Examples with Median org.apache.commons.math3.stat.descriptive.rank.Median used on opensource projects

Example 16 with Median

use of org.apache.commons.math3.stat.descriptive.rank.Median in project gatk-protected by broadinstitute.

the class CoveragePoNQCUtils method getContigToMedianCRMap.

@VisibleForTesting
static Map<String, Double> getContigToMedianCRMap(final ReadCountCollection readCountCollection) {
    final List<String> allContigsPresent = retrieveAllContigsPresent(readCountCollection);
    final Map<String, Double> contigToMedian = new LinkedHashMap<>();
    for (String contig : allContigsPresent) {
        final ReadCountCollection oneContigReadCountCollection = readCountCollection.subsetTargets(readCountCollection.targets().stream().filter(t -> t.getContig().equals(contig)).collect(Collectors.toSet()));
        final double[] flatCounts = Doubles.concat(oneContigReadCountCollection.counts().getData());
        // Put into CRSpace
        final double[] flatCountsInCRSpace = DoubleStream.of(flatCounts).map(d -> Math.pow(2, d)).toArray();
        contigToMedian.put(contig, new Median().evaluate(flatCountsInCRSpace));
    }
    return contigToMedian;
}

Example 17 with Median

use of org.apache.commons.math3.stat.descriptive.rank.Median in project gatk-protected by broadinstitute.

the class PCATangentNormalizationUtils method composeTangentNormalizationInputMatrix.

/**
     * Prepares the data to perform tangent normalization.
     * <p>
     * This is done by count group or column:
     *   <ol>
     *     </li>we divide counts by the column mean,</li>
     *     </li>then we transform value to their log_2,</li>
     *     </li>and finally we center them around the median.</li>
     *   </ol>
     * </p>
     *
     * @param matrix input matrix.
     * @return never {@code null}.
     */
private static RealMatrix composeTangentNormalizationInputMatrix(final RealMatrix matrix) {
    final RealMatrix result = matrix.copy();
    // step 1: divide by column means and log_2 transform
    final double[] columnMeans = GATKProtectedMathUtils.columnMeans(matrix);
    result.walkInOptimizedOrder(new DefaultRealMatrixChangingVisitor() {

        @Override
        public double visit(final int row, final int column, final double value) {
            return truncatedLog2(value / columnMeans[column]);
        }
    });
    // step 2: subtract column medians
    final double[] columnMedians = IntStream.range(0, matrix.getColumnDimension()).mapToDouble(c -> new Median().evaluate(result.getColumn(c))).toArray();
    result.walkInOptimizedOrder(new DefaultRealMatrixChangingVisitor() {

        @Override
        public double visit(final int row, final int column, final double value) {
            return value - columnMedians[column];
        }
    });
    return result;
}

Example 18 with Median

use of org.apache.commons.math3.stat.descriptive.rank.Median in project gatk-protected by broadinstitute.

the class ReadCountCollectionUtilsUnitTest method testImputeZeroCounts.

@Test(dataProvider = "tooManyZerosData")
public void testImputeZeroCounts(final ReadCountCollection readCounts) {
    final Median median = new Median();
    final RealMatrix counts = readCounts.counts();
    final double[] targetNonZeroMedians = IntStream.range(0, counts.getRowDimension()).mapToDouble(i -> median.evaluate(DoubleStream.of(counts.getRow(i)).filter(d -> d != 0.0).toArray())).toArray();
    final double[][] expected = new double[counts.getRowDimension()][];
    final double[][] original = counts.getData();
    for (int i = 0; i < expected.length; i++) {
        final double[] rowCounts = counts.getRow(i).clone();
        expected[i] = rowCounts;
        for (int j = 0; j < expected[i].length; j++) {
            if (expected[i][j] == 0.0) {
                expected[i][j] = targetNonZeroMedians[i];
            }
        }
    }
    ReadCountCollectionUtils.imputeZeroCountsAsTargetMedians(readCounts, NULL_LOGGER);
    final RealMatrix newCounts = readCounts.counts();
    Assert.assertEquals(newCounts.getColumnDimension(), expected[0].length);
    Assert.assertEquals(newCounts.getRowDimension(), expected.length);
    for (int i = 0; i < expected.length; i++) {
        for (int j = 0; j < expected[i].length; j++) {
            Assert.assertEquals(newCounts.getEntry(i, j), expected[i][j], "i,j == " + i + "," + j + " " + original[i][j]);
        }
    }
}

Example 19 with Median

use of org.apache.commons.math3.stat.descriptive.rank.Median in project gatk-protected by broadinstitute.

the class ReadCountCollectionUtilsUnitTest method testExtremeMedianColumnsData.

