1 // Ceres Solver - A fast non-linear least squares minimizer 2 // Copyright 2010, 2011, 2012 Google Inc. All rights reserved. 3 // http://code.google.com/p/ceres-solver/ 4 // 5 // Redistribution and use in source and binary forms, with or without 6 // modification, are permitted provided that the following conditions are met: 7 // 8 // * Redistributions of source code must retain the above copyright notice, 9 // this list of conditions and the following disclaimer. 10 // * Redistributions in binary form must reproduce the above copyright notice, 11 // this list of conditions and the following disclaimer in the documentation 12 // and/or other materials provided with the distribution. 13 // * Neither the name of Google Inc. nor the names of its contributors may be 14 // used to endorse or promote products derived from this software without 15 // specific prior written permission. 16 // 17 // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" 18 // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 19 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE 20 // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE 21 // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR 22 // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 23 // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS 24 // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN 25 // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) 26 // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 27 // POSSIBILITY OF SUCH DAMAGE. 28 // 29 // Author: sameeragarwal (at) google.com (Sameer Agarwal) 30 31 #include "ceres/autodiff_cost_function.h" 32 33 #include <cstddef> 34 35 #include "gtest/gtest.h" 36 #include "ceres/cost_function.h" 37 38 namespace ceres { 39 namespace internal { 40 41 class BinaryScalarCost { 42 public: 43 explicit BinaryScalarCost(double a): a_(a) {} 44 template <typename T> 45 bool operator()(const T* const x, const T* const y, 46 T* cost) const { 47 cost[0] = x[0] * y[0] + x[1] * y[1] - T(a_); 48 return true; 49 } 50 private: 51 double a_; 52 }; 53 54 TEST(AutodiffCostFunction, BilinearDifferentiationTest) { 55 CostFunction* cost_function = 56 new AutoDiffCostFunction<BinaryScalarCost, 1, 2, 2>( 57 new BinaryScalarCost(1.0)); 58 59 double** parameters = new double*[2]; 60 parameters[0] = new double[2]; 61 parameters[1] = new double[2]; 62 63 parameters[0][0] = 1; 64 parameters[0][1] = 2; 65 66 parameters[1][0] = 3; 67 parameters[1][1] = 4; 68 69 double** jacobians = new double*[2]; 70 jacobians[0] = new double[2]; 71 jacobians[1] = new double[2]; 72 73 double residuals = 0.0; 74 75 cost_function->Evaluate(parameters, &residuals, NULL); 76 EXPECT_EQ(10.0, residuals); 77 cost_function->Evaluate(parameters, &residuals, jacobians); 78 79 EXPECT_EQ(3, jacobians[0][0]); 80 EXPECT_EQ(4, jacobians[0][1]); 81 EXPECT_EQ(1, jacobians[1][0]); 82 EXPECT_EQ(2, jacobians[1][1]); 83 84 delete[] jacobians[0]; 85 delete[] jacobians[1]; 86 delete[] parameters[0]; 87 delete[] parameters[1]; 88 delete[] jacobians; 89 delete[] parameters; 90 delete cost_function; 91 } 92 93 struct TenParameterCost { 94 template <typename T> 95 bool operator()(const T* const x0, 96 const T* const x1, 97 const T* const x2, 98 const T* const x3, 99 const T* const x4, 100 const T* const x5, 101 const T* const x6, 102 const T* const x7, 103 const T* const x8, 104 const T* const x9, 105 T* cost) const { 106 cost[0] = *x0 + *x1 + *x2 + *x3 + *x4 + *x5 + *x6 + *x7 + *x8 + *x9; 107 return true; 108 } 109 }; 110 111 TEST(AutodiffCostFunction, ManyParameterAutodiffInstantiates) { 112 CostFunction* cost_function = 113 new AutoDiffCostFunction< 114 TenParameterCost, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1>( 115 new TenParameterCost); 116 117 double** parameters = new double*[10]; 118 double** jacobians = new double*[10]; 119 for (int i = 0; i < 10; ++i) { 120 parameters[i] = new double[1]; 121 parameters[i][0] = i; 122 jacobians[i] = new double[1]; 123 } 124 125 double residuals = 0.0; 126 127 cost_function->Evaluate(parameters, &residuals, NULL); 128 EXPECT_EQ(45.0, residuals); 129 130 cost_function->Evaluate(parameters, &residuals, jacobians); 131 EXPECT_EQ(residuals, 45.0); 132 for (int i = 0; i < 10; ++i) { 133 EXPECT_EQ(1.0, jacobians[i][0]); 134 } 135 136 for (int i = 0; i < 10; ++i) { 137 delete[] jacobians[i]; 138 delete[] parameters[i]; 139 } 140 delete[] jacobians; 141 delete[] parameters; 142 delete cost_function; 143 } 144 145 } // namespace internal 146 } // namespace ceres 147