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