mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 08:34:37 +08:00
Keir Mierle
94 lines
3.0 KiB
C++
94 lines
3.0 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
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// http://code.google.com/p/ceres-solver/
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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: sameeragarwal@google.com (Sameer Agarwal)
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//
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// Purpose: See .h file.
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#include "ceres/loss_function.h"
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#include <cmath>
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#include <cstddef>
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namespace ceres {
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void TrivialLoss::Evaluate(double s, double rho[3]) const {
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rho[0] = s;
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rho[1] = 1;
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rho[2] = 0;
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}
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void HuberLoss::Evaluate(double s, double rho[3]) const {
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if (s > b_) {
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// Outlier region.
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// 'r' is always positive.
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const double r = sqrt(s);
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rho[0] = 2 * a_ * r - b_;
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rho[1] = a_ / r;
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rho[2] = - rho[1] / (2 * s);
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} else {
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// Inlier region.
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rho[0] = s;
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rho[1] = 1;
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rho[2] = 0;
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}
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}
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void SoftLOneLoss::Evaluate(double s, double rho[3]) const {
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const double sum = 1 + s * c_;
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const double tmp = sqrt(sum);
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// 'sum' and 'tmp' are always positive, assuming that 's' is.
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rho[0] = 2 * b_ * (tmp - 1);
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rho[1] = 1 / tmp;
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rho[2] = - (c_ * rho[1]) / (2 * sum);
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}
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void CauchyLoss::Evaluate(double s, double rho[3]) const {
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const double sum = 1 + s * c_;
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const double inv = 1 / sum;
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// 'sum' and 'inv' are always positive, assuming that 's' is.
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rho[0] = b_ * log(sum);
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rho[1] = inv;
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rho[2] = - c_ * (inv * inv);
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}
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void ScaledLoss::Evaluate(double s, double rho[3]) const {
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if (rho_.get() == NULL) {
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rho[0] = a_ * s;
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rho[1] = a_;
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rho[2] = 0.0;
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} else {
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rho_->Evaluate(s, rho);
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rho[0] *= a_;
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rho[1] *= a_;
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rho[2] *= a_;
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}
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}
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} // namespace ceres
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