Examples with HypergeometricDistribution org.apache.commons.math3.distribution.HypergeometricDistribution used on opensource projects

Example 1 with HypergeometricDistribution

use of org.apache.commons.math3.distribution.HypergeometricDistribution in project gatk by broadinstitute.

the class FisherExactTest method twoSidedPValue.

/**
     * Computes the 2-sided pvalue of the Fisher's exact test on a normalized table that ensures that the sum of
     * all four entries is less than 2 * 200.
     */
public static double twoSidedPValue(final int[][] normalizedTable) {
    Utils.nonNull(normalizedTable);
    Utils.validateArg(normalizedTable.length == 2, () -> "input must be 2x2 " + Arrays.deepToString(normalizedTable));
    Utils.validateArg(normalizedTable[0] != null && normalizedTable[0].length == 2, () -> "input must be 2x2 " + Arrays.deepToString(normalizedTable));
    Utils.validateArg(normalizedTable[1] != null && normalizedTable[1].length == 2, () -> "input must be 2x2 " + Arrays.deepToString(normalizedTable));
    //Note: this implementation follows the one in R base package
    final int[][] x = normalizedTable;
    final int m = x[0][0] + x[0][1];
    final int n = x[1][0] + x[1][1];
    final int k = x[0][0] + x[1][0];
    final int lo = Math.max(0, k - n);
    final int hi = Math.min(k, m);
    final IndexRange support = new IndexRange(lo, hi + 1);
    if (support.size() <= 1) {
        //special case, support has only one value
        return 1.0;
    }
    final AbstractIntegerDistribution dist = new HypergeometricDistribution(null, m + n, m, k);
    final double[] logds = support.mapToDouble(dist::logProbability);
    final double threshold = logds[x[0][0] - lo] * REL_ERR;
    final double[] log10ds = DoubleStream.of(logds).filter(d -> d <= threshold).map(MathUtils::logToLog10).toArray();
    final double pValue = MathUtils.sumLog10(log10ds);
    // min is necessary as numerical precision can result in pValue being slightly greater than 1.0
    return Math.min(pValue, 1.0);
}