Examples with IntArrayList cern.colt.list.IntArrayList used on opensource projects

Example 11 with IntArrayList

use of cern.colt.list.IntArrayList in project tdq-studio-se by Talend.

the class AbstractIntDoubleMap method keys.

/**
 * Returns a list filled with all keys contained in the receiver.
 * The returned list has a size that equals <tt>this.size()</tt>.
 * Iteration order is guaranteed to be <i>identical</i> to the order used by method {@link #forEachKey(IntProcedure)}.
 * <p>
 * This method can be used to iterate over the keys of the receiver.
 *
 * @return the keys.
 */
public IntArrayList keys() {
    IntArrayList list = new IntArrayList(size());
    keys(list);
    return list;
}

Example 12 with IntArrayList

use of cern.colt.list.IntArrayList in project tdq-studio-se by Talend.

the class AbstractIntObjectMap method keys.

/**
 * Returns a list filled with all keys contained in the receiver.
 * The returned list has a size that equals <tt>this.size()</tt>.
 * Iteration order is guaranteed to be <i>identical</i> to the order used by method {@link #forEachKey(IntProcedure)}.
 * <p>
 * This method can be used to iterate over the keys of the receiver.
 *
 * @return the keys.
 */
public IntArrayList keys() {
    IntArrayList list = new IntArrayList(size());
    keys(list);
    return list;
}

Example 13 with IntArrayList

use of cern.colt.list.IntArrayList in project Gemma by PavlidisLab.

the class RowMissingValueFilter method filter.

@Override
public ExpressionDataDoubleMatrix filter(ExpressionDataDoubleMatrix data) {
    int numRows = data.rows();
    int numCols = data.columns();
    IntArrayList present = new IntArrayList(numRows);
    List<CompositeSequence> kept = new ArrayList<>();
    /*
         * Do not allow minPresentFraction to override minPresent if minPresent is higher.
         */
    if (minPresentFractionIsSet) {
        int proposedMinimumNumberOfSamples = (int) Math.ceil(minPresentFraction * numCols);
        if (!minPresentIsSet) {
            this.setMinPresentCount(proposedMinimumNumberOfSamples);
        } else if (proposedMinimumNumberOfSamples > minPresentCount) {
            RowMissingValueFilter.log.info("The minimum number of samples is already set to " + this.minPresentCount + " but computed missing threshold from fraction of " + minPresentFraction + " is higher (" + proposedMinimumNumberOfSamples + ")");
            this.setMinPresentCount(proposedMinimumNumberOfSamples);
        } else {
            RowMissingValueFilter.log.info("The minimum number of samples is already set to " + this.minPresentCount + " and computed missing threshold from fraction of " + minPresentFraction + " is lower (" + proposedMinimumNumberOfSamples + "), keeping higher value.");
        }
    }
    if (minPresentCount > numCols) {
        throw new IllegalStateException("Minimum present count is set to " + minPresentCount + " but there are only " + numCols + " columns in the matrix.");
    }
    if (!minPresentIsSet) {
        RowMissingValueFilter.log.info("No filtering was requested");
        return data;
    }
    /* first pass - determine how many missing values there are per row */
    for (int i = 0; i < numRows; i++) {
        CompositeSequence designElementForRow = data.getDesignElementForRow(i);
        /* allow for the possibility that the absent/present matrix is not in the same order, etc. */
        int absentPresentRow = absentPresentCalls == null ? -1 : absentPresentCalls.getRowIndex(designElementForRow);
        int presentCount = 0;
        for (int j = 0; j < numCols; j++) {
            boolean callIsPresent = true;
            if (absentPresentRow >= 0) {
                callIsPresent = absentPresentCalls.get(absentPresentRow, j);
            }
            if (!Double.isNaN(data.get(i, j)) && callIsPresent) {
                presentCount++;
            }
        }
        present.add(presentCount);
        if (presentCount >= RowMissingValueFilter.ABSOLUTE_MIN_PRESENT && presentCount >= minPresentCount) {
            kept.add(designElementForRow);
        }
    }
    /* decide whether we need to invoke the 'too many removed' clause, to avoid removing too many rows. */
    if (maxFractionRemoved != 0.0 && kept.size() < numRows * (1.0 - maxFractionRemoved)) {
        IntArrayList sortedPresent = present.copy();
        sortedPresent.sort();
        sortedPresent.reverse();
        RowMissingValueFilter.log.info("There are " + kept.size() + " rows that meet criterion of at least " + minPresentCount + " non-missing values, but that's too many given the max fraction of " + maxFractionRemoved + "; minPresent adjusted to " + sortedPresent.get((int) (numRows * (maxFractionRemoved))));
        minPresentCount = sortedPresent.get((int) (numRows * (maxFractionRemoved)));
        // Do another pass to add rows we missed before.
        for (int i = 0; i < numRows; i++) {
            if (present.get(i) >= minPresentCount && present.get(i) >= RowMissingValueFilter.ABSOLUTE_MIN_PRESENT) {
                CompositeSequence designElementForRow = data.getDesignElementForRow(i);
                if (kept.contains(designElementForRow))
                    continue;
                kept.add(designElementForRow);
            }
        }
    }
    RowMissingValueFilter.log.info("Retaining " + kept.size() + " rows that meet criterion of at least " + minPresentCount + " non-missing values");
    return new ExpressionDataDoubleMatrix(data, kept);
}

Example 14 with IntArrayList

use of cern.colt.list.IntArrayList in project Gemma by PavlidisLab.

the class BatchConfound method factorBatchConfoundTest.

