSolver::Summary summary; - summary.num_iterations = 1; - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.message = "Success."; - - // Compute the normal equations. J'J delta = J'f and solve them - // using a sparse Cholesky factorization. Notice that when compared - // to SuiteSparse we have to explicitly compute the normal equations - // before they can be factorized. CHOLMOD/SuiteSparse on the other - // hand can just work off of Jt to compute the Cholesky - // factorization of the normal equations. - if (outer_product_.get() == NULL) { - outer_product_.reset( - CompressedRowSparseMatrix::CreateOuterProductMatrixAndProgram( - *A, &pattern_)); - } - - CompressedRowSparseMatrix::ComputeOuterProduct( - *A, pattern_, outer_product_.get()); - cs_di lhs = - cxsparse_.CreateSparseMatrixTransposeView(outer_product_.get()); - - event_logger.AddEvent("Setup"); - - // Compute symbolic factorization if not available. - if (cxsparse_factor_ == NULL) { - if (options_.use_postordering) { - cxsparse_factor_ = cxsparse_.BlockAnalyzeCholesky(&lhs, - A->col_blocks(), - A->col_blocks()); - } else { - cxsparse_factor_ = cxsparse_.AnalyzeCholeskyWithNaturalOrdering(&lhs); - } - } - event_logger.AddEvent("Analysis"); - - if (cxsparse_factor_ == NULL) { - summary.termination_type = LINEAR_SOLVER_FATAL_ERROR; - summary.message = - "CXSparse failure. Unable to find symbolic factorization."; - } else if (!cxsparse_.SolveCholesky(&lhs, - cxsparse_factor_, - rhs_and_solution)) { - summary.termination_type = LINEAR_SOLVER_FAILURE; - summary.message = "CXSparse::SolveCholesky failed."; - } - event_logger.AddEvent("Solve"); - - return summary; -#endif -} - -LinearSolver::Summary SparseNormalCholeskySolver::SolveImplUsingSuiteSparse( - CompressedRowSparseMatrix* A, - double * rhs_and_solution) { -#ifdef CERES_NO_SUITESPARSE - - LinearSolver::Summary summary; - summary.num_iterations = 0; - summary.termination_type = LINEAR_SOLVER_FATAL_ERROR; - summary.message = - "SPARSE_NORMAL_CHOLESKY cannot be used with SUITE_SPARSE " - "because Ceres was not built with support for SuiteSparse. " - "This requires enabling building with -DSUITESPARSE=ON."; - return summary; - -#else - - EventLogger event_logger("SparseNormalCholeskySolver::SuiteSparse::Solve"); - LinearSolver::Summary summary; - summary.termination_type = LINEAR_SOLVER_SUCCESS; - summary.num_iterations = 1; - summary.message = "Success."; - - const int num_cols = A->num_cols(); - cholmod_sparse lhs = ss_.CreateSparseMatrixTransposeView(A); - event_logger.AddEvent("Setup"); - - if (options_.dynamic_sparsity) { - FreeFactorization(); - } - - if (factor_ == NULL) { - if (options_.use_postordering) { - factor_ = ss_.BlockAnalyzeCholesky(&lhs, - A->col_blocks(), - A->row_blocks(), - &summary.message); - } else { - if (options_.dynamic_sparsity) { - factor_ = ss_.AnalyzeCholesky(&lhs, &summary.message); - } else { - factor_ = ss_.AnalyzeCholeskyWithNaturalOrdering(&lhs, - &summary.message); - } - } - } - event_logger.AddEvent("Analysis"); - - if (factor_ == NULL) { - summary.termination_type = LINEAR_SOLVER_FATAL_ERROR; - // No need to set message as it has already been set by the - // symbolic analysis routines above. - return summary; - } - - summary.termination_type = ss_.Cholesky(&lhs, factor_, &summary.message); - if (summary.termination_type != LINEAR_SOLVER_SUCCESS) { - return summary; - } - - cholmod_dense* rhs = ss_.CreateDenseVector(rhs_and_solution, - num_cols, - num_cols); - cholmod_dense* solution = ss_.Solve(factor_, rhs, &summary.message); - event_logger.AddEvent("Solve"); - - ss_.Free(rhs); - if (solution != NULL) { - memcpy(rhs_and_solution, solution->x, num_cols * sizeof(*rhs_and_solution)); - ss_.Free(solution); - } else { - // No need to set message as it has already been set by the - // numeric factorization routine above. - summary.termination_type = LINEAR_SOLVER_FAILURE; - } - - event_logger.AddEvent("Teardown"); - return summary; -#endif -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.h b/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.h deleted file mode 100644 index 2a93bc56d29..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.h +++ /dev/null @@ -1,127 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// A solver for sparse linear least squares problem based on solving -// the normal equations via a sparse cholesky factorization. - -#ifndef CERES_INTERNAL_SPARSE_NORMAL_CHOLESKY_SOLVER_H_ -#define CERES_INTERNAL_SPARSE_NORMAL_CHOLESKY_SOLVER_H_ - -#include <vector> - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#include "ceres/internal/macros.h" -#include "ceres/linear_solver.h" -#include "ceres/suitesparse.h" -#include "ceres/cxsparse.h" - -#ifdef CERES_USE_EIGEN_SPARSE -#include "Eigen/SparseCholesky" -#endif - -namespace ceres { -namespace internal { - -class CompressedRowSparseMatrix; - -// Solves the normal equations (A'A + D'D) x = A'b, using the CHOLMOD sparse -// cholesky solver. -class SparseNormalCholeskySolver : public CompressedRowSparseMatrixSolver { - public: - explicit SparseNormalCholeskySolver(const LinearSolver::Options& options); - virtual ~SparseNormalCholeskySolver(); - - private: - virtual LinearSolver::Summary SolveImpl( - CompressedRowSparseMatrix* A, - const double* b, - const LinearSolver::PerSolveOptions& options, - double* x); - - LinearSolver::Summary SolveImplUsingSuiteSparse( - CompressedRowSparseMatrix* A, - double* rhs_and_solution); - - - LinearSolver::Summary SolveImplUsingCXSparse( - CompressedRowSparseMatrix* A, - double* rhs_and_solution); - - LinearSolver::Summary SolveImplUsingEigen( - CompressedRowSparseMatrix* A, - double* rhs_and_solution); - - void FreeFactorization(); - - SuiteSparse ss_; - // Cached factorization - cholmod_factor* factor_; - - CXSparse cxsparse_; - // Cached factorization - cs_dis* cxsparse_factor_; - -#ifdef CERES_USE_EIGEN_SPARSE - - // The preprocessor gymnastics here are dealing with the fact that - // before version 3.2.2, Eigen did not support a third template - // parameter to specify the ordering. -#if EIGEN_VERSION_AT_LEAST(3,2,2) - typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>, Eigen::Upper, - Eigen::NaturalOrdering<int> > - SimplicialLDLTWithNaturalOrdering; - scoped_ptr<SimplicialLDLTWithNaturalOrdering> natural_ldlt_; - - typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>, Eigen::Upper, - Eigen::AMDOrdering<int> > - SimplicialLDLTWithAMDOrdering; - scoped_ptr<SimplicialLDLTWithAMDOrdering> amd_ldlt_; - -#else - typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>, Eigen::Upper> - SimplicialLDLTWithAMDOrdering; - - scoped_ptr<SimplicialLDLTWithAMDOrdering> amd_ldlt_; -#endif - -#endif - - scoped_ptr<CompressedRowSparseMatrix> outer_product_; - std::vector<int> pattern_; - const LinearSolver::Options options_; - CERES_DISALLOW_COPY_AND_ASSIGN(SparseNormalCholeskySolver); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_SPARSE_NORMAL_CHOLESKY_SOLVER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/split.cc b/extern/libmv/third_party/ceres/internal/ceres/split.cc deleted file mode 100644 index 296c09a6440..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/split.cc +++ /dev/null @@ -1,123 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#include "ceres/split.h" - -#include <iterator> -#include <string> -#include <vector> - -#include "ceres/internal/port.h" - -namespace ceres { -namespace internal { - -using std::string; -using std::vector; - -// If we know how much to allocate for a vector of strings, we can allocate the -// vector<string> only once and directly to the right size. This saves in -// between 33-66 % of memory space needed for the result, and runs faster in the -// microbenchmarks. -// -// The reserve is only implemented for the single character delim. -// -// The implementation for counting is cut-and-pasted from -// SplitStringToIteratorUsing. I could have written my own counting iterator, -// and use the existing template function, but probably this is more clear and -// more sure to get optimized to reasonable code. -static int CalculateReserveForVector(const string& full, const char* delim) { - int count = 0; - if (delim[0] != '\0' && delim[1] == '\0') { - // Optimize the common case where delim is a single character. - char c = delim[0]; - const char* p = full.data(); - const char* end = p + full.size(); - while (p != end) { - if (*p == c) { // This could be optimized with hasless(v,1) trick. - ++p; - } else { - while (++p != end && *p != c) { - // Skip to the next occurence of the delimiter. - } - ++count; - } - } - } - return count; -} - -template <typename StringType, typename ITR> -static inline -void SplitStringToIteratorUsing(const StringType& full, - const char* delim, - ITR& result) { - // Optimize the common case where delim is a single character. - if (delim[0] != '\0' && delim[1] == '\0') { - char c = delim[0]; - const char* p = full.data(); - const char* end = p + full.size(); - while (p != end) { - if (*p == c) { - ++p; - } else { - const char* start = p; - while (++p != end && *p != c) { - // Skip to the next occurence of the delimiter. - } - *result++ = StringType(start, p - start); - } - } - return; - } - - string::size_type begin_index, end_index; - begin_index = full.find_first_not_of(delim); - while (begin_index != string::npos) { - end_index = full.find_first_of(delim, begin_index); - if (end_index == string::npos) { - *result++ = full.substr(begin_index); - return; - } - *result++ = full.substr(begin_index, (end_index - begin_index)); - begin_index = full.find_first_not_of(delim, end_index); - } -} - -void SplitStringUsing(const string& full, - const char* delim, - vector<string>* result) { - result->reserve(result->size() + CalculateReserveForVector(full, delim)); - std::back_insert_iterator<vector<string> > it(*result); - SplitStringToIteratorUsing(full, delim, it); -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/split.h b/extern/libmv/third_party/ceres/internal/ceres/split.h deleted file mode 100644 index 94b773dee4d..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/split.h +++ /dev/null @@ -1,50 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#ifndef CERES_INTERNAL_SPLIT_H_ -#define CERES_INTERNAL_SPLIT_H_ - -#include <string> -#include <vector> -#include "ceres/internal/port.h" - -namespace ceres { -namespace internal { - -// Split a string using one or more character delimiters, presented as a -// nul-terminated c string. Append the components to 'result'. If there are -// consecutive delimiters, this function skips over all of them. -void SplitStringUsing(const std::string& full, const char* delim, - std::vector<std::string>* res); - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_SPLIT_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/stl_util.h b/extern/libmv/third_party/ceres/internal/ceres/stl_util.h deleted file mode 100644 index 0595a4cf2e9..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/stl_util.h +++ /dev/null @@ -1,91 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: keir@google.com (Keir Mierle) - -#ifndef CERES_INTERNAL_STL_UTIL_H_ -#define CERES_INTERNAL_STL_UTIL_H_ - -#include <algorithm> - -namespace ceres { - -// STLDeleteContainerPointers() -// For a range within a container of pointers, calls delete -// (non-array version) on these pointers. -// NOTE: for these three functions, we could just implement a DeleteObject -// functor and then call for_each() on the range and functor, but this -// requires us to pull in all of algorithm.h, which seems expensive. -// For hash_[multi]set, it is important that this deletes behind the iterator -// because the hash_set may call the hash function on the iterator when it is -// advanced, which could result in the hash function trying to deference a -// stale pointer. -template <class ForwardIterator> -void STLDeleteContainerPointers(ForwardIterator begin, - ForwardIterator end) { - while (begin != end) { - ForwardIterator temp = begin; - ++begin; - delete *temp; - } -} - -// Variant of STLDeleteContainerPointers which allows the container to -// contain duplicates. -template <class ForwardIterator> -void STLDeleteUniqueContainerPointers(ForwardIterator begin, - ForwardIterator end) { - sort(begin, end); - ForwardIterator new_end = unique(begin, end); - while (begin != new_end) { - ForwardIterator temp = begin; - ++begin; - delete *temp; - } -} - -// STLDeleteElements() deletes all the elements in an STL container and clears -// the container. This function is suitable for use with a vector, set, -// hash_set, or any other STL container which defines sensible begin(), end(), -// and clear() methods. -// -// If container is NULL, this function is a no-op. -// -// As an alternative to calling STLDeleteElements() directly, consider -// ElementDeleter (defined below), which ensures that your container's elements -// are deleted when the ElementDeleter goes out of scope. -template <class T> -void STLDeleteElements(T *container) { - if (!container) return; - STLDeleteContainerPointers(container->begin(), container->end()); - container->clear(); -} - -} // namespace ceres - -#endif // CERES_INTERNAL_STL_UTIL_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/stringprintf.cc b/extern/libmv/third_party/ceres/internal/ceres/stringprintf.cc deleted file mode 100644 index d1d8b5fe8ab..