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.sem;
  
  import org.apache.commons.math3.distribution.RealDistribution;
  import org.apache.commons.math3.exception.NumberIsTooLargeException;
  import org.apache.commons.math3.exception.OutOfRangeException;
  
  import java.util.Collections;
  import java.util.List;
  
  /**
   * Only the cumulativeProbability, density, setShift methods are implemented.
   */
  public class EmpiricalCdf implements RealDistribution {
      private List<Double> data;
  
      public EmpiricalCdf(List<Double> data) {
          if (data == null) throw new NullPointerException();
          this.data = data;
          Collections.sort(data);
      }
  
      public double cumulativeProbability(double x) {
          int count = 0;
  
          for (double y : data) {
              if (y <= x) {
                  count++;
              } else {
                  break;
              }
          }
  
          return count / (double) data.size();
      }
  
      @Override
      public double probability(double v) {
          return 0;
      }
  
      @Override
      public double density(double v) {
          double d1 = v - 0.05;
          double d2 = v + 0.05;
          double n2 = cumulativeProbability(d1);
          double n1 = cumulativeProbability(d2);
          return (n1 - n2) / (d2 - d1);
      }
  
      @Override
      @Deprecated
      public double cumulativeProbability(double v, double v1) throws NumberIsTooLargeException {
          throw new UnsupportedOperationException();
      }
  
      @Override
      public double inverseCumulativeProbability(double v) throws OutOfRangeException {
          return 0;
      }
  
      @Override
      public double getNumericalMean() {
          return 0;
      }
  
      @Override
      public double getNumericalVariance() {
          return 0;
      }
  
      @Override
      public double getSupportLowerBound() {
          return 0;
      }
  
      @Override
      public double getSupportUpperBound() {
          return 0;
      }
  
      @Override
      @Deprecated
      public boolean isSupportLowerBoundInclusive() {
          throw new UnsupportedOperationException();
      }
  
      @Override
      @Deprecated
      public boolean isSupportUpperBoundInclusive() {
          throw new UnsupportedOperationException();
      }
  
      @Override
      public boolean isSupportConnected() {
          return false;
      }
  
      @Override
      public void reseedRandomGenerator(long l) {
  
      }
  
      @Override
      public double sample() {
          return 0;
      }
  
      @Override
      public double[] sample(int i) {
          return new double[0];
      }
  }
  
  