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First Pool Caller exact model: silly straightforward math implementation of biallelic pool caller exact likelihood model, no attempt and any smartness or optimization, no support yet for generalized multiallelic form, just hooking up for testing

This commit is contained in:
Guillermo del Angel 2012-03-27 20:59:44 -04:00
parent ed322bd73f
commit 8f34412fb8
2 changed files with 7 additions and 3 deletions
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4
public/java/src/org/broadinstitute/sting/gatk/walkers/genotyper/ExactAFCalculationModel.java
View File

@ -152,7 +152,7 @@ public class ExactAFCalculationModel extends AlleleFrequencyCalculationModel {
@Override
public boolean equals(Object obj) {
return (obj instanceof ExactACcounts) ? Arrays.equals(counts, ((ExactACcounts)obj).counts) : false;
return (obj instanceof ExactACcounts) && Arrays.equals(counts, ((ExactACcounts)obj).counts);
}
@Override
@ -202,7 +202,7 @@ public class ExactAFCalculationModel extends AlleleFrequencyCalculationModel {
}
public boolean equals(Object obj) {
return (obj instanceof ExactACset) ? ACcounts.equals(((ExactACset)obj).ACcounts) : false;
return (obj instanceof ExactACset) && ACcounts.equals(((ExactACset)obj).ACcounts);
}
}

6
public/java/src/org/broadinstitute/sting/utils/MathUtils.java
View File

@ -49,6 +49,7 @@ public class MathUtils {
}
public static final double[] log10Cache;
public static final double[] log10FactorialCache;
private static final double[] jacobianLogTable;
private static final double JACOBIAN_LOG_TABLE_STEP = 0.001;
private static final double JACOBIAN_LOG_TABLE_INV_STEP = 1.0 / 0.001;
@ -59,11 +60,14 @@ public class MathUtils {
static {
log10Cache = new double[LOG10_CACHE_SIZE];
log10FactorialCache = new double[LOG10_CACHE_SIZE];
jacobianLogTable = new double[JACOBIAN_LOG_TABLE_SIZE];
log10Cache[0] = Double.NEGATIVE_INFINITY;
for (int k = 1; k < LOG10_CACHE_SIZE; k++)
for (int k = 1; k < LOG10_CACHE_SIZE; k++) {
log10Cache[k] = Math.log10(k);
log10FactorialCache[k] = log10FactorialCache[k-1] + log10Cache[k];
}
for (int k = 0; k < JACOBIAN_LOG_TABLE_SIZE; k++) {
jacobianLogTable[k] = Math.log10(1.0 + Math.pow(10.0, -((double) k) * JACOBIAN_LOG_TABLE_STEP));