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/stringprintf.cc +++ /dev/null @@ -1,132 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: Sanjay Ghemawat - -#include "ceres/stringprintf.h" - -#include <cerrno> -#include <cstdarg> // For va_list and related operations -#include <cstdio> // MSVC requires this for _vsnprintf -#include <string> -#include <vector> - -#include "ceres/internal/port.h" - -namespace ceres { -namespace internal { - -using std::string; - -#ifdef _MSC_VER -enum { IS_COMPILER_MSVC = 1 }; -#if _MSC_VER < 1800 -#define va_copy(d, s) ((d) = (s)) -#endif -#else -enum { IS_COMPILER_MSVC = 0 }; -#endif - -void StringAppendV(string* dst, const char* format, va_list ap) { - // First try with a small fixed size buffer - char space[1024]; - - // It's possible for methods that use a va_list to invalidate - // the data in it upon use. The fix is to make a copy - // of the structure before using it and use that copy instead. - va_list backup_ap; - va_copy(backup_ap, ap); - int result = vsnprintf(space, sizeof(space), format, backup_ap); - va_end(backup_ap); - - if (result < sizeof(space)) { - if (result >= 0) { - // Normal case -- everything fit. - dst->append(space, result); - return; - } - - if (IS_COMPILER_MSVC) { - // Error or MSVC running out of space. MSVC 8.0 and higher - // can be asked about space needed with the special idiom below: - va_copy(backup_ap, ap); - result = vsnprintf(NULL, 0, format, backup_ap); - va_end(backup_ap); - } - - if (result < 0) { - // Just an error. - return; - } - } - - // Increase the buffer size to the size requested by vsnprintf, - // plus one for the closing \0. - int length = result+1; - char* buf = new char[length]; - - // Restore the va_list before we use it again - va_copy(backup_ap, ap); - result = vsnprintf(buf, length, format, backup_ap); - va_end(backup_ap); - - if (result >= 0 && result < length) { - // It fit - dst->append(buf, result); - } - delete[] buf; -} - - -string StringPrintf(const char* format, ...) { - va_list ap; - va_start(ap, format); - string result; - StringAppendV(&result, format, ap); - va_end(ap); - return result; -} - -const string& SStringPrintf(string* dst, const char* format, ...) { - va_list ap; - va_start(ap, format); - dst->clear(); - StringAppendV(dst, format, ap); - va_end(ap); - return *dst; -} - -void StringAppendF(string* dst, const char* format, ...) { - va_list ap; - va_start(ap, format); - StringAppendV(dst, format, ap); - va_end(ap); -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/stringprintf.h b/extern/libmv/third_party/ceres/internal/ceres/stringprintf.h deleted file mode 100644 index feeb9c23430..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/stringprintf.h +++ /dev/null @@ -1,89 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: Sanjay Ghemawat -// -// Printf variants that place their output in a C++ string. -// -// Usage: -// string result = StringPrintf("%d %s\n", 10, "hello"); -// SStringPrintf(&result, "%d %s\n", 10, "hello"); -// StringAppendF(&result, "%d %s\n", 20, "there"); - -#ifndef CERES_INTERNAL_STRINGPRINTF_H_ -#define CERES_INTERNAL_STRINGPRINTF_H_ - -#include <cstdarg> -#include <string> - -#include "ceres/internal/port.h" - -namespace ceres { -namespace internal { - -#if (defined(__GNUC__) || defined(__clang__)) -// Tell the compiler to do printf format string checking if the compiler -// supports it; see the 'format' attribute in -// <http://gcc.gnu.org/onlinedocs/gcc-4.3.0/gcc/Function-Attributes.html>. -// -// N.B.: As the GCC manual states, "[s]ince non-static C++ methods -// have an implicit 'this' argument, the arguments of such methods -// should be counted from two, not one." -#define CERES_PRINTF_ATTRIBUTE(string_index, first_to_check) \ - __attribute__((__format__ (__printf__, string_index, first_to_check))) -#define CERES_SCANF_ATTRIBUTE(string_index, first_to_check) \ - __attribute__((__format__ (__scanf__, string_index, first_to_check))) -#else -#define CERES_PRINTF_ATTRIBUTE(string_index, first_to_check) -#endif - -// Return a C++ string. -extern std::string StringPrintf(const char* format, ...) - // Tell the compiler to do printf format string checking. - CERES_PRINTF_ATTRIBUTE(1, 2); - -// Store result into a supplied string and return it. -extern const std::string& SStringPrintf(std::string* dst, const char* format, ...) - // Tell the compiler to do printf format string checking. - CERES_PRINTF_ATTRIBUTE(2, 3); - -// Append result to a supplied string. -extern void StringAppendF(std::string* dst, const char* format, ...) - // Tell the compiler to do printf format string checking. - CERES_PRINTF_ATTRIBUTE(2, 3); - -// Lower-level routine that takes a va_list and appends to a specified string. -// All other routines are just convenience wrappers around it. -extern void StringAppendV(std::string* dst, const char* format, va_list ap); - -#undef CERES_PRINTF_ATTRIBUTE - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_STRINGPRINTF_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/suitesparse.h b/extern/libmv/third_party/ceres/internal/ceres/suitesparse.h deleted file mode 100644 index 380d76e003a..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/suitesparse.h +++ /dev/null @@ -1,306 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// A simple C++ interface to the SuiteSparse and CHOLMOD libraries. - -#ifndef CERES_INTERNAL_SUITESPARSE_H_ -#define CERES_INTERNAL_SUITESPARSE_H_ - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_NO_SUITESPARSE - -#include <cstring> -#include <string> -#include <vector> - -#include "ceres/linear_solver.h" -#include "cholmod.h" -#include "glog/logging.h" -#include "SuiteSparseQR.hpp" - -// Before SuiteSparse version 4.2.0, cholmod_camd was only enabled -// if SuiteSparse was compiled with Metis support. This makes -// calling and linking into cholmod_camd problematic even though it -// has nothing to do with Metis. This has been fixed reliably in -// 4.2.0. -// -// The fix was actually committed in 4.1.0, but there is -// some confusion about a silent update to the tar ball, so we are -// being conservative and choosing the next minor version where -// things are stable. -#if (SUITESPARSE_VERSION < 4002) -#define CERES_NO_CAMD -#endif - -// UF_long is deprecated but SuiteSparse_long is only available in -// newer versions of SuiteSparse. So for older versions of -// SuiteSparse, we define SuiteSparse_long to be the same as UF_long, -// which is what recent versions of SuiteSparse do anyways. -#ifndef SuiteSparse_long -#define SuiteSparse_long UF_long -#endif - -namespace ceres { -namespace internal { - -class CompressedRowSparseMatrix; -class TripletSparseMatrix; - -// The raw CHOLMOD and SuiteSparseQR libraries have a slightly -// cumbersome c like calling format. This object abstracts it away and -// provides the user with a simpler interface. The methods here cannot -// be static as a cholmod_common object serves as a global variable -// for all cholmod function calls. -class SuiteSparse { - public: - SuiteSparse(); - ~SuiteSparse(); - - // Functions for building cholmod_sparse objects from sparse - // matrices stored in triplet form. The matrix A is not - // modifed. Called owns the result. - cholmod_sparse* CreateSparseMatrix(TripletSparseMatrix* A); - - // This function works like CreateSparseMatrix, except that the - // return value corresponds to A' rather than A. - cholmod_sparse* CreateSparseMatrixTranspose(TripletSparseMatrix* A); - - // Create a cholmod_sparse wrapper around the contents of A. This is - // a shallow object, which refers to the contents of A and does not - // use the SuiteSparse machinery to allocate memory. - cholmod_sparse CreateSparseMatrixTransposeView(CompressedRowSparseMatrix* A); - - // Given a vector x, build a cholmod_dense vector of size out_size - // with the first in_size entries copied from x. If x is NULL, then - // an all zeros vector is returned. Caller owns the result. - cholmod_dense* CreateDenseVector(const double* x, int in_size, int out_size); - - // The matrix A is scaled using the matrix whose diagonal is the - // vector scale. mode describes how scaling is applied. Possible - // values are CHOLMOD_ROW for row scaling - diag(scale) * A, - // CHOLMOD_COL for column scaling - A * diag(scale) and CHOLMOD_SYM - // for symmetric scaling which scales both the rows and the columns - // - diag(scale) * A * diag(scale). - void Scale(cholmod_dense* scale, int mode, cholmod_sparse* A) { - cholmod_scale(scale, mode, A, &cc_); - } - - // Create and return a matrix m = A * A'. Caller owns the - // result. The matrix A is not modified. - cholmod_sparse* AATranspose(cholmod_sparse* A) { - cholmod_sparse*m = cholmod_aat(A, NULL, A->nrow, 1, &cc_); - m->stype = 1; // Pay attention to the upper triangular part. - return m; - } - - // y = alpha * A * x + beta * y. Only y is modified. - void SparseDenseMultiply(cholmod_sparse* A, double alpha, double beta, - cholmod_dense* x, cholmod_dense* y) { - double alpha_[2] = {alpha, 0}; - double beta_[2] = {beta, 0}; - cholmod_sdmult(A, 0, alpha_, beta_, x, y, &cc_); - } - - // Find an ordering of A or AA' (if A is unsymmetric) that minimizes - // the fill-in in the Cholesky factorization of the corresponding - // matrix. This is done by using the AMD algorithm. - // - // Using this ordering, the symbolic Cholesky factorization of A (or - // AA') is computed and returned. - // - // A is not modified, only the pattern of non-zeros of A is used, - // the actual numerical values in A are of no consequence. - // - // message contains an explanation of the failures if any. - // - // Caller owns the result. - cholmod_factor* AnalyzeCholesky(cholmod_sparse* A, std::string* message); - - cholmod_factor* BlockAnalyzeCholesky(cholmod_sparse* A, - const std::vector<int>& row_blocks, - const std::vector<int>& col_blocks, - std::string* message); - - // If A is symmetric, then compute the symbolic Cholesky - // factorization of A(ordering, ordering). If A is unsymmetric, then - // compute the symbolic factorization of - // A(ordering,:) A(ordering,:)'. - // - // A is not modified, only the pattern of non-zeros of A is used, - // the actual numerical values in A are of no consequence. - // - // message contains an explanation of the failures if any. - // - // Caller owns the result. - cholmod_factor* AnalyzeCholeskyWithUserOrdering( - cholmod_sparse* A, - const std::vector<int>& ordering, - std::string* message); - - // Perform a symbolic factorization of A without re-ordering A. No - // postordering of the elimination tree is performed. This ensures - // that the symbolic factor does not introduce an extra permutation - // on the matrix. See the documentation for CHOLMOD for more details. - // - // message contains an explanation of the failures if any. - cholmod_factor* AnalyzeCholeskyWithNaturalOrdering(cholmod_sparse* A, - std::string* message); - - // Use the symbolic factorization in L, to find the numerical - // factorization for the matrix A or AA^T. Return true if - // successful, false otherwise. L contains the numeric factorization - // on return. - // - // message contains an explanation of the failures if any. - LinearSolverTerminationType Cholesky(cholmod_sparse* A, - cholmod_factor* L, - std::string* message); - - // Given a Cholesky factorization of a matrix A = LL^T, solve the - // linear system Ax = b, and return the result. If the Solve fails - // NULL is returned. Caller owns the result. - // - // message contains an explanation of the failures if any. - cholmod_dense* Solve(cholmod_factor* L, cholmod_dense* b, std::string* message); - - // By virtue of the modeling layer in Ceres being block oriented, - // all the matrices used by Ceres are also block oriented. When - // doing sparse direct factorization of these matrices the - // fill-reducing ordering algorithms (in particular AMD) can either - // be run on the block or the scalar form of these matrices. The two - // SuiteSparse::AnalyzeCholesky methods allows the the client to - // compute the symbolic factorization of a matrix by either using - // AMD on the matrix or a user provided ordering of the rows. - // - // But since the underlying matrices are block oriented, it is worth - // running AMD on just the block structre of these matrices and then - // lifting these block orderings to a full scalar ordering. This - // preserves the block structure of the permuted matrix, and exposes - // more of the super-nodal structure of the matrix to the numerical - // factorization routines. - // - // Find the block oriented AMD ordering of a matrix A, whose row and - // column blocks are given by row_blocks, and col_blocks - // respectively. The matrix may or may not be symmetric. The entries - // of col_blocks do not need to sum to the number of columns in - // A. If this is the case, only the first sum(col_blocks) are used - // to compute the ordering. - bool BlockAMDOrdering(const cholmod_sparse* A, - const std::vector<int>& row_blocks, - const