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.bayes;
  
  import edu.cmu.tetrad.graph.Node;
  import edu.cmu.tetrad.util.TetradSerializable;
  
  import java.io.IOException;
  import java.io.ObjectInputStream;
  import java.util.*;
  
  /**
   * Calculates marginals of the form P(V=v') for an updated Bayes net for
   * purposes of the CPT Invariant Updater.
   *
   * @author Joseph Ramsey
   */
  public final class CptInvariantMarginalCalculator
          implements TetradSerializable {
      static final long serialVersionUID = 23L;
  
      /**
       * @serial Cannot be null.
       */
      private BayesIm bayesIm;
  
      /**
       * @serial Cannot be null.
       */
      private double[][] storedMarginals;
  
      /**
       * @serial Cannot be null.
       */
      private Evidence evidence;
  
      /**
       * @serial Cannot be null.
       */
      private UpdatedBayesIm updatedBayesIm;
  
      //=============================CONSTRUCTORS==========================//
  
      /**
       * Constructs a new marginal calculator for the given updated Bayes IM. It
       * is assumed that the first BayesIm encountered on calling the
       * getParentIm() method recursively is the Bayes IM with respect to which
       * conjunctions of the form P(V1=v1' & V2=v2' & ... & Vn=vn') should be
       * calculated.
       */
      public CptInvariantMarginalCalculator(BayesIm bayesIm, Evidence evidence) {
          if (bayesIm == null) {
              throw new NullPointerException();
          }
  
          if (evidence == null) {
              throw new NullPointerException();
          }
  
          if (evidence.isIncompatibleWith(bayesIm)) {
              throw new IllegalArgumentException("The variables for the given " +
                      "Bayes IM and evidence must be compatible.");
          }
  
          this.bayesIm = bayesIm;
          this.evidence = evidence;
          this.updatedBayesIm = new UpdatedBayesIm(bayesIm, evidence);
          this.storedMarginals = initStoredMarginals();
      }
  
      /**
       * Generates a simple exemplar of this class to test serialization.
       */
      public static CptInvariantMarginalCalculator serializableInstance() {
          MlBayesIm bayesIm = MlBayesIm.serializableInstance();
          Evidence evidence = Evidence.tautology(bayesIm);
          return new CptInvariantMarginalCalculator(bayesIm, evidence);
      }
  
      //=============================PUBLIC METHODS========================//
  
      /**
       * @return P&lpar;variable &equals; category&rpar;.
       */
      public double getMarginal(int variable, int category) {
          if (this.storedMarginals[variable][category] != -99.0) {
              return this.storedMarginals[variable][category];
          }
  
          double marginal = 0.0;
          boolean foundANumber = false;
  
          for (int row = 0; row < bayesIm.getNumRows(variable); row++) {
              double probability =
                      updatedBayesIm.getProbability(variable, row, category);
  
              if (Double.isNaN(probability)) {
                  continue;
              }
  
              double probabilityOfRow = getProbabilityOfRow(variable, row);
  
              if (Double.isNaN(probabilityOfRow)) {
                  continue;
              }
  
              marginal += probability * probabilityOfRow;
              foundANumber = true;
          }
  
          if (!foundANumber) {
              marginal = Double.NaN;
          }
  
          this.storedMarginals[variable][category] = marginal;
          return marginal;
      }
  
      public UpdatedBayesIm getUpdatedBayesIm() {
          return this.updatedBayesIm;
      }
  
      private double[][] initStoredMarginals() {
          this.storedMarginals = new double[this.bayesIm.getNumNodes()][];
  
          for (int i = 0; i < this.bayesIm.getNumNodes(); i++) {
              this.storedMarginals[i] = new double[this.bayesIm.getNumColumns(i)];
              Arrays.fill(this.storedMarginals[i], -99.0);
          }
          return storedMarginals;
      }
  
  
      private double getProbabilityOfRow(int variable, final int row) {
          int[] parents = bayesIm.getParents(variable);
          int[] parentValues = bayesIm.getParentValues(variable, row);
  
          double probabilityOfRow = 1.0;
  
          for (int index = 0; index < parents.length; index++) {
  
              if (noModifiedCpts(parents, index)) {
                  double marginal =
                          getMarginal(parents[index], parentValues[index]);
  
                  if (!Double.isNaN(marginal)) {
                      probabilityOfRow *= marginal;
                  }
              } else {
                  Evidence evidence = new Evidence(this.evidence);
                  CptInvariantMarginalCalculator marginals =
                          new CptInvariantMarginalCalculator(bayesIm, evidence);
                  double marginal = marginals.getMarginal(parents[index],
                          parentValues[index]);
  
                  if (!Double.isNaN(marginal)) {
                      probabilityOfRow *= marginal;
                  }
              }
          }
  
          return probabilityOfRow;
      }
  
      /**
       * @return true iff conditioning on parents 0 through i - 1 would change any
       * of the conditional probability tables relevant to calculating P(node i =
       * value i).
       */
      private boolean noModifiedCpts(int[] parents, int i) {
          List<Node> target =
                  Collections.singletonList(bayesIm.getNode(parents[i]));
          List<Node> conditioners = new LinkedList<>();
  
          for (int j = 0; j < i; j++) {
              conditioners.add(bayesIm.getNode(parents[j]));
          }
  
          List<Node> condAncestors = bayesIm.getDag().getAncestors(conditioners);
          List<Node> targetAncestor = bayesIm.getDag().getAncestors(target);
          Set<Node> intersection = new HashSet<>(condAncestors);
          intersection.retainAll(targetAncestor);
  
          return intersection.isEmpty();
      }
  
      /**
       * Adds semantic checks to the default deserialization method. This method
       * must have the standard signature for a readObject method, and the body of
       * the method must begin with "s.defaultReadObject();". Other than that, any
       * semantic checks can be specified and do not need to stay the same from
       * version to version. A readObject method of this form may be added to any
       * class, even if Tetrad sessions were previously saved out using a version
       * of the class that didn't include it. (That's what the
       * "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.
       *
       * @throws java.io.IOException
       * @throws ClassNotFoundException
       */
      private void readObject(ObjectInputStream s)
              throws IOException, ClassNotFoundException {
          s.defaultReadObject();
  
          if (bayesIm == null) {
              throw new NullPointerException();
          }
  
          if (evidence == null) {
              throw new NullPointerException();
          }
  
          if (storedMarginals == null) {
              throw new NullPointerException();
          }
  
          if (updatedBayesIm == null) {
              throw new NullPointerException();
          }
      }
  }
  
  
  
  
  
  