Files
ceres-solver/internal/ceres/types.cc
T
Sameer Agarwal 031598295c Enable Eigen as sparse linear algebra library.
SPARSE_NORMAL_CHOLESKY and SPARSE_SCHUR can now be used
with EIGEN_SPARSE as the backend.

The performance is not as good as CXSparse. This needs to be
investigated. Is it because the quality of AMD ordering that
we are computing is not as good as the one for CXSparse? This
could be because we are working with the scalar matrix instead
of the block matrix.

Also, the upper/lower triangular story is not completely clear.
Both of these issues will be benchmarked and tackled in the
near future.

Also included in this change is a bunch of cleanup to the
SparseNormalCholeskySolver and SparseSchurComplementSolver
classes around the use of the of defines used to conditionally
compile out parts of the code.

The system_test has been updated to test EIGEN_SPARSE also.

Change-Id: I46a57e9c4c97782696879e0b15cfc7a93fe5496a
2014-07-31 22:05:34 -07:00

363 lines
8.6 KiB
C++

// 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.
//
// Author: sameeragarwal@google.com (Sameer Agarwal)
#include <algorithm>
#include <cctype>
#include <string>
#include "ceres/types.h"
#include "glog/logging.h"
namespace ceres {
#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);
default:
return "UNKNOWN";
}
}
bool StringToSparseLinearAlgebraLibraryType(
string value,
SparseLinearAlgebraLibraryType* type) {
UpperCase(&value);
STRENUM(SUITE_SPARSE);
STRENUM(CX_SPARSE);
STRENUM(EIGEN_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* 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
}
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