std::vector<int>& col_blocks, - std::vector<int>* ordering); - - // Find a fill reducing approximate minimum degree - // ordering. ordering is expected to be large enough to hold the - // ordering. - bool ApproximateMinimumDegreeOrdering(cholmod_sparse* matrix, int* ordering); - - - // Before SuiteSparse version 4.2.0, cholmod_camd was only enabled - // if SuiteSparse was compiled with Metis support. This makes - // calling and linking into cholmod_camd problematic even though it - // has nothing to do with Metis. This has been fixed reliably in - // 4.2.0. - // - // The fix was actually committed in 4.1.0, but there is - // some confusion about a silent update to the tar ball, so we are - // being conservative and choosing the next minor version where - // things are stable. - static bool IsConstrainedApproximateMinimumDegreeOrderingAvailable() { - return (SUITESPARSE_VERSION > 4001); - } - - // Find a fill reducing approximate minimum degree - // ordering. constraints is an array which associates with each - // column of the matrix an elimination group. i.e., all columns in - // group 0 are eliminated first, all columns in group 1 are - // eliminated next etc. This function finds a fill reducing ordering - // that obeys these constraints. - // - // Calling ApproximateMinimumDegreeOrdering is equivalent to calling - // ConstrainedApproximateMinimumDegreeOrdering with a constraint - // array that puts all columns in the same elimination group. - // - // If CERES_NO_CAMD is defined then calling this function will - // result in a crash. - bool ConstrainedApproximateMinimumDegreeOrdering(cholmod_sparse* matrix, - int* constraints, - int* ordering); - - void Free(cholmod_sparse* m) { cholmod_free_sparse(&m, &cc_); } - void Free(cholmod_dense* m) { cholmod_free_dense(&m, &cc_); } - void Free(cholmod_factor* m) { cholmod_free_factor(&m, &cc_); } - - void Print(cholmod_sparse* m, const std::string& name) { - cholmod_print_sparse(m, const_cast<char*>(name.c_str()), &cc_); - } - - void Print(cholmod_dense* m, const std::string& name) { - cholmod_print_dense(m, const_cast<char*>(name.c_str()), &cc_); - } - - void Print(cholmod_triplet* m, const std::string& name) { - cholmod_print_triplet(m, const_cast<char*>(name.c_str()), &cc_); - } - - cholmod_common* mutable_cc() { return &cc_; } - - private: - cholmod_common cc_; -}; - -} // namespace internal -} // namespace ceres - -#else // CERES_NO_SUITESPARSE - -typedef void cholmod_factor; - -class SuiteSparse { - public: - // Defining this static function even when SuiteSparse is not - // available, allows client code to check for the presence of CAMD - // without checking for the absence of the CERES_NO_CAMD symbol. - // - // This is safer because the symbol maybe missing due to a user - // accidently not including suitesparse.h in their code when - // checking for the symbol. - static bool IsConstrainedApproximateMinimumDegreeOrderingAvailable() { - return false; - } - - void Free(void* arg) {} -}; - -#endif // CERES_NO_SUITESPARSE - -#endif // CERES_INTERNAL_SUITESPARSE_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.cc deleted file mode 100644 index 8df405ca115..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.cc +++ /dev/null @@ -1,264 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/triplet_sparse_matrix.h" - -#include <algorithm> -#include <cstddef> -#include "ceres/internal/eigen.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -TripletSparseMatrix::TripletSparseMatrix() - : num_rows_(0), - num_cols_(0), - max_num_nonzeros_(0), - num_nonzeros_(0), - rows_(NULL), - cols_(NULL), - values_(NULL) {} - -TripletSparseMatrix::~TripletSparseMatrix() {} - -TripletSparseMatrix::TripletSparseMatrix(int num_rows, - int num_cols, - int max_num_nonzeros) - : num_rows_(num_rows), - num_cols_(num_cols), - max_num_nonzeros_(max_num_nonzeros), - num_nonzeros_(0), - rows_(NULL), - cols_(NULL), - values_(NULL) { - // All the sizes should at least be zero - CHECK_GE(num_rows, 0); - CHECK_GE(num_cols, 0); - CHECK_GE(max_num_nonzeros, 0); - AllocateMemory(); -} - -TripletSparseMatrix::TripletSparseMatrix(const TripletSparseMatrix& orig) - : SparseMatrix(), - num_rows_(orig.num_rows_), - num_cols_(orig.num_cols_), - max_num_nonzeros_(orig.max_num_nonzeros_), - num_nonzeros_(orig.num_nonzeros_), - rows_(NULL), - cols_(NULL), - values_(NULL) { - AllocateMemory(); - CopyData(orig); -} - -TripletSparseMatrix& TripletSparseMatrix::operator=( - const TripletSparseMatrix& rhs) { - num_rows_ = rhs.num_rows_; - num_cols_ = rhs.num_cols_; - num_nonzeros_ = rhs.num_nonzeros_; - max_num_nonzeros_ = rhs.max_num_nonzeros_; - AllocateMemory(); - CopyData(rhs); - return *this; -} - -bool TripletSparseMatrix::AllTripletsWithinBounds() const { - for (int i = 0; i < num_nonzeros_; ++i) { - if ((rows_[i] < 0) || (rows_[i] >= num_rows_) || - (cols_[i] < 0) || (cols_[i] >= num_cols_)) - return false; - } - return true; -} - -void TripletSparseMatrix::Reserve(int new_max_num_nonzeros) { - CHECK_LE(num_nonzeros_, new_max_num_nonzeros) - << "Reallocation will cause data loss"; - - // Nothing to do if we have enough space already. - if (new_max_num_nonzeros <= max_num_nonzeros_) - return; - - int* new_rows = new int[new_max_num_nonzeros]; - int* new_cols = new int[new_max_num_nonzeros]; - double* new_values = new double[new_max_num_nonzeros]; - - for (int i = 0; i < num_nonzeros_; ++i) { - new_rows[i] = rows_[i]; - new_cols[i] = cols_[i]; - new_values[i] = values_[i]; - } - - rows_.reset(new_rows); - cols_.reset(new_cols); - values_.reset(new_values); - - max_num_nonzeros_ = new_max_num_nonzeros; -} - -void TripletSparseMatrix::SetZero() { - std::fill(values_.get(), values_.get() + max_num_nonzeros_, 0.0); - num_nonzeros_ = 0; -} - -void TripletSparseMatrix::set_num_nonzeros(int num_nonzeros) { - CHECK_GE(num_nonzeros, 0); - CHECK_LE(num_nonzeros, max_num_nonzeros_); - num_nonzeros_ = num_nonzeros; -} - -void TripletSparseMatrix::AllocateMemory() { - rows_.reset(new int[max_num_nonzeros_]); - cols_.reset(new int[max_num_nonzeros_]); - values_.reset(new double[max_num_nonzeros_]); -} - -void TripletSparseMatrix::CopyData(const TripletSparseMatrix& orig) { - for (int i = 0; i < num_nonzeros_; ++i) { - rows_[i] = orig.rows_[i]; - cols_[i] = orig.cols_[i]; - values_[i] = orig.values_[i]; - } -} - -void TripletSparseMatrix::RightMultiply(const double* x, double* y) const { - for (int i = 0; i < num_nonzeros_; ++i) { - y[rows_[i]] += values_[i]*x[cols_[i]]; - } -} - -void TripletSparseMatrix::LeftMultiply(const double* x, double* y) const { - for (int i = 0; i < num_nonzeros_; ++i) { - y[cols_[i]] += values_[i]*x[rows_[i]]; - } -} - -void TripletSparseMatrix::SquaredColumnNorm(double* x) const { - CHECK_NOTNULL(x); - VectorRef(x, num_cols_).setZero(); - for (int i = 0; i < num_nonzeros_; ++i) { - x[cols_[i]] += values_[i] * values_[i]; - } -} - -void TripletSparseMatrix::ScaleColumns(const double* scale) { - CHECK_NOTNULL(scale); - for (int i = 0; i < num_nonzeros_; ++i) { - values_[i] = values_[i] * scale[cols_[i]]; - } -} - -void TripletSparseMatrix::ToDenseMatrix(Matrix* dense_matrix) const { - dense_matrix->resize(num_rows_, num_cols_); - dense_matrix->setZero(); - Matrix& m = *dense_matrix; - for (int i = 0; i < num_nonzeros_; ++i) { - m(rows_[i], cols_[i]) += values_[i]; - } -} - -void TripletSparseMatrix::AppendRows(const TripletSparseMatrix& B) { - CHECK_EQ(B.num_cols(), num_cols_); - Reserve(num_nonzeros_ + B.num_nonzeros_); - for (int i = 0; i < B.num_nonzeros_; ++i) { - rows_.get()[num_nonzeros_] = B.rows()[i] + num_rows_; - cols_.get()[num_nonzeros_] = B.cols()[i]; - values_.get()[num_nonzeros_++] = B.values()[i]; - } - num_rows_ = num_rows_ + B.num_rows(); -} - -void TripletSparseMatrix::AppendCols(const TripletSparseMatrix& B) { - CHECK_EQ(B.num_rows(), num_rows_); - Reserve(num_nonzeros_ + B.num_nonzeros_); - for (int i = 0; i < B.num_nonzeros_; ++i, ++num_nonzeros_) { - rows_.get()[num_nonzeros_] = B.rows()[i]; - cols_.get()[num_nonzeros_] = B.cols()[i] + num_cols_; - values_.get()[num_nonzeros_] = B.values()[i]; - } - num_cols_ = num_cols_ + B.num_cols(); -} - - -void TripletSparseMatrix::Resize(int new_num_rows, int new_num_cols) { - if ((new_num_rows >= num_rows_) && (new_num_cols >= num_cols_)) { - num_rows_ = new_num_rows; - num_cols_ = new_num_cols; - return; - } - - num_rows_ = new_num_rows; - num_cols_ = new_num_cols; - - int* r_ptr = rows_.get(); - int* c_ptr = cols_.get(); - double* v_ptr = values_.get(); - - int dropped_terms = 0; - for (int i = 0; i < num_nonzeros_; ++i) { - if ((r_ptr[i] < num_rows_) && (c_ptr[i] < num_cols_)) { - if (dropped_terms) { - r_ptr[i-dropped_terms] = r_ptr[i]; - c_ptr[i-dropped_terms] = c_ptr[i]; - v_ptr[i-dropped_terms] = v_ptr[i]; - } - } else { - ++dropped_terms; - } - } - num_nonzeros_ -= dropped_terms; -} - -TripletSparseMatrix* TripletSparseMatrix::CreateSparseDiagonalMatrix( - const double* values, int num_rows) { - TripletSparseMatrix* m = - new TripletSparseMatrix(num_rows, num_rows, num_rows); - for (int i = 0; i < num_rows; ++i) { - m->mutable_rows()[i] = i; - m->mutable_cols()[i] = i; - m->mutable_values()[i] = values[i]; - } - m->set_num_nonzeros(num_rows); - return m; -} - -void TripletSparseMatrix::ToTextFile(FILE* file) const { - CHECK_NOTNULL(file); - for (int i = 0; i < num_nonzeros_; ++i) { - fprintf(file, "% 10d % 10d %17f\n", rows_[i], cols_[i], values_[i]); - } -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.h deleted file mode 100644 index f3f5370df6f..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.h +++ /dev/null @@ -1,129 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_TRIPLET_SPARSE_MATRIX_H_ -#define CERES_INTERNAL_TRIPLET_SPARSE_MATRIX_H_ - -#include "ceres/sparse_matrix.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -// An implementation of the SparseMatrix interface to store and -// manipulate sparse matrices in triplet (i,j,s) form. This object is -// inspired by the design of the cholmod_triplet struct used in the -// SuiteSparse package and is memory layout compatible with it. -class TripletSparseMatrix : public SparseMatrix { - public: - TripletSparseMatrix(); - TripletSparseMatrix(int num_rows, int num_cols, int max_num_nonzeros); - explicit TripletSparseMatrix(const TripletSparseMatrix& orig); - - TripletSparseMatrix& operator=(const TripletSparseMatrix& rhs); - - ~TripletSparseMatrix(); - - // Implementation of the SparseMatrix interface. - virtual void SetZero(); - virtual void RightMultiply(const double* x, double* y) const; - virtual void LeftMultiply(const double* x, double* y) const; - virtual void SquaredColumnNorm(double* x) const; - virtual void ScaleColumns(const double* scale); - virtual void ToDenseMatrix(Matrix* dense_matrix) const; - virtual void ToTextFile(FILE* file) const; - virtual int num_rows() const { return num_rows_; } - virtual int num_cols() const { return num_cols_; } - virtual int num_nonzeros() const { return num_nonzeros_; } - virtual const double* values() const { return values_.get(); } - virtual double* mutable_values() { return values_.get(); } - virtual void set_num_nonzeros(int num_nonzeros); - - // Increase max_num_nonzeros and correspondingly increase the size - // of rows_, cols_ and values_. If new_max_num_nonzeros is smaller - // than max_num_nonzeros_, then num_non_zeros should be less than or - // equal to new_max_num_nonzeros, otherwise data loss is possible - // and the method crashes. - void Reserve(int new_max_num_nonzeros); - - // Append the matrix B at the bottom of this matrix. B should have - // the same number of columns as num_cols_. - void AppendRows(const TripletSparseMatrix& B); - - // Append the matrix B at the right of this matrix. B should have - // the same number of rows as num_rows_; - void AppendCols(const TripletSparseMatrix& B); - - // Resize the matrix. Entries which fall outside the new matrix - // bounds are dropped and the num_non_zeros changed accordingly. - void Resize(int new_num_rows, int new_num_cols); - - int max_num_nonzeros() const { return max_num_nonzeros_; } - const int* rows() const { return rows_.get(); } - const int* cols() const { return cols_.get(); } - int* mutable_rows() { return rows_.get(); } - int* mutable_cols() { return cols_.get(); } - - // Returns true if the entries of the matrix obey the row, column, - // and column size bounds and false otherwise. - bool AllTripletsWithinBounds() const; - - bool IsValid() const { return AllTripletsWithinBounds(); } - - // Build a sparse diagonal matrix of size num_rows x num_rows from - // the array values. Entries of the values array are copied into the - // sparse matrix. - static TripletSparseMatrix* CreateSparseDiagonalMatrix(const double* values, - int num_rows); - - private: - void AllocateMemory(); - void CopyData(const TripletSparseMatrix& orig); - - int num_rows_; - int num_cols_; - int max_num_nonzeros_; - int num_nonzeros_; - - // The data is stored as three arrays. For each i, values_[i] is - // stored at the location (rows_[i], cols_[i]). If the there are - // multiple entries with the same (rows_[i], cols_[i]), the values_ - // entries corresponding to them are summed up. - scoped_array<int> rows_; - scoped_array<int> cols_; - scoped_array<double> values_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_TRIPLET_SPARSE_MATRIX_H__ diff --git a/extern/libmv/third_party/ceres/internal/ceres/trust_region_minimizer.cc b/extern/libmv/third_party/ceres/internal/ceres/trust_region_minimizer.cc deleted file mode 100644 index d654d0867f1..