| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2015 Google Inc. All rights reserved. |
| // http://ceres-solver.org/ |
| // |
| // 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 |
| // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE |
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| // 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 std::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_ |