private static Collection<BatchConfoundValueObject> factorBatchConfoundTest(ExpressionExperiment ee, Map<ExperimentalFactor, Map<Long, Double>> bioMaterialFactorMap) throws IllegalArgumentException {
    Map<Long, Long> batchMembership = new HashMap<>();
    ExperimentalFactor batchFactor = null;
    Map<Long, Integer> batchIndexes = new HashMap<>();
    for (ExperimentalFactor ef : bioMaterialFactorMap.keySet()) {
        if (ExperimentalDesignUtils.isBatch(ef)) {
            batchFactor = ef;
            Map<Long, Double> bmToFv = bioMaterialFactorMap.get(batchFactor);
            if (bmToFv == null) {
                log.warn("No biomaterial --> factor value map for batch factor: " + batchFactor);
                continue;
            }
            int index = 0;
            for (FactorValue fv : batchFactor.getFactorValues()) {
                batchIndexes.put(fv.getId(), index++);
            }
            for (Long bmId : bmToFv.keySet()) {
                batchMembership.put(bmId, bmToFv.get(bmId).longValue());
            }
            break;
        }
    }
    Set<BatchConfoundValueObject> result = new HashSet<>();
    if (batchFactor == null) {
        return result;
    }
    for (ExperimentalFactor ef : bioMaterialFactorMap.keySet()) {
        if (ef.equals(batchFactor))
            continue;
        Map<Long, Double> bmToFv = bioMaterialFactorMap.get(ef);
        int numBioMaterials = bmToFv.keySet().size();
        assert numBioMaterials > 0 : "No biomaterials for " + ef;
        double p = Double.NaN;
        double chiSquare;
        int df;
        int numBatches = batchFactor.getFactorValues().size();
        if (ExperimentalDesignUtils.isContinuous(ef)) {
            DoubleArrayList factorValues = new DoubleArrayList(numBioMaterials);
            factorValues.setSize(numBioMaterials);
            IntArrayList batches = new IntArrayList(numBioMaterials);
            batches.setSize(numBioMaterials);
            int j = 0;
            for (Long bmId : bmToFv.keySet()) {
                assert factorValues.size() > 0 : "Biomaterial to factorValue is empty for " + ef;
                factorValues.set(j, bmToFv.get(bmId));
                long batch = batchMembership.get(bmId);
                batches.set(j, batchIndexes.get(batch));
                j++;
            }
            p = KruskalWallis.test(factorValues, batches);
            df = KruskalWallis.dof(factorValues, batches);
            chiSquare = KruskalWallis.kwStatistic(factorValues, batches);
            log.debug("KWallis\t" + ee.getId() + "\t" + ee.getShortName() + "\t" + ef.getId() + "\t" + ef.getName() + "\t" + String.format("%.2f", chiSquare) + "\t" + df + "\t" + String.format("%.2g", p) + "\t" + numBatches);
        } else {
            Map<Long, Integer> factorValueIndexes = new HashMap<>();
            int index = 0;
            for (FactorValue fv : ef.getFactorValues()) {
                factorValueIndexes.put(fv.getId(), index++);
            }
            Map<Long, Long> factorValueMembership = new HashMap<>();
            for (Long bmId : bmToFv.keySet()) {
                factorValueMembership.put(bmId, bmToFv.get(bmId).longValue());
            }
            long[][] counts = new long[numBatches][ef.getFactorValues().size()];
            for (int i = 0; i < batchIndexes.size(); i++) {
                for (int j = 0; j < factorValueIndexes.size(); j++) {
                    counts[i][j] = 0;
                }
            }
            for (Long bm : bmToFv.keySet()) {
                long fv = factorValueMembership.get(bm);
                Long batch = batchMembership.get(bm);
                if (batch == null) {
                    log.warn("No batch membership for : " + bm);
                    continue;
                }
                int batchIndex = batchIndexes.get(batch);
                int factorIndex = factorValueIndexes.get(fv);
                counts[batchIndex][factorIndex]++;
            }
            ChiSquareTest cst = new ChiSquareTest();
            try {
                chiSquare = cst.chiSquare(counts);
            } catch (IllegalArgumentException e) {
                log.warn("IllegalArgumentException exception computing ChiSq for : " + ef + "; Error was: " + e.getMessage());
                chiSquare = Double.NaN;
            }
            df = (counts.length - 1) * (counts[0].length - 1);
            ChiSquaredDistribution distribution = new ChiSquaredDistribution(df);
            if (!Double.isNaN(chiSquare)) {
                p = 1.0 - distribution.cumulativeProbability(chiSquare);
            }
            log.debug("ChiSq\t" + ee.getId() + "\t" + ee.getShortName() + "\t" + ef.getId() + "\t" + ef.getName() + "\t" + String.format("%.2f", chiSquare) + "\t" + df + "\t" + String.format("%.2g", p) + "\t" + numBatches);
        }
        BatchConfoundValueObject summary = new BatchConfoundValueObject(ee, ef, chiSquare, df, p, numBatches);
        result.add(summary);
    }
    return result;
}

Example 15 with IntArrayList

use of cern.colt.list.IntArrayList in project Gemma by PavlidisLab.

the class GeneCoexpressionNodeDegreeValueObject method asIntArray.

private int[] asIntArray(TreeMap<Integer, Integer> nodeDegreesNeg) {
    IntArrayList list = new IntArrayList();
    if (nodeDegreesNeg.isEmpty())
        return this.toPrimitive(list);
    Integer maxSupport = nodeDegreesNeg.lastKey();
    list.setSize(maxSupport + 1);
    for (Integer s = 0; s <= maxSupport; s++) {
        if (nodeDegreesNeg.containsKey(s)) {
            list.set(s, nodeDegreesNeg.get(s));
        } else {
            list.set(s, 0);
        }
    }
    return this.toPrimitive(list);
}