kld-sampling.hh

/*********************************************************************

  KLD-SAMPLING: Adequately Sampling from an Unknown Distribution.
  
  Copyright (C) 2006 - Patrick Beeson  (pbeeson@cs.utexas.edu)


  This program is free software; you can redistribute it and/or modify
  it under the terms of the GNU General Public License as published by
  the Free Software Foundation; either version 2 of the License, or
  (at your option) any later version.
  
  This program is distributed in the hope that it will be useful, but
  WITHOUT ANY WARRANTY; without even the implied warranty of
  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
  General Public License for more details.
  
  You should have received a copy of the GNU General Public License
  along with this program; if not, write to the Free Software
  Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301
  USA

*********************************************************************/


#ifndef kld_sampling_hh
#define kld_sampling_hh

#include <vector>

using namespace std;


/**
   This class uses KL-Divergence to determine when a distribution has
   been adequately sampled.
**/
class kld_sampling {
  
public:
  kld_sampling();
  void init(float, float, const vector<float>&, int sample_min=absolute_min);
  int update(const vector<float>&);
  
private:
  static const int absolute_min=10;
  float confidence, max_error;
  vector<float> bin_size;

  static vector<float> ztable;
  int num_samples;
  vector< vector <float> > bins;

  vector<float> curr_sample;
  int support_samples, kld_samples;
  float zvalue;

  bool in_empty_bin();
  void build_table();
};

#endif