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/trust_region_minimizer.cc +++ /dev/null @@ -1,716 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/trust_region_minimizer.h" - -#include <algorithm> -#include <cmath> -#include <cstdlib> -#include <cstring> -#include <limits> -#include <string> -#include <vector> - -#include "Eigen/Core" -#include "ceres/array_utils.h" -#include "ceres/coordinate_descent_minimizer.h" -#include "ceres/evaluator.h" -#include "ceres/file.h" -#include "ceres/internal/eigen.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/line_search.h" -#include "ceres/linear_least_squares_problems.h" -#include "ceres/sparse_matrix.h" -#include "ceres/stringprintf.h" -#include "ceres/trust_region_strategy.h" -#include "ceres/types.h" -#include "ceres/wall_time.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { -namespace { - -LineSearch::Summary DoLineSearch(const Minimizer::Options& options, - const Vector& x, - const Vector& gradient, - const double cost, - const Vector& delta, - Evaluator* evaluator) { - LineSearchFunction line_search_function(evaluator); - - LineSearch::Options line_search_options; - line_search_options.is_silent = true; - line_search_options.interpolation_type = - options.line_search_interpolation_type; - line_search_options.min_step_size = options.min_line_search_step_size; - line_search_options.sufficient_decrease = - options.line_search_sufficient_function_decrease; - line_search_options.max_step_contraction = - options.max_line_search_step_contraction; - line_search_options.min_step_contraction = - options.min_line_search_step_contraction; - line_search_options.max_num_iterations = - options.max_num_line_search_step_size_iterations; - line_search_options.sufficient_curvature_decrease = - options.line_search_sufficient_curvature_decrease; - line_search_options.max_step_expansion = - options.max_line_search_step_expansion; - line_search_options.function = &line_search_function; - - std::string message; - scoped_ptr<LineSearch> line_search( - CHECK_NOTNULL(LineSearch::Create(ceres::ARMIJO, - line_search_options, - &message))); - LineSearch::Summary summary; - line_search_function.Init(x, delta); - line_search->Search(1.0, cost, gradient.dot(delta), &summary); - return summary; -} - -} // namespace - -// Compute a scaling vector that is used to improve the conditioning -// of the Jacobian. -void TrustRegionMinimizer::EstimateScale(const SparseMatrix& jacobian, - double* scale) const { - jacobian.SquaredColumnNorm(scale); - for (int i = 0; i < jacobian.num_cols(); ++i) { - scale[i] = 1.0 / (1.0 + sqrt(scale[i])); - } -} - -void TrustRegionMinimizer::Init(const Minimizer::Options& options) { - options_ = options; - sort(options_.trust_region_minimizer_iterations_to_dump.begin(), - options_.trust_region_minimizer_iterations_to_dump.end()); -} - -void TrustRegionMinimizer::Minimize(const Minimizer::Options& options, - double* parameters, - Solver::Summary* summary) { - double start_time = WallTimeInSeconds(); - double iteration_start_time = start_time; - Init(options); - - Evaluator* evaluator = CHECK_NOTNULL(options_.evaluator.get()); - SparseMatrix* jacobian = CHECK_NOTNULL(options_.jacobian.get()); - TrustRegionStrategy* strategy = - CHECK_NOTNULL(options_.trust_region_strategy.get()); - - const bool is_not_silent = !options.is_silent; - - // If the problem is bounds constrained, then enable the use of a - // line search after the trust region step has been computed. This - // line search will automatically use a projected test point onto - // the feasible set, there by guaranteeing the feasibility of the - // final output. - // - // TODO(sameeragarwal): Make line search available more generally. - const bool use_line_search = options.is_constrained; - - summary->termination_type = NO_CONVERGENCE; - summary->num_successful_steps = 0; - summary->num_unsuccessful_steps = 0; - summary->is_constrained = options.is_constrained; - - const int num_parameters = evaluator->NumParameters(); - const int num_effective_parameters = evaluator->NumEffectiveParameters(); - const int num_residuals = evaluator->NumResiduals(); - - Vector residuals(num_residuals); - Vector trust_region_step(num_effective_parameters); - Vector delta(num_effective_parameters); - Vector x_plus_delta(num_parameters); - Vector gradient(num_effective_parameters); - Vector model_residuals(num_residuals); - Vector scale(num_effective_parameters); - Vector negative_gradient(num_effective_parameters); - Vector projected_gradient_step(num_parameters); - - IterationSummary iteration_summary; - iteration_summary.iteration = 0; - iteration_summary.step_is_valid = false; - iteration_summary.step_is_successful = false; - iteration_summary.cost_change = 0.0; - iteration_summary.gradient_max_norm = 0.0; - iteration_summary.gradient_norm = 0.0; - iteration_summary.step_norm = 0.0; - iteration_summary.relative_decrease = 0.0; - iteration_summary.trust_region_radius = strategy->Radius(); - iteration_summary.eta = options_.eta; - iteration_summary.linear_solver_iterations = 0; - iteration_summary.step_solver_time_in_seconds = 0; - - VectorRef x_min(parameters, num_parameters); - Vector x = x_min; - // Project onto the feasible set. - if (options.is_constrained) { - delta.setZero(); - if (!evaluator->Plus(x.data(), delta.data(), x_plus_delta.data())) { - summary->message = - "Unable to project initial point onto the feasible set."; - summary->termination_type = FAILURE; - LOG_IF(WARNING, is_not_silent) << "Terminating: " << summary->message; - return; - } - x_min = x_plus_delta; - x = x_plus_delta; - } - - double x_norm = x.norm(); - - // Do initial cost and Jacobian evaluation. - double cost = 0.0; - if (!evaluator->Evaluate(x.data(), - &cost, - residuals.data(), - gradient.data(), - jacobian)) { - summary->message = "Residual and Jacobian evaluation failed."; - summary->termination_type = FAILURE; - LOG_IF(WARNING, is_not_silent) << "Terminating: " << summary->message; - return; - } - - negative_gradient = -gradient; - if (!evaluator->Plus(x.data(), - negative_gradient.data(), - projected_gradient_step.data())) { - summary->message = "Unable to compute gradient step."; - summary->termination_type = FAILURE; - LOG(ERROR) << "Terminating: " << summary->message; - return; - } - - summary->initial_cost = cost + summary->fixed_cost; - iteration_summary.cost = cost + summary->fixed_cost; - iteration_summary.gradient_max_norm = - (x - projected_gradient_step).lpNorm<Eigen::Infinity>(); - iteration_summary.gradient_norm = (x - projected_gradient_step).norm(); - - if (iteration_summary.gradient_max_norm <= options.gradient_tolerance) { - summary->message = StringPrintf("Gradient tolerance reached. " - "Gradient max norm: %e <= %e", - iteration_summary.gradient_max_norm, - options_.gradient_tolerance); - summary->termination_type = CONVERGENCE; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - - // Ensure that there is an iteration summary object for iteration - // 0 in Summary::iterations. - iteration_summary.iteration_time_in_seconds = - WallTimeInSeconds() - iteration_start_time; - iteration_summary.cumulative_time_in_seconds = - WallTimeInSeconds() - start_time + - summary->preprocessor_time_in_seconds; - summary->iterations.push_back(iteration_summary); - return; - } - - if (options_.jacobi_scaling) { - EstimateScale(*jacobian, scale.data()); - jacobian->ScaleColumns(scale.data()); - } else { - scale.setOnes(); - } - - iteration_summary.iteration_time_in_seconds = - WallTimeInSeconds() - iteration_start_time; - iteration_summary.cumulative_time_in_seconds = - WallTimeInSeconds() - start_time - + summary->preprocessor_time_in_seconds; - summary->iterations.push_back(iteration_summary); - - int num_consecutive_nonmonotonic_steps = 0; - double minimum_cost = cost; - double reference_cost = cost; - double accumulated_reference_model_cost_change = 0.0; - double candidate_cost = cost; - double accumulated_candidate_model_cost_change = 0.0; - int num_consecutive_invalid_steps = 0; - bool inner_iterations_are_enabled = - options.inner_iteration_minimizer.get() != NULL; - while (true) { - bool inner_iterations_were_useful = false; - if (!RunCallbacks(options, iteration_summary, summary)) { - return; - } - - iteration_start_time = WallTimeInSeconds(); - if (iteration_summary.iteration >= options_.max_num_iterations) { - summary->message = "Maximum number of iterations reached."; - summary->termination_type = NO_CONVERGENCE; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - return; - } - - const double total_solver_time = iteration_start_time - start_time + - summary->preprocessor_time_in_seconds; - if (total_solver_time >= options_.max_solver_time_in_seconds) { - summary->message = "Maximum solver time reached."; - summary->termination_type = NO_CONVERGENCE; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - return; - } - - const double strategy_start_time = WallTimeInSeconds(); - TrustRegionStrategy::PerSolveOptions per_solve_options; - per_solve_options.eta = options_.eta; - if (find(options_.trust_region_minimizer_iterations_to_dump.begin(), - options_.trust_region_minimizer_iterations_to_dump.end(), - iteration_summary.iteration) != - options_.trust_region_minimizer_iterations_to_dump.end()) { - per_solve_options.dump_format_type = - options_.trust_region_problem_dump_format_type; - per_solve_options.dump_filename_base = - JoinPath(options_.trust_region_problem_dump_directory, - StringPrintf("ceres_solver_iteration_%03d", - iteration_summary.iteration)); - } else { - per_solve_options.dump_format_type = TEXTFILE; - per_solve_options.dump_filename_base.clear(); - } - - TrustRegionStrategy::Summary strategy_summary = - strategy->ComputeStep(per_solve_options, - jacobian, - residuals.data(), - trust_region_step.data()); - - if (strategy_summary.termination_type == LINEAR_SOLVER_FATAL_ERROR) { - summary->message = - "Linear solver failed due to unrecoverable " - "non-numeric causes. Please see the error log for clues. "; - summary->termination_type = FAILURE; - LOG_IF(WARNING, is_not_silent) << "Terminating: " << summary->message; - return; - } - - iteration_summary = IterationSummary(); - iteration_summary.iteration = summary->iterations.back().iteration + 1; - iteration_summary.step_solver_time_in_seconds = - WallTimeInSeconds() - strategy_start_time; - iteration_summary.linear_solver_iterations = - strategy_summary.num_iterations; - iteration_summary.step_is_valid = false; - iteration_summary.step_is_successful = false; - - double model_cost_change = 0.0; - if (strategy_summary.termination_type != LINEAR_SOLVER_FAILURE) { - // new_model_cost - // = 1/2 [f + J * step]^2 - // = 1/2 [ f'f + 2f'J * step + step' * J' * J * step ] - // model_cost_change - // = cost - new_model_cost - // = f'f/2 - 1/2 [ f'f + 2f'J * step + step' * J' * J * step] - // = -f'J * step - step' * J' * J * step / 2 - model_residuals.setZero(); - jacobian->RightMultiply(trust_region_step.data(), model_residuals.data()); - model_cost_change = - - model_residuals.dot(residuals + model_residuals / 2.0); - - if (model_cost_change < 0.0) { - VLOG_IF(1, is_not_silent) - << "Invalid step: current_cost: " << cost - << " absolute difference " << model_cost_change - << " relative difference " << (model_cost_change / cost); - } else { - iteration_summary.step_is_valid = true; - } - } - - if (!iteration_summary.step_is_valid) { - // Invalid steps can happen due to a number of reasons, and we - // allow a limited number of successive failures, and return with - // FAILURE if this limit is exceeded. - if (++num_consecutive_invalid_steps >= - options_.max_num_consecutive_invalid_steps) { - summary->message = StringPrintf( - "Number of successive invalid steps more " - "than Solver::Options::max_num_consecutive_invalid_steps: %d", - options_.max_num_consecutive_invalid_steps); - summary->termination_type = FAILURE; - LOG_IF(WARNING, is_not_silent) << "Terminating: " << summary->message; - return; - } - - // We are going to try and reduce the trust region radius and - // solve again. To do this, we are going to treat this iteration - // as an unsuccessful iteration. Since the various callbacks are - // still executed, we are going to fill the iteration summary - // with data that assumes a step of length zero and no progress. - iteration_summary.cost = cost + summary->fixed_cost; - iteration_summary.cost_change = 0.0; - iteration_summary.gradient_max_norm = - summary->iterations.back().gradient_max_norm; - iteration_summary.gradient_norm = - summary->iterations.back().gradient_norm; - iteration_summary.step_norm = 0.0; - iteration_summary.relative_decrease = 0.0; - iteration_summary.eta = options_.eta; - } else { - // The step is numerically valid, so now we can judge its quality. - num_consecutive_invalid_steps = 0; - - // Undo the Jacobian column