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diff --git a/extern/libmv/third_party/ssba/Math/v3d_optimization.h b/extern/libmv/third_party/ssba/Math/v3d_optimization.h
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-// -*- C++ -*-
-/*
-Copyright (c) 2008 University of North Carolina at Chapel Hill
-
-This file is part of SSBA (Simple Sparse Bundle Adjustment).
-
-SSBA is free software: you can redistribute it and/or modify it under the
-terms of the GNU Lesser General Public License as published by the Free
-Software Foundation, either version 3 of the License, or (at your option) any
-later version.
-
-SSBA 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 Lesser General Public License for more
-details.
-
-You should have received a copy of the GNU Lesser General Public License along
-with SSBA. If not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef V3D_OPTIMIZATION_H
-#define V3D_OPTIMIZATION_H
-
-#include "Math/v3d_linear.h"
-#include "Math/v3d_mathutilities.h"
-
-#include <vector>
-#include <iostream>
-
-namespace V3D
-{
-
- enum
- {
- LEVENBERG_OPTIMIZER_TIMEOUT = 0,
- LEVENBERG_OPTIMIZER_SMALL_UPDATE = 1,
- LEVENBERG_OPTIMIZER_CONVERGED = 2
- };
-
- extern int optimizerVerbosenessLevel;
-
- struct LevenbergOptimizerCommon
- {
- LevenbergOptimizerCommon()
- : status(LEVENBERG_OPTIMIZER_TIMEOUT), currentIteration(0), maxIterations(50),
- tau(1e-3), lambda(1e-3),
- gradientThreshold(1e-10), updateThreshold(1e-10),
- _nu(2.0)
- { }
- virtual ~LevenbergOptimizerCommon() {}
-
- // See Madsen et al., "Methods for non-linear least squares problems."
- virtual void increaseLambda()
- {
- lambda *= _nu; _nu *= 2.0;
- }
-
- virtual void decreaseLambda(double const rho)
- {
- double const r = 2*rho - 1.0;
- lambda *= std::max(1.0/3.0, 1 - r*r*r);
- if (lambda < 1e-10) lambda = 1e-10;
- _nu = 2;
- }
-
- bool applyGradientStoppingCriteria(double maxGradient) const
- {
- return maxGradient < gradientThreshold;
- }
-
- bool applyUpdateStoppingCriteria(double paramLength, double updateLength) const
- {
- return updateLength < updateThreshold * (paramLength + updateThreshold);
- }
-
- int status;
- int currentIteration, maxIterations;
- double tau, lambda;
- double gradientThreshold, updateThreshold;
-
- protected:
- double _nu;
- }; // end struct LevenbergOptimizerCommon
-
-# if defined(V3DLIB_ENABLE_SUITESPARSE)
-
- struct SparseLevenbergOptimizer : public LevenbergOptimizerCommon
- {
- SparseLevenbergOptimizer(int measurementDimension,
- int nParametersA, int paramDimensionA,
- int nParametersB, int paramDimensionB,
- int paramDimensionC,
- std::vector<int> const& correspondingParamA,
- std::vector<int> const& correspondingParamB)
- : LevenbergOptimizerCommon(),
- _nMeasurements(correspondingParamA.size()),
- _measurementDimension(measurementDimension),
- _nParametersA(nParametersA), _paramDimensionA(paramDimensionA),
- _nParametersB(nParametersB), _paramDimensionB(paramDimensionB),
- _paramDimensionC(paramDimensionC),
- _nNonvaryingA(0), _nNonvaryingB(0), _nNonvaryingC(0),
- _correspondingParamA(correspondingParamA),
- _correspondingParamB(correspondingParamB)
- {
- assert(correspondingParamA.size() == correspondingParamB.size());
- }
-
- ~SparseLevenbergOptimizer() { }
-
- void setNonvaryingCounts(int nNonvaryingA, int nNonvaryingB, int nNonvaryingC)
- {
- _nNonvaryingA = nNonvaryingA;
- _nNonvaryingB = nNonvaryingB;
- _nNonvaryingC = nNonvaryingC;
- }
-
- void getNonvaryingCounts(int& nNonvaryingA, int& nNonvaryingB, int& nNonvaryingC) const
- {
- nNonvaryingA = _nNonvaryingA;
- nNonvaryingB = _nNonvaryingB;
- nNonvaryingC = _nNonvaryingC;
- }
-
- void minimize();
-
- virtual void evalResidual(VectorArray<double>& residuals) = 0;
-
- virtual void fillWeights(VectorArray<double> const& residuals, Vector<double>& w)
- {
- (void)residuals;
- std::fill(w.begin(), w.end(), 1.0);
- }
-
- void fillAllJacobians(Vector<double> const& w,
- MatrixArray<double>& Ak,
- MatrixArray<double>& Bk,
- MatrixArray<double>& Ck)
- {
- int const nVaryingA = _nParametersA - _nNonvaryingA;
- int const nVaryingB = _nParametersB - _nNonvaryingB;
- int const nVaryingC = _paramDimensionC - _nNonvaryingC;
-
- for (unsigned k = 0; k < _nMeasurements; ++k)
- {
- int const i = _correspondingParamA[k];
- int const j = _correspondingParamB[k];
