Examples with FourierLinearOperatorNDArray org.broadinstitute.hellbender.tools.coveragemodel.linalg.FourierLinearOperatorNDArray used on opensource projects

Example 1 with FourierLinearOperatorNDArray

use of org.broadinstitute.hellbender.tools.coveragemodel.linalg.FourierLinearOperatorNDArray in project gatk-protected by broadinstitute.

the class CoverageModelEMWorkspace method getBiasCovariatesRegularizedLinearOperators.

/**
     * Returns the pair of (linear operator, preconditioner) invoked in the M-step update of bias
     * covariates in w/ regularization
     *
     * @return a pair of linear operators
     */
@EvaluatesRDD
private ImmutablePair<GeneralLinearOperator<INDArray>, GeneralLinearOperator<INDArray>> getBiasCovariatesRegularizedLinearOperators() {
    final INDArray Q_ll, Q_tll, Z_ll;
    final GeneralLinearOperator<INDArray> linop, precond;
    final FourierLinearOperatorNDArray regularizerFourierLinearOperator = createRegularizerFourierLinearOperator();
    switch(config.getWSolverType()) {
        case LOCAL:
            /* fetch the required INDArrays */
            Q_ll = mapWorkersAndReduce(cb -> cb.getINDArrayFromCache(CoverageModelEMComputeBlock.CoverageModelICGCacheNode.sum_Q_ll), INDArray::add).div(numTargets);
            Q_tll = fetchFromWorkers(CoverageModelEMComputeBlock.CoverageModelICGCacheNode.Q_tll, 0);
            Z_ll = sampleBiasLatentPosteriorSecondMoments.sum(0);
            /* instantiate the local implementation of linear operators */
            linop = new CoverageModelWLinearOperatorLocal(Q_tll, Z_ll, regularizerFourierLinearOperator);
            precond = new CoverageModelWPreconditionerLocal(Q_ll, Z_ll, regularizerFourierLinearOperator, numTargets);
            return ImmutablePair.of(linop, precond);
        case SPARK:
            if (!sparkContextIsAvailable) {
                throw new UserException("The Spark W solver is only available in the Spark mode");
            }
            /* fetch the required INDArrays */
            Q_ll = mapWorkersAndReduce(cb -> cb.getINDArrayFromCache(CoverageModelEMComputeBlock.CoverageModelICGCacheNode.sum_Q_ll), INDArray::add).div(numTargets);
            Z_ll = sampleBiasLatentPosteriorSecondMoments.sum(0);
            /* instantiate the spark implementation of linear operators */
            linop = new CoverageModelWLinearOperatorSpark(Z_ll, regularizerFourierLinearOperator, numTargets, ctx, computeRDD, targetBlocks);
            precond = new CoverageModelWPreconditionerSpark(Q_ll, Z_ll, regularizerFourierLinearOperator, numTargets, ctx, numTargetBlocks);
            return ImmutablePair.of(linop, precond);
        default:
            throw new IllegalArgumentException("The solver type for M-step update of bias covariates" + " is not properly set");
    }
}

Example 2 with FourierLinearOperatorNDArray

use of org.broadinstitute.hellbender.tools.coveragemodel.linalg.FourierLinearOperatorNDArray in project gatk-protected by broadinstitute.

the class CoverageModelEMWorkspace method updateFilteredBiasCovariates.

/**
     * This method applies the Fourier filter on a given bias covariates matrix, applies the Fourier filter on it,
     * partitions the result, and pushes it to compute block(s)
     *
     * @param biasCovariates any T x D bias covariates matrix
     */
@UpdatesRDD
private void updateFilteredBiasCovariates(@Nonnull final INDArray biasCovariates) {
    final INDArray filteredBiasCovariates = Nd4j.create(biasCovariates.shape());
    /* instantiate the Fourier filter */
    final FourierLinearOperatorNDArray regularizerFourierLinearOperator = createRegularizerFourierLinearOperator();
    /* FFT by resolving W_tl on l */
    for (int li = 0; li < numLatents; li++) {
        final INDArrayIndex[] slice = { NDArrayIndex.all(), NDArrayIndex.point(li) };
        filteredBiasCovariates.get(slice).assign(regularizerFourierLinearOperator.operate(biasCovariates.get(slice)));
    }
    /* sent the new W to workers */
    switch(config.getBiasCovariatesComputeNodeCommunicationPolicy()) {
        case BROADCAST_HASH_JOIN:
            pushToWorkers(mapINDArrayToBlocks(filteredBiasCovariates), (W, cb) -> cb.cloneWithUpdatedPrimitive(CoverageModelEMComputeBlock.CoverageModelICGCacheNode.F_W_tl, W.get(cb.getTargetSpaceBlock())));
            break;
        case RDD_JOIN:
            joinWithWorkersAndMap(chopINDArrayToBlocks(filteredBiasCovariates), p -> p._1.cloneWithUpdatedPrimitive(CoverageModelEMComputeBlock.CoverageModelICGCacheNode.F_W_tl, p._2));
            break;
    }
}

Example 3 with FourierLinearOperatorNDArray

use of org.broadinstitute.hellbender.tools.coveragemodel.linalg.FourierLinearOperatorNDArray in project gatk by broadinstitute.

the class CoverageModelEMWorkspace method updateFilteredBiasCovariates.

