| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2010, 2011, 2012 Google Inc. All rights reserved. | |
| // http://code.google.com/p/ceres-solver/ | |
| // | |
| // Redistribution and use in source and binary forms, with or without | |
| // modification, are permitted provided that the following conditions are met: | |
| // | |
| // * Redistributions of source code must retain the above copyright notice, | |
| // this list of conditions and the following disclaimer. | |
| // * Redistributions in binary form must reproduce the above copyright notice, | |
| // this list of conditions and the following disclaimer in the documentation | |
| // and/or other materials provided with the distribution. | |
| // * Neither the name of Google Inc. nor the names of its contributors may be | |
| // used to endorse or promote products derived from this software without | |
| // specific prior written permission. | |
| // | |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | |
| // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | |
| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE | |
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| // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN | |
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| // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | |
| // POSSIBILITY OF SUCH DAMAGE. | |
| // | |
| // Author: keir@google.com (Keir Mierle) | |
| #ifndef CERES_INTERNAL_GRADIENT_CHECKING_COST_FUNCTION_H_ | |
| #define CERES_INTERNAL_GRADIENT_CHECKING_COST_FUNCTION_H_ | |
| #include <string> | |
| #include "ceres/cost_function.h" | |
| namespace ceres { | |
| namespace internal { | |
| class ProblemImpl; | |
| // Creates a CostFunction that checks the jacobians that cost_function computes | |
| // with finite differences. Bad results are logged; required precision is | |
| // controlled by relative_precision and the numeric differentiation step size is | |
| // controlled with relative_step_size. See solver.h for a better explanation of | |
| // relative_step_size. Caller owns result. | |
| // | |
| // The condition enforced is that | |
| // | |
| // (J_actual(i, j) - J_numeric(i, j)) | |
| // ------------------------------------ < relative_precision | |
| // max(J_actual(i, j), J_numeric(i, j)) | |
| // | |
| // where J_actual(i, j) is the jacobian as computed by the supplied cost | |
| // function (by the user) and J_numeric is the jacobian as computed by finite | |
| // differences. | |
| // | |
| // Note: This is quite inefficient and is intended only for debugging. | |
| CostFunction* CreateGradientCheckingCostFunction( | |
| const CostFunction* cost_function, | |
| double relative_step_size, | |
| double relative_precision, | |
| const string& extra_info); | |
| // Create a new ProblemImpl object from the input problem_impl, where | |
| // each CostFunctions in problem_impl are wrapped inside a | |
| // GradientCheckingCostFunctions. This gives us a ProblemImpl object | |
| // which checks its derivatives against estimates from numeric | |
| // differentiation everytime a ResidualBlock is evaluated. | |
| // | |
| // relative_step_size and relative_precision are parameters to control | |
| // the numeric differentiation and the relative tolerance between the | |
| // jacobian computed by the CostFunctions in problem_impl and | |
| // jacobians obtained by numerically differentiating them. For more | |
| // details see the documentation for | |
| // CreateGradientCheckingCostFunction above. | |
| ProblemImpl* CreateGradientCheckingProblemImpl(ProblemImpl* problem_impl, | |
| double relative_step_size, | |
| double relative_precision); | |
| } // namespace internal | |
| } // namespace ceres | |
| #endif // CERES_INTERNAL_GRADIENT_CHECKING_COST_FUNCTION_H_ |