Examples with Array2DRowRealMatrix org.apache.commons.math3.linear.Array2DRowRealMatrix used on opensource projects

Example 71 with Array2DRowRealMatrix

use of org.apache.commons.math3.linear.Array2DRowRealMatrix in project gatk by broadinstitute.

the class JointAFCRSegmenterUnitTest method testSegmentation.

@Test
public void testSegmentation() {
    final RandomGenerator rng = RandomGeneratorFactory.createRandomGenerator(new Random(563));
    // probability that a datum is a het i.e. #hets / (#hets + #targets)
    final double hetProportion = 0.25;
    final List<Double> trueWeights = Arrays.asList(0.2, 0.5, 0.3);
    final double[] trueMinorAlleleFractions = new double[] { 0.12, 0.32, 0.5 };
    final double[] trueLog2CopyRatios = new double[] { -2.0, 0.0, 1.7 };
    final List<AFCRHiddenState> trueJointStates = IntStream.range(0, trueLog2CopyRatios.length).mapToObj(n -> new AFCRHiddenState(trueMinorAlleleFractions[n], trueLog2CopyRatios[n])).collect(Collectors.toList());
    final double trueMemoryLength = 1e5;
    final double trueCauchyWidth = 0.2;
    final int initialNumCRStates = 20;
    final int initialNumAFStates = 20;
    final AlleleFractionGlobalParameters trueAFParams = new AlleleFractionGlobalParameters(1.0, 0.01, 0.01);
    final JointAFCRHMM trueJointModel = new JointAFCRHMM(trueJointStates, trueWeights, trueMemoryLength, trueAFParams, AllelicPanelOfNormals.EMPTY_PON, trueCauchyWidth);
    // generate joint truth
    final int chainLength = 10000;
    final List<SimpleInterval> positions = CopyRatioSegmenterUnitTest.randomPositions("chr1", chainLength, rng, trueMemoryLength / 4);
    final List<Integer> trueHiddenStates = trueJointModel.generateHiddenStateChain(positions);
    final List<AFCRHiddenState> trueAFCRSequence = trueHiddenStates.stream().map(trueJointModel::getHiddenStateValue).collect(Collectors.toList());
    final double[] trueCopyRatioSequence = trueAFCRSequence.stream().mapToDouble(AFCRHiddenState::getLog2CopyRatio).toArray();
    final double[] trueAlleleFractionSequence = trueAFCRSequence.stream().mapToDouble(AFCRHiddenState::getMinorAlleleFraction).toArray();
    // generate separate af and cr data
    final GammaDistribution biasGenerator = AlleleFractionSegmenterUnitTest.getGammaDistribution(trueAFParams, rng);
    final double outlierProbability = trueAFParams.getOutlierProbability();
    final AllelicCountCollection afData = new AllelicCountCollection();
    final List<Double> crData = new ArrayList<>();
    final List<Target> crTargets = new ArrayList<>();
    for (int n = 0; n < positions.size(); n++) {
        final SimpleInterval position = positions.get(n);
        final AFCRHiddenState jointState = trueAFCRSequence.get(n);
        final double minorFraction = jointState.getMinorAlleleFraction();
        final double log2CopyRatio = jointState.getLog2CopyRatio();
        if (rng.nextDouble() < hetProportion) {
            // het datum
            afData.add(AlleleFractionSegmenterUnitTest.generateAllelicCount(minorFraction, position, rng, biasGenerator, outlierProbability));
        } else {
            //target datum
            crTargets.add(new Target(position));
            crData.add(CopyRatioSegmenterUnitTest.generateData(trueCauchyWidth, log2CopyRatio, rng));
        }
    }
    final ReadCountCollection rcc = new ReadCountCollection(crTargets, Arrays.asList("SAMPLE"), new Array2DRowRealMatrix(crData.stream().mapToDouble(x -> x).toArray()));
    final JointAFCRSegmenter segmenter = JointAFCRSegmenter.createJointSegmenter(initialNumCRStates, rcc, initialNumAFStates, afData, AllelicPanelOfNormals.EMPTY_PON);
    final TargetCollection<SimpleInterval> tc = new HashedListTargetCollection<>(positions);
    final List<Pair<SimpleInterval, AFCRHiddenState>> segmentation = segmenter.findSegments();
    final List<ACNVModeledSegment> jointSegments = segmentation.stream().map(pair -> {
        final SimpleInterval position = pair.getLeft();
        final AFCRHiddenState jointState = pair.getRight();
        final PosteriorSummary crSummary = PerformJointSegmentation.errorlessPosterior(jointState.getLog2CopyRatio());
        final PosteriorSummary afSummary = PerformJointSegmentation.errorlessPosterior(jointState.getMinorAlleleFraction());
        return new ACNVModeledSegment(position, crSummary, afSummary);
    }).collect(Collectors.toList());
    final double[] segmentCopyRatios = jointSegments.stream().flatMap(s -> Collections.nCopies(tc.targetCount(s.getInterval()), s.getSegmentMeanPosteriorSummary().getCenter()).stream()).mapToDouble(x -> x).toArray();
    final double[] segmentMinorFractions = jointSegments.stream().flatMap(s -> Collections.nCopies(tc.targetCount(s.getInterval()), s.getMinorAlleleFractionPosteriorSummary().getCenter()).stream()).mapToDouble(x -> x).toArray();
    final double averageMinorFractionError = Arrays.stream(MathArrays.ebeSubtract(trueAlleleFractionSequence, segmentMinorFractions)).map(Math::abs).average().getAsDouble();
    final double averageCopyRatioError = Arrays.stream(MathArrays.ebeSubtract(trueCopyRatioSequence, segmentCopyRatios)).map(Math::abs).average().getAsDouble();
    Assert.assertEquals(averageMinorFractionError, 0, 0.04);
    Assert.assertEquals(averageCopyRatioError, 0, 0.04);
}

Example 72 with Array2DRowRealMatrix

use of org.apache.commons.math3.linear.Array2DRowRealMatrix in project gatk-protected by broadinstitute.

the class PreAdapterOrientationScorer method countOrientationBiasMetricsOverContext.