-
- if (i < _nNonvaryingA && j < _nNonvaryingB) continue;
-
- fillJacobians(Ak[k], Bk[k], Ck[k], i, j, k);
- } // end for (k)
-
- if (nVaryingA > 0)
- {
- for (unsigned k = 0; k < _nMeasurements; ++k)
- scaleMatrixIP(w[k], Ak[k]);
- }
- if (nVaryingB > 0)
- {
- for (unsigned k = 0; k < _nMeasurements; ++k)
- scaleMatrixIP(w[k], Bk[k]);
- }
- if (nVaryingC > 0)
- {
- for (unsigned k = 0; k < _nMeasurements; ++k)
- scaleMatrixIP(w[k], Ck[k]);
- }
- } // end fillAllJacobians()
-
- virtual void setupJacobianGathering() { }
-
- virtual void fillJacobians(Matrix<double>& Ak, Matrix<double>& Bk, Matrix<double>& Ck,
- int i, int j, int k) = 0;
-
- virtual double getParameterLength() const = 0;
-
- virtual void updateParametersA(VectorArray<double> const& deltaAi) = 0;
- virtual void updateParametersB(VectorArray<double> const& deltaBj) = 0;
- virtual void updateParametersC(Vector<double> const& deltaC) = 0;
- virtual void saveAllParameters() = 0;
- virtual void restoreAllParameters() = 0;
-
- int currentIteration, maxIterations;
-
- protected:
- void serializeNonZerosJtJ(std::vector<std::pair<int, int> >& dst) const;
- void setupSparseJtJ();
- void fillSparseJtJ(MatrixArray<double> const& Ui, MatrixArray<double> const& Vj, MatrixArray<double> const& Wk,
- Matrix<double> const& Z, Matrix<double> const& X, Matrix<double> const& Y);
-
- int const _nMeasurements, _measurementDimension;
- int const _nParametersA, _paramDimensionA;
- int const _nParametersB, _paramDimensionB;
- int const _paramDimensionC;
-
- int _nNonvaryingA, _nNonvaryingB, _nNonvaryingC;
-
- std::vector<int> const& _correspondingParamA;
- std::vector<int> const& _correspondingParamB;
-
- std::vector<pair<int, int> > _jointNonzerosW;
- std::vector<int> _jointIndexW;
-
- std::vector<int> _JtJ_Lp, _JtJ_Parent, _JtJ_Lnz;
- std::vector<int> _perm_JtJ, _invPerm_JtJ;
-
- CCS_Matrix<double> _JtJ;
- }; // end struct SparseLevenbergOptimizer
-
- struct StdSparseLevenbergOptimizer : public SparseLevenbergOptimizer
- {
- StdSparseLevenbergOptimizer(int measurementDimension,
- int nParametersA, int paramDimensionA,
- int nParametersB, int paramDimensionB,
- int paramDimensionC,
- std::vector<int> const& correspondingParamA,
- std::vector<int> const& correspondingParamB)
- : SparseLevenbergOptimizer(measurementDimension, nParametersA, paramDimensionA,
- nParametersB, paramDimensionB, paramDimensionC,
- correspondingParamA, correspondingParamB),
- curParametersA(nParametersA, paramDimensionA), savedParametersA(nParametersA, paramDimensionA),
- curParametersB(nParametersB, paramDimensionB), savedParametersB(nParametersB, paramDimensionB),
- curParametersC(paramDimensionC), savedParametersC(paramDimensionC)
- { }
-
- virtual double getParameterLength() const
- {
- double res = 0.0;
- for (int i = 0; i < _nParametersA; ++i) res += sqrNorm_L2(curParametersA[i]);
- for (int j = 0; j < _nParametersB; ++j) res += sqrNorm_L2(curParametersB[j]);
- res += sqrNorm_L2(curParametersC);
- return sqrt(res);
- }
-
- virtual void updateParametersA(VectorArray<double> const& deltaAi)
- {
- for (int i = 0; i < _nParametersA; ++i) addVectors(deltaAi[i], curParametersA[i], curParametersA[i]);
- }
-
- virtual void updateParametersB(VectorArray<double> const& deltaBj)
- {
- for (int j = 0; j < _nParametersB; ++j) addVectors(deltaBj[j], curParametersB[j], curParametersB[j]);
- }
-
- virtual void updateParametersC(Vector<double> const& deltaC)
- {
- addVectors(deltaC, curParametersC, curParametersC);
- }
-
- virtual void saveAllParameters()
- {
- for (int i = 0; i < _nParametersA; ++i) savedParametersA[i] = curParametersA[i];
- for (int j = 0; j < _nParametersB; ++j) savedParametersB[j] = curParametersB[j];
- savedParametersC = curParametersC;
- }
-
- virtual void restoreAllParameters()
- {
- for (int i = 0; i < _nParametersA; ++i) curParametersA[i] = savedParametersA[i];
- for (int j = 0; j < _nParametersB; ++j) curParametersB[j] = savedParametersB[j];
- curParametersC = savedParametersC;
- }
-
- VectorArray<double> curParametersA, savedParametersA;
- VectorArray<double> curParametersB, savedParametersB;
- Vector<double> curParametersC, savedParametersC;
- }; // end struct StdSparseLevenbergOptimizer
-
-# endif
-
-} // end namespace V3D
-
-#endif
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