TrainingSets class is obsolete now.
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@ -1,71 +0,0 @@
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/*
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* Copyright (c) 2011 The Broad Institute
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*
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* Permission is hereby granted, free of charge, to any person
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* obtaining a copy of this software and associated documentation
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* files (the "Software"), to deal in the Software without
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* restriction, including without limitation the rights to use,
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* copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the
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* Software is furnished to do so, subject to the following
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* conditions:
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*
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* The above copyright notice and this permission notice shall be
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* included in all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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* OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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* NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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* HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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* WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR
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* THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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*/
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package org.broadinstitute.sting.gatk.walkers.variantrecalibration;
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import org.apache.log4j.Logger;
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import org.broadinstitute.sting.commandline.Tags;
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/**
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* Created by IntelliJ IDEA.
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* User: rpoplin
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* Date: 3/12/11
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*/
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public class TrainingSet {
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public String name;
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public boolean isKnown = false;
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public boolean isTraining = false;
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public boolean isAntiTraining = false;
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public boolean isTruth = false;
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public boolean isConsensus = false;
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public double prior = 0.0;
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protected final static Logger logger = Logger.getLogger(TrainingSet.class);
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public TrainingSet( final String name, final Tags tags ) {
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this.name = name;
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// Parse the tags to decide which tracks have which properties
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if( tags != null ) {
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isKnown = tags.containsKey("known") && tags.getValue("known").equals("true");
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isTraining = tags.containsKey("training") && tags.getValue("training").equals("true");
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isAntiTraining = tags.containsKey("bad") && tags.getValue("bad").equals("true");
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isTruth = tags.containsKey("truth") && tags.getValue("truth").equals("true");
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isConsensus = tags.containsKey("consensus") && tags.getValue("consensus").equals("true");
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prior = ( tags.containsKey("prior") ? Double.parseDouble(tags.getValue("prior")) : prior );
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}
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// Report back to the user which tracks were found and the properties that were detected
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if( !isConsensus && !isAntiTraining ) {
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logger.info( String.format( "Found %s track: \tKnown = %s \tTraining = %s \tTruth = %s \tPrior = Q%.1f", this.name, isKnown, isTraining, isTruth, prior) );
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} else if( isConsensus ) {
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logger.info( String.format( "Found consensus track: %s", this.name) );
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} else {
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logger.info( String.format( "Found bad sites training track: %s", this.name) );
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}
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}
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}
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@ -52,7 +52,6 @@ public class VariantDataManager {
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private final double[] meanVector;
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private final double[] varianceVector; // this is really the standard deviation
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public final ArrayList<String> annotationKeys;
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private final ExpandingArrayList<TrainingSet> trainingSets;
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private final VariantRecalibratorArgumentCollection VRAC;
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protected final static Logger logger = Logger.getLogger(VariantDataManager.class);
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@ -63,7 +62,6 @@ public class VariantDataManager {
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this.VRAC = VRAC;
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meanVector = new double[this.annotationKeys.size()];
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varianceVector = new double[this.annotationKeys.size()];
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trainingSets = new ExpandingArrayList<TrainingSet>();
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}
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public void setData( final ExpandingArrayList<VariantDatum> data ) {
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