80 lines
3.5 KiB
C
80 lines
3.5 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: tbennun@gmail.com (Tal Ben-Nun)
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//
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#ifndef CERES_PUBLIC_NUMERIC_DIFF_OPTIONS_H_
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#define CERES_PUBLIC_NUMERIC_DIFF_OPTIONS_H_
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namespace ceres {
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// Options pertaining to numeric differentiation (e.g., convergence criteria,
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// step sizes).
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struct CERES_EXPORT NumericDiffOptions {
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NumericDiffOptions() {
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relative_step_size = 1e-6;
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ridders_relative_initial_step_size = 1e-2;
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max_num_ridders_extrapolations = 10;
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ridders_epsilon = 1e-12;
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ridders_step_shrink_factor = 2.0;
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}
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// Numeric differentiation step size (multiplied by parameter block's
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// order of magnitude). If parameters are close to zero, the step size
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// is set to sqrt(machine_epsilon).
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double relative_step_size;
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// Initial step size for Ridders adaptive numeric differentiation (multiplied
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// by parameter block's order of magnitude).
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// If parameters are close to zero, Ridders' method sets the step size
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// directly to this value. This parameter is separate from
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// "relative_step_size" in order to set a different default value.
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//
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// Note: For Ridders' method to converge, the step size should be initialized
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// to a value that is large enough to produce a significant change in the
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// function. As the derivative is estimated, the step size decreases.
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double ridders_relative_initial_step_size;
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// Maximal number of adaptive extrapolations (sampling) in Ridders' method.
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int max_num_ridders_extrapolations;
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// Convergence criterion on extrapolation error for Ridders adaptive
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// differentiation. The available error estimation methods are defined in
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// NumericDiffErrorType and set in the "ridders_error_method" field.
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double ridders_epsilon;
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// The factor in which to shrink the step size with each extrapolation in
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// Ridders' method.
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double ridders_step_shrink_factor;
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};
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} // namespace ceres
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#endif // CERES_PUBLIC_NUMERIC_DIFF_OPTIONS_H_
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