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.data.ICovarianceMatrix;
  import edu.cmu.tetrad.graph.Node;
  import edu.cmu.tetrad.graph.NodeType;
  import edu.cmu.tetrad.util.TetradLogger;
  import edu.cmu.tetrad.util.TetradMatrix;
  
  import java.util.*;
  
  
  /**
   * Checks independence facts for variables associated associated with a sepset by simply querying the sepset
   *
   * @author Robert Tillman
   */
  public class IndTestSepset implements IndependenceTest {
  
      /**
       * The sepset being queried
       */
      private SepsetMapDci sepset;
  
      /**
       * The map from nodes to variables.
       */
      private Map<Node, Node> nodesToVariables;
  
      /**
       * The map from variables to nodes.
       */
      private Map<Node, Node> variablesToNodes;
  
      /**
       * The list of observed variables (i.e. variables for observed nodes).
       */
      private List<Node> observedVars;
      private boolean verbose = false;
  
      /**
       * Constructs a new independence test that returns d-separation facts for the given graph as independence results.
       */
      public IndTestSepset(SepsetMapDci sepset, List<Node> nodes) {
          if (sepset == null) {
              throw new NullPointerException();
          }
  
          this.sepset = sepset;
          this.nodesToVariables = new HashMap<>();
          this.variablesToNodes = new HashMap<>();
  
          for (Node node : nodes) {
              this.nodesToVariables.put(node, node);
              this.variablesToNodes.put(node, node);
          }
  
          this.observedVars = calcObservedVars(nodes);
      }
  
      /**
       * Required by IndependenceTest.
       */
      public IndependenceTest indTestSubset(List<Node> vars) {
          if (vars.isEmpty()) {
              throw new IllegalArgumentException("Subset may not be empty.");
          }
  
          for (Node var : vars) {
              if (!getVariables().contains(var)) {
                  throw new IllegalArgumentException(
                          "All vars must be original vars");
              }
          }
  
          return this;
      }
  
      /**
       * @return the list of observed nodes in the given graph.
       */
      private List<Node> calcObservedVars(List<Node> nodes) {
          List<Node> observedVars = new ArrayList<>();
  
          for (Node node : nodes) {
              if (node.getNodeType() == NodeType.MEASURED) {
                  observedVars.add(getVariable(node));
              }
          }
  
          return observedVars;
      }
  
      /**
       * Checks the indicated independence fact.
       *
       * @param x one node.
       * @param y a second node.
       * @param z a List of nodes (conditioning variables)
       * @return true iff x _||_ y | z
       */
      public boolean isIndependent(Node x, Node y, List<Node> z) {
          if (z == null) {
              throw new NullPointerException();
          }
  
          for (Node node : z) {
              if (node == null) {
                  throw new NullPointerException();
              }
          }
  
          boolean independent = false;
  
          if (sepset.get(x, y) != null) {
              List<List<Node>> condSets = sepset.getSet(x, y);
              for (List<Node> condSet : condSets) {
                  if (condSet.size() == z.size() && condSet.containsAll(z)) {
                      double pValue = 1.0;
  
                      if (verbose) {
                          TetradLogger.getInstance().log("independencies", SearchLogUtils.independenceFactMsg(x, y, z, pValue));
                      }
                      independent = true;
                      break;
  //                    return true;
                  }
              }
          }
  
          if (verbose) {
              if (independent) {
                  TetradLogger.getInstance().log("independencies", SearchLogUtils.independenceFactMsg(x, y, z, getPValue()));
              } else {
                  TetradLogger.getInstance().log("dependencies", SearchLogUtils.dependenceFactMsg(x, y, z, getPValue()));
              }
          }
  
          return independent;
  
  //        return false;
      }
  
      public boolean isIndependent(Node x, Node y, Node... z) {
          List<Node> zList = Arrays.asList(z);
          return isIndependent(x, y, zList);
      }
  
      public boolean isDependent(Node x, Node y, List<Node> z) {
          return !isIndependent(x, y, z);
      }
  
      public boolean isDependent(Node x, Node y, Node... z) {
          List<Node> zList = Arrays.asList(z);
          return isDependent(x, y, zList);
      }
  
      /**
       * Needed for IndependenceTest interface. P value is not meaningful here.
       */
      public double getPValue() {
          return Double.NaN;
      }
  
      /**
       * @return the list of TetradNodes over which this independence checker is capable of determinine independence
       * relations-- that is, all the variables in the given graph or the given data set.
       */
      public List<Node> getVariables() {
          return Collections.unmodifiableList(observedVars);
      }
  
      /**
       * @return the list of variable varNames.
       */
      public List<String> getVariableNames() {
          List<Node> nodes = getVariables();
          List<String> nodeNames = new ArrayList<>();
          for (Node var : nodes) {
              nodeNames.add(var.getName());
          }
          return nodeNames;
      }
  
      public boolean determines(List z, Node x1) {
          return z.contains(x1);
      }
  
      public double getAlpha() {
          throw new UnsupportedOperationException();
      }
  
      public void setAlpha(double alpha) {
          throw new UnsupportedOperationException();
      }
  
      public Node getVariable(String name) {
          for (int i = 0; i < getVariables().size(); i++) {
              Node variable = getVariables().get(i);
  
              if (variable.getName().equals(name)) {
                  return variable;
              }
          }
  
          return null;
      }
  
      /**
       * @return the variable associated with the given node in the graph.
       */
      public Node getVariable(Node node) {
          return nodesToVariables.get(node);
      }
  
      /**
       * @return the node associated with the given variable in the graph.
       */
      public Node getNode(Node variable) {
          return variablesToNodes.get(variable);
      }
  
      public String toString() {
          return "D-separation";
      }
  
      public DataSet getData() {
          return null;  //To change body of implemented methods use File | Settings | File Templates.
      }
  
      @Override
      public ICovarianceMatrix getCov() {
          return null;
      }
  
      @Override
      public List<DataSet> getDataSets() {
          return null;
      }
  
      @Override
      public int getSampleSize() {
          return 0;
      }
  
      @Override
      public List<TetradMatrix> getCovMatrices() {
          return null;
      }
  
      @Override
      public double getScore() {
          return getPValue();
      }
  
      public boolean isVerbose() {
          return verbose;
      }
  
      public void setVerbose(boolean verbose) {
          this.verbose = verbose;
      }
  }
  
  
  
  
  
  
  