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AnalyzeCovariates gets the same performance improvements as the recalibrator. NHashMap class is removed completely. 

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2483 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
rpoplin 2009-12-30 18:10:10 +00:00
parent 9b2733a54a
commit 80658fd99e
3 changed files with 35 additions and 181 deletions
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42
java/src/org/broadinstitute/sting/analyzecovariates/AnalysisDataManager.java
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@ -1,10 +1,9 @@
package org.broadinstitute.sting.analyzecovariates;
import org.broadinstitute.sting.gatk.walkers.recalibration.RecalDatum;
import org.broadinstitute.sting.utils.NHashMap;
import org.broadinstitute.sting.utils.NestedHashMap;
import java.util.ArrayList;
import java.util.List;
/**
* Created by IntelliJ IDEA.
@ -17,17 +16,17 @@ import java.util.List;
public class AnalysisDataManager {
private NHashMap<RecalDatum> dataCollapsedReadGroup; // Table where everything except read group has been collapsed
private ArrayList<NHashMap<RecalDatum>> dataCollapsedByCovariate; // Tables where everything except read group and given covariate has been collapsed
private NestedHashMap dataCollapsedReadGroup; // Table where everything except read group has been collapsed
private ArrayList<NestedHashMap> dataCollapsedByCovariate; // Tables where everything except read group and given covariate has been collapsed
AnalysisDataManager() {
}
AnalysisDataManager( final int numCovariates ) {
dataCollapsedReadGroup = new NHashMap<RecalDatum>();
dataCollapsedByCovariate = new ArrayList<NHashMap<RecalDatum>>();
dataCollapsedReadGroup = new NestedHashMap();
dataCollapsedByCovariate = new ArrayList<NestedHashMap>();
for( int iii = 0; iii < numCovariates - 1; iii++ ) { // readGroup isn't counted here, its table is separate
dataCollapsedByCovariate.add( new NHashMap<RecalDatum>() );
dataCollapsedByCovariate.add( new NestedHashMap() );
}
}
@ -37,35 +36,34 @@ public class AnalysisDataManager {
* @param fullDatum The RecalDatum which is the data for this mapping
* @param IGNORE_QSCORES_LESS_THAN The threshold in report quality for adding to the aggregate collapsed table
*/
public final void addToAllTables( final List<? extends Comparable> key, final RecalDatum fullDatum, final int IGNORE_QSCORES_LESS_THAN ) {
public final void addToAllTables( final Object[] key, final RecalDatum fullDatum, final int IGNORE_QSCORES_LESS_THAN ) {
int qscore = Integer.parseInt( key.get(1).toString() );
ArrayList<Comparable> newKey;
int qscore = Integer.parseInt( key[1].toString() );
RecalDatum collapsedDatum;
final Object[] readGroupCollapsedKey = new Object[1];
final Object[] covariateCollapsedKey = new Object[2];
if( !(qscore < IGNORE_QSCORES_LESS_THAN) ) {
// Create dataCollapsedReadGroup, the table where everything except read group has been collapsed
newKey = new ArrayList<Comparable>();
newKey.add( key.get(0) ); // Make a new key with just the read group
collapsedDatum = dataCollapsedReadGroup.get( newKey );
readGroupCollapsedKey[0] = key[0]; // Make a new key with just the read group
collapsedDatum = (RecalDatum)dataCollapsedReadGroup.get( readGroupCollapsedKey );
if( collapsedDatum == null ) {
dataCollapsedReadGroup.put( newKey, new RecalDatum(fullDatum) );
dataCollapsedReadGroup.put( new RecalDatum(fullDatum), readGroupCollapsedKey );
} else {
collapsedDatum.combine( fullDatum ); // using combine instead of increment in order to calculate overall aggregateQReported
}
}
// Create dataCollapsedByCovariate's, the tables where everything except read group, quality score, and given covariate has been collapsed
// Create dataCollapsedByCovariate's, the tables where everything except read group and given covariate has been collapsed
for( int iii = 0; iii < dataCollapsedByCovariate.size(); iii++ ) {
if( iii == 0 || !(qscore < IGNORE_QSCORES_LESS_THAN) ) { // use all data for the plot versus reported quality, but not for the other plots versus cycle and etc.
newKey = new ArrayList<Comparable>();
newKey.add( key.get(0) ); // Make a new key with the read group ...
Comparable theCovariateElement = key.get(iii + 1); // and the given covariate
covariateCollapsedKey[0] = key[0]; // Make a new key with the read group ...
