code: package edu.cmu.tetrad.algcomparison.simulation;
  
  import edu.cmu.tetrad.algcomparison.graph.RandomGraph;
  import edu.cmu.tetrad.algcomparison.graph.SingleGraph;
  import edu.cmu.tetrad.data.DataModel;
  import edu.cmu.tetrad.data.DataSet;
  import edu.cmu.tetrad.data.DataType;
  import edu.cmu.tetrad.data.DataUtils;
  import edu.cmu.tetrad.graph.Graph;
  import edu.cmu.tetrad.graph.Node;
  import edu.cmu.tetrad.graph.SemGraph;
  import edu.cmu.tetrad.sem.GeneralizedSemIm;
  import edu.cmu.tetrad.sem.GeneralizedSemPm;
  import edu.cmu.tetrad.sem.TemplateExpander;
  import edu.cmu.tetrad.util.Parameters;
  import edu.cmu.tetrad.util.RandomUtil;
  
  import java.text.ParseException;
  import java.util.ArrayList;
  import java.util.List;
  
  /**
   * @author jdramsey
   */
  public class GeneralSemSimulation implements Simulation {
      static final long serialVersionUID = 23L;
      private RandomGraph randomGraph;
      private GeneralizedSemPm pm;
      private GeneralizedSemIm im;
      private List<DataSet> dataSets = new ArrayList<>();
      private List<DataSet> dataWithLatents = new ArrayList<>();
      private List<Graph> graphs = new ArrayList<>();
      private List<GeneralizedSemIm> ims = new ArrayList<>();
  
      public GeneralSemSimulation(RandomGraph graph) {
          this.randomGraph = graph;
      }
  
      public GeneralSemSimulation(GeneralizedSemPm pm) {
          SemGraph graph = pm.getGraph();
          graph.setShowErrorTerms(false);
          this.randomGraph = new SingleGraph(graph);
          this.pm = pm;
      }
  
      public GeneralSemSimulation(GeneralizedSemIm im) {
          SemGraph graph = im.getSemPm().getGraph();
          graph.setShowErrorTerms(false);
          this.randomGraph = new SingleGraph(graph);
          this.im = im;
          this.ims = new ArrayList<>();
          ims.add(im);
          this.pm = im.getGeneralizedSemPm();
      }
  
      @Override
      public void createData(Parameters parameters) {
          Graph graph = randomGraph.createGraph(parameters);
  
          dataSets = new ArrayList<>();
          graphs = new ArrayList<>();
          ims = 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);
  
              if (parameters.getBoolean("standardize")) {
                  dataSet = DataUtils.standardizeData(dataSet);
              }
  
              double variance = parameters.getDouble("measurementVariance");
  
              if (variance > 0) {
                  for (int k = 0; k < dataSet.getNumRows(); k++) {
                      for (int j = 0; j < dataSet.getNumColumns(); j++) {
                          double d = dataSet.getDouble(k, j);
                          double norm = RandomUtil.getInstance().nextNormal(0, Math.sqrt(variance));
                          dataSet.setDouble(k, j, d + norm);
                      }
                  }
              }
  
              if (parameters.getBoolean("randomizeColumns")) {
                  dataSet = DataUtils.reorderColumns(dataSet);
              }
  
              dataSet.setName("" + (i + 1));
              dataSets.add(DataUtils.restrictToMeasured(dataSet));
              dataWithLatents.add(dataSet);
          }
      }
  
      private synchronized DataSet simulate(Graph graph, Parameters parameters) {
          if (pm == null) {
              pm = getPm(graph, parameters);
          }
  
          System.out.println(pm);
  
          im = new GeneralizedSemIm(pm);
  
          System.out.println(im);
  
          ims.add(im);
          return im.simulateData(parameters.getInt("sampleSize"), true);
      }
  
      @Override
      public Graph getTrueGraph(int index) {
          return graphs.get(index);
      }
  
      @Override
      public int getNumDataModels() {
          return dataSets.size();
      }
  
      @Override
      public DataModel getDataModel(int index) {
          return dataSets.get(index);
      }
  
      @Override
      public DataType getDataType() {
          return DataType.Continuous;
      }
  
      public String getDescription() {
          return "Nonlinear, non-Gaussian SEM simulation using " + randomGraph.getDescription();
      }
  
      @Override
      public List<String> getParameters() {
          List<String> parameters = new ArrayList<>();
  
          if (!(randomGraph instanceof SingleGraph)) {
              parameters.addAll(randomGraph.getParameters());
          }
  
          if (pm == null) {
              parameters.addAll(GeneralizedSemPm.getParameterNames());
          }
  
          parameters.add("numRuns");
          parameters.add("differentGraphs");
          parameters.add("sampleSize");
  
          return parameters;
      }
  
      private GeneralizedSemPm getPm(Graph graph, Parameters parameters) {
          GeneralizedSemPm pm = new GeneralizedSemPm(graph);
  
          List<Node> variablesNodes = pm.getVariableNodes();
          List<Node> errorNodes = pm.getErrorNodes();
  
          try {
  
              for (Node node : variablesNodes) {
                  String _template = TemplateExpander.getInstance().expandTemplate(
                          parameters.getString("generalSemFunctionTemplateMeasured"), pm, node);
                  pm.setNodeExpression(node, _template);
              }
  
              for (Node node : errorNodes) {
                  String _template = TemplateExpander.getInstance().expandTemplate(
                          parameters.getString("generalSemErrorTemplate"), pm, node);
                  pm.setNodeExpression(node, _template);
              }
  
              for (String parameter : pm.getParameters()) {
                  pm.setParameterExpression(parameter, parameters.getString("generalSemParameterTemplate"));
              }
  
              pm.setVariablesTemplate(parameters.getString("generalSemFunctionTemplateMeasured"));
              pm.setErrorsTemplate(parameters.getString("generalSemErrorTemplate"));
              pm.setParametersTemplate(parameters.getString("generalSemParameterTemplate"));
  
          } catch (ParseException e) {
              System.out.println(e);
          }
  
          return pm;
      }
  
      public List<GeneralizedSemIm> getIms() {
          return ims;
      }
  }
  