/**
     * Gets PreAdapterQ collapsed over contexts.
     *
     * rows {PRO, CON} x cols {ref, alt}
     * @param metrics metrics usually read from a picard preadapter detail file.
     * @return mapping to score all orientation bias artifact modes to a PreAdapterQ score.  This score can be used as a bam-file level score for level of artifacts.
     */
@VisibleForTesting
static Map<Transition, RealMatrix> countOrientationBiasMetricsOverContext(final List<SequencingArtifactMetrics.PreAdapterDetailMetrics> metrics) {
    Utils.nonNull(metrics, "Input metrics cannot be null");
    // Artifact mode to a matrix
    final Map<Transition, RealMatrix> result = new HashMap<>();
    // Collapse over context
    for (SequencingArtifactMetrics.PreAdapterDetailMetrics metric : metrics) {
        final Transition key = Transition.transitionOf(metric.REF_BASE, metric.ALT_BASE);
        result.putIfAbsent(key, new Array2DRowRealMatrix(2, 2));
        final RealMatrix preAdapterCountMatrix = result.get(key);
        preAdapterCountMatrix.addToEntry(PreAdapterOrientationScorer.PRO, PreAdapterOrientationScorer.ALT, metric.PRO_ALT_BASES);
        preAdapterCountMatrix.addToEntry(PreAdapterOrientationScorer.CON, PreAdapterOrientationScorer.ALT, metric.CON_ALT_BASES);
        preAdapterCountMatrix.addToEntry(PreAdapterOrientationScorer.PRO, PreAdapterOrientationScorer.REF, metric.PRO_REF_BASES);
        preAdapterCountMatrix.addToEntry(PreAdapterOrientationScorer.CON, PreAdapterOrientationScorer.REF, metric.CON_REF_BASES);
    }
    return result;
}

Example 73 with Array2DRowRealMatrix

use of org.apache.commons.math3.linear.Array2DRowRealMatrix in project gatk-protected by broadinstitute.

the class MatrixSummaryUtilsUnitTest method testGetRowAndColumnMedians.

@Test(dataProvider = "rowAndColumnMedianTestData")
public void testGetRowAndColumnMedians(double[][] testdata, double[] gtRowMedian, double[] gtColumnMedian) {
    final RealMatrix tmp = new Array2DRowRealMatrix(testdata);
    PoNTestUtils.assertEqualsDoubleArrays(MatrixSummaryUtils.getRowMedians(tmp), gtRowMedian);
    PoNTestUtils.assertEqualsDoubleArrays(MatrixSummaryUtils.getColumnMedians(tmp), gtColumnMedian);
}

Example 74 with Array2DRowRealMatrix

use of org.apache.commons.math3.linear.Array2DRowRealMatrix in project gatk-protected by broadinstitute.

the class HDF5LibraryUnitTest method testCreateLargeMatrix.

@Test
public void testCreateLargeMatrix() {
    // Creates a large PoN of junk values and simply tests that these can be written and read.
    // Make a big, fake set of read counts.
    final int numRows = 2500000;
    final int numCols = 10;
    final double mean = 3e-7;
    final double sigma = 1e-9;
    final RealMatrix bigCounts = createMatrixOfGaussianValues(numRows, numCols, mean, sigma);
    final File tempOutputHD5 = IOUtils.createTempFile("big-ol-", ".hd5");
    final HDF5File hdf5File = new HDF5File(tempOutputHD5, HDF5File.OpenMode.CREATE);
    final String hdf5Path = "/test/m";
    hdf5File.makeDoubleMatrix(hdf5Path, bigCounts.getData());
    hdf5File.close();
    final HDF5File hdf5FileForReading = new HDF5File(tempOutputHD5, HDF5File.OpenMode.READ_ONLY);
    final double[][] result = hdf5FileForReading.readDoubleMatrix(hdf5Path);
    final RealMatrix resultAsRealMatrix = new Array2DRowRealMatrix(result);
    Assert.assertTrue(resultAsRealMatrix.getRowDimension() == numRows);
    Assert.assertTrue(resultAsRealMatrix.getColumnDimension() == numCols);
    final RealMatrix readMatrix = new Array2DRowRealMatrix(result);
    PoNTestUtils.assertEqualsMatrix(readMatrix, bigCounts, false);
}

Example 75 with Array2DRowRealMatrix

use of org.apache.commons.math3.linear.Array2DRowRealMatrix in project gatk-protected by broadinstitute.

the class GATKProtectedMathUtilsTest method testRowInf.

@Test
public void testRowInf() {
    final double[][] array = { { 1, 2, Double.POSITIVE_INFINITY }, { 5, 5, 5 }, { 7, 8, 9 }, { -15, 2, 12 } };
    final double[] guess = GATKProtectedMathUtils.rowSums(new Array2DRowRealMatrix(array));
    final double[] gt = { Double.POSITIVE_INFINITY, 15, 24, -1 };
    Assert.assertEquals(guess.length, 4);
    Assert.assertEquals(guess[1], gt[1]);
    Assert.assertEquals(guess[2], gt[2]);
    Assert.assertEquals(guess[3], gt[3]);
    Assert.assertTrue(Double.isInfinite(guess[0]));
}