code: ///////////////////////////////////////////////////////////////////////////////
  // For information as to what this class does, see the Javadoc, below.       //
  // Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006,       //
  // 2007, 2008, 2009, 2010, 2014, 2015 by Peter Spirtes, Richard Scheines, Joseph   //
  // Ramsey, and Clark Glymour.                                                //
  //                                                                           //
  // 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., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA //
  ///////////////////////////////////////////////////////////////////////////////
  
  package edu.cmu.tetrad.search;
  
  import edu.cmu.tetrad.data.DataSet;
  import edu.cmu.tetrad.graph.Node;
  
  import java.util.List;
  
  /**
   * Implements a mixed variable polynomial BIC score for fGES.
   *
   * @author Bryan Andrews
   */
  public class MNLRScore implements Score {
  
      private DataSet dataSet;
  
      // The variables of the continuousData set.
      private List<Node> variables;
  
      // Likelihood function
      private MNLRLikelihood likelihood;
  
      // Log number of instances
      private double logn;
  
      public MNLRScore(DataSet dataSet, double structurePrior, int fDegree) {
  
              if (dataSet == null) {
              throw new NullPointerException();
          }
  
          this.dataSet = dataSet;
          this.variables = dataSet.getVariables();
          this.likelihood = new MNLRLikelihood(dataSet, structurePrior, fDegree);
          this.logn = Math.log(dataSet.getNumRows());
      }
  
      public double localScore(int i, int... parents) {
  
          double lik = likelihood.getLik(i, parents);
          double dof = likelihood.getDoF(i, parents);
          double sp = likelihood.getStructurePrior(parents.length);
  
          return 2.0 * lik - dof * logn + sp;
      }
  
      public double localScoreDiff(int x, int y, int[] z) {
          return localScore(y, append(z, x)) - localScore(y, z);
      }
  
      @Override
      public double localScoreDiff(int x, int y) {
          return localScore(y, x) - localScore(y);
      }
  
      private int[] append(int[] parents, int extra) {
          int[] all = new int[parents.length + 1];
          System.arraycopy(parents, 0, all, 0, parents.length);
          all[parents.length] = extra;
          return all;
      }
  
      /**
       * Specialized scoring method for a single parent. Used to speed up the effect edges search.
       */
      public double localScore(int i, int parent) {
          return localScore(i, new int[]{parent});
      }
  
      /**
       * Specialized scoring method for no parents. Used to speed up the effect edges search.
       */
      public double localScore(int i) {
          return localScore(i, new int[0]);
      }
  
      public int getSampleSize() {
          return dataSet.getNumRows();
      }
  
      @Override
      public boolean isEffectEdge(double bump) {
          return bump > 0;
      }
  
      @Override
      public List<Node> getVariables() {
          return variables;
      }
  
      @Override
      public Node getVariable(String targetName) {
  
          for (Node node : variables) {
              if (node.getName().equals(targetName)) {
                  return node;
              }
          }
  
          return null;
      }
  
      @Override
      public int getMaxDegree() {
          return (int) Math.ceil(Math.log(dataSet.getNumRows()));
      }
  
      @Override
      public boolean determines(List<Node> z, Node y) {
          return false;
      }
  
  }
  
  
  
  