code: package edu.cmu.tetrad.algcomparison.simulation;
  
  import edu.cmu.tetrad.algcomparison.graph.RandomGraph;
  import edu.cmu.tetrad.data.DataModel;
  import edu.cmu.tetrad.util.Parameters;
  import edu.cmu.tetrad.data.DataSet;
  import edu.cmu.tetrad.data.DataType;
  import edu.cmu.tetrad.data.Discretizer;
  import edu.cmu.tetrad.graph.Graph;
  import edu.cmu.tetrad.graph.Node;
  import edu.cmu.tetrad.sem.SemIm;
  import edu.cmu.tetrad.sem.SemPm;
  
  import java.util.ArrayList;
  import java.util.Collections;
  import java.util.List;
  
  /**
   * @author jdramsey
   */
  public class SemThenDiscretize implements Simulation {
      static final long serialVersionUID = 23L;
      private final RandomGraph randomGraph;
      private List<Graph> graphs = new ArrayList<>();
      private List<DataSet> dataSets = new ArrayList<>();
      private DataType dataType;
      private List<Node> shuffledOrder;
  
      public SemThenDiscretize(RandomGraph randomGraph) {
          this.randomGraph = randomGraph;
          this.dataType = DataType.Mixed;
      }
  
      public SemThenDiscretize(RandomGraph randomGraph, DataType dataType) {
          this.randomGraph = randomGraph;
          this.dataType = dataType;
      }
  
      @Override
      public void createData(Parameters parameters) {
          double percentDiscrete = parameters.getDouble("percentDiscrete");
  
          boolean discrete = parameters.getString("dataType").equals("discrete");
          boolean continuous = parameters.getString("dataType").equals("continuous");
  
          if (discrete && percentDiscrete != 100.0) {
              throw new IllegalArgumentException("To simulate discrete data, 'percentDiscrete' must be set to 0.0.");
          } else if (continuous && percentDiscrete != 0.0) {
              throw new IllegalArgumentException("To simulate continuoue data, 'percentDiscrete' must be set to 100.0.");
          }
  
          if (discrete) this.dataType = DataType.Discrete;
          if (continuous) this.dataType = DataType.Continuous;
  
          dataSets = new ArrayList<>();
          shuffledOrder = null;
  
          Graph graph = randomGraph.createGraph(parameters);
  
          dataSets = new ArrayList<>();
          graphs = new ArrayList<>();
  
          for (int i = 0; i < parameters.getInt("numRuns"); i++) {
              System.out.println("Simulating dataset #" + (i + 1));
  
              if (parameters.getBoolean("differentGraphs") && i > 0) {
                  graph = randomGraph.createGraph(parameters);
              }
  
              graphs.add(graph);
  
              DataSet dataSet = simulate(graph, parameters);
              dataSet.setName("" + (i + 1));
              dataSets.add(dataSet);
          }
      }
  
      @Override
      public Graph getTrueGraph(int index) {
          return graphs.get(index);
      }
  
      @Override
      public String getDescription() {
          return "Simulation SEM data then discretizing some variables, using " +
                  randomGraph.getDescription();
      }
  
      @Override
      public List<String> getParameters() {
          List<String> parameters = randomGraph.getParameters();
          parameters.add("numCategories");
          parameters.add("percentDiscrete");
          parameters.add("numRuns");
          parameters.add("differentGraphs");
          parameters.add("sampleSize");
          return parameters;
      }
  
      @Override
      public int getNumDataModels() {
          return dataSets.size();
      }
  
      @Override
      public DataModel getDataModel(int index) {
          return dataSets.get(index);
      }
  
      @Override
      public DataType getDataType() {
          return dataType;
      }
  
      private DataSet simulate(Graph graph, Parameters parameters) {
          SemPm pm = new SemPm(graph);
          SemIm im = new SemIm(pm);
          DataSet continuousData = im.simulateData(parameters.getInt("sampleSize"), false);
  
          if (this.shuffledOrder == null) {
              List<Node> shuffledNodes = new ArrayList<>(continuousData.getVariables());
              Collections.shuffle(shuffledNodes);
              this.shuffledOrder = shuffledNodes;
          }
  
          Discretizer discretizer = new Discretizer(continuousData);
  
          for (int i = 0; i < shuffledOrder.size() * parameters.getDouble("percentDiscrete") * 0.01; i++) {
              discretizer.equalIntervals(continuousData.getVariable(shuffledOrder.get(i).getName()),
                      parameters.getInt("numCategories"));
          }
  
          return discretizer.discretize();
      }
  }
  