Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 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@google.com (Sameer Agarwal) |
| 30 | // mierle@gmail.com (Keir Mierle) |
| 31 | // |
| 32 | // Finite differencing routine used by NumericDiffCostFunction. |
| 33 | |
| 34 | #ifndef CERES_PUBLIC_INTERNAL_NUMERIC_DIFF_H_ |
| 35 | #define CERES_PUBLIC_INTERNAL_NUMERIC_DIFF_H_ |
| 36 | |
| 37 | #include <cstring> |
| 38 | |
| 39 | #include "Eigen/Dense" |
| 40 | #include "ceres/cost_function.h" |
| 41 | #include "ceres/internal/scoped_ptr.h" |
| 42 | #include "ceres/internal/variadic_evaluate.h" |
| 43 | #include "ceres/types.h" |
| 44 | #include "glog/logging.h" |
| 45 | |
| 46 | |
| 47 | namespace ceres { |
| 48 | namespace internal { |
| 49 | |
| 50 | // Helper templates that allow evaluation of a variadic functor or a |
| 51 | // CostFunction object. |
| 52 | template <typename CostFunctor, |
| 53 | int N0, int N1, int N2, int N3, int N4, |
| 54 | int N5, int N6, int N7, int N8, int N9 > |
| 55 | bool EvaluateImpl(const CostFunctor* functor, |
| 56 | double const* const* parameters, |
| 57 | double* residuals, |
| 58 | const void* /* NOT USED */) { |
| 59 | return VariadicEvaluate<CostFunctor, |
| 60 | double, |
| 61 | N0, N1, N2, N3, N4, N5, N6, N7, N8, N9>::Call( |
| 62 | *functor, |
| 63 | parameters, |
| 64 | residuals); |
| 65 | } |
| 66 | |
| 67 | template <typename CostFunctor, |
| 68 | int N0, int N1, int N2, int N3, int N4, |
| 69 | int N5, int N6, int N7, int N8, int N9 > |
| 70 | bool EvaluateImpl(const CostFunctor* functor, |
| 71 | double const* const* parameters, |
| 72 | double* residuals, |
| 73 | const CostFunction* /* NOT USED */) { |
| 74 | return functor->Evaluate(parameters, residuals, NULL); |
| 75 | } |
| 76 | |
| 77 | // This is split from the main class because C++ doesn't allow partial template |
| 78 | // specializations for member functions. The alternative is to repeat the main |
| 79 | // class for differing numbers of parameters, which is also unfortunate. |
| 80 | template <typename CostFunctor, |
| 81 | NumericDiffMethod kMethod, |
| 82 | int kNumResiduals, |
| 83 | int N0, int N1, int N2, int N3, int N4, |
| 84 | int N5, int N6, int N7, int N8, int N9, |
| 85 | int kParameterBlock, |
| 86 | int kParameterBlockSize> |
| 87 | struct NumericDiff { |
| 88 | // Mutates parameters but must restore them before return. |
| 89 | static bool EvaluateJacobianForParameterBlock( |
| 90 | const CostFunctor* functor, |
| 91 | double const* residuals_at_eval_point, |
| 92 | const double relative_step_size, |
Carlos Hernandez | 79397c2 | 2014-08-07 17:51:38 -0700 | [diff] [blame] | 93 | int num_residuals, |
Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 94 | double **parameters, |
| 95 | double *jacobian) { |
| 96 | using Eigen::Map; |
| 97 | using Eigen::Matrix; |
| 98 | using Eigen::RowMajor; |
| 99 | using Eigen::ColMajor; |
| 100 | |
Carlos Hernandez | 79397c2 | 2014-08-07 17:51:38 -0700 | [diff] [blame] | 101 | const int NUM_RESIDUALS = |
| 102 | (kNumResiduals != ceres::DYNAMIC ? kNumResiduals : num_residuals); |
| 103 | |
Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 104 | typedef Matrix<double, kNumResiduals, 1> ResidualVector; |
| 105 | typedef Matrix<double, kParameterBlockSize, 1> ParameterVector; |
Carlos Hernandez | 79397c2 | 2014-08-07 17:51:38 -0700 | [diff] [blame] | 106 | typedef Matrix<double, |
| 107 | kNumResiduals, |
| 108 | kParameterBlockSize, |
Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 109 | (kParameterBlockSize == 1 && |
Carlos Hernandez | 79397c2 | 2014-08-07 17:51:38 -0700 | [diff] [blame] | 110 | kNumResiduals > 1) ? ColMajor : RowMajor> |
| 111 | JacobianMatrix; |
Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 112 | |
| 113 | |
| 114 | Map<JacobianMatrix> parameter_jacobian(jacobian, |
Carlos Hernandez | 79397c2 | 2014-08-07 17:51:38 -0700 | [diff] [blame] | 115 | NUM_RESIDUALS, |
Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 116 | kParameterBlockSize); |
| 117 | |
| 118 | // Mutate 1 element at a time and then restore. |
| 119 | Map<ParameterVector> x_plus_delta(parameters[kParameterBlock], |
| 120 | kParameterBlockSize); |
| 121 | ParameterVector x(x_plus_delta); |
