Sameer Agarwal | 2f0d724 | 2013-01-18 13:11:32 -0800 | [diff] [blame] | 1 | #include "ceres/numeric_diff_test_utils.h" |
| 2 | |
| 3 | #include <algorithm> |
| 4 | #include <cmath> |
| 5 | #include "ceres/cost_function.h" |
| 6 | #include "ceres/internal/macros.h" |
| 7 | #include "ceres/test_util.h" |
| 8 | #include "ceres/types.h" |
| 9 | #include "gtest/gtest.h" |
| 10 | |
| 11 | |
| 12 | namespace ceres { |
| 13 | namespace internal { |
| 14 | |
| 15 | bool EasyFunctor::operator()(const double* x1, |
| 16 | const double* x2, |
| 17 | double* residuals) const { |
| 18 | residuals[0] = residuals[1] = residuals[2] = 0; |
| 19 | for (int i = 0; i < 5; ++i) { |
| 20 | residuals[0] += x1[i] * x2[i]; |
| 21 | residuals[2] += x2[i] * x2[i]; |
| 22 | } |
| 23 | residuals[1] = residuals[0] * residuals[0]; |
| 24 | return true; |
| 25 | } |
| 26 | |
| 27 | void EasyFunctor::ExpectCostFunctionEvaluationIsNearlyCorrect( |
| 28 | const CostFunction& cost_function, |
| 29 | NumericDiffMethod method) const { |
| 30 | double x1[] = { 1.0, 2.0, 3.0, 4.0, 5.0 }; |
| 31 | double x2[] = { 9.0, 9.0, 5.0, 5.0, 1.0 }; |
| 32 | double *parameters[] = { &x1[0], &x2[0] }; |
| 33 | |
| 34 | double dydx1[15]; // 3 x 5, row major. |
| 35 | double dydx2[15]; // 3 x 5, row major. |
| 36 | double *jacobians[2] = { &dydx1[0], &dydx2[0] }; |
| 37 | |
| 38 | double residuals[3] = {-1e-100, -2e-100, -3e-100 }; |
| 39 | |
| 40 | ASSERT_TRUE(cost_function.Evaluate(¶meters[0], |
| 41 | &residuals[0], |
| 42 | &jacobians[0])); |
| 43 | |
| 44 | EXPECT_EQ(residuals[0], 67); |
| 45 | EXPECT_EQ(residuals[1], 4489); |
| 46 | EXPECT_EQ(residuals[2], 213); |
| 47 | |
| 48 | const double tolerance = (method == CENTRAL)? 3e-9 : 2e-5; |
| 49 | |
| 50 | for (int i = 0; i < 5; ++i) { |
| 51 | ExpectClose(x2[i], dydx1[5 * 0 + i], tolerance); // y1 |
| 52 | ExpectClose(x1[i], dydx2[5 * 0 + i], tolerance); |
| 53 | ExpectClose(2 * x2[i] * residuals[0], dydx1[5 * 1 + i], tolerance); // y2 |
| 54 | ExpectClose(2 * x1[i] * residuals[0], dydx2[5 * 1 + i], tolerance); |
| 55 | ExpectClose(0.0, dydx1[5 * 2 + i], tolerance); // y3 |
| 56 | ExpectClose(2 * x2[i], dydx2[5 * 2 + i], tolerance); |
| 57 | } |
| 58 | } |
| 59 | |
| 60 | bool TranscendentalFunctor::operator()(const double* x1, |
| 61 | const double* x2, |
| 62 | double* residuals) const { |
| 63 | double x1x2 = 0; |
| 64 | for (int i = 0; i < 5; ++i) { |
| 65 | x1x2 += x1[i] * x2[i]; |
| 66 | } |
| 67 | residuals[0] = sin(x1x2); |
| 68 | residuals[1] = exp(-x1x2 / 10); |
| 69 | return true; |
| 70 | } |
| 71 | |
| 72 | void TranscendentalFunctor::ExpectCostFunctionEvaluationIsNearlyCorrect( |
| 73 | const CostFunction& cost_function, |
| 74 | NumericDiffMethod method) const { |
| 75 | struct { |
| 76 | double x1[5]; |
| 77 | double x2[5]; |
| 78 | } kTests[] = { |
| 79 | { { 1.0, 2.0, 3.0, 4.0, 5.0 }, // No zeros. |
| 80 | { 9.0, 9.0, 5.0, 5.0, 1.0 }, |
| 81 | }, |
| 82 | { { 0.0, 2.0, 3.0, 0.0, 5.0 }, // Some zeros x1. |
| 83 | { 9.0, 9.0, 5.0, 5.0, 1.0 }, |
| 84 | }, |
| 85 | { { 1.0, 2.0, 3.0, 1.0, 5.0 }, // Some zeros x2. |
| 86 | { 0.0, 9.0, 0.0, 5.0, 0.0 }, |
| 87 | }, |
| 88 | { { 0.0, 0.0, 0.0, 0.0, 0.0 }, // All zeros x1. |
| 89 | { 9.0, 9.0, 5.0, 5.0, 1.0 }, |
| 90 | }, |
| 91 | { { 1.0, 2.0, 3.0, 4.0, 5.0 }, // All zeros x2. |
| 92 | { 0.0, 0.0, 0.0, 0.0, 0.0 }, |
| 93 | }, |
| 94 | { { 0.0, 0.0, 0.0, 0.0, 0.0 }, // All zeros. |
| 95 | { 0.0, 0.0, 0.0, 0.0, 0.0 }, |
| 96 | }, |
| 97 | }; |
| 98 | |
| 99 | for (int k = 0; k < CERES_ARRAYSIZE(kTests); ++k) { |
| 100 | double *x1 = &(kTests[k].x1[0]); |
| 101 | double *x2 = &(kTests[k].x2[0]); |
| 102 | double *parameters[] = { x1, x2 }; |
| 103 | |
| 104 | double dydx1[10]; |
| 105 | double dydx2[10]; |
| 106 | double *jacobians[2] = { &dydx1[0], &dydx2[0] }; |
| 107 | |
| 108 | double residuals[2]; |
| 109 | |
| 110 | ASSERT_TRUE(cost_function.Evaluate(¶meters[0], |
| 111 | &residuals[0], |
| 112 | &jacobians[0])); |
| 113 | double x1x2 = 0; |
| 114 | for (int i = 0; i < 5; ++i) { |
| 115 | x1x2 += x1[i] * x2[i]; |
| 116 | } |
| 117 | |
| 118 | const double tolerance = (method == CENTRAL)? 3e-9 : 2e-5; |
| 119 | |
| 120 | for (int i = 0; i < 5; ++i) { |
| 121 | ExpectClose( x2[i] * cos(x1x2), dydx1[5 * 0 + i], tolerance); |
| 122 | ExpectClose( x1[i] * cos(x1x2), dydx2[5 * 0 + i], tolerance); |
| 123 | ExpectClose(-x2[i] * exp(-x1x2 / 10.) / 10., dydx1[5 * 1 + i], tolerance); |
| 124 | ExpectClose(-x1[i] * exp(-x1x2 / 10.) / 10., dydx2[5 * 1 + i], tolerance); |
| 125 | } |
| 126 | } |
| 127 | } |
| 128 | |
| 129 | } // namespace internal |
| 130 | } // namespace ceres |