Knocking out some quick findBugs.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@3887 348d0f76-0448-11de-a6fe-93d51630548a
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rpoplin
parent
894623858d
commit
f5566a6593
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@ -34,7 +34,7 @@ import net.sf.picard.util.IlluminaUtil;
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public class TileCovariate implements ExperimentalCovariate {
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private static boolean exceptionWhenNoTile = false;
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private boolean exceptionWhenNoTile = false;
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// Initialize any member variables using the command-line arguments passed to the walkers
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public void initialize( final RecalibrationArgumentCollection RAC ) {
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@ -53,8 +53,8 @@ public class VariantQualityScore extends VariantEvaluator {
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@DataPoint(name="Quality by Allele Count", description = "average variant quality for each allele count")
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AlleleCountStats alleleCountStats = null;
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class TiTvStats implements TableType {
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final int NUM_BINS = 20;
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static class TiTvStats implements TableType {
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final static int NUM_BINS = 20;
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final HashMap<Integer, Pair<Long,Long>> qualByIsTransition = new HashMap<Integer, Pair<Long,Long>>(); // A hashMap holds all the qualities until we are able to bin them appropriately
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final long transitionByQuality[] = new long[NUM_BINS];
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final long transversionByQuality[] = new long[NUM_BINS];
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@ -81,13 +81,14 @@ public class VariantQualityScore extends VariantEvaluator {
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}
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public String toString() {
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String returnString = "";
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StringBuffer returnString = new StringBuffer();
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// output the ti/tv array
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returnString += "titvByQuality: ";
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returnString.append("titvByQuality: ");
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for( int iii = 0; iii < NUM_BINS; iii++ ) {
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returnString += titvByQuality[iii] + " ";
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returnString.append(titvByQuality[iii]);
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returnString.append(" ");
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}
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return returnString;
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return returnString.toString();
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}
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public void incrValue( final double qual, final boolean isTransition ) {
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@ -586,6 +586,7 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
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}
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annIndex++;
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outputFile.close();
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}
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// BUGBUG: next output the actual cluster on top by integrating out every other annotation
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@ -1,78 +0,0 @@
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package org.broadinstitute.sting.gatk.walkers.variantrecalibration;
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import org.broadinstitute.sting.utils.StingException;
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import java.io.PrintStream;
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/*
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* Copyright (c) 2010 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 THE USE OR
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* OTHER DEALINGS IN THE SOFTWARE.
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*/
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/**
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* Created by IntelliJ IDEA.
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* User: rpoplin
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* Date: Mar 1, 2010
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*/
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public final class VariantNearestNeighborsModel extends VariantOptimizationModel {
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private final int numKNN;
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public VariantNearestNeighborsModel( VariantDataManager _dataManager, final double _targetTITV, final int _numKNN ) {
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super( _targetTITV );
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//dataManager = _dataManager;
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numKNN = _numKNN;
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}
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public void run( final String outputPrefix ) {
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throw new StingException( "Nearest Neighbors model hasn't been updated yet." );
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/*
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final int numVariants = dataManager.numVariants;
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final double[] pTrueVariant = new double[numVariants];
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final VariantTree vTree = new VariantTree( numKNN );
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vTree.createTreeFromData( dataManager.data );
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System.out.println("Finished creating the kd-tree.");
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for(int iii = 0; iii < numVariants; iii++) {
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pTrueVariant[iii] = calcTruePositiveRateFromTITV( vTree.calcNeighborhoodTITV( dataManager.data[iii] ) );
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}
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PrintStream outputFile;
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try {
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outputFile = new PrintStream( outputPrefix + ".knn.optimize" );
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} catch (Exception e) {
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throw new StingException( "Unable to create output file: " + outputPrefix + ".knn.optimize" );
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}
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for(int iii = 0; iii < numVariants; iii++) {
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outputFile.print(String.format("%.4f",pTrueVariant[iii]) + ",");
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outputFile.println( (dataManager.data[iii].isTransition ? 1 : 0)
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+ "," + (dataManager.data[iii].isKnown? 1 : 0));
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}
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*/
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}
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}
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@ -1,144 +0,0 @@
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package org.broadinstitute.sting.gatk.walkers.variantrecalibration;
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import org.broadinstitute.sting.utils.StingException;
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/*
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* Copyright (c) 2010 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 THE USE OR
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* OTHER DEALINGS IN THE SOFTWARE.
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*/
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/**
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* Created by IntelliJ IDEA.
