86 lines
3.8 KiB
C
86 lines
3.8 KiB
C
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// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2015 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: keir@google.com (Keir Mierle)
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#ifndef CERES_INTERNAL_GRADIENT_CHECKING_COST_FUNCTION_H_
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#define CERES_INTERNAL_GRADIENT_CHECKING_COST_FUNCTION_H_
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#include <string>
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#include "ceres/cost_function.h"
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namespace ceres {
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namespace internal {
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class ProblemImpl;
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// Creates a CostFunction that checks the jacobians that cost_function computes
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// with finite differences. Bad results are logged; required precision is
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// controlled by relative_precision and the numeric differentiation step size is
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// controlled with relative_step_size. See solver.h for a better explanation of
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// relative_step_size. Caller owns result.
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//
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// The condition enforced is that
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//
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// (J_actual(i, j) - J_numeric(i, j))
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// ------------------------------------ < relative_precision
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// max(J_actual(i, j), J_numeric(i, j))
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//
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// where J_actual(i, j) is the jacobian as computed by the supplied cost
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// function (by the user) and J_numeric is the jacobian as computed by finite
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// differences.
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//
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// Note: This is quite inefficient and is intended only for debugging.
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CostFunction* CreateGradientCheckingCostFunction(
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const CostFunction* cost_function,
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double relative_step_size,
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double relative_precision,
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const std::string& extra_info);
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// Create a new ProblemImpl object from the input problem_impl, where
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// each CostFunctions in problem_impl are wrapped inside a
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// GradientCheckingCostFunctions. This gives us a ProblemImpl object
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// which checks its derivatives against estimates from numeric
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// differentiation everytime a ResidualBlock is evaluated.
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//
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// relative_step_size and relative_precision are parameters to control
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// the numeric differentiation and the relative tolerance between the
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// jacobian computed by the CostFunctions in problem_impl and
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// jacobians obtained by numerically differentiating them. For more
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// details see the documentation for
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// CreateGradientCheckingCostFunction above.
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ProblemImpl* CreateGradientCheckingProblemImpl(ProblemImpl* problem_impl,
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double relative_step_size,
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double relative_precision);
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} // namespace internal
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} // namespace ceres
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#endif // CERES_INTERNAL_GRADIENT_CHECKING_COST_FUNCTION_H_
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