Java tutorial
/* * Copyright (C) 2016 University of Pittsburgh. * * This library is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * This library 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 * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this library; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, * MA 02110-1301 USA */ package edu.cmu.tetrad.cli.search; import edu.cmu.tetrad.algcomparison.algorithm.Algorithm; import edu.cmu.tetrad.algcomparison.algorithm.oracle.pattern.Fgs; import edu.cmu.tetrad.algcomparison.score.SemBicScore; import edu.cmu.tetrad.cli.AbstractAlgorithmCli; import edu.cmu.tetrad.cli.AlgorithmType; import edu.cmu.tetrad.cli.CmdOptions; import edu.cmu.tetrad.cli.ParamAttrs; import edu.cmu.tetrad.cli.validation.DataValidation; import edu.cmu.tetrad.cli.validation.NonZeroVariance; import edu.cmu.tetrad.cli.validation.UniqueVariableNames; import edu.cmu.tetrad.data.DataSet; import edu.cmu.tetrad.data.IKnowledge; import edu.cmu.tetrad.io.DataReader; import edu.cmu.tetrad.io.TabularContinuousDataReader; import edu.cmu.tetrad.util.Parameters; import java.nio.file.Path; import java.nio.file.Paths; import java.util.Collections; import java.util.Formatter; import java.util.LinkedList; import java.util.List; import org.apache.commons.cli.CommandLine; import org.apache.commons.cli.Option; /** * * Sep 12, 2016 1:56:30 PM * * @author Kevin V. Bui (kvb2@pitt.edu) */ public class FgscCli extends AbstractAlgorithmCli { protected double penaltyDiscount; protected int maxDegree; protected boolean faithfulnessAssumed; protected boolean skipUniqueVarName; protected boolean skipZeroVariance; public FgscCli(String[] args) { super(args); } @Override public void printValidationInfos(Formatter fmt) { fmt.format("ensure variable names are unique = %s%n", !skipUniqueVarName); fmt.format("ensure variables have non-zero variance = %s%n", !skipZeroVariance); } @Override public void printParameterInfos(Formatter fmt) { fmt.format("penalty discount = %f%n", penaltyDiscount); fmt.format("max degree = %d%n", maxDegree); fmt.format("faithfulness assumed = %s%n", faithfulnessAssumed); } @Override public Parameters getParameters() { Parameters parameters = new Parameters(); parameters.set(ParamAttrs.PENALTY_DISCOUNT, penaltyDiscount); parameters.set(ParamAttrs.MAX_DEGREE, maxDegree); parameters.set(ParamAttrs.FAITHFULNESS_ASSUMED, faithfulnessAssumed); parameters.set(ParamAttrs.VERBOSE, verbose); return parameters; } @Override public Algorithm getAlgorithm(IKnowledge knowledge) { Fgs fgs = new Fgs(new SemBicScore()); if (knowledge != null) { fgs.setKnowledge(knowledge); } return fgs; } @Override public DataReader getDataReader(Path dataFile, char delimiter) { return new TabularContinuousDataReader(dataFile, delimiter); } @Override public List<DataValidation> getDataValidations(DataSet dataSet, Path dirOut, String filePrefix) { List<DataValidation> validations = new LinkedList<>(); String outputDir = dirOut.toString(); if (!skipUniqueVarName) { if (validationOutput) { validations.add(new UniqueVariableNames(dataSet, Paths.get(outputDir, filePrefix + "_duplicate_var_name.txt"))); } else { validations.add(new UniqueVariableNames(dataSet)); } } if (!skipZeroVariance) { if (validationOutput) { validations.add(new NonZeroVariance(dataSet, numOfThreads, Paths.get(outputDir, filePrefix + "_zero_variance.txt"))); } else { validations.add(new NonZeroVariance(dataSet, numOfThreads)); } } return validations; } @Override public void parseRequiredOptions(CommandLine cmd) throws Exception { } @Override public void parseOptionalOptions(CommandLine cmd) throws Exception { penaltyDiscount = CmdOptions.getDouble(CmdOptions.PENALTY_DISCOUNT, ParamAttrs.PENALTY_DISCOUNT, cmd); maxDegree = CmdOptions.getInt(CmdOptions.MAX_DEGREE, ParamAttrs.MAX_DEGREE, cmd); faithfulnessAssumed = cmd.hasOption(CmdOptions.FAITHFULNESS_ASSUMED); skipUniqueVarName = cmd.hasOption(CmdOptions.SKIP_UNIQUE_VAR_NAME); skipZeroVariance = cmd.hasOption(CmdOptions.SKIP_NONZERO_VARIANCE); } @Override public List<Option> getRequiredOptions() { return Collections.EMPTY_LIST; } @Override public List<Option> getOptionalOptions() { List<Option> options = new LinkedList<>(); options.add(new Option(null, CmdOptions.PENALTY_DISCOUNT, true, CmdOptions.getDescription(CmdOptions.PENALTY_DISCOUNT))); options.add( new Option(null, CmdOptions.MAX_DEGREE, true, CmdOptions.getDescription(CmdOptions.MAX_DEGREE))); options.add(new Option(null, CmdOptions.FAITHFULNESS_ASSUMED, false, CmdOptions.getDescription(CmdOptions.FAITHFULNESS_ASSUMED))); options.add(new Option(null, CmdOptions.SKIP_UNIQUE_VAR_NAME, false, CmdOptions.getDescription(CmdOptions.SKIP_UNIQUE_VAR_NAME))); options.add(new Option(null, CmdOptions.SKIP_NONZERO_VARIANCE, false, CmdOptions.getDescription(CmdOptions.SKIP_NONZERO_VARIANCE))); return options; } @Override public AlgorithmType getAlgorithmType() { return AlgorithmType.FGSC; } }