scaling. - delta = (trust_region_step.array() * scale.array()).matrix(); - - // Try improving the step further by using an ARMIJO line - // search. - // - // TODO(sameeragarwal): What happens to trust region sizing as - // it interacts with the line search ? - if (use_line_search) { - const LineSearch::Summary line_search_summary = - DoLineSearch(options, x, gradient, cost, delta, evaluator); - - summary->line_search_cost_evaluation_time_in_seconds += - line_search_summary.cost_evaluation_time_in_seconds; - summary->line_search_gradient_evaluation_time_in_seconds += - line_search_summary.gradient_evaluation_time_in_seconds; - summary->line_search_polynomial_minimization_time_in_seconds += - line_search_summary.polynomial_minimization_time_in_seconds; - summary->line_search_total_time_in_seconds += - line_search_summary.total_time_in_seconds; - - if (line_search_summary.success) { - delta *= line_search_summary.optimal_step_size; - } - } - - double new_cost = std::numeric_limits<double>::max(); - if (evaluator->Plus(x.data(), delta.data(), x_plus_delta.data())) { - if (!evaluator->Evaluate(x_plus_delta.data(), - &new_cost, - NULL, - NULL, - NULL)) { - LOG_IF(WARNING, is_not_silent) - << "Step failed to evaluate. " - << "Treating it as a step with infinite cost"; - new_cost = std::numeric_limits<double>::max(); - } - } else { - LOG_IF(WARNING, is_not_silent) - << "x_plus_delta = Plus(x, delta) failed. " - << "Treating it as a step with infinite cost"; - } - - if (new_cost < std::numeric_limits<double>::max()) { - // Check if performing an inner iteration will make it better. - if (inner_iterations_are_enabled) { - ++summary->num_inner_iteration_steps; - double inner_iteration_start_time = WallTimeInSeconds(); - const double x_plus_delta_cost = new_cost; - Vector inner_iteration_x = x_plus_delta; - Solver::Summary inner_iteration_summary; - options.inner_iteration_minimizer->Minimize(options, - inner_iteration_x.data(), - &inner_iteration_summary); - if (!evaluator->Evaluate(inner_iteration_x.data(), - &new_cost, - NULL, NULL, NULL)) { - VLOG_IF(2, is_not_silent) << "Inner iteration failed."; - new_cost = x_plus_delta_cost; - } else { - x_plus_delta = inner_iteration_x; - // Boost the model_cost_change, since the inner iteration - // improvements are not accounted for by the trust region. - model_cost_change += x_plus_delta_cost - new_cost; - VLOG_IF(2, is_not_silent) - << "Inner iteration succeeded; Current cost: " << cost - << " Trust region step cost: " << x_plus_delta_cost - << " Inner iteration cost: " << new_cost; - - inner_iterations_were_useful = new_cost < cost; - - const double inner_iteration_relative_progress = - 1.0 - new_cost / x_plus_delta_cost; - // Disable inner iterations once the relative improvement - // drops below tolerance. - inner_iterations_are_enabled = - (inner_iteration_relative_progress > - options.inner_iteration_tolerance); - VLOG_IF(2, is_not_silent && !inner_iterations_are_enabled) - << "Disabling inner iterations. Progress : " - << inner_iteration_relative_progress; - } - summary->inner_iteration_time_in_seconds += - WallTimeInSeconds() - inner_iteration_start_time; - } - } - - iteration_summary.step_norm = (x - x_plus_delta).norm(); - - // Convergence based on parameter_tolerance. - const double step_size_tolerance = options_.parameter_tolerance * - (x_norm + options_.parameter_tolerance); - if (iteration_summary.step_norm <= step_size_tolerance) { - summary->message = - StringPrintf("Parameter tolerance reached. " - "Relative step_norm: %e <= %e.", - (iteration_summary.step_norm / - (x_norm + options_.parameter_tolerance)), - options_.parameter_tolerance); - summary->termination_type = CONVERGENCE; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - return; - } - - iteration_summary.cost_change = cost - new_cost; - const double absolute_function_tolerance = - options_.function_tolerance * cost; - if (fabs(iteration_summary.cost_change) <= absolute_function_tolerance) { - summary->message = - StringPrintf("Function tolerance reached. " - "|cost_change|/cost: %e <= %e", - fabs(iteration_summary.cost_change) / cost, - options_.function_tolerance); - summary->termination_type = CONVERGENCE; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - return; - } - - const double relative_decrease = - iteration_summary.cost_change / model_cost_change; - - const double historical_relative_decrease = - (reference_cost - new_cost) / - (accumulated_reference_model_cost_change + model_cost_change); - - // If monotonic steps are being used, then the relative_decrease - // is the usual ratio of the change in objective function value - // divided by the change in model cost. - // - // If non-monotonic steps are allowed, then we take the maximum - // of the relative_decrease and the - // historical_relative_decrease, which measures the increase - // from a reference iteration. The model cost change is - // estimated by accumulating the model cost changes since the - // reference iteration. The historical relative_decrease offers - // a boost to a step which is not too bad compared to the - // reference iteration, allowing for non-monotonic steps. - iteration_summary.relative_decrease = - options.use_nonmonotonic_steps - ? std::max(relative_decrease, historical_relative_decrease) - : relative_decrease; - - // Normally, the quality of a trust region step is measured by - // the ratio - // - // cost_change - // r = ----------------- - // model_cost_change - // - // All the change in the nonlinear objective is due to the trust - // region step so this ratio is a good measure of the quality of - // the trust region radius. However, when inner iterations are - // being used, cost_change includes the contribution of the - // inner iterations and its not fair to credit it all to the - // trust region algorithm. So we change the ratio to be - // - // cost_change - // r = ------------------------------------------------ - // (model_cost_change + inner_iteration_cost_change) - // - // In most cases this is fine, but it can be the case that the - // change in solution quality due to inner iterations is so large - // and the trust region step is so bad, that this ratio can become - // quite small. - // - // This can cause the trust region loop to reject this step. To - // get around this, we expicitly check if the inner iterations - // led to a net decrease in the objective function value. If - // they did, we accept the step even if the trust region ratio - // is small. - // - // Notice that we do not just check that cost_change is positive - // which is a weaker condition and would render the - // min_relative_decrease threshold useless. Instead, we keep - // track of inner_iterations_were_useful, which is true only - // when inner iterations lead to a net decrease in the cost. - iteration_summary.step_is_successful = - (inner_iterations_were_useful || - iteration_summary.relative_decrease > - options_.min_relative_decrease); - - if (iteration_summary.step_is_successful) { - accumulated_candidate_model_cost_change += model_cost_change; - accumulated_reference_model_cost_change += model_cost_change; - - if (!inner_iterations_were_useful && - relative_decrease <= options_.min_relative_decrease) { - iteration_summary.step_is_nonmonotonic = true; - VLOG_IF(2, is_not_silent) - << "Non-monotonic step! " - << " relative_decrease: " - << relative_decrease - << " historical_relative_decrease: " - << historical_relative_decrease; - } - } - } - - if (iteration_summary.step_is_successful) { - ++summary->num_successful_steps; - strategy->StepAccepted(iteration_summary.relative_decrease); - - x = x_plus_delta; - x_norm = x.norm(); - - // Step looks good, evaluate the residuals and Jacobian at this - // point. - if (!evaluator->Evaluate(x.data(), - &cost, - residuals.data(), - gradient.data(), - jacobian)) { - summary->message = "Residual and Jacobian evaluation failed."; - summary->termination_type = FAILURE; - LOG_IF(WARNING, is_not_silent) << "Terminating: " << summary->message; - return; - } - - negative_gradient = -gradient; - if (!evaluator->Plus(x.data(), - negative_gradient.data(), - projected_gradient_step.data())) { - summary->message = - "projected_gradient_step = Plus(x, -gradient) failed."; - summary->termination_type = FAILURE; - LOG(ERROR) << "Terminating: " << summary->message; - return; - } - - iteration_summary.gradient_max_norm = - (x - projected_gradient_step).lpNorm<Eigen::Infinity>(); - iteration_summary.gradient_norm = (x - projected_gradient_step).norm(); - - if (options_.jacobi_scaling) { - jacobian->ScaleColumns(scale.data()); - } - - // Update the best, reference and candidate iterates. - // - // Based on algorithm 10.1.2 (page 357) of "Trust Region - // Methods" by Conn Gould & Toint, or equations 33-40 of - // "Non-monotone trust-region algorithms for nonlinear - // optimization subject to convex constraints" by Phil Toint, - // Mathematical Programming, 77, 1997. - if (cost < minimum_cost) { - // A step that improves solution quality was found. - x_min = x; - minimum_cost = cost; - // Set the candidate iterate to the current point. - candidate_cost = cost; - num_consecutive_nonmonotonic_steps = 0; - accumulated_candidate_model_cost_change = 0.0; - } else { - ++num_consecutive_nonmonotonic_steps; - if (cost > candidate_cost) { - // The current iterate is has a higher cost than the - // candidate iterate. Set the candidate to this point. - VLOG_IF(2, is_not_silent) - << "Updating the candidate iterate to the current point."; - candidate_cost = cost; - accumulated_candidate_model_cost_change = 0.0; - } - - // At this point we have made too many non-monotonic steps and - // we are going to reset the value of the reference iterate so - // as to force the algorithm to descend. - // - // This is the case because the candidate iterate has a value - // greater than minimum_cost but smaller than the reference - // iterate. - if (num_consecutive_nonmonotonic_steps == - options.max_consecutive_nonmonotonic_steps) { - VLOG_IF(2, is_not_silent) - << "Resetting the reference point to the candidate point"; - reference_cost = candidate_cost; - accumulated_reference_model_cost_change = - accumulated_candidate_model_cost_change; - } - } - } else { - ++summary->num_unsuccessful_steps; - if (iteration_summary.step_is_valid) { - strategy->StepRejected(iteration_summary.relative_decrease); - } else { - strategy->StepIsInvalid(); - } - } - - iteration_summary.cost = cost + summary->fixed_cost; - iteration_summary.trust_region_radius = strategy->Radius(); - iteration_summary.iteration_time_in_seconds = - WallTimeInSeconds() - iteration_start_time; - iteration_summary.cumulative_time_in_seconds = - WallTimeInSeconds() - start_time - + summary->preprocessor_time_in_seconds; - summary->iterations.push_back(iteration_summary); - - // If the step was successful, check for the gradient norm - // collapsing to zero, and if the step is unsuccessful then check - // if the trust region radius has collapsed to zero. - // - // For correctness (Number of IterationSummary objects, correct - // final cost, and state update) these convergence tests need to - // be performed at the end of the iteration. - if (iteration_summary.step_is_successful) { - // Gradient norm can only go down in successful steps. - if (iteration_summary.gradient_max_norm <= options.gradient_tolerance) { - summary->message = StringPrintf("Gradient tolerance reached. " - "Gradient max norm: %e <= %e", - iteration_summary.gradient_max_norm, - options_.gradient_tolerance); - summary->termination_type = CONVERGENCE; - VLOG_IF(1, is_not_silent) << "Terminating: " << summary->message; - return; - } - } else { - // Trust region radius can only go down if the step if - // unsuccessful. - if (iteration_summary.trust_region_radius < - options_.min_trust_region_radius) { - summary->message = "Termination. Minimum trust region radius reached."; - summary->termination_type = CONVERGENCE; - VLOG_IF(1, is_not_silent) << summary->message; - return; - } - } - } -} - - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/trust_region_minimizer.h b/extern/libmv/third_party/ceres/internal/ceres/trust_region_minimizer.h deleted file mode 100644 index ed52c2642d1..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/trust_region_minimizer.h +++ /dev/null @@ -1,65 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_TRUST_REGION_MINIMIZER_H_ -#define CERES_INTERNAL_TRUST_REGION_MINIMIZER_H_ - -#include "ceres/minimizer.h" -#include "ceres/solver.h" -#include "ceres/types.h" - -namespace ceres { -namespace internal { - -// Generic trust region minimization algorithm. The heavy lifting is -// done by a TrustRegionStrategy object passed in as part of options. -// -// For example usage, see SolverImpl::Minimize. -class TrustRegionMinimizer : public Minimizer { - public: - ~TrustRegionMinimizer() {} - virtual void Minimize(const Minimizer::Options& options, - double* parameters, - Solver::Summary* summary); - - private: - void Init(const Minimizer::Options& options); - void EstimateScale(const SparseMatrix& jacobian, double* scale) const; - bool MaybeDumpLinearLeastSquaresProblem(const int iteration, - const SparseMatrix* jacobian, - const double* residuals, - const double* step) const; - - Minimizer::Options options_; -}; - -} // namespace internal -} // namespace ceres -#endif // CERES_INTERNAL_TRUST_REGION_MINIMIZER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/trust_region_preprocessor.cc b/extern/libmv/third_party/ceres/internal/ceres/trust_region_preprocessor.cc deleted file mode 100644 index 4020e4ca115..