| 122 | ParameterVector step_size = x.array().abs() * relative_step_size; |
| 123 | |
| 124 | // To handle cases where a parameter is exactly zero, instead use |
| 125 | // the mean step_size for the other dimensions. If all the |
| 126 | // parameters are zero, there's no good answer. Take |
| 127 | // relative_step_size as a guess and hope for the best. |
| 128 | const double fallback_step_size = |
| 129 | (step_size.sum() == 0) |
| 130 | ? relative_step_size |
| 131 | : step_size.sum() / step_size.rows(); |
| 132 | |
| 133 | // For each parameter in the parameter block, use finite differences to |
| 134 | // compute the derivative for that parameter. |
Carlos Hernandez | 79397c2 | 2014-08-07 17:51:38 -0700 | [diff] [blame] | 135 | |
| 136 | ResidualVector residuals(NUM_RESIDUALS); |
Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 137 | for (int j = 0; j < kParameterBlockSize; ++j) { |
| 138 | const double delta = |
| 139 | (step_size(j) == 0.0) ? fallback_step_size : step_size(j); |
| 140 | |
| 141 | x_plus_delta(j) = x(j) + delta; |
| 142 | |
Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 143 | if (!EvaluateImpl<CostFunctor, N0, N1, N2, N3, N4, N5, N6, N7, N8, N9>( |
Carlos Hernandez | 79397c2 | 2014-08-07 17:51:38 -0700 | [diff] [blame] | 144 | functor, parameters, residuals.data(), functor)) { |
Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 145 | return false; |
| 146 | } |
| 147 | |
| 148 | // Compute this column of the jacobian in 3 steps: |
| 149 | // 1. Store residuals for the forward part. |
| 150 | // 2. Subtract residuals for the backward (or 0) part. |
| 151 | // 3. Divide out the run. |
Carlos Hernandez | 79397c2 | 2014-08-07 17:51:38 -0700 | [diff] [blame] | 152 | parameter_jacobian.col(j) = residuals; |
Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 153 | |
| 154 | double one_over_delta = 1.0 / delta; |
| 155 | if (kMethod == CENTRAL) { |
| 156 | // Compute the function on the other side of x(j). |
| 157 | x_plus_delta(j) = x(j) - delta; |
| 158 | |
| 159 | if (!EvaluateImpl<CostFunctor, N0, N1, N2, N3, N4, N5, N6, N7, N8, N9>( |
Carlos Hernandez | 79397c2 | 2014-08-07 17:51:38 -0700 | [diff] [blame] | 160 | functor, parameters, residuals.data(), functor)) { |
Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 161 | return false; |
| 162 | } |
| 163 | |
Carlos Hernandez | 79397c2 | 2014-08-07 17:51:38 -0700 | [diff] [blame] | 164 | parameter_jacobian.col(j) -= residuals; |
Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 165 | one_over_delta /= 2; |
| 166 | } else { |
| 167 | // Forward difference only; reuse existing residuals evaluation. |
| 168 | parameter_jacobian.col(j) -= |
Carlos Hernandez | 79397c2 | 2014-08-07 17:51:38 -0700 | [diff] [blame] | 169 | Map<const ResidualVector>(residuals_at_eval_point, NUM_RESIDUALS); |
Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 170 | } |
| 171 | x_plus_delta(j) = x(j); // Restore x_plus_delta. |
| 172 | |
| 173 | // Divide out the run to get slope. |
| 174 | parameter_jacobian.col(j) *= one_over_delta; |
| 175 | } |
| 176 | return true; |
| 177 | } |
| 178 | }; |
| 179 | |
| 180 | template <typename CostFunctor, |
| 181 | NumericDiffMethod kMethod, |
| 182 | int kNumResiduals, |
| 183 | int N0, int N1, int N2, int N3, int N4, |
| 184 | int N5, int N6, int N7, int N8, int N9, |
| 185 | int kParameterBlock> |
| 186 | struct NumericDiff<CostFunctor, kMethod, kNumResiduals, |
| 187 | N0, N1, N2, N3, N4, N5, N6, N7, N8, N9, |
| 188 | kParameterBlock, 0> { |
| 189 | // Mutates parameters but must restore them before return. |
| 190 | static bool EvaluateJacobianForParameterBlock( |
| 191 | const CostFunctor* functor, |
| 192 | double const* residuals_at_eval_point, |
| 193 | const double relative_step_size, |
Carlos Hernandez | 79397c2 | 2014-08-07 17:51:38 -0700 | [diff] [blame] | 194 | const int num_residuals, |
Sascha Haeberling | 1d2624a | 2013-07-23 19:00:21 -0700 | [diff] [blame] | 195 | double **parameters, |
| 196 | double *jacobian) { |
| 197 | LOG(FATAL) << "Control should never reach here."; |
| 198 | return true; |
| 199 | } |
| 200 | }; |
| 201 | |
| 202 | } // namespace internal |
| 203 | } // namespace ceres |
| 204 | |
| 205 | #endif // CERES_PUBLIC_INTERNAL_NUMERIC_DIFF_H_ |