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.                                       //
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  // 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.                              //
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  // 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.pitt.csb.mgm;
  
  import cern.colt.matrix.DoubleMatrix2D;
  import edu.cmu.tetrad.data.DataSet;
  import edu.cmu.tetrad.graph.Graph;
  import edu.cmu.tetrad.graph.GraphUtils;
  
  import java.io.File;
  import java.io.IOException;
  
  /**
   * Created by ajsedgewick on 8/18/15.
   */
  public class ExampleMixedSearch {
      public static void main(String[] args){
          try {
              String path = args[0];
              //String path = ExampleMixedSearch.class.getResource("test_data").getPath();
              //DoubleMatrix2D xIn = DoubleFactory2D.dense.make(MixedUtils.loadDataSelect(path, "med_test_C.txt"));
              //DoubleMatrix2D yIn = DoubleFactory2D.dense.make(MixedUtils.loadDataSelect(path, "med_test_D.txt"));
              Graph trueGraph = GraphUtils.loadGraphTxt(new File(path, "DAG_0_graph.txt"));
              DataSet data = MixedUtils.loadDataSet(path, "DAG_0_data.txt");
  
              //lambda is a sparsity parameter, higher values result in sparser graphs
              //separate lambda entries for continuous-continuous, continuous-discrete and discrete-discrete edges
              //respectively, generally lower lambdas for edges with discrete variables
              double[] lambda = {.2, .2, .2};
              double tolerance = 1e-7; //convergeance tolerance
              int iterLimit = 1000; //iteration limit
  
              MGM model = new MGM(data, lambda);
              model.learn(tolerance,iterLimit);
              Graph mgmGraph = model.graphFromMGM();
  
              //Graph class can't deal with edge weights, so we put them in a matrix
              DoubleMatrix2D adjMat = model.adjMatFromMGM();
  
              System.out.println("True Graph");
              System.out.println(trueGraph);
  
              System.out.println("MGM Graph");
              System.out.println(mgmGraph);
  
              System.out.println("AdjMat");
              System.out.println(adjMat.toString());
  
              System.out.println(MixedUtils.EdgeStatHeader);
              System.out.println(MixedUtils.stringFrom2dArray(MixedUtils.allEdgeStats(trueGraph, mgmGraph)));
  
  
          } catch (IOException e){
              e.printStackTrace();
          }
      }
  }
  
  