| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2020 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: darius.rueckert@fau.de (Darius Rueckert) |
| |
| #include "codegen/test_utils.h" |
| |
| namespace ceres { |
| namespace internal { |
| |
| std::pair<std::vector<double>, std::vector<double> > EvaluateCostFunction( |
| CostFunction* cost_function, double value) { |
| auto num_residuals = cost_function->num_residuals(); |
| auto parameter_block_sizes = cost_function->parameter_block_sizes(); |
| auto num_parameter_blocks = parameter_block_sizes.size(); |
| |
| int total_num_parameters = 0; |
| for (auto block_size : parameter_block_sizes) { |
| total_num_parameters += block_size; |
| } |
| |
| std::vector<double> params_array(total_num_parameters, value); |
| std::vector<double*> params(num_parameter_blocks); |
| std::vector<double> residuals(num_residuals, 0); |
| std::vector<double> jacobians_array(num_residuals * total_num_parameters, 0); |
| std::vector<double*> jacobians(num_parameter_blocks); |
| |
| for (int i = 0, k = 0; i < num_parameter_blocks; |
| k += parameter_block_sizes[i], ++i) { |
| params[i] = ¶ms_array[k]; |
| } |
| |
| for (int i = 0, k = 0; i < num_parameter_blocks; |
| k += parameter_block_sizes[i], ++i) { |
| jacobians[i] = &jacobians_array[k * num_residuals]; |
| } |
| |
| cost_function->Evaluate(params.data(), residuals.data(), jacobians.data()); |
| |
| return std::make_pair(residuals, jacobians_array); |
| } |
| |
| void CompareCostFunctions(CostFunction* cost_function1, |
| CostFunction* cost_function2, |
| |
| double value, |
| double tol) { |
| auto residuals_and_jacobians_1 = EvaluateCostFunction(cost_function1, value); |
| auto residuals_and_jacobians_2 = EvaluateCostFunction(cost_function2, value); |
| |
| ExpectArraysClose(residuals_and_jacobians_1.first.size(), |
| residuals_and_jacobians_1.first.data(), |
| residuals_and_jacobians_2.first.data(), |
| tol); |
| ExpectArraysClose(residuals_and_jacobians_1.second.size(), |
| residuals_and_jacobians_1.second.data(), |
| residuals_and_jacobians_2.second.data(), |
| tol); |
| } |
| |
| } // namespace internal |
| } // namespace ceres |