| // 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 "ceres/autodiff_cost_function.h" |
| |
| #include <cstddef> |
| |
| #include "gtest/gtest.h" |
| #include "ceres/cost_function.h" |
| |
| namespace ceres { |
| namespace internal { |
| |
| class BinaryScalarCost { |
| public: |
| explicit BinaryScalarCost(double a): a_(a) {} |
| template <typename T> |
| bool operator()(const T* const x, const T* const y, |
| T* cost) const { |
| cost[0] = |
| x[0] * y[0] + x[1] * y[1] - T(a_); |
| return true; |
| } |
| private: |
| double a_; |
| }; |
| |
| |
| TEST(AutoDiffResidualAndJacobian, BilinearDifferentiationTest) { |
| CostFunction* cost_function = |
| new AutoDiffCostFunction<BinaryScalarCost, 1, 2, 2>( |
| new BinaryScalarCost(1.0)); |
| |
| double** parameters = new double*[2]; |
| parameters[0] = new double[2]; |
| parameters[1] = new double[2]; |
| |
| parameters[0][0] = 1; |
| parameters[0][1] = 2; |
| |
| parameters[1][0] = 3; |
| parameters[1][1] = 4; |
| |
| double** jacobians = new double*[2]; |
| jacobians[0] = new double[2]; |
| jacobians[1] = new double[2]; |
| |
| |
| double residuals = 0.0; |
| |
| cost_function->Evaluate(parameters, &residuals, NULL); |
| EXPECT_EQ(residuals, 10); |
| cost_function->Evaluate(parameters, &residuals, jacobians); |
| |
| EXPECT_EQ(jacobians[0][0], 3); |
| EXPECT_EQ(jacobians[0][1], 4); |
| EXPECT_EQ(jacobians[1][0], 1); |
| EXPECT_EQ(jacobians[1][1], 2); |
| |
| delete []jacobians[0]; |
| delete []jacobians[1]; |
| delete []parameters[0]; |
| delete []parameters[1]; |
| delete []jacobians; |
| delete []parameters; |
| delete cost_function; |
| } |
| |
| } // namespace internal |
| } // namespace ceres |