Examples with DoubleMatrix2D cern.colt.matrix.DoubleMatrix2D used on opensource projects

Example 61 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project Gemma by PavlidisLab.

the class ComBat method run.

/**
 * @param parametric if false, use the non-parametric (slower) method for estimating the priors.
 * @return corrected data
 * @throws ComBatException combat problems
 */
public DoubleMatrix2D run(boolean parametric) throws ComBatException {
    StopWatch timer = new StopWatch();
    timer.start();
    final DoubleMatrix2D sdata = this.standardize(y, x);
    this.checkForProblems(sdata);
    if (timer.getTime() > 1000) {
        ComBat.log.info("Standardized");
    }
    timer.reset();
    timer.start();
    this.gammaHat(sdata);
    this.deltaHat(sdata);
    // assertEquals( 1.618, deltaHat.get( 0, 0 ), 0.001 );
    // gamma.bar <- apply(gamma.hat, 1, mean)
    gammaBar = new DoubleArrayList();
    t2 = new DoubleArrayList();
    for (int batchIndex = 0; batchIndex < gammaHat.rows(); batchIndex++) {
        double mean = DescriptiveWithMissing.mean(new DoubleArrayList(gammaHat.viewRow(batchIndex).toArray()));
        gammaBar.add(mean);
        t2.add(DescriptiveWithMissing.sampleVariance(new DoubleArrayList(gammaHat.viewRow(batchIndex).toArray()), mean));
    }
    // assertEquals( -0.092144, gammaBar.get( 0 ), 0.001 );
    // assertEquals( 0.2977, t2.get( 1 ), 0.001 );
    aPrior = this.aPrior(deltaHat);
    bPrior = this.bPrior(deltaHat);
    if (timer.getTime() > 1000) {
        ComBat.log.info("Computed priors");
    }
    // assertEquals( 17.4971, aPrior.get( 0 ), 0.0001 );
    // assertEquals( 4.514, bPrior.get( 1 ), 0.0001 );
    DoubleMatrix2D gammastar = new DenseDoubleMatrix2D(numBatches, numProbes);
    DoubleMatrix2D deltastar = new DenseDoubleMatrix2D(numBatches, numProbes);
    if (!parametric) {
        this.runNonParametric(sdata, gammastar, deltastar);
    } else {
        this.runParametric(sdata, gammastar, deltastar);
    }
    DoubleMatrix2D adjustedData = this.rawAdjust(sdata, gammastar, deltastar);
    // assertEquals( -0.95099, adjustedData.get( 18, 0 ), 0.0001 );
    // assertEquals( -0.30273984, adjustedData.get( 14, 6 ), 0.0001 );
    // assertEquals( 0.2097977, adjustedData.get( 7, 3 ), 0.0001 );
    // log.info( adjustedData );
    DoubleMatrix2D result = this.restoreScale(adjustedData);
    if (timer.getTime() > 1000) {
        ComBat.log.info("Done");
    }
    return result;
}

Example 62 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project Gemma by PavlidisLab.

the class ComBat method restoreScale.

private DoubleMatrix2D restoreScale(DoubleMatrix2D adjustedData) {
    DoubleMatrix2D ones = new DenseDoubleMatrix2D(1, numSamples);
    ones.assign(1.0);
    DoubleMatrix2D adj = solver.mult(varpooled.copy().assign(Functions.sqrt), ones);
    DoubleMatrix2D varRestore = adjustedData.assign(adj, Functions.mult);
    // log.info( varRestore );
    return varRestore.assign(standMean, Functions.plus);
}

Example 63 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project Gemma by PavlidisLab.

the class ComBat method deltaHat.

private void deltaHat(DoubleMatrix2D sdata) {
    int batchIndex;
    deltaHat = new DenseDoubleMatrix2D(numBatches, numProbes);
    batchIndex = 0;
    for (String batchId : batches.keySet()) {
        DoubleMatrix2D batchData = this.getBatchData(sdata, batchId);
        for (int j = 0; j < batchData.rows(); j++) {
            DoubleArrayList row = new DoubleArrayList(batchData.viewRow(j).toArray());
            double variance = DescriptiveWithMissing.sampleVariance(row, DescriptiveWithMissing.mean(row));
            deltaHat.set(batchIndex, j, variance);
        }
        batchIndex++;
    }
}

Example 64 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project Gemma by PavlidisLab.

the class ComBat method rawAdjust.

private DoubleMatrix2D rawAdjust(DoubleMatrix2D sdata, DoubleMatrix2D gammastar, DoubleMatrix2D deltastar) {
    int batchIndex;
    int batchNum = 0;
    DoubleMatrix2D adjustedData = new DenseDoubleMatrix2D(sdata.rows(), sdata.columns());
    for (String batchId : batches.keySet()) {
        DoubleMatrix2D batchData = this.getBatchData(sdata, batchId);
        DoubleMatrix2D Xbb = this.getBatchDesign(batchId);
        DoubleMatrix2D adjustedBatch = batchData.copy().assign(solver.transpose(solver.mult(Xbb, gammastar)), Functions.minus);
        DoubleMatrix1D deltaStarRow = deltastar.viewRow(batchNum);
        deltaStarRow.assign(Functions.sqrt);
        DoubleMatrix1D ones = new DenseDoubleMatrix1D(batchData.columns());
        ones.assign(1.0);
        DoubleMatrix2D divisor = solver.multOuter(deltaStarRow, ones, null);
        adjustedBatch.assign(divisor, Functions.div);
        /*
             * Now we have to put the data back in the right order -- the batches are all together.
             */
        Map<C, Integer> locations = originalLocationsInMatrix.get(batchId);
        for (batchIndex = 0; batchIndex < adjustedBatch.rows(); batchIndex++) {
            int j = 0;
            for (Integer index : locations.values()) {
                adjustedData.set(batchIndex, index, adjustedBatch.get(batchIndex, j));
                j++;
            }
        }
        batchNum++;
    }
    return adjustedData;
}

Example 65 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project Gemma by PavlidisLab.

the class ComBat method getBatchDesign.

private DoubleMatrix2D getBatchDesign(String batchId) {
    Collection<C> sampleNames = batches.get(batchId);
    DoubleMatrix2D result = new DenseDoubleMatrix2D(sampleNames.size(), batches.keySet().size());
    for (int j = 0; j < batches.keySet().size(); j++) {
        int i = 0;
        for (C sname : sampleNames) {
            DoubleMatrix1D rowInBatch = x.viewRow(data.getColIndexByName(sname));
            result.set(i, j, rowInBatch.get(j));
            i++;
        }
    }
    // log.info( result );
    return result;
}