// 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