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/trust_region_preprocessor.cc +++ /dev/null @@ -1,362 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/trust_region_preprocessor.h" - -#include <numeric> -#include <string> -#include "ceres/callbacks.h" -#include "ceres/evaluator.h" -#include "ceres/linear_solver.h" -#include "ceres/minimizer.h" -#include "ceres/parameter_block.h" -#include "ceres/preconditioner.h" -#include "ceres/preprocessor.h" -#include "ceres/problem_impl.h" -#include "ceres/program.h" -#include "ceres/reorder_program.h" -#include "ceres/suitesparse.h" -#include "ceres/trust_region_strategy.h" -#include "ceres/wall_time.h" - -namespace ceres { -namespace internal { - -using std::vector; - -namespace { - -ParameterBlockOrdering* CreateDefaultLinearSolverOrdering( - const Program& program) { - ParameterBlockOrdering* ordering = new ParameterBlockOrdering; - const vector<ParameterBlock*>& parameter_blocks = - program.parameter_blocks(); - for (int i = 0; i < parameter_blocks.size(); ++i) { - ordering->AddElementToGroup( - const_cast<double*>(parameter_blocks[i]->user_state()), 0); - } - return ordering; -} - -// Check if all the user supplied values in the parameter blocks are -// sane or not, and if the program is feasible or not. -bool IsProgramValid(const Program& program, std::string* error) { - return (program.ParameterBlocksAreFinite(error) && - program.IsFeasible(error)); -} - -void AlternateLinearSolverAndPreconditionerForSchurTypeLinearSolver( - Solver::Options* options) { - if (!IsSchurType(options->linear_solver_type)) { - return; - } - - const LinearSolverType linear_solver_type_given = options->linear_solver_type; - const PreconditionerType preconditioner_type_given = - options->preconditioner_type; - options->linear_solver_type = LinearSolver::LinearSolverForZeroEBlocks( - linear_solver_type_given); - - std::string message; - if (linear_solver_type_given == ITERATIVE_SCHUR) { - options->preconditioner_type = Preconditioner::PreconditionerForZeroEBlocks( - preconditioner_type_given); - - message = - StringPrintf( - "No E blocks. Switching from %s(%s) to %s(%s).", - LinearSolverTypeToString(linear_solver_type_given), - PreconditionerTypeToString(preconditioner_type_given), - LinearSolverTypeToString(options->linear_solver_type), - PreconditionerTypeToString(options->preconditioner_type)); - } else { - message = - StringPrintf( - "No E blocks. Switching from %s to %s.", - LinearSolverTypeToString(linear_solver_type_given), - LinearSolverTypeToString(options->linear_solver_type)); - } - - VLOG_IF(1, options->logging_type != SILENT) << message; -} - -// For Schur type and SPARSE_NORMAL_CHOLESKY linear solvers, reorder -// the program to reduce fill-in and increase cache coherency. -bool ReorderProgram(PreprocessedProblem* pp) { - Solver::Options& options = pp->options; - if (IsSchurType(options.linear_solver_type)) { - return ReorderProgramForSchurTypeLinearSolver( - options.linear_solver_type, - options.sparse_linear_algebra_library_type, - pp->problem->parameter_map(), - options.linear_solver_ordering.get(), - pp->reduced_program.get(), - &pp->error); - } - - if (options.linear_solver_type == SPARSE_NORMAL_CHOLESKY && - !options.dynamic_sparsity) { - return ReorderProgramForSparseNormalCholesky( - options.sparse_linear_algebra_library_type, - *options.linear_solver_ordering, - pp->reduced_program.get(), - &pp->error); - } - - return true; -} - -// Configure and create a linear solver object. In doing so, if a -// sparse direct factorization based linear solver is being used, then -// find a fill reducing ordering and reorder the program as needed -// too. -bool SetupLinearSolver(PreprocessedProblem* pp) { - Solver::Options& options = pp->options; - if (options.linear_solver_ordering.get() == NULL) { - // If the user has not supplied a linear solver ordering, then we - // assume that they are giving all the freedom to us in choosing - // the best possible ordering. This intent can be indicated by - // putting all the parameter blocks in the same elimination group. - options.linear_solver_ordering.reset( - CreateDefaultLinearSolverOrdering(*pp->reduced_program)); - } else { - // If the user supplied an ordering, then check if the first - // elimination group is still non-empty after the reduced problem - // has been constructed. - // - // This is important for Schur type linear solvers, where the - // first elimination group is special -- it needs to be an - // independent set. - // - // If the first elimination group is empty, then we cannot use the - // user's requested linear solver (and a preconditioner as the - // case may be) so we must use a different one. - ParameterBlockOrdering* ordering = options.linear_solver_ordering.get(); - const int min_group_id = ordering->MinNonZeroGroup(); - ordering->Remove(pp->removed_parameter_blocks); - if (IsSchurType(options.linear_solver_type) && - min_group_id != ordering->MinNonZeroGroup()) { - AlternateLinearSolverAndPreconditionerForSchurTypeLinearSolver( - &options); - } - } - - // Reorder the program to reduce fill in and improve cache coherency - // of the Jacobian. - if (!ReorderProgram(pp)) { - return false; - } - - // Configure the linear solver. - pp->linear_solver_options = LinearSolver::Options(); - pp->linear_solver_options.min_num_iterations = - options.min_linear_solver_iterations; - pp->linear_solver_options.max_num_iterations = - options.max_linear_solver_iterations; - pp->linear_solver_options.type = options.linear_solver_type; - pp->linear_solver_options.preconditioner_type = options.preconditioner_type; - pp->linear_solver_options.visibility_clustering_type = - options.visibility_clustering_type; - pp->linear_solver_options.sparse_linear_algebra_library_type = - options.sparse_linear_algebra_library_type; - pp->linear_solver_options.dense_linear_algebra_library_type = - options.dense_linear_algebra_library_type; - pp->linear_solver_options.use_explicit_schur_complement = - options.use_explicit_schur_complement; - pp->linear_solver_options.dynamic_sparsity = options.dynamic_sparsity; - pp->linear_solver_options.num_threads = options.num_linear_solver_threads; - - // Ignore user's postordering preferences and force it to be true if - // cholmod_camd is not available. This ensures that the linear - // solver does not assume that a fill-reducing pre-ordering has been - // done. - pp->linear_solver_options.use_postordering = options.use_postordering; - if (options.linear_solver_type == SPARSE_SCHUR && - options.sparse_linear_algebra_library_type == SUITE_SPARSE && - !SuiteSparse::IsConstrainedApproximateMinimumDegreeOrderingAvailable()) { - pp->linear_solver_options.use_postordering = true; - } - - OrderingToGroupSizes(options.linear_solver_ordering.get(), - &pp->linear_solver_options.elimination_groups); - - // Schur type solvers expect at least two elimination groups. If - // there is only one elimination group, then it is guaranteed that - // this group only contains e_blocks. Thus we add a dummy - // elimination group with zero blocks in it. - if (IsSchurType(pp->linear_solver_options.type) && - pp->linear_solver_options.elimination_groups.size() == 1) { - pp->linear_solver_options.elimination_groups.push_back(0); - } - - pp->linear_solver.reset(LinearSolver::Create(pp->linear_solver_options)); - return (pp->linear_solver.get() != NULL); -} - -// Configure and create the evaluator. -bool SetupEvaluator(PreprocessedProblem* pp) { - const Solver::Options& options = pp->options; - pp->evaluator_options = Evaluator::Options(); - pp->evaluator_options.linear_solver_type = options.linear_solver_type; - pp->evaluator_options.num_eliminate_blocks = 0; - if (IsSchurType(options.linear_solver_type)) { - pp->evaluator_options.num_eliminate_blocks = - options - .linear_solver_ordering - ->group_to_elements().begin() - ->second.size(); - } - - pp->evaluator_options.num_threads = options.num_threads; - pp->evaluator_options.dynamic_sparsity = options.dynamic_sparsity; - pp->evaluator.reset(Evaluator::Create(pp->evaluator_options, - pp->reduced_program.get(), - &pp->error)); - - return (pp->evaluator.get() != NULL); -} - -// If the user requested inner iterations, then find an inner -// iteration ordering as needed and configure and create a -// CoordinateDescentMinimizer object to perform the inner iterations. -bool SetupInnerIterationMinimizer(PreprocessedProblem* pp) { - Solver::Options& options = pp->options; - if (!options.use_inner_iterations) { - return true; - } - - // With just one parameter block, the outer iteration of the trust - // region method and inner iterations are doing exactly the same - // thing, and thus inner iterations are not needed. - if (pp->reduced_program->NumParameterBlocks() == 1) { - LOG(WARNING) << "Reduced problem only contains one parameter block." - << "Disabling inner iterations."; - return true; - } - - if (options.inner_iteration_ordering.get() != NULL) { - // If the user supplied an ordering, then remove the set of - // inactive parameter blocks from it - options.inner_iteration_ordering->Remove(pp->removed_parameter_blocks); - if (options.inner_iteration_ordering->NumElements() == 0) { - LOG(WARNING) << "No remaining elements in the inner iteration ordering."; - return true; - } - - // Validate the reduced ordering. - if (!CoordinateDescentMinimizer::IsOrderingValid( - *pp->reduced_program, - *options.inner_iteration_ordering, - &pp->error)) { - return false; - } - } else { - // The user did not supply an ordering, so create one. - options.inner_iteration_ordering.reset( - CoordinateDescentMinimizer::CreateOrdering(*pp->reduced_program)); - } - - pp->inner_iteration_minimizer.reset(new CoordinateDescentMinimizer); - return pp->inner_iteration_minimizer->Init(*pp->reduced_program, - pp->problem->parameter_map(), - *options.inner_iteration_ordering, - &pp->error); -} - -// Configure and create a TrustRegionMinimizer object. -void SetupMinimizerOptions(PreprocessedProblem* pp) { - const Solver::Options& options = pp->options; - - SetupCommonMinimizerOptions(pp); - pp->minimizer_options.is_constrained = - pp->reduced_program->IsBoundsConstrained(); - pp->minimizer_options.jacobian.reset(pp->evaluator->CreateJacobian()); - pp->minimizer_options.inner_iteration_minimizer = - pp->inner_iteration_minimizer; - - TrustRegionStrategy::Options strategy_options; - strategy_options.linear_solver = pp->linear_solver.get(); - strategy_options.initial_radius = - options.initial_trust_region_radius; - strategy_options.max_radius = options.max_trust_region_radius; - strategy_options.min_lm_diagonal = options.min_lm_diagonal; - strategy_options.max_lm_diagonal = options.max_lm_diagonal; - strategy_options.trust_region_strategy_type = - options.trust_region_strategy_type; - strategy_options.dogleg_type = options.dogleg_type; - pp->minimizer_options.trust_region_strategy.reset( - CHECK_NOTNULL(TrustRegionStrategy::Create(strategy_options))); -} - -} // namespace - -TrustRegionPreprocessor::~TrustRegionPreprocessor() { -} - -bool TrustRegionPreprocessor::Preprocess(const Solver::Options& options, - ProblemImpl* problem, - PreprocessedProblem* pp) { - CHECK_NOTNULL(pp); - pp->options = options; - ChangeNumThreadsIfNeeded(&pp->options); - - pp->problem = problem; - Program* program = problem->mutable_program(); - if (!IsProgramValid(*program, &pp->error)) { - return false; - } - - pp->reduced_program.reset( - program->CreateReducedProgram(&pp->removed_parameter_blocks, - &pp->fixed_cost, - &pp->error)); - - if (pp->reduced_program.get() == NULL) { - return false; - } - - if (pp->reduced_program->NumParameterBlocks() == 0) { - // The reduced problem has no parameter or residual blocks. There - // is nothing more to do. - return true; - } - - if (!SetupLinearSolver(pp) || - !SetupEvaluator(pp) || - !SetupInnerIterationMinimizer(pp)) { - return false; - } - - SetupMinimizerOptions(pp); - return true; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/trust_region_preprocessor.h b/extern/libmv/third_party/ceres/internal/ceres/trust_region_preprocessor.h deleted file mode 100644 index a6631ab3d40..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/trust_region_preprocessor.h +++ /dev/null @@ -1,50 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_TRUST_REGION_PREPROCESSOR_H_ -#define CERES_INTERNAL_TRUST_REGION_PREPROCESSOR_H_ - -#include "ceres/preprocessor.h" - -namespace ceres { -namespace internal { - -class TrustRegionPreprocessor : public Preprocessor { - public: - virtual ~TrustRegionPreprocessor(); - virtual bool Preprocess(const Solver::Options& options, - ProblemImpl* problem, - PreprocessedProblem* preprocessed_problem); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_TRUST_REGION_PREPROCESSOR_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/trust_region_strategy.cc b/extern/libmv/third_party/ceres/internal/ceres/trust_region_strategy.cc deleted file mode 100644 index 2db6a6c899b..