Sampling/exsample/selectors.icc

0001 // -*- C++ -*-
0002 //
0003 // selectors.icc is part of ExSample -- A Library for Sampling Sudakov-Type Distributions
0004 //
0005 // Copyright (C) 2008-2019 Simon Platzer -- simon.plaetzer@desy.de, The Herwig Collaboration
0006 //
0007 // ExSample is licenced under version 3 of the GPL, see COPYING for details.
0008 // Please respect the MCnet academic guidelines, see GUIDELINES for details.
0009 //
0010 //
0011 namespace exsample {
0012
0013   template<class Random>
0014   std::pair<bool,bool> sampling_selector<Random>::use(cell& parent,
0015                               const cell& first_child,
0016                               const cell& second_child) const {
0017     std::pair<bool,bool> selected (false,false);
0018     if (compensate) {
0019       if (first_child.missing_events() > 0 && second_child.missing_events() <= 0) {
0020     selected.first = true;
0021     --parent.missing_events();
0022     return selected;
0023       }
0024       if (first_child.missing_events() <= 0 && second_child.missing_events() > 0) {
0025     selected.second = true;
0026     --parent.missing_events();
0027     return selected;
0028       }
0029       if (first_child.missing_events() > 0 && second_child.missing_events() > 0) {
0030     if (first_child.integral()/parent.integral() > rnd_gen())
0031       selected.first = true;
0032     else
0033       selected.second = true;
0034     --parent.missing_events();
0035     return selected;
0036       }
0037     }
0038     if (first_child.integral()/parent.integral() > rnd_gen())
0039       selected.first = true;
0040     else
0041       selected.second = true;
0042     return selected;
0043   }
0044
0045   template<class Random>
0046   bool sampling_selector<Random>::use(cell& leaf) const {
0047     if (compensate) {
0048       if (leaf.missing_events() < 0) {
0049     ++leaf.missing_events();
0050     return false;
0051       }
0052       if (leaf.missing_events() > 0)
0053     --leaf.missing_events();
0054     }
0055     return true;
0056   }
0057
0058   inline std::pair<bool,bool> parametric_selector::use(const cell& parent,
0059                                const cell&,
0060                                const cell&) const {
0061     std::pair<bool,bool> match_para (true,true);
0062     if (!sampled_variables_[parent.split_dimension()]) {
0063       match_para.first = (parent.split_point() > (*point_)[parent.split_dimension()]);
0064       match_para.second = (parent.split_point() <= (*point_)[parent.split_dimension()]);
0065     }
0066     return match_para;
0067   }
0068
0069   template<class Random>
0070   std::pair<bool,bool> parametric_sampling_selector<Random>::use(cell& parent,
0071                                  const cell& first_child,
0072                                  const cell& second_child) const {
0073     std::pair<bool,bool> match_para (true,true);
0074     std::pair<bool,bool> selected (false,false);
0075     if (!sampled_variables_[parent.split_dimension()]) {
0076       match_para.first = (parent.split_point() > (*point_)[parent.split_dimension()]);
0077       match_para.second = (parent.split_point() <= (*point_)[parent.split_dimension()]);
0078     }
0079     if (match_para.first && match_para.second) {
0080       if (compensate_) {
0081     if (first_child.missing_events() > 0 && second_child.missing_events() <= 0) {
0082       selected.first = true;
0083       --parent.missing_events();
0084       return selected;
0085     }
0086     if (first_child.missing_events() <= 0 && second_child.missing_events() > 0) {
0087       selected.second = true;
0088       --parent.missing_events();
0089       return selected;
0090     }
0091
0092     if (first_child.missing_events() > 0 && second_child.missing_events() > 0) {
0093       if (first_child.integral()/parent.integral() > rnd_gen_())
0094         selected.first = true;
0095       else
0096         selected.second = true;
0097       --parent.missing_events();
0098       return selected;
0099     }
0100       }
0101       if (first_child.integral()/parent.integral() > rnd_gen_())
0102     selected.first = true;
0103       else
0104     selected.second = true;
0105       return selected;
0106     }
0107     assert(match_para.first || match_para.second);
0108     if (compensate_)
0109       if ((match_para.first && first_child.missing_events() > 0) ||
0110       (match_para.second && second_child.missing_events() > 0))
0111     --parent.missing_events();
0112     return match_para;
0113   }
0114
0115   template<class Random>
0116   bool parametric_sampling_selector<Random>::use (cell& leaf) const {
0117     if (compensate_) {
0118       long pmissing = leaf.info().parametric_missing(*bin_id_);
0119       assert(leaf.missing_events() == pmissing);
0120       if (pmissing < 0) {
0121     leaf.info().increase_parametric_missing(*bin_id_);
0122     ++leaf.missing_events();
0123     return false;
0124       }
0125       if (pmissing > 0) {
0126     leaf.info().decrease_parametric_missing(*bin_id_);
0127     --leaf.missing_events();
0128       }
0129     }
0130     return true;
0131   }
0132
0133 }