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Diffstat (limited to 'extern/libmv/third_party/ceres/internal/ceres/cxsparse.cc')
| -rw-r--r-- | extern/libmv/third_party/ceres/internal/ceres/cxsparse.cc | 217 |
1 files changed, 0 insertions, 217 deletions
diff --git a/extern/libmv/third_party/ceres/internal/ceres/cxsparse.cc b/extern/libmv/third_party/ceres/internal/ceres/cxsparse.cc deleted file mode 100644 index 87503d06c99..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/cxsparse.cc +++ /dev/null @@ -1,217 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 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. -// -// Author: strandmark@google.com (Petter Strandmark) - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_NO_CXSPARSE - -#include "ceres/cxsparse.h" - -#include <vector> -#include "ceres/compressed_col_sparse_matrix_utils.h" -#include "ceres/compressed_row_sparse_matrix.h" -#include "ceres/internal/port.h" -#include "ceres/triplet_sparse_matrix.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -CXSparse::CXSparse() : scratch_(NULL), scratch_size_(0) { -} - -CXSparse::~CXSparse() { - if (scratch_size_ > 0) { - cs_di_free(scratch_); - } -} - - -bool CXSparse::SolveCholesky(cs_di* A, - cs_dis* symbolic_factorization, - double* b) { - // Make sure we have enough scratch space available. - if (scratch_size_ < A->n) { - if (scratch_size_ > 0) { - cs_di_free(scratch_); - } - scratch_ = - reinterpret_cast<CS_ENTRY*>(cs_di_malloc(A->n, sizeof(CS_ENTRY))); - scratch_size_ = A->n; - } - - // Solve using Cholesky factorization - csn* numeric_factorization = cs_di_chol(A, symbolic_factorization); - if (numeric_factorization == NULL) { - LOG(WARNING) << "Cholesky factorization failed."; - return false; - } - - // When the Cholesky factorization succeeded, these methods are - // guaranteed to succeeded as well. In the comments below, "x" - // refers to the scratch space. - // - // Set x = P * b. - cs_di_ipvec(symbolic_factorization->pinv, b, scratch_, A->n); - // Set x = L \ x. - cs_di_lsolve(numeric_factorization->L, scratch_); - // Set x = L' \ x. - cs_di_ltsolve(numeric_factorization->L, scratch_); - // Set b = P' * x. - cs_di_pvec(symbolic_factorization->pinv, scratch_, b, A->n); - - // Free Cholesky factorization. - cs_di_nfree(numeric_factorization); - return true; -} - -cs_dis* CXSparse::AnalyzeCholesky(cs_di* A) { - // order = 1 for Cholesky factorization. - return cs_schol(1, A); -} - -cs_dis* CXSparse::AnalyzeCholeskyWithNaturalOrdering(cs_di* A) { - // order = 0 for Natural ordering. - return cs_schol(0, A); -} - -cs_dis* CXSparse::BlockAnalyzeCholesky(cs_di* A, - const vector<int>& row_blocks, - const vector<int>& col_blocks) { - const int num_row_blocks = row_blocks.size(); - const int num_col_blocks = col_blocks.size(); - - vector<int> block_rows; - vector<int> block_cols; - CompressedColumnScalarMatrixToBlockMatrix(A->i, - A->p, - row_blocks, - col_blocks, - &block_rows, - &block_cols); - cs_di block_matrix; - block_matrix.m = num_row_blocks; - block_matrix.n = num_col_blocks; - block_matrix.nz = -1; - block_matrix.nzmax = block_rows.size(); - block_matrix.p = &block_cols[0]; - block_matrix.i = &block_rows[0]; - block_matrix.x = NULL; - - int* ordering = cs_amd(1, &block_matrix); - vector<int> block_ordering(num_row_blocks, -1); - copy(ordering, ordering + num_row_blocks, &block_ordering[0]); - cs_free(ordering); - - vector<int> scalar_ordering; - BlockOrderingToScalarOrdering(row_blocks, block_ordering, &scalar_ordering); - - cs_dis* symbolic_factorization = - reinterpret_cast<cs_dis*>(cs_calloc(1, sizeof(cs_dis))); - symbolic_factorization->pinv = cs_pinv(&scalar_ordering[0], A->n); - cs* permuted_A = cs_symperm(A, symbolic_factorization->pinv, 0); - - symbolic_factorization->parent = cs_etree(permuted_A, 0); - int* postordering = cs_post(symbolic_factorization->parent, A->n); - int* column_counts = cs_counts(permuted_A, - symbolic_factorization->parent, - postordering, - 0); - cs_free(postordering); - cs_spfree(permuted_A); - - symbolic_factorization->cp = (int*) cs_malloc(A->n+1, sizeof(int)); - symbolic_factorization->lnz = cs_cumsum(symbolic_factorization->cp, - column_counts, - A->n); - symbolic_factorization->unz = symbolic_factorization->lnz; - - cs_free(column_counts); - - if (symbolic_factorization->lnz < 0) { - cs_sfree(symbolic_factorization); - symbolic_factorization = NULL; - } - - return symbolic_factorization; -} - -cs_di CXSparse::CreateSparseMatrixTransposeView(CompressedRowSparseMatrix* A) { - cs_di At; - At.m = A->num_cols(); - At.n = A->num_rows(); - At.nz = -1; - At.nzmax = A->num_nonzeros(); - At.p = A->mutable_rows(); - At.i = A->mutable_cols(); - At.x = A->mutable_values(); - return At; -} - -cs_di* CXSparse::CreateSparseMatrix(TripletSparseMatrix* tsm) { - cs_di_sparse tsm_wrapper; - tsm_wrapper.nzmax = tsm->num_nonzeros(); - tsm_wrapper.nz = tsm->num_nonzeros(); - tsm_wrapper.m = tsm->num_rows(); - tsm_wrapper.n = tsm->num_cols(); - tsm_wrapper.p = tsm->mutable_cols(); - tsm_wrapper.i = tsm->mutable_rows(); - tsm_wrapper.x = tsm->mutable_values(); - - return cs_compress(&tsm_wrapper); -} - -void CXSparse::ApproximateMinimumDegreeOrdering(cs_di* A, int* ordering) { - int* cs_ordering = cs_amd(1, A); - copy(cs_ordering, cs_ordering + A->m, ordering); - cs_free(cs_ordering); -} - -cs_di* CXSparse::TransposeMatrix(cs_di* A) { - return cs_di_transpose(A, 1); -} - -cs_di* CXSparse::MatrixMatrixMultiply(cs_di* A, cs_di* B) { - return cs_di_multiply(A, B); -} - -void CXSparse::Free(cs_di* sparse_matrix) { - cs_di_spfree(sparse_matrix); -} - -void CXSparse::Free(cs_dis* symbolic_factorization) { - cs_di_sfree(symbolic_factorization); -} - -} // namespace internal -} // namespace ceres - -#endif // CERES_NO_CXSPARSE |