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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.                               //
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package edu.cmu.tetrad.study.examples.conditions;

import edu.cmu.tetrad.algcomparison.Comparison;
import edu.cmu.tetrad.algcomparison.algorithm.Algorithms;
import edu.cmu.tetrad.algcomparison.algorithm.external.*;
import edu.cmu.tetrad.algcomparison.statistic.*;
import edu.cmu.tetrad.util.Parameters;

/**
 * An example script to load in data sets and graphs from files and analyze them. The files loaded must be in the same
 * format as
 * 

* new Comparison().saveDataSetAndGraphs("comparison/save1", simulation, parameters); *

* saves them. For other formats, specialty data loaders can be written to implement the Simulation interface. * * @author josephramsey */ public class Condition2 { public static void main(String... args) { new Condition2().compileTable(); } public void generateTetradResults() { Parameters parameters = new Parameters(); parameters.set("alpha", 0.01); parameters.set("numRuns", 10); // parameters.set("penaltyDiscount", 4); parameters.set("useMaxPOrientationHeuristic", false); // parameters.set("maxPOrientationMaxPathLength", 3); Statistics statistics = new Statistics(); statistics.add(new ParameterColumn("numMeasures")); statistics.add(new ParameterColumn("avgDegree")); statistics.add(new ParameterColumn("sampleSize")); statistics.add(new ParameterColumn("faithfulnessAssumed")); statistics.add(new AdjacencyPrecision()); statistics.add(new AdjacencyRecall()); statistics.add(new ArrowheadPrecision()); statistics.add(new ArrowheadRecall()); statistics.add(new ElapsedCpuTime()); statistics.setWeight("AP", 1.0); statistics.setWeight("AR", 0.5); statistics.setWeight("AHP", 1.0); statistics.setWeight("AHR", 0.5); Algorithms algorithms = new Algorithms(); Comparison comparison = new Comparison(); comparison.setShowAlgorithmIndices(true); comparison.setShowSimulationIndices(true); comparison.setSortByUtility(false); comparison.setShowUtilities(true); comparison.setSaveGraphs(true); comparison.compareFromFiles("/Users/user/comparison-data/condition_2", "/Users/user/causal-comparisons/condition_2", algorithms, statistics, parameters); } public void compileTable() { Parameters parameters = new Parameters(); parameters.set("numRuns", 10); 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 MathewsCorrAdj()); statistics.add(new MathewsCorrArrow()); statistics.add(new ElapsedCpuTime()); statistics.setWeight("AP", 1.0); statistics.setWeight("AR", 0.5); statistics.setWeight("AHP", 1.0); statistics.setWeight("AHR", 0.5); Algorithms algorithms = new Algorithms(); algorithms.add(new ExternalAlgorithmTetrad("PC_(\"Peter_and_Clark\"),_Priority_Rule,_using_Fisher_Z_test,_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmTetrad("PC_(\"Peter_and_Clark\"),_Priority_Rule,_using_Fisher_Z_test,_alpha_=_0.001")); algorithms.add(new ExternalAlgorithmTetrad("PC-Stable_(\"Peter_and_Clark\"_Stable),_Priority_Rule,_using_Fisher_Z_test,_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmTetrad("PC-Stable_(\"Peter_and_Clark\"_Stable),_Priority_Rule,_using_Fisher_Z_test,_alpha_=_0.001")); algorithms.add(new ExternalAlgorithmTetrad("PC-Stable-Max_(\"Peter_and_Clark\"),_Priority_Rule,_using_Fisher_Z_test,_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmTetrad("PC-Stable-Max_(\"Peter_and_Clark\"),_Priority_Rule,_using_Fisher_Z_test,_alpha_=_0.001")); algorithms.add(new ExternalAlgorithmTetrad("CPC_(Conservative_\"Peter_and_Clark\"),_Priority_Rule,_using_Fisher_Z_test,_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmTetrad("CPC_(Conservative_\"Peter_and_Clark\"),_Priority_Rule,_using_Fisher_Z_test,_alpha_=_0.001")); algorithms.add(new ExternalAlgorithmTetrad("CPC-Stable_(Conservative_\"Peter_and_Clark\"_Stable),_Priority_Rule,_using_Fisher_Z_test,_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmTetrad("CPC-Stable_(Conservative_\"Peter_and_Clark\"_Stable),_Priority_Rule,_using_Fisher_Z_test,_alpha_=_0.001")); // algorithms.add(new ExternalAlgorithmTetrad("FGES_(Fast_Greedy_Equivalence_Search)_using_Fisher_Z_Score,_alpha_=_0.001,_faithfulnessAssumed_=_false")); algorithms.add(new ExternalAlgorithmTetrad("FGES_(Fast_Greedy_Equivalence_Search)_using_Fisher_Z_Score,_alpha_=_1.0E-4,_faithfulnessAssumed_=_false")); algorithms.add(new