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.DataModel;
  import edu.cmu.tetrad.data.DataSet;
  import edu.cmu.tetrad.data.ICovarianceMatrix;
  import edu.cmu.tetrad.data.IndependenceFacts;
  import edu.cmu.tetrad.graph.Node;
  import edu.cmu.tetrad.util.TetradLogger;
  import edu.cmu.tetrad.util.TetradMatrix;
  
  import java.util.ArrayList;
  import java.util.List;
  
  /**
   * Checks conditional independence against a list of conditional independence facts, manually entered.
   *
   * @author Joseph Ramsey
   * @see edu.cmu.tetrad.search.ChiSquareTest
   */
  public final class IndTestIndependenceFacts implements IndependenceTest {
  
      private IndependenceFacts facts;
      private boolean verbose = false;
  
      public IndTestIndependenceFacts(IndependenceFacts facts) {
          this.facts = facts;
  
  //        System.out.println("Independence Facts for test: ");
  //        System.out.println(facts);
      }
  
  
      public IndependenceTest indTestSubset(List<Node> vars) {
          throw new UnsupportedOperationException();
      }
  
      public boolean isIndependent(Node x, Node y, List<Node> z) {
          Node[] _z = new Node[z.size()];
  
          for (int i = 0; i < z.size(); i++) {
              _z[i] = z.get(i);
          }
  
          boolean independent = facts.isIndependent(x, y, _z);
  
          if (verbose) {
              if (independent) {
                  TetradLogger.getInstance().log("independencies",
                          SearchLogUtils.independenceFactMsg(x, y, z, Double.NaN));
  //            System.out.println(SearchLogUtils.independenceFactMsg(x, y, z, Double.NaN));
              } else {
                  TetradLogger.getInstance().log("dependencies",
                          SearchLogUtils.dependenceFactMsg(x, y, z, Double.NaN));
  //            System.out.println(SearchLogUtils.dependenceFactMsg(x, y, z, Double.NaN));
              }
          }
  
          return independent;
      }
  
      public boolean isIndependent(Node x, Node y, Node... z) {
          List<Node> zz = new ArrayList<>();
  
          for (Node node : z) {
              zz.add(node);
          }
  
          return isIndependent(x, y, zz);
      }
  
      public boolean isDependent(Node x, Node y, List<Node> z) {
          return !isIndependent(x, y, z);
      }
  
      public boolean isDependent(Node x, Node y, Node... z) {
          return !isIndependent(x, y, z);
      }
  
      public double getPValue() {
          return Double.NaN;
      }
  
      public List<Node> getVariables() {
          return facts.getVariables();
      }
  
      public Node getVariable(String name) {
          if (name == null) throw new NullPointerException();
  
          List<Node> variables = facts.getVariables();
  
          for (Node node : variables) {
              if (name.equals(node.getName())) {
                  return node;
              }
          }
  
          return null;
      }
  
      public List<String> getVariableNames() {
          return facts.getVariableNames();
      }
  
      public boolean determines(List<Node> z, Node y) {
          return false;
      }
  
      public double getAlpha() {
          return Double.NaN;
      }
  
      public void setAlpha(double alpha) {
          throw new UnsupportedOperationException();
      }
  
      public DataModel getData() {
          return facts;
      }
  
      @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;
      }
  }
  
  
  
  
  
  