// Ceres Solver - A fast non-linear least squares minimizer // Copyright 2017 Google Inc. All rights reserved. // http://ceres-solver.org/ // // 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) // // Template specialization of PartitionedMatrixView. // // ======================================== // THIS FILE IS AUTOGENERATED. DO NOT EDIT. // THIS FILE IS AUTOGENERATED. DO NOT EDIT. // THIS FILE IS AUTOGENERATED. DO NOT EDIT. // THIS FILE IS AUTOGENERATED. DO NOT EDIT. //========================================= // // This file is generated using generate_template_specializations.py. #include "ceres/linear_solver.h" #include "ceres/partitioned_matrix_view.h" #include "ceres/internal/eigen.h" namespace ceres { namespace internal { PartitionedMatrixViewBase* PartitionedMatrixViewBase::Create(const LinearSolver::Options& options, const BlockSparseMatrix& matrix) { #ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION if ((options.row_block_size == 2) && (options.e_block_size == 2) && (options.f_block_size == 2)) { return new PartitionedMatrixView<2, 2, 2>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 2) && (options.e_block_size == 2) && (options.f_block_size == 3)) { return new PartitionedMatrixView<2, 2, 3>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 2) && (options.e_block_size == 2) && (options.f_block_size == 4)) { return new PartitionedMatrixView<2, 2, 4>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 2) && (options.e_block_size == 2)) { return new PartitionedMatrixView<2, 2, Eigen::Dynamic>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 2) && (options.e_block_size == 3) && (options.f_block_size == 3)) { return new PartitionedMatrixView<2, 3, 3>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 2) && (options.e_block_size == 3) && (options.f_block_size == 4)) { return new PartitionedMatrixView<2, 3, 4>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 2) && (options.e_block_size == 3) && (options.f_block_size == 6)) { return new PartitionedMatrixView<2, 3, 6>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 2) && (options.e_block_size == 3) && (options.f_block_size == 9)) { return new PartitionedMatrixView<2, 3, 9>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 2) && (options.e_block_size == 3)) { return new PartitionedMatrixView<2, 3, Eigen::Dynamic>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 2) && (options.e_block_size == 4) && (options.f_block_size == 3)) { return new PartitionedMatrixView<2, 4, 3>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 2) && (options.e_block_size == 4) && (options.f_block_size == 4)) { return new PartitionedMatrixView<2, 4, 4>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 2) && (options.e_block_size == 4) && (options.f_block_size == 8)) { return new PartitionedMatrixView<2, 4, 8>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 2) && (options.e_block_size == 4) && (options.f_block_size == 9)) { return new PartitionedMatrixView<2, 4, 9>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 2) && (options.e_block_size == 4)) { return new PartitionedMatrixView<2, 4, Eigen::Dynamic>(matrix, options.elimination_groups[0]); } if (options.row_block_size == 2){ return new PartitionedMatrixView<2, Eigen::Dynamic, Eigen::Dynamic>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 4) && (options.e_block_size == 4) && (options.f_block_size == 2)) { return new PartitionedMatrixView<4, 4, 2>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 4) && (options.e_block_size == 4) && (options.f_block_size == 3)) { return new PartitionedMatrixView<4, 4, 3>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 4) && (options.e_block_size == 4) && (options.f_block_size == 4)) { return new PartitionedMatrixView<4, 4, 4>(matrix, options.elimination_groups[0]); } if ((options.row_block_size == 4) && (options.e_block_size == 4)) { return new PartitionedMatrixView<4, 4, Eigen::Dynamic>(matrix, options.elimination_groups[0]); } #endif VLOG(1) << "Template specializations not found for <" << options.row_block_size << "," << options.e_block_size << "," << options.f_block_size << ">"; return new PartitionedMatrixView( matrix, options.elimination_groups[0]); }; } // namespace internal } // namespace ceres