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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2019 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
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// Author: tbennun@gmail.com (Tal Ben-Nun)
//
#ifndef CERES_PUBLIC_NUMERIC_DIFF_OPTIONS_H_
#define CERES_PUBLIC_NUMERIC_DIFF_OPTIONS_H_
#include "ceres/internal/port.h"
namespace ceres {
// Options pertaining to numeric differentiation (e.g., convergence criteria,
// step sizes).
struct CERES_EXPORT NumericDiffOptions {
// Numeric differentiation step size (multiplied by parameter block's
// order of magnitude). If parameters are close to zero, the step size
// is set to sqrt(machine_epsilon).
double relative_step_size = 1e-6;
// Initial step size for Ridders adaptive numeric differentiation (multiplied
// by parameter block's order of magnitude).
// If parameters are close to zero, Ridders' method sets the step size
// directly to this value. This parameter is separate from
// "relative_step_size" in order to set a different default value.
//
// Note: For Ridders' method to converge, the step size should be initialized
// to a value that is large enough to produce a significant change in the
// function. As the derivative is estimated, the step size decreases.
double ridders_relative_initial_step_size = 1e-2;
// Maximal number of adaptive extrapolations (sampling) in Ridders' method.
int max_num_ridders_extrapolations = 10;
// Convergence criterion on extrapolation error for Ridders adaptive
// differentiation. The available error estimation methods are defined in
// NumericDiffErrorType and set in the "ridders_error_method" field.
double ridders_epsilon = 1e-12;
// The factor in which to shrink the step size with each extrapolation in
// Ridders' method.
double ridders_step_shrink_factor = 2.0;
};
} // namespace ceres
#endif // CERES_PUBLIC_NUMERIC_DIFF_OPTIONS_H_
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