/**
     * This method applies the Fourier filter on a given bias covariates matrix, applies the Fourier filter on it,
     * partitions the result, and pushes it to compute block(s)
     *
     * @param biasCovariates any T x D bias covariates matrix
     */
@UpdatesRDD
private void updateFilteredBiasCovariates(@Nonnull final INDArray biasCovariates) {
    final INDArray filteredBiasCovariates = Nd4j.create(biasCovariates.shape());
    /* instantiate the Fourier filter */
    final FourierLinearOperatorNDArray regularizerFourierLinearOperator = createRegularizerFourierLinearOperator();
    /* FFT by resolving W_tl on l */
    for (int li = 0; li < numLatents; li++) {
        final INDArrayIndex[] slice = { NDArrayIndex.all(), NDArrayIndex.point(li) };
        filteredBiasCovariates.get(slice).assign(regularizerFourierLinearOperator.operate(biasCovariates.get(slice)));
    }
    /* sent the new W to workers */
    switch(config.getBiasCovariatesComputeNodeCommunicationPolicy()) {
        case BROADCAST_HASH_JOIN:
            pushToWorkers(mapINDArrayToBlocks(filteredBiasCovariates), (W, cb) -> cb.cloneWithUpdatedPrimitive(CoverageModelEMComputeBlock.CoverageModelICGCacheNode.F_W_tl, W.get(cb.getTargetSpaceBlock())));
            break;
        case RDD_JOIN:
            joinWithWorkersAndMap(chopINDArrayToBlocks(filteredBiasCovariates), p -> p._1.cloneWithUpdatedPrimitive(CoverageModelEMComputeBlock.CoverageModelICGCacheNode.F_W_tl, p._2));
            break;
    }
}

Example 4 with FourierLinearOperatorNDArray

use of org.broadinstitute.hellbender.tools.coveragemodel.linalg.FourierLinearOperatorNDArray in project gatk by broadinstitute.

the class CoverageModelEMWorkspace method getBiasCovariatesRegularizedLinearOperators.

/**
     * Returns the pair of (linear operator, preconditioner) invoked in the M-step update of bias
     * covariates in w/ regularization
     *
     * @return a pair of linear operators
     */
@EvaluatesRDD
private ImmutablePair<GeneralLinearOperator<INDArray>, GeneralLinearOperator<INDArray>> getBiasCovariatesRegularizedLinearOperators() {
    final INDArray Q_ll, Q_tll, Z_ll;
    final GeneralLinearOperator<INDArray> linop, precond;
    final FourierLinearOperatorNDArray regularizerFourierLinearOperator = createRegularizerFourierLinearOperator();
    switch(config.getWSolverType()) {
        case LOCAL:
            /* fetch the required INDArrays */
            Q_ll = mapWorkersAndReduce(cb -> cb.getINDArrayFromCache(CoverageModelEMComputeBlock.CoverageModelICGCacheNode.sum_Q_ll), INDArray::add).div(numTargets);
            Q_tll = fetchFromWorkers(CoverageModelEMComputeBlock.CoverageModelICGCacheNode.Q_tll, 0);
            Z_ll = sampleBiasLatentPosteriorSecondMoments.sum(0);
            /* instantiate the local implementation of linear operators */
            linop = new CoverageModelWLinearOperatorLocal(Q_tll, Z_ll, regularizerFourierLinearOperator);
            precond = new CoverageModelWPreconditionerLocal(Q_ll, Z_ll, regularizerFourierLinearOperator, numTargets);
            return ImmutablePair.of(linop, precond);
        case SPARK:
            if (!sparkContextIsAvailable) {
                throw new UserException("The Spark W solver is only available in the Spark mode");
            }
            /* fetch the required INDArrays */
            Q_ll = mapWorkersAndReduce(cb -> cb.getINDArrayFromCache(CoverageModelEMComputeBlock.CoverageModelICGCacheNode.sum_Q_ll), INDArray::add).div(numTargets);
            Z_ll = sampleBiasLatentPosteriorSecondMoments.sum(0);
            /* instantiate the spark implementation of linear operators */
            linop = new CoverageModelWLinearOperatorSpark(Z_ll, regularizerFourierLinearOperator, numTargets, ctx, computeRDD, targetBlocks);
            precond = new CoverageModelWPreconditionerSpark(Q_ll, Z_ll, regularizerFourierLinearOperator, numTargets, ctx, numTargetBlocks);
            return ImmutablePair.of(linop, precond);
        default:
            throw new IllegalArgumentException("The solver type for M-step update of bias covariates" + " is not properly set");
    }
}