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/trust_region_strategy.cc +++ /dev/null @@ -1,59 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// keir@google.com (Keir Mierle) - -#include "ceres/trust_region_strategy.h" -#include "ceres/dogleg_strategy.h" -#include "ceres/levenberg_marquardt_strategy.h" - -namespace ceres { -namespace internal { - -TrustRegionStrategy::~TrustRegionStrategy() {} - -TrustRegionStrategy* TrustRegionStrategy::Create(const Options& options) { - switch (options.trust_region_strategy_type) { - case LEVENBERG_MARQUARDT: - return new LevenbergMarquardtStrategy(options); - case DOGLEG: - return new DoglegStrategy(options); - default: - LOG(FATAL) << "Unknown trust region strategy: " - << options.trust_region_strategy_type; - } - - LOG(FATAL) << "Unknown trust region strategy: " - << options.trust_region_strategy_type; - return NULL; -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/trust_region_strategy.h b/extern/libmv/third_party/ceres/internal/ceres/trust_region_strategy.h deleted file mode 100644 index 9560e67459a..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/trust_region_strategy.h +++ /dev/null @@ -1,164 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_INTERNAL_TRUST_REGION_STRATEGY_H_ -#define CERES_INTERNAL_TRUST_REGION_STRATEGY_H_ - -#include <string> -#include "ceres/internal/port.h" -#include "ceres/linear_solver.h" - -namespace ceres { -namespace internal { - -class LinearSolver; -class SparseMatrix; - -// Interface for classes implementing various trust region strategies -// for nonlinear least squares problems. -// -// The object is expected to maintain and update a trust region -// radius, which it then uses to solve for the trust region step using -// the jacobian matrix and residual vector. -// -// Here the term trust region radius is used loosely, as the strategy -// is free to treat it as guidance and violate it as need be. e.g., -// the LevenbergMarquardtStrategy uses the inverse of the trust region -// radius to scale the damping term, which controls the step size, but -// does not set a hard limit on its size. -class TrustRegionStrategy { - public: - struct Options { - Options() - : trust_region_strategy_type(LEVENBERG_MARQUARDT), - initial_radius(1e4), - max_radius(1e32), - min_lm_diagonal(1e-6), - max_lm_diagonal(1e32), - dogleg_type(TRADITIONAL_DOGLEG) { - } - - TrustRegionStrategyType trust_region_strategy_type; - // Linear solver used for actually solving the trust region step. - LinearSolver* linear_solver; - double initial_radius; - double max_radius; - - // Minimum and maximum values of the diagonal damping matrix used - // by LevenbergMarquardtStrategy. The DoglegStrategy also uses - // these bounds to construct a regularizing diagonal to ensure - // that the Gauss-Newton step computation is of full rank. - double min_lm_diagonal; - double max_lm_diagonal; - - // Further specify which dogleg method to use - DoglegType dogleg_type; - }; - - // Per solve options. - struct PerSolveOptions { - PerSolveOptions() - : eta(0), - dump_filename_base(""), - dump_format_type(TEXTFILE) { - } - - // Forcing sequence for inexact solves. - double eta; - - // If non-empty and dump_format_type is not CONSOLE, the trust - // regions strategy will write the linear system to file(s) with - // name starting with dump_filename_base. If dump_format_type is - // CONSOLE then dump_filename_base will be ignored and the linear - // system will be written to the standard error. - std::string dump_filename_base; - DumpFormatType dump_format_type; - }; - - struct Summary { - Summary() - : residual_norm(0.0), - num_iterations(-1), - termination_type(LINEAR_SOLVER_FAILURE) { - } - - // If the trust region problem is, - // - // 1/2 x'Ax + b'x + c, - // - // then - // - // residual_norm = |Ax -b| - double residual_norm; - - // Number of iterations used by the linear solver. If a linear - // solver was not called (e.g., DogLegStrategy after an - // unsuccessful step), then this would be zero. - int num_iterations; - - // Status of the linear solver used to solve the Newton system. - LinearSolverTerminationType termination_type; - }; - - virtual ~TrustRegionStrategy(); - - // Use the current radius to solve for the trust region step. - virtual Summary ComputeStep(const PerSolveOptions& per_solve_options, - SparseMatrix* jacobian, - const double* residuals, - double* step) = 0; - - // Inform the strategy that the current step has been accepted, and - // that the ratio of the decrease in the non-linear objective to the - // decrease in the trust region model is step_quality. - virtual void StepAccepted(double step_quality) = 0; - - // Inform the strategy that the current step has been rejected, and - // that the ratio of the decrease in the non-linear objective to the - // decrease in the trust region model is step_quality. - virtual void StepRejected(double step_quality) = 0; - - // Inform the strategy that the current step has been rejected - // because it was found to be numerically invalid. - // StepRejected/StepAccepted will not be called for this step, and - // the strategy is free to do what it wants with this information. - virtual void StepIsInvalid() = 0; - - // Current trust region radius. - virtual double Radius() const = 0; - - // Factory. - static TrustRegionStrategy* Create(const Options& options); -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_TRUST_REGION_STRATEGY_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/types.cc b/extern/libmv/third_party/ceres/internal/ceres/types.cc deleted file mode 100644 index f86fb78eb8c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/types.cc +++ /dev/null @@ -1,395 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include <algorithm> -#include <cctype> -#include <string> -#include "ceres/types.h" -#include "glog/logging.h" - -namespace ceres { - -using std::string; - -#define CASESTR(x) case x: return #x -#define STRENUM(x) if (value == #x) { *type = x; return true;} - -static void UpperCase(string* input) { - std::transform(input->begin(), input->end(), input->begin(), ::toupper); -} - -const char* LinearSolverTypeToString(LinearSolverType type) { - switch (type) { - CASESTR(DENSE_NORMAL_CHOLESKY); - CASESTR(DENSE_QR); - CASESTR(SPARSE_NORMAL_CHOLESKY); - CASESTR(DENSE_SCHUR); - CASESTR(SPARSE_SCHUR); - CASESTR(ITERATIVE_SCHUR); - CASESTR(CGNR); - default: - return "UNKNOWN"; - } -} - -bool StringToLinearSolverType(string value, LinearSolverType* type) { - UpperCase(&value); - STRENUM(DENSE_NORMAL_CHOLESKY); - STRENUM(DENSE_QR); - STRENUM(SPARSE_NORMAL_CHOLESKY); - STRENUM(DENSE_SCHUR); - STRENUM(SPARSE_SCHUR); - STRENUM(ITERATIVE_SCHUR); - STRENUM(CGNR); - return false; -} - -const char* PreconditionerTypeToString(PreconditionerType type) { - switch (type) { - CASESTR(IDENTITY); - CASESTR(JACOBI); - CASESTR(SCHUR_JACOBI); - CASESTR(CLUSTER_JACOBI); - CASESTR(CLUSTER_TRIDIAGONAL); - default: - return "UNKNOWN"; - } -} - -bool StringToPreconditionerType(string value, PreconditionerType* type) { - UpperCase(&value); - STRENUM(IDENTITY); - STRENUM(JACOBI); - STRENUM(SCHUR_JACOBI); - STRENUM(CLUSTER_JACOBI); - STRENUM(CLUSTER_TRIDIAGONAL); - return false; -} - -const char* SparseLinearAlgebraLibraryTypeToString( - SparseLinearAlgebraLibraryType type) { - switch (type) { - CASESTR(SUITE_SPARSE); - CASESTR(CX_SPARSE); - CASESTR(EIGEN_SPARSE); - CASESTR(NO_SPARSE); - default: - return "UNKNOWN"; - } -} - -bool StringToSparseLinearAlgebraLibraryType( - string value, - SparseLinearAlgebraLibraryType* type) { - UpperCase(&value); - STRENUM(SUITE_SPARSE); - STRENUM(CX_SPARSE); - STRENUM(EIGEN_SPARSE); - STRENUM(NO_SPARSE); - return false; -} - -const char* DenseLinearAlgebraLibraryTypeToString( - DenseLinearAlgebraLibraryType type) { - switch (type) { - CASESTR(EIGEN); - CASESTR(LAPACK); - default: - return "UNKNOWN"; - } -} - -bool StringToDenseLinearAlgebraLibraryType( - string value, - DenseLinearAlgebraLibraryType* type) { - UpperCase(&value); - STRENUM(EIGEN); - STRENUM(LAPACK); - return false; -} - -const char* TrustRegionStrategyTypeToString(TrustRegionStrategyType type) { - switch (type) { - CASESTR(LEVENBERG_MARQUARDT); - CASESTR(DOGLEG); - default: - return "UNKNOWN"; - } -} - -bool StringToTrustRegionStrategyType(string value, - TrustRegionStrategyType* type) { - UpperCase(&value); - STRENUM(LEVENBERG_MARQUARDT); - STRENUM(DOGLEG); - return false; -} - -const char* DoglegTypeToString(DoglegType type) { - switch (type) { - CASESTR(TRADITIONAL_DOGLEG); - CASESTR(SUBSPACE_DOGLEG); - default: - return "UNKNOWN"; - } -} - -bool StringToDoglegType(string value, DoglegType* type) { - UpperCase(&value); - STRENUM(TRADITIONAL_DOGLEG); - STRENUM(SUBSPACE_DOGLEG); - return false; -} - -const char* MinimizerTypeToString(MinimizerType type) { - switch (type) { - CASESTR(TRUST_REGION); - CASESTR(LINE_SEARCH); - default: - return "UNKNOWN"; - } -} - -bool StringToMinimizerType(string value, MinimizerType* type) { - UpperCase(&value); - STRENUM(TRUST_REGION); - STRENUM(LINE_SEARCH); - return false; -} - -const char* LineSearchDirectionTypeToString(LineSearchDirectionType type) { - switch (type) { - CASESTR(STEEPEST_DESCENT); - CASESTR(NONLINEAR_CONJUGATE_GRADIENT); - CASESTR(LBFGS); - CASESTR(BFGS); - default: - return "UNKNOWN"; - } -} - -bool StringToLineSearchDirectionType(string value, - LineSearchDirectionType* type) { - UpperCase(&value); - STRENUM(STEEPEST_DESCENT); - STRENUM(NONLINEAR_CONJUGATE_GRADIENT); - STRENUM(LBFGS); - STRENUM(BFGS); - return false; -} - -const char* LineSearchTypeToString(LineSearchType type) { - switch (type) { - CASESTR(ARMIJO); - CASESTR(WOLFE); - default: - return "UNKNOWN"; - } -} - -bool StringToLineSearchType(string value, LineSearchType* type) { - UpperCase(&value); - STRENUM(ARMIJO); - STRENUM(WOLFE); - return false; -} - -const char* LineSearchInterpolationTypeToString( - LineSearchInterpolationType type) { - switch (type) { - CASESTR(BISECTION); - CASESTR(QUADRATIC); - CASESTR(CUBIC); - default: - return "UNKNOWN"; - } -} - -bool StringToLineSearchInterpolationType( - string value, - LineSearchInterpolationType* type) { - UpperCase(&value); - STRENUM(BISECTION); - STRENUM(QUADRATIC); - STRENUM(CUBIC); - return false; -} - -const char* NonlinearConjugateGradientTypeToString( - NonlinearConjugateGradientType type) { - switch (type) { - CASESTR(FLETCHER_REEVES); - CASESTR(POLAK_RIBIERE); - CASESTR(HESTENES_STIEFEL); - default: - return "UNKNOWN"; - } -} - -bool StringToNonlinearConjugateGradientType( - string value, - NonlinearConjugateGradientType* type) { - UpperCase(&value); - STRENUM(FLETCHER_REEVES); - STRENUM(POLAK_RIBIERE); - STRENUM(HESTENES_STIEFEL); - return false; -} - -const char* CovarianceAlgorithmTypeToString( - CovarianceAlgorithmType type) { - switch (type) { - CASESTR(DENSE_SVD); - CASESTR(EIGEN_SPARSE_QR); - CASESTR(SUITE_SPARSE_QR); - default: - return "UNKNOWN"; - } -} - -bool StringToCovarianceAlgorithmType( - string value, - CovarianceAlgorithmType* type) { - UpperCase(&value); - STRENUM(DENSE_SVD); - STRENUM(EIGEN_SPARSE_QR); - STRENUM(SUITE_SPARSE_QR); - return false; -} - -const char* NumericDiffMethodTypeToString( - NumericDiffMethodType type) { - switch (type) { - CASESTR(CENTRAL); - CASESTR(FORWARD); - CASESTR(RIDDERS); - default: - return "UNKNOWN"; - } -} - -bool StringToNumericDiffMethodType( - string value, - NumericDiffMethodType* type) { - UpperCase(&value); - STRENUM(CENTRAL); - STRENUM(FORWARD); - STRENUM(RIDDERS); - return false; -} - -const char* VisibilityClusteringTypeToString( - VisibilityClusteringType type) { - switch (type) { - CASESTR(CANONICAL_VIEWS); - CASESTR(SINGLE_LINKAGE); - default: - return "UNKNOWN"; - } -} - -bool StringToVisibilityClusteringType( - string value, - VisibilityClusteringType* type) { - UpperCase(&value); - STRENUM(CANONICAL_VIEWS); - STRENUM(SINGLE_LINKAGE); - return false; -} - -const char* TerminationTypeToString(TerminationType type) { - switch (type) { - CASESTR(CONVERGENCE); - CASESTR(NO_CONVERGENCE); - CASESTR(FAILURE); - CASESTR(USER_SUCCESS); - CASESTR(USER_FAILURE); - default: - return "UNKNOWN"; - } -} - -#undef CASESTR -#undef STRENUM - -bool IsSchurType(LinearSolverType type) { - return ((type == SPARSE_SCHUR) || - (type == DENSE_SCHUR) || - (type == ITERATIVE_SCHUR)); -} - -bool IsSparseLinearAlgebraLibraryTypeAvailable( - SparseLinearAlgebraLibraryType type) { - if (type == SUITE_SPARSE) { -#ifdef CERES_NO_SUITESPARSE - return false; -#else - return true; -#endif - } - - if (type == CX_SPARSE) { -#ifdef CERES_NO_CXSPARSE - return false; -#else - return true; -#endif - } - - if (type == EIGEN_SPARSE) { -#ifdef CERES_USE_EIGEN_SPARSE - return true; -#else - return false; -#endif - } - - LOG(WARNING) << "Unknown sparse linear algebra library " << type; - return false; -} - -bool IsDenseLinearAlgebraLibraryTypeAvailable( - DenseLinearAlgebraLibraryType type) { - if (type == EIGEN) { - return true; - } - if (type == LAPACK) { -#ifdef CERES_NO_LAPACK - return false; -#else - return true; -#endif - } - - LOG(WARNING) << "Unknown dense linear algebra library " << type; - return false; -} - -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/visibility_based_preconditioner.h b/extern/libmv/third_party/ceres/internal/ceres/visibility_based_preconditioner.h deleted file mode 100644 index a627c13523c..