Object theCovariateElement = key[iii + 1]; // and the given covariate
if( theCovariateElement != null ) {
newKey.add( theCovariateElement );
collapsedDatum = dataCollapsedByCovariate.get(iii).get( newKey );
covariateCollapsedKey[1] = theCovariateElement;
collapsedDatum = (RecalDatum)dataCollapsedByCovariate.get(iii).get( covariateCollapsedKey );
if( collapsedDatum == null ) {
dataCollapsedByCovariate.get(iii).put( newKey, new RecalDatum(fullDatum) );
dataCollapsedByCovariate.get(iii).put( new RecalDatum(fullDatum), covariateCollapsedKey );
} else {
collapsedDatum.combine( fullDatum );
}
@ -79,7 +77,7 @@ public class AnalysisDataManager {
* @param covariate Which covariate indexes the desired collapsed HashMap
* @return The desired collapsed HashMap
*/
public final NHashMap<RecalDatum> getCollapsedTable( final int covariate ) {
public final NestedHashMap getCollapsedTable( final int covariate ) {
if( covariate == 0) {
return dataCollapsedReadGroup; // Table where everything except read group has been collapsed
} else {

35
java/src/org/broadinstitute/sting/analyzecovariates/AnalyzeCovariates.java
View File

@ -5,10 +5,10 @@ import org.broadinstitute.sting.utils.PackageUtils;
import org.broadinstitute.sting.utils.xReadLines;
import org.broadinstitute.sting.utils.cmdLine.CommandLineProgram;
import org.broadinstitute.sting.utils.cmdLine.Argument;
import org.broadinstitute.sting.utils.NHashMap;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.regex.Pattern;
import java.io.*;
@ -169,12 +169,12 @@ class AnalyzeCovariatesCLP extends CommandLineProgram {
" --Perhaps the read group string contains a comma and isn't being parsed correctly.");
}
ArrayList<Comparable> key = new ArrayList<Comparable>();
Object[] key = new Object[requestedCovariates.size()];
Covariate cov;
int iii;
for( iii = 0; iii < requestedCovariates.size(); iii++ ) {
cov = requestedCovariates.get( iii );
key.add( cov.getValue( vals[iii] ) );
key[iii] = cov.getValue( vals[iii] );
}
// Create a new datum using the number of observations, number of mismatches, and reported quality score
RecalDatum datum = new RecalDatum( Long.parseLong( vals[iii] ), Long.parseLong( vals[iii + 1] ), Double.parseDouble( vals[1] ), 0.0 );
@ -188,12 +188,11 @@ class AnalyzeCovariatesCLP extends CommandLineProgram {
int numReadGroups = 0;
// for each read group
NHashMap<RecalDatum> readGroupTable = dataManager.getCollapsedTable(0);
for( List<? extends Comparable> readGroupKey : readGroupTable.keySet() ) {
for( Object readGroupKey : dataManager.getCollapsedTable(0).data.keySet() ) {
if(NUM_READ_GROUPS_TO_PROCESS == -1 || ++numReadGroups <= NUM_READ_GROUPS_TO_PROCESS) {
String readGroup = readGroupKey.get(0).toString();
RecalDatum readGroupDatum = readGroupTable.get(readGroupKey);
String readGroup = readGroupKey.toString();
RecalDatum readGroupDatum = (RecalDatum) dataManager.getCollapsedTable(0).data.get(readGroupKey);
System.out.print("Writing out data tables for read group: " + readGroup + "\twith " + readGroupDatum.getNumObservations() + " observations" );
System.out.println("\tand aggregate residual error = " + String.format("%.3f", readGroupDatum.empiricalQualDouble(0) - readGroupDatum.getEstimatedQReported()));
@ -214,17 +213,13 @@ class AnalyzeCovariatesCLP extends CommandLineProgram {
// Output the header
output.println("Covariate\tQreported\tQempirical\tnMismatches\tnBases");
// Loop through the covariate table looking for keys with matching read groups
// BUGBUG: hopefully rewrite this to be more efficient
for( List<? extends Comparable> covariateKey : dataManager.getCollapsedTable(iii).keySet() ) {
if( covariateKey.get(0).toString().equals(readGroup) ) {
output.print( covariateKey.get(1).toString() + "\t" ); // Covariate
RecalDatum thisDatum = dataManager.getCollapsedTable(iii).get(covariateKey);
output.print( String.format("%.3f", thisDatum.getEstimatedQReported()) + "\t" ); // Qreported
output.print( String.format("%.3f", thisDatum.empiricalQualDouble(0)) + "\t" ); // Qempirical
output.print( thisDatum.getNumMismatches() + "\t" ); // nMismatches
output.println( thisDatum.getNumObservations() ); // nBases
}
for( Object covariateKey : ((Map)dataManager.getCollapsedTable(iii).data.get(readGroupKey)).keySet()) {
output.print( covariateKey.toString() + "\t" ); // Covariate
RecalDatum thisDatum = (RecalDatum)((Map)dataManager.getCollapsedTable(iii).data.get(readGroupKey)).get(covariateKey);
output.print( String.format("%.3f", thisDatum.getEstimatedQReported()) + "\t" ); // Qreported
