/**
* Constructs a new {@code GprobsStatistics} instance from the specified scaled genotype
* probabilities.
*
* @param gv scaled sample posterior genotype probabilities.
* @param marker a marker index
* @throws IndexOutOfBoundsException if {@code marker<0 || marker>=gv.nMarkers()}
*/
public GprobsStatistics(GenotypeValues gv, int marker) {
int nAlleles = gv.marker(marker).nAlleles();
this.marker = gv.marker(marker);
this.nSamples = gv.nSamples();
this.alleleFreq = new float[nAlleles];
float[] gtProbs = new float[3];
for (int j = 0; j < this.nSamples; ++j) {
setProbs(gv, marker, j, gtProbs, alleleFreq);
int call = maxIndex(gtProbs, random);
float exp = (gtProbs[1] + 2 * gtProbs[2]);
float expSquare = (gtProbs[1] + 4 * gtProbs[2]);
sumCall += call;
sumSquareCall += call * call;
sumExpected += exp;
sumExpectedSquare += expSquare;
sumSquareExpected += (exp * exp);
sumCallExpected += (call * exp);
}
divideBySum(alleleFreq);
}
private static void setProbs(
GenotypeValues gv, int marker, int sample, float[] gtProbs, float[] alleleFreq) {
Arrays.fill(gtProbs, 0.0f);
int nGt = gv.marker(marker).nGenotypes();
float sum = 0.0f;
for (int gt = 0; gt < nGt; ++gt) {
sum += gv.value(marker, sample, gt);
}
int gt = -1;
for (int a2 = 0; a2 < alleleFreq.length; ++a2) {
for (int a1 = 0; a1 < a2; ++a1) {
float gprob = gv.value(marker, sample, ++gt) / sum;
alleleFreq[a1] += gprob;
alleleFreq[a2] += gprob;
gtProbs[(a1 == 0) ? 1 : 2] += gprob;
}
float gprob = gv.value(marker, sample, ++gt) / sum;
alleleFreq[a2] += 2 * gprob;
gtProbs[(a2 == 0) ? 0 : 2] += gprob;
}
}
