1 // Ceres Solver - A fast non-linear least squares minimizer 2 // Copyright 2013 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/numeric_diff_test_utils.h" 32 33 #include <algorithm> 34 #include <cmath> 35 #include "ceres/cost_function.h" 36 #include "ceres/internal/macros.h" 37 #include "ceres/test_util.h" 38 #include "ceres/types.h" 39 #include "gtest/gtest.h" 40 41 42 namespace ceres { 43 namespace internal { 44 45 bool EasyFunctor::operator()(const double* x1, 46 const double* x2, 47 double* residuals) const { 48 residuals[0] = residuals[1] = residuals[2] = 0; 49 for (int i = 0; i < 5; ++i) { 50 residuals[0] += x1[i] * x2[i]; 51 residuals[2] += x2[i] * x2[i]; 52 } 53 residuals[1] = residuals[0] * residuals[0]; 54 return true; 55 } 56 57 void EasyFunctor::ExpectCostFunctionEvaluationIsNearlyCorrect( 58 const CostFunction& cost_function, 59 NumericDiffMethod method) const { 60 double x1[] = { 1.0, 2.0, 3.0, 4.0, 5.0 }; 61 double x2[] = { 9.0, 9.0, 5.0, 5.0, 1.0 }; 62 double *parameters[] = { &x1[0], &x2[0] }; 63 64 double dydx1[15]; // 3 x 5, row major. 65 double dydx2[15]; // 3 x 5, row major. 66 double *jacobians[2] = { &dydx1[0], &dydx2[0] }; 67 68 double residuals[3] = {-1e-100, -2e-100, -3e-100 }; 69 70 ASSERT_TRUE(cost_function.Evaluate(¶meters[0], 71 &residuals[0], 72 &jacobians[0])); 73 74 EXPECT_EQ(residuals[0], 67); 75 EXPECT_EQ(residuals[1], 4489); 76 EXPECT_EQ(residuals[2], 213); 77 78 const double tolerance = (method == CENTRAL)? 3e-9 : 2e-5; 79 80 for (int i = 0; i < 5; ++i) { 81 ExpectClose(x2[i], dydx1[5 * 0 + i], tolerance); // y1 82 ExpectClose(x1[i], dydx2[5 * 0 + i], tolerance); 83 ExpectClose(2 * x2[i] * residuals[0], dydx1[5 * 1 + i], tolerance); // y2 84 ExpectClose(2 * x1[i] * residuals[0], dydx2[5 * 1 + i], tolerance); 85 ExpectClose(0.0, dydx1[5 * 2 + i], tolerance); // y3 86 ExpectClose(2 * x2[i], dydx2[5 * 2 + i], tolerance); 87 } 88 } 89 90 bool TranscendentalFunctor::operator()(const double* x1, 91 const double* x2, 92 double* residuals) const { 93 double x1x2 = 0; 94 for (int i = 0; i < 5; ++i) { 95 x1x2 += x1[i] * x2[i]; 96 } 97 residuals[0] = sin(x1x2); 98 residuals[1] = exp(-x1x2 / 10); 99 return true; 100 } 101 102 void TranscendentalFunctor::ExpectCostFunctionEvaluationIsNearlyCorrect( 103 const CostFunction& cost_function, 104 NumericDiffMethod method) const { 105 struct { 106 double x1[5]; 107 double x2[5]; 108 } kTests[] = { 109 { { 1.0, 2.0, 3.0, 4.0, 5.0 }, // No zeros. 110 { 9.0, 9.0, 5.0, 5.0, 1.0 }, 111 }, 112 { { 0.0, 2.0, 3.0, 0.0, 5.0 }, // Some zeros x1. 113 { 9.0, 9.0, 5.0, 5.0, 1.0 }, 114 }, 115 { { 1.0, 2.0, 3.0, 1.0, 5.0 }, // Some zeros x2. 116 { 0.0, 9.0, 0.0, 5.0, 0.0 }, 117 }, 118 { { 0.0, 0.0, 0.0, 0.0, 0.0 }, // All zeros x1. 119 { 9.0, 9.0, 5.0, 5.0, 1.0 }, 120 }, 121 { { 1.0, 2.0, 3.0, 4.0, 5.0 }, // All zeros x2. 122 { 0.0, 0.0, 0.0, 0.0, 0.0 }, 123 }, 124 { { 0.0, 0.0, 0.0, 0.0, 0.0 }, // All zeros. 125 { 0.0, 0.0, 0.0, 0.0, 0.0 }, 126 }, 127 }; 128 129 for (int k = 0; k < CERES_ARRAYSIZE(kTests); ++k) { 130 double *x1 = &(kTests[k].x1[0]); 131 double *x2 = &(kTests[k].x2[0]); 132 double *parameters[] = { x1, x2 }; 133 134 double dydx1[10]; 135 double dydx2[10]; 136 double *jacobians[2] = { &dydx1[0], &dydx2[0] }; 137 138 double residuals[2]; 139 140 ASSERT_TRUE(cost_function.Evaluate(¶meters[0], 141 &residuals[0], 142 &jacobians[0])); 143 double x1x2 = 0; 144 for (int i = 0; i < 5; ++i) { 145 x1x2 += x1[i] * x2[i]; 146 } 147 148 const double tolerance = (method == CENTRAL)? 3e-9 : 2e-5; 149 150 for (int i = 0; i < 5; ++i) { 151 ExpectClose( x2[i] * cos(x1x2), dydx1[5 * 0 + i], tolerance); 152 ExpectClose( x1[i] * cos(x1x2), dydx2[5 * 0 + i], tolerance); 153 ExpectClose(-x2[i] * exp(-x1x2 / 10.) / 10., dydx1[5 * 1 + i], tolerance); 154 ExpectClose(-x1[i] * exp(-x1x2 / 10.) / 10., dydx2[5 * 1 + i], tolerance); 155 } 156 } 157 } 158 159 } // namespace internal 160 } // namespace ceres 161
