Home | History | Annotate | Download | only in ceres
      1 // Ceres Solver - A fast non-linear least squares minimizer
      2 // Copyright 2010, 2011, 2012 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: keir (at) google.com (Keir Mierle)
     30 
     31 #ifndef CERES_INTERNAL_GRADIENT_CHECKING_COST_FUNCTION_H_
     32 #define CERES_INTERNAL_GRADIENT_CHECKING_COST_FUNCTION_H_
     33 
     34 #include <string>
     35 
     36 #include "ceres/cost_function.h"
     37 
     38 namespace ceres {
     39 namespace internal {
     40 
     41 class ProblemImpl;
     42 
     43 // Creates a CostFunction that checks the jacobians that cost_function computes
     44 // with finite differences. Bad results are logged; required precision is
     45 // controlled by relative_precision and the numeric differentiation step size is
     46 // controlled with relative_step_size. See solver.h for a better explanation of
     47 // relative_step_size. Caller owns result.
     48 //
     49 // The condition enforced is that
     50 //
     51 //    (J_actual(i, j) - J_numeric(i, j))
     52 //   ------------------------------------  <  relative_precision
     53 //   max(J_actual(i, j), J_numeric(i, j))
     54 //
     55 // where J_actual(i, j) is the jacobian as computed by the supplied cost
     56 // function (by the user) and J_numeric is the jacobian as computed by finite
     57 // differences.
     58 //
     59 // Note: This is quite inefficient and is intended only for debugging.
     60 CostFunction* CreateGradientCheckingCostFunction(
     61     const CostFunction* cost_function,
     62     double relative_step_size,
     63     double relative_precision,
     64     const string& extra_info);
     65 
     66 // Create a new ProblemImpl object from the input problem_impl, where
     67 // each CostFunctions in problem_impl are wrapped inside a
     68 // GradientCheckingCostFunctions. This gives us a ProblemImpl object
     69 // which checks its derivatives against estimates from numeric
     70 // differentiation everytime a ResidualBlock is evaluated.
     71 //
     72 // relative_step_size and relative_precision are parameters to control
     73 // the numeric differentiation and the relative tolerance between the
     74 // jacobian computed by the CostFunctions in problem_impl and
     75 // jacobians obtained by numerically differentiating them. For more
     76 // details see the documentation for
     77 // CreateGradientCheckingCostFunction above.
     78 ProblemImpl* CreateGradientCheckingProblemImpl(ProblemImpl* problem_impl,
     79                                                double relative_step_size,
     80                                                double relative_precision);
     81 
     82 }  // namespace internal
     83 }  // namespace ceres
     84 
     85 #endif  // CERES_INTERNAL_GRADIENT_CHECKING_COST_FUNCTION_H_
     86