// 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)
#ifndef CERES_NO_CXSPARSE
#include "ceres/cxsparse.h"
#include "ceres/compressed_row_sparse_matrix.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_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_free(scratch_);
}
scratch_ = reinterpret_cast<CS_ENTRY*>(cs_malloc(A->n, sizeof(CS_ENTRY)));
}
// Solve using Cholesky factorization
csn* numeric_factorization = cs_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_ipvec(symbolic_factorization->pinv, b, scratch_, A->n);
// Set x = L \ x.
cs_lsolve(numeric_factorization->L, scratch_);
// Set x = L' \ x.
cs_ltsolve(numeric_factorization->L, scratch_);
// Set b = P' * x.
cs_pvec(symbolic_factorization->pinv, scratch_, b, A->n);
// Free Cholesky factorization.
cs_nfree(numeric_factorization);
return true;
}
cs_dis* CXSparse::AnalyzeCholesky(cs_di* A) {
// order = 1 for Cholesky factorization.
return cs_schol(1, A);
}
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::Free(cs_di* factor) {
cs_free(factor);
}
void CXSparse::Free(cs_dis* factor) {
cs_sfree(factor);
}
} // namespace internal
} // namespace ceres
#endif // CERES_NO_CXSPARSE