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* User: rpoplin
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* Date: Feb 24, 2010
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*/
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public class VariantTree {
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private final VariantTreeNode root;
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private final int numKNN;
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public VariantTree( final int _numKNN ) {
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root = new VariantTreeNode();
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numKNN = _numKNN;
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}
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public void createTreeFromData( VariantDatum[] data ) {
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root.cutData( data, 0, 0, data[0].annotations.length );
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}
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public double calcNeighborhoodTITV( final VariantDatum variant ) {
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double[] distances;
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// Grab the subset of points that are approximately near this point
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final VariantDatum[] data = getBin( variant.annotations, root );
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if( data.length < numKNN ) {
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throw new StingException( "Bin is too small. Should be > " + numKNN );
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}
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// Find the X nearest points in the subset
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final double[] originalDistances = calcDistances( variant.annotations, data );
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distances = originalDistances.clone();
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quickSort( distances, 0, distances.length-1 ); // BUGBUG: distances.length or distances.length-1
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final double minDistance = distances[numKNN - 1];
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// Calculate probability of being true based on this set of SNPs
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int numTi = 0;
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int numTv = 0;
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for( int iii = 0; iii < distances.length; iii++ ) {
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if( originalDistances[iii] <= minDistance ) {
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if( data[iii].isTransition ) { numTi++; }
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else { numTv++; }
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}
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}
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return ((double) numTi) / ((double) numTv);
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}
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private VariantDatum[] getBin( final double[] variant, final VariantTreeNode node ) {
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if( node.variants != null ) {
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return node.variants;
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} else {
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if( variant[node.cutDim] < node.cutValue ) {
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return getBin( variant, node.left );
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} else {
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return getBin( variant, node.right );
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}
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}
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}
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private double[] calcDistances( final double[] variant, final VariantDatum[] data ) {
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final double[] distSquared = new double[data.length];
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int iii = 0;
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for( final VariantDatum variantDatum : data ) {
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distSquared[iii] = 0.0;
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int jjj = 0;
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for( final double value : variantDatum.annotations) {
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final double diff = variant[jjj] - value;
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distSquared[iii] += ( diff * diff );
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jjj++;
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}
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iii++;
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}
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return distSquared;
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}
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public static int partition(final double arr[], final int left, final int right)
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{
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int i = left, j = right;
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double tmp;
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final double pivot = arr[(left + right) / 2];
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while (i <= j) {
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while (arr[i] < pivot) {
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i++;
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}
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while (arr[j] > pivot) {
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j--;
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}
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if (i <= j) {
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tmp = arr[i];
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arr[i] = arr[j];
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arr[j] = tmp;
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i++;
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j--;
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}
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}
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return i;
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}
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public static void quickSort(final double arr[], final int left, final int right) {
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final int index = partition(arr, left, right);
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if (left < index - 1) {
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quickSort(arr, left, index - 1);
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}
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if (index < right) {
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quickSort(arr, index, right);
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}
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}
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}
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@ -1,104 +0,0 @@
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package org.broadinstitute.sting.gatk.walkers.variantrecalibration;
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/*
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* Copyright (c) 2010 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 THE USE OR
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* OTHER DEALINGS IN THE SOFTWARE.
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*/
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/**
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* Created by IntelliJ IDEA.
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* User: rpoplin
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* Date: Feb 24, 2010
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*/
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public class VariantTreeNode {
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public VariantTreeNode left;
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public VariantTreeNode right;
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public int cutDim;
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public double cutValue;
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public VariantDatum[] variants;
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private final int minBinSize = 8000; // BUGBUG: must be larger than number of kNN
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public VariantTreeNode() {
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left = null;
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right = null;
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variants = null;
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cutDim = -1;
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cutValue = -1;
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}
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public final void cutData( final VariantDatum[] data, final int depth, final int lastCutDepth, final int numAnnotations ) {
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cutDim = depth % numAnnotations;
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if( depth != lastCutDepth && (cutDim == (lastCutDepth % numAnnotations)) ) { // Base case: we've tried to cut on all the annotations
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variants = data;
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return;
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}
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final double[] values = new double[data.length];
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for( int iii = 0; iii < data.length; iii++ ) {
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values[iii] = data[iii].annotations[cutDim];
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}
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final double[] sortedValues = values.clone();
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VariantTree.quickSort( sortedValues, 0, values.length-1 ); // BUGBUG: values.length or values.length-1
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final int lowPivotIndex = Math.round(0.40f * sortedValues.length);
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final int highPivotIndex = Math.round(0.60f * sortedValues.length);
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final double lowPivot = sortedValues[lowPivotIndex];
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final double highPivot = sortedValues[highPivotIndex];
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cutValue = highPivot;
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int numLow = 0;
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int numHigh = 0;
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for( int iii = 0; iii < data.length; iii++ ) {
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if( values[iii] < highPivot ) { numLow++; }
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if( values[iii] >= lowPivot ) { numHigh++; }
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}
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// If cutting here makes the bin too small then don't cut
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if( numLow < minBinSize || numHigh < minBinSize || (numLow == numHigh && numLow == data.length) ) {
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cutValue = sortedValues[0];
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right = new VariantTreeNode();
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right.cutData(data, depth+1, lastCutDepth, numAnnotations);
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} else {
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final VariantDatum[] leftData = new VariantDatum[numLow];
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final VariantDatum[] rightData = new VariantDatum[numHigh];
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int leftIndex = 0;
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int rightIndex = 0;
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for( int iii = 0; iii < data.length; iii++ ) {
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if( values[iii] < highPivot ) { leftData[leftIndex++] = data[iii]; }
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if( values[iii] >= lowPivot ) { rightData[rightIndex++] = data[iii]; }
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}
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left = new VariantTreeNode();
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right = new VariantTreeNode();
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left.cutData(leftData, depth+1, depth, numAnnotations);
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right.cutData(rightData, depth+1, depth, numAnnotations);
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}
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}
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}
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@ -68,8 +68,8 @@ public class ReadQualityScoreWalker extends ReadWalker<SAMRecord, SAMFileWriter>
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@Argument(fullName = "threshold", shortName = "th", doc="Flag reads whose read quality score is below this threshold", required = false)
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protected int qualityThreshold = 13;
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protected static BufferedReader inputReader = null;
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protected static String line = null;
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private BufferedReader inputReader = null;
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private static String line = null;
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public SAMRecord map( ReferenceContext ref, SAMRecord read, ReadMetaDataTracker metaDataTracker ) {
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return read; // all the work is done in the reduce step for this walker
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