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150 lines
6.3 KiB
150 lines
6.3 KiB
// 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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// Copyright 2007 Google Inc. All Rights Reserved.
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//
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// Authors: wjr@google.com (William Rucklidge),
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// keir@google.com (Keir Mierle),
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// dgossow@google.com (David Gossow)
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#ifndef CERES_PUBLIC_GRADIENT_CHECKER_H_
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#define CERES_PUBLIC_GRADIENT_CHECKER_H_
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#include <vector>
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#include <string>
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#include "ceres/cost_function.h"
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#include "ceres/dynamic_numeric_diff_cost_function.h"
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#include "ceres/internal/eigen.h"
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#include "ceres/internal/fixed_array.h"
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#include "ceres/internal/macros.h"
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#include "ceres/internal/scoped_ptr.h"
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#include "ceres/local_parameterization.h"
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#include "glog/logging.h"
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namespace ceres {
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// GradientChecker compares the Jacobians returned by a cost function against
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// derivatives estimated using finite differencing.
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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) multiplied by the local parameterization Jacobian
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// and J_numeric is the jacobian as computed by finite differences, multiplied
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// by the local parameterization Jacobian as well.
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//
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// How to use: Fill in an array of pointers to parameter blocks for your
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// CostFunction, and then call Probe(). Check that the return value is 'true'.
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class CERES_EXPORT GradientChecker {
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public:
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// This will not take ownership of the cost function or local
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// parameterizations.
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//
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// function: The cost function to probe.
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// local_parameterization: A vector of local parameterizations for each
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// parameter. May be NULL or contain NULL pointers to indicate that the
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// respective parameter does not have a local parameterization.
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// options: Options to use for numerical differentiation.
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GradientChecker(
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const CostFunction* function,
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const std::vector<const LocalParameterization*>* local_parameterizations,
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const NumericDiffOptions& options);
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// Contains results from a call to Probe for later inspection.
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struct CERES_EXPORT ProbeResults {
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// The return value of the cost function.
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bool return_value;
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// Computed residual vector.
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Vector residuals;
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// The sizes of the Jacobians below are dictated by the cost function's
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// parameter block size and residual block sizes. If a parameter block
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// has a local parameterization associated with it, the size of the "local"
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// Jacobian will be determined by the local parameterization dimension and
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// residual block size, otherwise it will be identical to the regular
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// Jacobian.
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// Derivatives as computed by the cost function.
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std::vector<Matrix> jacobians;
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// Derivatives as computed by the cost function in local space.
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std::vector<Matrix> local_jacobians;
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// Derivatives as computed by nuerical differentiation in local space.
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std::vector<Matrix> numeric_jacobians;
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// Derivatives as computed by nuerical differentiation in local space.
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std::vector<Matrix> local_numeric_jacobians;
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// Contains the maximum relative error found in the local Jacobians.
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double maximum_relative_error;
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// If an error was detected, this will contain a detailed description of
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// that error.
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std::string error_log;
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};
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// Call the cost function, compute alternative Jacobians using finite
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// differencing and compare results. If local parameterizations are given,
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// the Jacobians will be multiplied by the local parameterization Jacobians
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// before performing the check, which effectively means that all errors along
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// the null space of the local parameterization will be ignored.
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// Returns false if the Jacobians don't match, the cost function return false,
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// or if the cost function returns different residual when called with a
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// Jacobian output argument vs. calling it without. Otherwise returns true.
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//
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// parameters: The parameter values at which to probe.
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// relative_precision: A threshold for the relative difference between the
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// Jacobians. If the Jacobians differ by more than this amount, then the
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// probe fails.
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// results: On return, the Jacobians (and other information) will be stored
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// here. May be NULL.
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//
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// Returns true if no problems are detected and the difference between the
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// Jacobians is less than error_tolerance.
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bool Probe(double const* const* parameters,
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double relative_precision,
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ProbeResults* results) const;
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private:
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CERES_DISALLOW_IMPLICIT_CONSTRUCTORS(GradientChecker);
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std::vector<const LocalParameterization*> local_parameterizations_;
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const CostFunction* function_;
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internal::scoped_ptr<CostFunction> finite_diff_cost_function_;
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};
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} // namespace ceres
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#endif // CERES_PUBLIC_GRADIENT_CHECKER_H_
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