Line data    Source code

       1             : /* 
       2             :  * File:   HuberLoss.cpp
       3             :  * Author: Pantelis Sopasakis
       4             :  * 
       5             :  * Created on October 30, 2015, 1:57 AM
       6             :  * 
       7             :  * ForBES is free software: you can redistribute it and/or modify
       8             :  * it under the terms of the GNU Lesser General Public License as published by
       9             :  * the Free Software Foundation, either version 3 of the License, or
      10             :  * (at your option) any later version.
      11             :  *  
      12             :  * ForBES is distributed in the hope that it will be useful,
      13             :  * but WITHOUT ANY WARRANTY; without even the implied warranty of
      14             :  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
      15             :  * GNU Lesser General Public License for more details.
      16             :  * 
      17             :  * You should have received a copy of the GNU Lesser General Public License
      18             :  * along with ForBES. If not, see <http://www.gnu.org/licenses/>.
      19             :  */
      20             : 
      21             : #include "HuberLoss.h"
      22             : #include <cmath>
      23             : 
      24           5 : HuberLoss::HuberLoss(double delta) :
      25           5 : Function(), m_delta(delta) {
      26           5 : }
      27             : 
      28           4 : HuberLoss::~HuberLoss() {
      29           4 : }
      30             : 
      31           1 : int HuberLoss::call(Matrix& x, double& f) {
      32             :     //LCOV_EXCL_START
      33             :     if (!x.isColumnVector()) {
      34             :         throw std::invalid_argument("x must be a column-vector");
      35             :     }
      36             :     //LCOV_EXCL_STOP
      37           1 :     f = 0.0;
      38          11 :     for (size_t i = 0; i < x.getNrows(); i++) {
      39             :         double xi;
      40          10 :         xi = x[i];
      41          10 :         if (std::abs(xi) <= m_delta) {
      42           3 :             f += std::pow(xi, 2) / (2.0 * m_delta);
      43             :         } else {
      44           7 :             f += std::abs(xi) - m_delta / 2.0;
      45             :         }
      46             :     }
      47           1 :     return ForBESUtils::STATUS_OK;
      48             : }
      49             : 
      50         355 : int HuberLoss::call(Matrix& x, double& f, Matrix& grad) {
      51             :     //LCOV_EXCL_START
      52             :     if (!x.isColumnVector()) {
      53             :         throw std::invalid_argument("x must be a column-vector");
      54             :     }
      55             :     //LCOV_EXCL_STOP
      56         355 :     f = 0.0;
      57         755 :     for (size_t i = 0; i < x.getNrows(); i++) {
      58             :         double xi;
      59         400 :         xi = x[i];
      60         400 :         if (std::abs(xi) <= m_delta) {
      61         186 :             f += std::pow(xi, 2) / (2.0 * m_delta);
      62         186 :             grad[i] = xi / m_delta;
      63             :         } else {
      64         214 :             f += std::abs(xi) - m_delta / 2.0;
      65         214 :             grad[i] = std::signbit(xi) ? -1.0 : 1.0;
      66             :         }
      67             :     }
      68         355 :     return ForBESUtils::STATUS_OK;
      69             : }
      70             : 
      71           5 : FunctionOntologicalClass HuberLoss::category() {
      72           5 :     FunctionOntologicalClass huberLoss("HuberLoss");
      73           5 :     huberLoss.set_defines_f(true);
      74           5 :     huberLoss.set_defines_grad(true);
      75           5 :     huberLoss.add_superclass(FunctionOntologyRegistry::loss());
      76           5 :     return huberLoss;
      77           9 : }
      78             : 
      79             :