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/visibility_based_preconditioner.h +++ /dev/null @@ -1,233 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// Preconditioners for linear systems that arise in Structure from -// Motion problems. VisibilityBasedPreconditioner implements: -// -// CLUSTER_JACOBI -// CLUSTER_TRIDIAGONAL -// -// Detailed descriptions of these preconditions beyond what is -// documented here can be found in -// -// Visibility Based Preconditioning for Bundle Adjustment -// A. Kushal & S. Agarwal, CVPR 2012. -// -// http://www.cs.washington.edu/homes/sagarwal/vbp.pdf -// -// The two preconditioners share enough code that its most efficient -// to implement them as part of the same code base. - -#ifndef CERES_INTERNAL_VISIBILITY_BASED_PRECONDITIONER_H_ -#define CERES_INTERNAL_VISIBILITY_BASED_PRECONDITIONER_H_ - -#include <set> -#include <vector> -#include <utility> -#include "ceres/collections_port.h" -#include "ceres/graph.h" -#include "ceres/internal/macros.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/linear_solver.h" -#include "ceres/preconditioner.h" -#include "ceres/suitesparse.h" - -namespace ceres { -namespace internal { - -class BlockRandomAccessSparseMatrix; -class BlockSparseMatrix; -struct CompressedRowBlockStructure; -class SchurEliminatorBase; - -// This class implements visibility based preconditioners for -// Structure from Motion/Bundle Adjustment problems. The name -// VisibilityBasedPreconditioner comes from the fact that the sparsity -// structure of the preconditioner matrix is determined by analyzing -// the visibility structure of the scene, i.e. which cameras see which -// points. -// -// The key idea of visibility based preconditioning is to identify -// cameras that we expect have strong interactions, and then using the -// entries in the Schur complement matrix corresponding to these -// camera pairs as an approximation to the full Schur complement. -// -// CLUSTER_JACOBI identifies these camera pairs by clustering cameras, -// and considering all non-zero camera pairs within each cluster. The -// clustering in the current implementation is done using the -// Canonical Views algorithm of Simon et al. (see -// canonical_views_clustering.h). For the purposes of clustering, the -// similarity or the degree of interaction between a pair of cameras -// is measured by counting the number of points visible in both the -// cameras. Thus the name VisibilityBasedPreconditioner. Further, if we -// were to permute the parameter blocks such that all the cameras in -// the same cluster occur contiguously, the preconditioner matrix will -// be a block diagonal matrix with blocks corresponding to the -// clusters. Thus in analogy with the Jacobi preconditioner we refer -// to this as the CLUSTER_JACOBI preconditioner. -// -// CLUSTER_TRIDIAGONAL adds more mass to the CLUSTER_JACOBI -// preconditioner by considering the interaction between clusters and -// identifying strong interactions between cluster pairs. This is done -// by constructing a weighted graph on the clusters, with the weight -// on the edges connecting two clusters proportional to the number of -// 3D points visible to cameras in both the clusters. A degree-2 -// maximum spanning forest is identified in this graph and the camera -// pairs contained in the edges of this forest are added to the -// preconditioner. The detailed reasoning for this construction is -// explained in the paper mentioned above. -// -// Degree-2 spanning trees and forests have the property that they -// correspond to tri-diagonal matrices. Thus there exist a permutation -// of the camera blocks under which the CLUSTER_TRIDIAGONAL -// preconditioner matrix is a block tridiagonal matrix, and thus the -// name for the preconditioner. -// -// Thread Safety: This class is NOT thread safe. -// -// Example usage: -// -// LinearSolver::Options options; -// options.preconditioner_type = CLUSTER_JACOBI; -// options.elimination_groups.push_back(num_points); -// options.elimination_groups.push_back(num_cameras); -// VisibilityBasedPreconditioner preconditioner( -// *A.block_structure(), options); -// preconditioner.Update(A, NULL); -// preconditioner.RightMultiply(x, y); -// -#ifndef CERES_NO_SUITESPARSE -class VisibilityBasedPreconditioner : public BlockSparseMatrixPreconditioner { - public: - // Initialize the symbolic structure of the preconditioner. bs is - // the block structure of the linear system to be solved. It is used - // to determine the sparsity structure of the preconditioner matrix. - // - // It has the same structural requirement as other Schur complement - // based solvers. Please see schur_eliminator.h for more details. - VisibilityBasedPreconditioner(const CompressedRowBlockStructure& bs, - const Preconditioner::Options& options); - virtual ~VisibilityBasedPreconditioner(); - - // Preconditioner interface - virtual void RightMultiply(const double* x, double* y) const; - virtual int num_rows() const; - - friend class VisibilityBasedPreconditionerTest; - - private: - virtual bool UpdateImpl(const BlockSparseMatrix& A, const double* D); - void ComputeClusterJacobiSparsity(const CompressedRowBlockStructure& bs); - void ComputeClusterTridiagonalSparsity(const CompressedRowBlockStructure& bs); - void InitStorage(const CompressedRowBlockStructure& bs); - void InitEliminator(const CompressedRowBlockStructure& bs); - LinearSolverTerminationType Factorize(); - void ScaleOffDiagonalCells(); - - void ClusterCameras(const std::vector<std::set<int> >& visibility); - void FlattenMembershipMap(const HashMap<int, int>& membership_map, - std::vector<int>* membership_vector) const; - void ComputeClusterVisibility( - const std::vector<std::set<int> >& visibility, - std::vector<std::set<int> >* cluster_visibility) const; - WeightedGraph<int>* CreateClusterGraph( - const std::vector<std::set<int> >& visibility) const; - void ForestToClusterPairs(const WeightedGraph<int>& forest, - HashSet<std::pair<int, int> >* cluster_pairs) const; - void ComputeBlockPairsInPreconditioner(const CompressedRowBlockStructure& bs); - bool IsBlockPairInPreconditioner(int block1, int block2) const; - bool IsBlockPairOffDiagonal(int block1, int block2) const; - - Preconditioner::Options options_; - - // Number of parameter blocks in the schur complement. - int num_blocks_; - int num_clusters_; - - // Sizes of the blocks in the schur complement. - std::vector<int> block_size_; - - // Mapping from cameras to clusters. - std::vector<int> cluster_membership_; - - // Non-zero camera pairs from the schur complement matrix that are - // present in the preconditioner, sorted by row (first element of - // each pair), then column (second). - std::set<std::pair<int, int> > block_pairs_; - - // Set of cluster pairs (including self pairs (i,i)) in the - // preconditioner. - HashSet<std::pair<int, int> > cluster_pairs_; - scoped_ptr<SchurEliminatorBase> eliminator_; - - // Preconditioner matrix. - scoped_ptr<BlockRandomAccessSparseMatrix> m_; - - // RightMultiply is a const method for LinearOperators. It is - // implemented using CHOLMOD's sparse triangular matrix solve - // function. This however requires non-const access to the - // SuiteSparse context object, even though it does not result in any - // of the state of the preconditioner being modified. - SuiteSparse ss_; - - // Symbolic and numeric factorization of the preconditioner. - cholmod_factor* factor_; - - // Temporary vector used by RightMultiply. - cholmod_dense* tmp_rhs_; - CERES_DISALLOW_COPY_AND_ASSIGN(VisibilityBasedPreconditioner); -}; -#else // SuiteSparse -// If SuiteSparse is not compiled in, the preconditioner is not -// available. -class VisibilityBasedPreconditioner : public BlockSparseMatrixPreconditioner { - public: - VisibilityBasedPreconditioner(const CompressedRowBlockStructure& bs, - const Preconditioner::Options& options) { - LOG(FATAL) << "Visibility based preconditioning is not available. Please " - "build Ceres with SuiteSparse."; - } - virtual ~VisibilityBasedPreconditioner() {} - virtual void RightMultiply(const double* x, double* y) const {} - virtual void LeftMultiply(const double* x, double* y) const {} - virtual int num_rows() const { return -1; } - virtual int num_cols() const { return -1; } - - private: - bool UpdateImpl(const BlockSparseMatrix& A, const double* D) { - return false; - } -}; -#endif // CERES_NO_SUITESPARSE - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_VISIBILITY_BASED_PRECONDITIONER_H_ diff --git a/extern/libmv/third_party/ceres/internal/ceres/wall_time.cc b/extern/libmv/third_party/ceres/internal/ceres/wall_time.cc deleted file mode 100644 index c353973cc3e..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/wall_time.cc +++ /dev/null @@ -1,96 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: strandmark@google.com (Petter Strandmark) - -#include "ceres/wall_time.h" - -#ifdef CERES_USE_OPENMP -#include <omp.h> -#else -#include <ctime> -#endif - -#ifdef _WIN32 -#include <windows.h> -#else -#include <sys/time.h> -#endif - -namespace ceres { -namespace internal { - -double WallTimeInSeconds() { -#ifdef CERES_USE_OPENMP - return omp_get_wtime(); -#else -#ifdef _WIN32 - return static_cast<double>(std::time(NULL)); -#else - timeval time_val; - gettimeofday(&time_val, NULL); - return (time_val.tv_sec + time_val.tv_usec * 1e-6); -#endif -#endif -} - -EventLogger::EventLogger(const std::string& logger_name) - : start_time_(WallTimeInSeconds()), - last_event_time_(start_time_), - events_("") { - StringAppendF(&events_, - "\n%s\n Delta Cumulative\n", - logger_name.c_str()); -} - -EventLogger::~EventLogger() { - if (VLOG_IS_ON(3)) { - AddEvent("Total"); - VLOG(2) << "\n" << events_ << "\n"; - } -} - -void EventLogger::AddEvent(const std::string& event_name) { - if (!VLOG_IS_ON(3)) { - return; - } - - const double current_time = WallTimeInSeconds(); - const double relative_time_delta = current_time - last_event_time_; - const double absolute_time_delta = current_time - start_time_; - last_event_time_ = current_time; - - StringAppendF(&events_, - " %30s : %10.5f %10.5f\n", - event_name.c_str(), - relative_time_delta, - absolute_time_delta); -} - -} // namespace internal -} // namespace ceres diff --git a/extern/libmv/third_party/ceres/internal/ceres/wall_time.h b/extern/libmv/third_party/ceres/internal/ceres/wall_time.h deleted file mode 100644 index 966aa67cab6..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/wall_time.h +++ /dev/null @@ -1,88 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2015 Google Inc. All rights reserved. -// http://ceres-solver.org/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: strandmark@google.com (Petter Strandmark) - -#ifndef CERES_INTERNAL_WALL_TIME_H_ -#define CERES_INTERNAL_WALL_TIME_H_ - -#include <map> -#include <string> -#include "ceres/internal/port.h" -#include "ceres/stringprintf.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -// Returns time, in seconds, from some arbitrary starting point. If -// OpenMP is available then the high precision openmp_get_wtime() -// function is used. Otherwise on unixes, gettimeofday is used. The -// granularity is in seconds on windows systems. -double WallTimeInSeconds(); - -// Log a series of events, recording for each event the time elapsed -// since the last event and since the creation of the object. -// -// The information is output to VLOG(3) upon destruction. A -// name::Total event is added as the final event right before -// destruction. -// -// Example usage: -// -// void Foo() { -// EventLogger event_logger("Foo"); -// Bar1(); -// event_logger.AddEvent("Bar1") -// Bar2(); -// event_logger.AddEvent("Bar2") -// Bar3(); -// } -// -// Will produce output that looks like -// -// Foo -// Bar1: time1 time1 -// Bar2: time2 time1 + time2; -// Total: time3 time1 + time2 + time3; -class EventLogger { - public: - explicit EventLogger(const std::string& logger_name); - ~EventLogger(); - void AddEvent(const std::string& event_name); - - private: - const double start_time_; - double last_event_time_; - std::string events_; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_INTERNAL_WALL_TIME_H_ diff --git a/extern/libmv/third_party/ceres/mkfiles.sh b/extern/libmv/third_party/ceres/mkfiles.sh deleted file mode 100755 index cb07663e94a..00000000000 --- a/extern/libmv/third_party/ceres/mkfiles.sh +++ /dev/null @@ -1,5 +0,0 @@ -#!/bin/sh - -find ./include/ -type f | sed -r 's/^\.\///' | sort > files.txt -find ./internal/ -type f | sed -r 's/^\.\///' | sort >> files.txt -find ./config/ -type f | sed -r 's/^\.\///' | sort >> files.txt diff --git a/extern/libmv/third_party/ceres/patches/series b/extern/libmv/third_party/ceres/patches/series deleted file mode 100644 index e69de29bb2d..00000000000 --- a/extern/libmv/third_party/ceres/patches/series +++ /dev/null |