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///////////////////////////////////////////////////////////////////////////////
// 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, 2022 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.performance;
import edu.cmu.tetrad.data.*;
import edu.cmu.tetrad.graph.*;
import edu.cmu.tetrad.search.GFci;
import edu.cmu.tetrad.search.Pc;
import edu.cmu.tetrad.search.score.SemBicScore;
import edu.cmu.tetrad.search.test.IndTestFisherZ;
import edu.cmu.tetrad.sem.SemIm;
import edu.cmu.tetrad.sem.SemPm;
import java.io.File;
import java.io.FileNotFoundException;
import java.io.PrintStream;
import java.text.DecimalFormat;
import java.text.NumberFormat;
import java.util.ArrayList;
import java.util.List;
/**
* Contains some tests for Dan Malinsky, that might be of interest to others.
*
* @author josephramsey.
*/
public class PerformanceTestsDan {
public static void main(String... args) {
System.out.println("Start ");
new PerformanceTestsDan().testIdaOutputForDan();
}
private void testIdaOutputForDan() {
final int numRuns = 100;
for (int run = 0; run < numRuns; run++) {
final double alphaGFci = 0.01;
final double alphaPc = 0.01;
final int penaltyDiscount = 1;
final int depth = 3;
final int maxPathLength = 3;
final int numVars = 15;
final double edgesPerNode = 1.0;
final int numCases = 1000;
// final int numLatents = RandomUtil.getInstance().nextInt(3) + 1;
final int numLatents = 6;
// writeToFile = false;
PrintStream out1;
PrintStream out2;
PrintStream out3;
PrintStream out4;
PrintStream out5;
PrintStream out6;
PrintStream out7;
PrintStream out8;
PrintStream out9;
PrintStream out10;
PrintStream out11;
PrintStream out12;
File dir0 = new File("gfci.output");
dir0.mkdirs();
File dir = new File(dir0, "" + (run + 1));
dir.mkdir();
try {
out1 = new PrintStream(new File(dir, "hyperparameters.txt"));
out2 = new PrintStream(new File(dir, "variables.txt"));
out3 = new PrintStream(new File(dir, "dag.long.txt"));
out4 = new PrintStream(new File(dir, "dag.matrix.txt"));
out5 = new PrintStream(new File(dir, "coef.matrix.txt"));
out6 = new PrintStream(new File(dir, "pag.long.txt"));
out7 = new PrintStream(new File(dir, "pag.matrix.txt"));
out8 = new PrintStream(new File(dir, "cpdag.long.txt"));
out9 = new PrintStream(new File(dir, "cpdag.matrix.txt"));
out10 = new PrintStream(new File(dir, "data.txt"));
out11 = new PrintStream(new File(dir, "true.pag.long.txt"));
out12 = new PrintStream(new File(dir, "true.pag.matrix.txt"));
} catch (FileNotFoundException e) {
e.printStackTrace();
throw new RuntimeException(e);
}
out1.println("Num _vars = " + numVars);
out1.println("Num edges = " + (int) (numVars * edgesPerNode));
out1.println("Num cases = " + numCases);
out1.println("Alpha for PC = " + alphaPc);
out1.println("Alpha for FFCI = " + alphaGFci);
out1.println("Penalty discount = " + penaltyDiscount);
out1.println("Depth = " + depth);
out1.println("Maximum reachable path length for msep search and discriminating undirectedPaths = " + maxPathLength);
List vars = new ArrayList<>();
for (int i = 0; i < numVars; i++) vars.add(new GraphNode("X" + (i + 1)));
// Graph dag = DataGraphUtils.randomDagQuick2(varsWithLatents, 0, (int) (varsWithLatents.size() * edgesPerNode));
Graph dag = RandomGraph.randomGraph(vars, 0, (int) (vars.size() * edgesPerNode), 5, 5, 5, false);
RandomGraph.fixLatents1(numLatents, dag);
out3.println(dag);
printDanMatrix(vars, dag, out4);
SemPm pm = new SemPm(dag);
SemIm im = new SemIm(pm);
NumberFormat nf = new DecimalFormat("0.0000");
for (int i = 0; i < vars.size(); i++) {
for (Node var : vars) {
if (im.existsEdgeCoef(var, vars.get(i))) {
double coef = im.getEdgeCoef(var, vars.get(i));
out5.print(nf.format(coef) + "\t");
} else {
out5.print(nf.format(0) + "\t");
}
}
out5.println();
}
out5.println();
String vars_temp = vars.toString();
vars_temp = vars_temp.replace("[", "");
vars_temp = vars_temp.replace("]", "");
vars_temp = vars_temp.replace("X", "");
out2.println(vars_temp);
List _vars = new ArrayList<>();
for (Node node : vars) {
if (node.getNodeType() == NodeType.MEASURED) {
_vars.add(node);
}
}
String _vars_temp = _vars.toString();
_vars_temp = _vars_temp.replace("[", "");
_vars_temp = _vars_temp.replace("]", "");
_vars_temp = _vars_temp.replace("X", "");
out2.println(_vars_temp);
DataSet fullData = im.simulateData(numCases, false);
DataSet data = DataTransforms.restrictToMeasured(fullData);
ICovarianceMatrix cov = new CovarianceMatrix(data);
IndTestFisherZ independenceTestGFci = new IndTestFisherZ(cov, alphaGFci);
SemBicScore scoreGfci = new SemBicScore(cov);
out6.println("GFCI.PAG_of_the_true_DAG");
GFci gFci = new GFci(independenceTestGFci, scoreGfci);
gFci.setVerbose(false);
gFci.setMaxDegree(depth);
gFci.setMaxPathLength(maxPathLength);
// gFci.setPossibleMsepSearchDone(true);
gFci.setCompleteRuleSetUsed(true);
Graph pag = gFci.search();
out6.println(pag);
printDanMatrix(_vars, pag, out7);
out8.println("CPDAG_of_the_true_DAG OVER MEASURED VARIABLES");
IndTestFisherZ independencePc = new IndTestFisherZ(cov, alphaPc);
Pc pc = new Pc(independencePc);
pc.setVerbose(false);
pc.setDepth(depth);
Graph CPDAG = pc.search();
out8.println(CPDAG);
printDanMatrix(_vars, CPDAG, out9);
out10.println(data);
out11.println("True PAG_of_the_true_DAG");
Graph truePag = GraphTransforms.dagToPag(dag);
out11.println(truePag);
printDanMatrix(_vars, truePag, out12);
out1.close();
out2.close();
out3.close();
out4.close();
out5.close();
out6.close();
out7.close();
out8.close();
out9.close();
out10.close();
out11.close();
out12.close();
}
}
private void printDanMatrix(List vars, Graph CPDAG, PrintStream out) {
CPDAG = GraphUtils.replaceNodes(CPDAG, vars);
for (int i = 0; i < vars.size(); i++) {
for (Node var : vars) {
Edge edge = CPDAG.getEdge(vars.get(i), var);
if (edge == null) {
out.print(0 + "\t");
} else {
Endpoint ej = edge.getProximalEndpoint(var);
if (ej == Endpoint.TAIL) {
out.print(3 + "\t");
} else if (ej == Endpoint.ARROW) {
out.print(2 + "\t");
} else if (ej == Endpoint.CIRCLE) {
out.print(1 + "\t");
}
}
}
out.println();
}
out.println();
}
}
