residual_block.cc revision 0ae28bd5885b5daa526898fcf7c323dc2c3e1963
1// Ceres Solver - A fast non-linear least squares minimizer
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3// http://code.google.com/p/ceres-solver/
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29// Author: keir@google.com (Keir Mierle)
30//         sameeragarwal@google.com (Sameer Agarwal)
31
32#include "ceres/residual_block.h"
33
34#include <algorithm>
35#include <cstddef>
36#include <vector>
37
38#include "ceres/corrector.h"
39#include "ceres/parameter_block.h"
40#include "ceres/residual_block_utils.h"
41#include "ceres/cost_function.h"
42#include "ceres/internal/eigen.h"
43#include "ceres/internal/fixed_array.h"
44#include "ceres/local_parameterization.h"
45#include "ceres/loss_function.h"
46
47namespace ceres {
48namespace internal {
49
50ResidualBlock::ResidualBlock(const CostFunction* cost_function,
51                             const LossFunction* loss_function,
52                             const vector<ParameterBlock*>& parameter_blocks)
53    : cost_function_(cost_function),
54      loss_function_(loss_function),
55      parameter_blocks_(
56          new ParameterBlock* [
57              cost_function->parameter_block_sizes().size()]) {
58  std::copy(parameter_blocks.begin(),
59            parameter_blocks.end(),
60            parameter_blocks_.get());
61}
62
63bool ResidualBlock::Evaluate(double* cost,
64                             double* residuals,
65                             double** jacobians,
66                             double* scratch) const {
67  const int num_parameter_blocks = NumParameterBlocks();
68  const int num_residuals = cost_function_->num_residuals();
69
70  // Collect the parameters from their blocks. This will rarely allocate, since
71  // residuals taking more than 8 parameter block arguments are rare.
72  FixedArray<const double*, 8> parameters(num_parameter_blocks);
73  for (int i = 0; i < num_parameter_blocks; ++i) {
74    parameters[i] = parameter_blocks_[i]->state();
75  }
76
77  // Put pointers into the scratch space into global_jacobians as appropriate.
78  FixedArray<double*, 8> global_jacobians(num_parameter_blocks);
79  if (jacobians != NULL) {
80    for (int i = 0; i < num_parameter_blocks; ++i) {
81      const ParameterBlock* parameter_block = parameter_blocks_[i];
82      if (jacobians[i] != NULL &&
83          parameter_block->LocalParameterizationJacobian() != NULL) {
84        global_jacobians[i] = scratch;
85        scratch += num_residuals * parameter_block->Size();
86      } else {
87        global_jacobians[i] = jacobians[i];
88      }
89    }
90  }
91
92  // If the caller didn't request residuals, use the scratch space for them.
93  bool outputting_residuals = (residuals != NULL);
94  if (!outputting_residuals) {
95    residuals = scratch;
96  }
97
98  // Invalidate the evaluation buffers so that we can check them after
99  // the CostFunction::Evaluate call, to see if all the return values
100  // that were required were written to and that they are finite.
101  double** eval_jacobians = (jacobians != NULL) ? global_jacobians.get() : NULL;
102
103  InvalidateEvaluation(*this, cost, residuals, eval_jacobians);
104
105  if (!cost_function_->Evaluate(parameters.get(), residuals, eval_jacobians)) {
106    return false;
107  }
108
109  if (!IsEvaluationValid(*this,
110                         parameters.get(),
111                         cost,
112                         residuals,
113                         eval_jacobians)) {
114    string message =
115        "\n\n"
116        "Error in evaluating the ResidualBlock.\n\n"
117        "There are two possible reasons. Either the CostFunction did not evaluate and fill all    \n"  // NOLINT
118        "residual and jacobians that were requested or there was a non-finite value (nan/infinite)\n"  // NOLINT
119        "generated during the or jacobian computation. \n\n" +
120        EvaluationToString(*this,
121                           parameters.get(),
122                           cost,
123                           residuals,
124                           eval_jacobians);
125    LOG(WARNING) << message;
126    return false;
127  }
128
129  double squared_norm = VectorRef(residuals, num_residuals).squaredNorm();
130
131  // Update the jacobians with the local parameterizations.
132  if (jacobians != NULL) {
133    for (int i = 0; i < num_parameter_blocks; ++i) {
134      if (jacobians[i] != NULL) {
135        const ParameterBlock* parameter_block = parameter_blocks_[i];
136
137        // Apply local reparameterization to the jacobians.
138        if (parameter_block->LocalParameterizationJacobian() != NULL) {
139          ConstMatrixRef local_to_global(
140              parameter_block->LocalParameterizationJacobian(),
141              parameter_block->Size(),
142              parameter_block->LocalSize());
143          MatrixRef global_jacobian(global_jacobians[i],
144                                    num_residuals,
145                                    parameter_block->Size());
146          MatrixRef local_jacobian(jacobians[i],
147                                   num_residuals,
148                                   parameter_block->LocalSize());
149          local_jacobian.noalias() = global_jacobian * local_to_global;
150        }
151      }
152    }
153  }
154
155  if (loss_function_ == NULL) {
156    *cost = 0.5 * squared_norm;
157    return true;
158  }
159
160  double rho[3];
161  loss_function_->Evaluate(squared_norm, rho);
162  *cost = 0.5 * rho[0];
163
164  // No jacobians and not outputting residuals? All done. Doing an early exit
165  // here avoids constructing the "Corrector" object below in a common case.
166  if (jacobians == NULL && !outputting_residuals) {
167    return true;
168  }
169
170  // Correct for the effects of the loss function. The jacobians need to be
171  // corrected before the residuals, since they use the uncorrected residuals.
172  Corrector correct(squared_norm, rho);
173  if (jacobians != NULL) {
174    for (int i = 0; i < num_parameter_blocks; ++i) {
175      if (jacobians[i] != NULL) {
176        const ParameterBlock* parameter_block = parameter_blocks_[i];
177
178        // Correct the jacobians for the loss function.
179        correct.CorrectJacobian(num_residuals,
180                                parameter_block->LocalSize(),
181                                residuals,
182                                jacobians[i]);
183      }
184    }
185  }
186
187  // Correct the residuals with the loss function.
188  if (outputting_residuals) {
189    correct.CorrectResiduals(num_residuals, residuals);
190  }
191  return true;
192}
193
194int ResidualBlock::NumScratchDoublesForEvaluate() const {
195  // Compute the amount of scratch space needed to store the full-sized
196  // jacobians. For parameters that have no local parameterization  no storage
197  // is needed and the passed-in jacobian array is used directly. Also include
198  // space to store the residuals, which is needed for cost-only evaluations.
199  // This is slightly pessimistic, since both won't be needed all the time, but
200  // the amount of excess should not cause problems for the caller.
201  int num_parameters = NumParameterBlocks();
202  int scratch_doubles = 1;
203  for (int i = 0; i < num_parameters; ++i) {
204    const ParameterBlock* parameter_block = parameter_blocks_[i];
205    if (!parameter_block->IsConstant() &&
206        parameter_block->LocalParameterizationJacobian() != NULL) {
207      scratch_doubles += parameter_block->Size();
208    }
209  }
210  scratch_doubles *= NumResiduals();
211  return scratch_doubles;
212}
213
214}  // namespace internal
215}  // namespace ceres
216