// Ceres Solver - A fast non-linear least squares minimizer // Copyright 2015 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_ namespace ceres { // Options pertaining to numeric differentiation (e.g., convergence criteria, // step sizes). struct CERES_EXPORT NumericDiffOptions { NumericDiffOptions() { relative_step_size = 1e-6; ridders_relative_initial_step_size = 1e-2; max_num_ridders_extrapolations = 10; ridders_epsilon = 1e-12; ridders_step_shrink_factor = 2.0; } // 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; // 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; // Maximal number of adaptive extrapolations (sampling) in Ridders' method. int max_num_ridders_extrapolations; // 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; // The factor in which to shrink the step size with each extrapolation in // Ridders' method. double ridders_step_shrink_factor; }; } // namespace ceres #endif // CERES_PUBLIC_NUMERIC_DIFF_OPTIONS_H_