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.study;
  
  import edu.cmu.tetrad.algcomparison.Comparison;
  import edu.cmu.tetrad.algcomparison.algorithm.Algorithm;
  import edu.cmu.tetrad.algcomparison.algorithm.Algorithms;
  import edu.cmu.tetrad.algcomparison.algorithm.FirstInflection;
  import edu.cmu.tetrad.algcomparison.algorithm.oracle.pattern.Fges;
  import edu.cmu.tetrad.algcomparison.graph.RandomForward;
  import edu.cmu.tetrad.algcomparison.score.SemBicScore;
  import edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel;
  import edu.cmu.tetrad.algcomparison.simulation.Simulations;
  import edu.cmu.tetrad.algcomparison.statistic.*;
  import edu.cmu.tetrad.util.Parameters;
  
  /**
   * An example script to simulate data and run a comparison analysis on it.
   *
   * @author jdramsey
   */
  public class ExampleFirstInflection {
      public static void main(String... args) {
          Parameters parameters = new Parameters();
  
          parameters.set("numMeasures", 40, 100);
          parameters.set("avgDegree", 2);
          parameters.set("sampleSize", 400, 800);
          parameters.set("numRuns", 10);
  
          parameters.set("differentGraphs", true);
          parameters.set("numLatents", 0);
          parameters.set("maxDegree", 100);
          parameters.set("maxIndegree", 100);
          parameters.set("maxOutdegree", 100);
          parameters.set("connected", false);
  
          parameters.set("coefLow", 0.2);
          parameters.set("coefHigh", 0.9);
          parameters.set("varLow", 1);
          parameters.set("varHigh", 3);
          parameters.set("verbose", false);
          parameters.set("coefSymmetric", true);
          parameters.set("percentDiscrete", 0);
          parameters.set("numCategories", 3);
          parameters.set("differentGraphs", true);
          parameters.set("intervalBetweenShocks", 10);
          parameters.set("intervalBetweenRecordings", 10);
          parameters.set("fisherEpsilon", 0.001);
          parameters.set("randomizeColumns", true);
  
          parameters.set("alpha", 1e-8);
          parameters.set("depth", -1);
          parameters.set("penaltyDiscount", 4);
  
          parameters.set("useMaxPOrientationHeuristic", false);
          parameters.set("maxPOrientationMaxPathLength", 3);
          parameters.set("verbose", false);
  
          parameters.set("scaleFreeAlpha", 0.00001);
          parameters.set("scaleFreeBeta", 0.4);
          parameters.set("scaleFreeDeltaIn", .1);
          parameters.set("scaleFreeDeltaOut", 3);
  
          parameters.set("symmetricFirstStep", false);
          parameters.set("faithfulnessAssumed", true);
          parameters.set("maxDegree", 100);
  
  //        parameters.set("logScale", true);
  
          Statistics statistics = new Statistics();
  
          statistics.add(new ParameterColumn("numMeasures"));
          statistics.add(new ParameterColumn("avgDegree"));
          statistics.add(new ParameterColumn("sampleSize"));
  
          statistics.add(new AdjacencyPrecision());
          statistics.add(new AdjacencyRecall());
          statistics.add(new ArrowheadPrecision());
          statistics.add(new ArrowheadRecall());
          statistics.add(new ElapsedTime());
  
          statistics.setWeight("AP", 0.25);
          statistics.setWeight("AR", 0.25);
          statistics.setWeight("AHP", 0.25);
          statistics.setWeight("AHR", 0.25);
  
          Algorithms algorithms = new Algorithms();
  
          Algorithm fges = new Fges(new SemBicScore());
  //        algorithms.add(new FirstInflection(fges, "alpha", -7, -2, -.5));
          algorithms.add(new FirstInflection(fges, "penaltyDiscount", 0.7, 5, 1));
  
          Simulations simulations = new Simulations();
  
          simulations.add(new LinearFisherModel(new RandomForward()));
  
          Comparison comparison = new Comparison();
  
          comparison.setShowAlgorithmIndices(true);
          comparison.setShowSimulationIndices(true);
          comparison.setSortByUtility(false);
          comparison.setShowUtilities(false);
          comparison.setParallelized(true);
          comparison.setComparisonGraph(Comparison.ComparisonGraph.Pattern_of_the_true_DAG);
  
          comparison.compareFromSimulations("first.inflection", simulations, algorithms, statistics, parameters);
      }
  }
  
  
  
  
  