ExternalAlgorithmTetrad("FGES_(Fast_Greedy_Equivalence_Search)_using_Fisher_Z_Score,_alpha_=_1.0E-8,_faithfulnessAssumed_=_false")); algorithms.add(new ExternalAlgorithmTetrad("FGES_(Fast_Greedy_Equivalence_Search)_using_Sem_BIC_Score,_penaltyDiscount_=_2,_faithfulnessAssumed_=_false")); algorithms.add(new ExternalAlgorithmTetrad("FGES_(Fast_Greedy_Equivalence_Search)_using_Sem_BIC_Score,_penaltyDiscount_=_4,_faithfulnessAssumed_=_false")); algorithms.add(new ExternalAlgorithmTetrad("FGES_(Fast_Greedy_Equivalence_Search)_using_Fisher_Z_Score,_alpha_=_0.001,_faithfulnessAssumed_=_true")); algorithms.add(new ExternalAlgorithmTetrad("FGES_(Fast_Greedy_Equivalence_Search)_using_Fisher_Z_Score,_alpha_=_1.0E-4,_faithfulnessAssumed_=_true")); algorithms.add(new ExternalAlgorithmTetrad("FGES_(Fast_Greedy_Equivalence_Search)_using_Fisher_Z_Score,_alpha_=_1.0E-8,_faithfulnessAssumed_=_true")); algorithms.add(new ExternalAlgorithmTetrad("FGES_(Fast_Greedy_Equivalence_Search)_using_Sem_BIC_Score,_penaltyDiscount_=_2,_faithfulnessAssumed_=_true")); algorithms.add(new ExternalAlgorithmTetrad("FGES_(Fast_Greedy_Equivalence_Search)_using_Sem_BIC_Score,_penaltyDiscount_=_4,_faithfulnessAssumed_=_true")); algorithms.add(new ExternalAlgorithmBnlearnMmhc("MMPC_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmBnlearnMmhc("MMPC_alpha_=_0.001")); algorithms.add(new ExternalAlgorithmBnlearnMmhc("GrowShrink alpha = 0.01")); algorithms.add(new ExternalAlgorithmBnlearnMmhc("GrowShrink alpha = 0.001")); algorithms.add(new ExternalAlgorithmBnlearnMmhc("IAMB_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmBnlearnMmhc("IAMB_alpha_=_0.001")); algorithms.add(new ExternalAlgorithmBnlearnMmhc("Fast.IAMB_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmBnlearnMmhc("Fast.IAMB_alpha_=_0.001")); algorithms.add(new ExternalAlgorithmBnlearnMmhc("Inter.IAMB_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmBnlearnMmhc("Inter.IAMB_alpha_=_0.001")); algorithms.add(new ExternalAlgorithmBnlearnMmhc("si.hiton.pc_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmBnlearnMmhc("si.hiton.pc_alpha_=_0.001")); algorithms.add(new ExternalAlgorithmBnlearnMmhc("MMHC")); algorithms.add(new ExternalAlgorithmPcalgPc("PC_pcalg_defaults_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmPcalgPc("PC_pcalg_defaults_alpha_=_0.001")); algorithms.add(new ExternalAlgorithmPcalgPc("PC-Stable_pcalg_ncores=4_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmPcalgPc("PC-Stable_pcalg_ncores=4_alpha_=_0.001")); algorithms.add(new ExternalAlgorithmPcalgPc("CPC_pcalg_defaults_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmPcalgPc("CPC_pcalg_defaults_alpha_=_0.001")); algorithms.add(new ExternalAlgorithmPcalgPc("CPC_pcalg_majority.rule_defaults_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmPcalgPc("CPC_pcalg_majority.rule_defaults_alpha_=_0.001")); algorithms.add(new ExternalAlgorithmPcalgGes("GES_pcalg_defaults_2*log(nrow(data)")); algorithms.add(new ExternalAlgorithmPcalgGes("GES_pcalg_defaults_4*log(nrow(data)")); algorithms.add(new ExternalAlgorithmBNTPc("learn.struct.pdag.pc_bnt_alpha_=_0.01")); algorithms.add(new ExternalAlgorithmBNTPc("learn.struct.pdag.pc_bnt_alpha_=_0.001")); Comparison comparison = new Comparison(); comparison.setShowAlgorithmIndices(true); comparison.setShowSimulationIndices(true); comparison.setSortByUtility(false); comparison.setShowUtilities(false); comparison.setSaveGraphs(true); comparison.setComparisonGraph(Comparison.ComparisonGraph.true_DAG); comparison.generateReportFromExternalAlgorithms("/Users/user/comparison-data/condition_2", "/Users/user/causal-comparisons/condition_2", "Comparison.txt", algorithms, statistics, parameters); Statistics statistics2 = new Statistics(); statistics2.add(new ParameterColumn("numMeasures")); statistics2.add(new ParameterColumn("avgDegree")); statistics2.add(new ParameterColumn("sampleSize")); statistics2.add(new AdjacencyFp()); statistics2.add(new AdjacencyFn()); statistics2.add(new AdjacencyTp()); statistics2.add(new AdjacencyTn()); statistics2.add(new ArrowheadFp()); statistics2.add(new ArrowheadFn()); statistics2.add(new ArrowheadTp()); statistics2.add(new ArrowheadTn()); statistics2.add(new ElapsedCpuTime()); // comparison.generateReportFromExternalAlgorithms("/Users/user/comparison-data/condition_2", "/Users/user/causal-comparisons/condition_2", "Counts.txt", algorithms, statistics2, parameters); } }





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