output.print( String.format("%.3f", thisDatum.empiricalQualDouble(0)) + "\t" ); // Qempirical
output.print( thisDatum.getNumMismatches() + "\t" ); // nMismatches
output.println( thisDatum.getNumObservations() ); // nBases
}
// Close the PrintStream
@ -242,11 +237,11 @@ class AnalyzeCovariatesCLP extends CommandLineProgram {
int numReadGroups = 0;
// for each read group
for( List<? extends Comparable> readGroupList : dataManager.getCollapsedTable(0).keySet() ) {
for( Object readGroupKey : dataManager.getCollapsedTable(0).data.keySet() ) {
if(NUM_READ_GROUPS_TO_PROCESS == -1 || ++numReadGroups <= NUM_READ_GROUPS_TO_PROCESS) {
String readGroup = readGroupList.get(0).toString();
String readGroup = readGroupKey.toString();
System.out.println("Analyzing read group: " + readGroup);
// for each covariate

139
java/src/org/broadinstitute/sting/utils/NHashMap.java
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@ -1,139 +0,0 @@
package org.broadinstitute.sting.utils;
import java.util.*;
/*
* Copyright (c) 2009 The Broad Institute
*
* Permission is hereby granted, free of charge, to any person
* obtaining a copy of this software and associated documentation
* files (the "Software"), to deal in the Software without
* restriction, including without limitation the rights to use,
* copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the
* Software is furnished to do so, subject to the following
* conditions:
*
* The above copyright notice and this permission notice shall be
* included in all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
* OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
* NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
* HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
* WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
* OTHER DEALINGS IN THE SOFTWARE.
*/
/**
* Created by IntelliJ IDEA.
* User: rpoplin
* Date: Oct 30, 2009
*
* A HashMap that maps a list of comparables to any Object <T>.
* There is functionality for the mappings to be given back to you in sorted order.
*/
public class NHashMap<T> extends HashMap<List<? extends Comparable>, T> {
private static final long serialVersionUID = 1L; // Added by Eclipse
private ArrayList<ArrayList<Comparable>> keyLists;
public NHashMap() {
super();
keyLists = null;
}
public NHashMap( int initialCapacity, float loadingFactor ) {
super( initialCapacity, loadingFactor );
keyLists = null;
}
// This method is here only to help facilitate outputting the mappings in sorted order
public T sortedPut(List<? extends Comparable> key, T value) {
if( keyLists == null ) {
keyLists = new ArrayList<ArrayList<Comparable>>();
for( Comparable comp : key ) {
keyLists.add( new ArrayList<Comparable>() );
}
}
ArrayList<Comparable> thisList;
for( int iii = 0; iii < key.size(); iii++ ) {
thisList = keyLists.get( iii );
if( thisList == null ) {
thisList = new ArrayList<Comparable>();
}
if( !thisList.contains( key.get( iii ) ) ) {
thisList.add( key.get(iii ) );
}
}
return super.put( key, value );
}
public ArrayList<Pair<List<? extends Comparable>, T>> entrySetSorted() {
ArrayList<Pair<List<? extends Comparable>, T>> theSet = new ArrayList<Pair<List<? extends Comparable>, T>>();
for( ArrayList<Comparable> list : keyLists ) {
Collections.sort(list);
}
int[] keyIndex = new int[ keyLists.size() ];
int[] maxIndex = new int[ keyLists.size() ];
for( int iii = 0; iii < keyLists.size(); iii++ ) {
keyIndex[iii] = 0;
maxIndex[iii] = keyLists.get(iii).size();
}
// Try all the possible keys in sorted order, add them to the output set if they are in the hashMap
boolean triedAllKeys = false;
ArrayList<Comparable> newKey = null;
while( !triedAllKeys ) {
newKey = new ArrayList<Comparable>();
for( int iii = 0; iii < keyLists.size(); iii++ ) {
newKey.add(keyLists.get(iii).get(keyIndex[iii]));
}
T value = this.get( newKey );
if( value!= null ) {
theSet.add(new Pair<List<? extends Comparable>,T>( newKey, value ) );
}
// Increment the keyIndex
keyIndex[keyLists.size() - 1]++;
for( int iii = keyLists.size() - 1; iii >= 0; iii-- ) {
if( keyIndex[iii] >= maxIndex[iii] ) { // Carry it forward
keyIndex[iii] = 0;
if( iii > 0 ) {
keyIndex[iii-1]++;
} else {
triedAllKeys = true;
break;
}
} else {
break;
}
}
}
return theSet;
}
// Used to make the key from a list of <T> objects
public static <T> List<T> makeList(T... args) {
List<T> list = new ArrayList<T>();
for( T arg : args )
{
list.add(arg);
}
return list;
}
}