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 com.mathworks.toolbox.javabuilder.MWException;
  //import com.mathworks.toolbox.javabuilder.MWLogicalArray;
  
  import edu.cmu.tetrad.data.DataSet;
  import edu.cmu.tetrad.data.ICovarianceMatrix;
  import edu.cmu.tetrad.graph.Node;
  import edu.cmu.tetrad.util.NumberFormatUtil;
  import edu.cmu.tetrad.util.TetradLogger;
  import edu.cmu.tetrad.util.TetradMatrix;
  
  import java.text.NumberFormat;
  import java.util.*;
  
  //import kci.Kci;
  //import kci.*;
  //import com.mathworks.toolbox.javabuilder.*;
  
  /**
   * Checks conditional independence of variable in a continuous data set using a conditional correlation test
   * for the nonlinear nonGaussian case.
   *
   * @author Joseph Ramsey
   * @deprecated
   */
  public final class IndTestKciMatlab implements IndependenceTest {
  
      private final double[][] _data;
      /**
       * The variables of the covariance data, in order. (Unmodifiable list.)
       */
      private List<Node> variables;
  
      /**
       * The significance level of the independence tests.
       */
      private double alpha;
  
      /**
       * Formats as 0.0000.
       */
      private static NumberFormat nf = NumberFormatUtil.getInstance().getNumberFormat();
  
      /**
       * Stores a reference to the dataset being analyzed.
       */
      private DataSet dataSet;
      private TetradMatrix data;
      private Map<Node, Integer> nodeMap;
      private int numTests;
      private boolean verbose = false;
  
      //==========================CONSTRUCTORS=============================//
  
      /**
       * Constructs a new Independence test which checks independence facts based on the correlation data implied by the
       * given data set (must be continuous). The given significance level is used.
       *
       * @param dataSet A data set containing only continuous columns.
       * @param alpha   The alpha level of the test.
       */
      public IndTestKciMatlab(DataSet dataSet, double alpha) {
          if (!(dataSet.isContinuous())) {
              throw new IllegalArgumentException("Data set must be continuous.");
          }
  
          List<Node> nodes = dataSet.getVariables();
  
          this.variables = Collections.unmodifiableList(nodes);
          setAlpha(alpha);
  
          this.dataSet = dataSet;
          data = this.dataSet.getDoubleData();
  
  //        _data = data.transpose().toArray();
          _data = data.toArray();
  
          nodeMap = new HashMap<>();
  
          for (int i = 0; i < nodes.size(); i++) {
              nodeMap.put(nodes.get(i), i);
          }
  
          numTests = 0;
      }
  
      //==========================PUBLIC METHODS=============================//
  
      /**
       * Creates a new IndTestCramerT instance for a subset of the variables.
       */
      public IndependenceTest indTestSubset(List<Node> vars) {
          throw new UnsupportedOperationException();
      }
  
      public boolean isIndependent(Node x, Node y, List<Node> z) {
          boolean independent = checkIndependent(x, y, z);
  
          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()));
              }
          }
  
          if (verbose) {
              SearchLogUtils.independenceFactMsg(x, y, z, getPValue());
          }
  
          return independent;
      }
  
      public boolean isIndependent(Node x, Node y, Node... z) {
          return isIndependent(x, y, Arrays.asList(z));
      }
  
      public boolean isDependent(Node x, Node y, List<Node> z) {
          boolean independent = checkIndependent(x, y, z);
  
          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;
      }
  
      public boolean isDependent(Node x, Node y, Node... z) {
          List<Node> zList = Arrays.asList(z);
          return isDependent(x, y, zList);
      }
  
      /**
       * @return the probability associated with the most recently computed independence test.
       */
      public double getPValue() {
          return 0.0;
      }
  
      /**
       * Sets the significance level at which independence judgments should be made.  Affects the cutoff for partial
       * correlations to be considered statistically equal to zero.
       */
      public void setAlpha(double alpha) {
          if (alpha < 0.0 || alpha > 1.0) {
              throw new IllegalArgumentException("Significance out of range.");
          }
  
          this.alpha = alpha;
      }
  
      /**
       * Gets the getModel significance level.
       */
      public double getAlpha() {
          return this.alpha;
      }
  
      /**
       * @return the list of variables 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 this.variables;
      }
  
      /**
       * @return the variable with the given name.
       */
      public Node getVariable(String name) {
          for (Node node : variables) {
              if (node.getName().equals(name)) {
                  return node;
              }
          }
  
          throw new IllegalArgumentException("Node a node in this test.");
      }
  
      /**
       * @return the list of variable varNames.
       */
      public List<String> getVariableNames() {
          List<Node> variables = getVariables();
          List<String> variableNames = new ArrayList<>();
          for (Node variable1 : variables) {
              variableNames.add(variable1.getName());
          }
          return variableNames;
      }
  
      /**
       * If <code>isDeterminismAllowed()</code>, deters to IndTestFisherZD; otherwise throws
       * UnsupportedOperationException.
       */
      public boolean determines(List<Node> z, Node x) throws UnsupportedOperationException {
          throw new UnsupportedOperationException();
      }
  
      /**
       * @return the data set being analyzed.
       */
      public DataSet getData() {
          return dataSet;
      }
  
      @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();
      }
  
      /**
       * @return a string representation of this test.
       */
      public String toString() {
          return "Conditional Correlation, alpha = " + nf.format(getAlpha());
      }
  
      //==================================PRIVATE METHODS================================
  
      private boolean checkIndependent(Node x, Node y, List<Node> z) {
  //        numTests++;
  //
  //        int xIndex = dataSet.getColumn(x) + 1;
  //        int yIndex = dataSet.getColumn(y) + 1;
  //
  //        int[] zIndices = new int[z.size()];
  //
  //        for (int i = 0; i < z.size(); i++) {
  //            zIndices[i] = dataSet.getColumn(z.get(i)) + 1;
  //        }
  //
  //        try {
  //            Kci _kci = new Kci();
  //            Object[] output = _kci.indtest(1, xIndex, yIndex, zIndices, _data);
  //
  //            MWLogicalArray arr = (MWLogicalArray) output[0];
  //            boolean out = arr.getBoolean(1);
  //
  //            return out;
  //        } catch (MWException e) {
  //            e.printStackTrace();
  //        }
  //
  //        throw new IllegalStateException();
          return true;
      }
  
      public int getNumTests() {
          return numTests;
      }
  
      public boolean isVerbose() {
          return verbose;
      }
  
      public void setVerbose(boolean verbose) {
          this.verbose = verbose;
      }
  }
  
  
  
  
  