@Test(dataProvider = "readCountAndPercentileData")
public void testExtremeMedianColumnsData(final ReadCountCollection readCount, final double percentile) {
    final Median median = new Median();
    final RealMatrix counts = readCount.counts();
    final double[] columnMedians = IntStream.range(0, counts.getColumnDimension()).mapToDouble(i -> median.evaluate(counts.getColumn(i))).toArray();
    final double top = new Percentile(100 - percentile).evaluate(columnMedians);
    final double bottom = new Percentile(percentile).evaluate(columnMedians);
    final Boolean[] toBeKept = DoubleStream.of(columnMedians).mapToObj(d -> d <= top && d >= bottom).toArray(Boolean[]::new);
    final int toBeKeptCount = (int) Stream.of(toBeKept).filter(b -> b).count();
    final ReadCountCollection result = ReadCountCollectionUtils.removeColumnsWithExtremeMedianCounts(readCount, percentile, NULL_LOGGER);
    Assert.assertEquals(result.columnNames().size(), toBeKeptCount);
    int nextIndex = 0;
    for (int i = 0; i < toBeKept.length; i++) {
        if (toBeKept[i]) {
            int index = result.columnNames().indexOf(readCount.columnNames().get(i));
            Assert.assertEquals(index, nextIndex++);
            Assert.assertEquals(counts.getColumn(i), result.counts().getColumn(index));
        } else {
            Assert.assertEquals(result.columnNames().indexOf(readCount.columnNames().get(i)), -1);
        }
    }
}

Example 20 with Median

use of org.apache.commons.math3.stat.descriptive.rank.Median in project FSensor by KalebKE.

the class CalibrationUtil method getCalibration.

/**
 * Transforms the ellipsoid into a sphere with the offset vector = [0,0,0]
 * and the radii vector = [1,1,1].
 *
 * @param fitPoints the representation of the calibration ellipsoid
 */
public static Calibration getCalibration(FitPoints fitPoints) {
    // The scalar values to transform the radii vector into [1,1,1]
    RealMatrix scalar = new Array2DRowRealMatrix(3, 3);
    // RIV determines the magnitude of the radii. We have to know the
    // magnitudes because the eigenvalues, and thus the radii, are returned
    // in ascending order. Without knowing the magnitudes, we wouldn't know
    // what radii to apply to what axis.
    // Find the max and minimum magnitudes.
    double max = fitPoints.riv.getEntry(0);
    double min = fitPoints.riv.getEntry(0);
    // The indexes of the maximum, median, and minimum radii.
    // Note that these are the opposite of the max and min
    // because a smaller riv value means a greater magnitude.
    int maxi = 0, midi = 0, mini = 0;
    // Find max and min radii
    for (int i = 0; i < fitPoints.riv.getDimension(); i++) {
        if (fitPoints.riv.getEntry(i) > max) {
            max = fitPoints.riv.getEntry(i);
            mini = i;
        }
        if (fitPoints.riv.getEntry(i) < min) {
            min = fitPoints.riv.getEntry(i);
            maxi = i;
        }
    }
    // Find median radii
    for (int i = 0; i < fitPoints.riv.getDimension(); i++) {
        if (fitPoints.riv.getEntry(i) < max && fitPoints.riv.getEntry(i) > min) {
            midi = i;
        }
    }
    // Create the scalar vector in the correct orientation.
    scalar.setEntry(0, 0, 1 / fitPoints.radii.getEntry(mini));
    scalar.setEntry(1, 1, 1 / fitPoints.radii.getEntry(midi));
    scalar.setEntry(2, 2, 1 / fitPoints.radii.getEntry(maxi));
    return new Calibration(scalar, fitPoints.center);
}