Examples with IntDoubleVectorStorage com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage used on opensource projects

Example 46 with IntDoubleVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage in project angel by Tencent.

the class IntDoubleVector method max.

public double max() {
    IntDoubleVectorStorage idstorage = (IntDoubleVectorStorage) storage;
    if (idstorage.size() == 0)
        return 0;
    double maxval = Double.MIN_VALUE;
    if (idstorage.isSparse()) {
        DoubleIterator iter = idstorage.valueIterator();
        while (iter.hasNext()) {
            double val = iter.nextDouble();
            if (val > maxval) {
                maxval = val;
            }
        }
    } else {
        for (double val : idstorage.getValues()) {
            if (val > maxval) {
                maxval = val;
            }
        }
    }
    return maxval;
}

Example 47 with IntDoubleVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage in project angel by Tencent.

the class IntDoubleVector method argmin.

public int argmin() {
    IntDoubleVectorStorage idstorage = (IntDoubleVectorStorage) storage;
    if (idstorage.size() == 0)
        return -1;
    double minval = Double.MAX_VALUE;
    int minidx = -1;
    if (idstorage.isDense()) {
        double[] val = idstorage.getValues();
        int length = val.length;
        for (int idx = 0; idx < length; idx++) {
            if (val[idx] < minval) {
                minval = val[idx];
                minidx = idx;
            }
        }
    } else if (idstorage.isSparse()) {
        ObjectIterator<Int2DoubleMap.Entry> iter = idstorage.entryIterator();
        while (iter.hasNext()) {
            Int2DoubleMap.Entry entry = iter.next();
            int idx = entry.getIntKey();
            double val = entry.getDoubleValue();
            if (val < minval) {
                minval = val;
                minidx = idx;
            }
        }
    } else {
        int[] indices = idstorage.getIndices();
        double[] val = idstorage.getValues();
        int size = idstorage.size();
        for (int i = 0; i < size; i++) {
            int idx = indices[i];
            if (val[i] < minval) {
                minval = val[i];
                minidx = idx;
            }
        }
    }
    return minidx;
}

Example 48 with IntDoubleVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage in project angel by Tencent.

the class IntDoubleVector method min.

public double min() {
    IntDoubleVectorStorage idstorage = (IntDoubleVectorStorage) storage;
    if (idstorage.size() == 0)
        return 0;
    double minval = Double.MAX_VALUE;
    if (idstorage.isSparse()) {
        DoubleIterator iter = idstorage.valueIterator();
        while (iter.hasNext()) {
            double val = iter.nextDouble();
            if (val < minval) {
                minval = val;
            }
        }
    } else {
        for (double val : idstorage.getValues()) {
            if (val < minval) {
                minval = val;
            }
        }
    }
    return minval;
}

Example 49 with IntDoubleVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage in project angel by Tencent.

the class IntDoubleVector method argmax.

public int argmax() {
    IntDoubleVectorStorage idstorage = (IntDoubleVectorStorage) storage;
    if (idstorage.size() == 0)
        return -1;
    double maxval = Double.MIN_VALUE;
    int maxidx = -1;
    if (idstorage.isDense()) {
        double[] val = idstorage.getValues();
        int length = val.length;
        for (int idx = 0; idx < length; idx++) {
            if (val[idx] > maxval) {
                maxval = val[idx];
                maxidx = idx;
            }
        }
    } else if (idstorage.isSparse()) {
        ObjectIterator<Int2DoubleMap.Entry> iter = idstorage.entryIterator();
        while (iter.hasNext()) {
            Int2DoubleMap.Entry entry = iter.next();
            int idx = entry.getIntKey();
            double val = entry.getDoubleValue();
            if (val > maxval) {
                maxval = val;
                maxidx = idx;
            }
        }
    } else {
        int[] indices = idstorage.getIndices();
        double[] val = idstorage.getValues();
        int size = idstorage.size();
        for (int i = 0; i < size; i++) {
            int idx = indices[i];
            if (val[i] > maxval) {
                maxval = val[i];
                maxidx = idx;
            }
        }
    }
    return maxidx;
}

Example 50 with IntDoubleVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage in project angel by Tencent.

the class MixedBinaryOutZAExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntDoubleVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        int base = 0;
        double[] v2Values = v2.getStorage().getValues();
        for (int i = 0; i < parts.length; i++) {
            IntDoubleVector part = parts[i];
            IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[i];
            if (part.isDense()) {
                double[] resPartValues = resPart.getValues();
                double[] partValues = part.getStorage().getValues();
                for (int j = 0; j < resPartValues.length; j++) {
                    resPartValues[j] = op.apply(partValues[j], v2Values[base + j]);
                }
            } else if (part.isSparse()) {
                ObjectIterator<Int2DoubleMap.Entry> iter = part.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2DoubleMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    resPart.set(idx, op.apply(entry.getDoubleValue(), v2Values[idx + base]));
                }
            } else {
                // sorted
                if (op.isKeepStorage()) {
                    int[] resPartIndices = resPart.getIndices();
                    double[] resPartValues = resPart.getValues();
                    int[] partIndices = part.getStorage().getIndices();
                    double[] partValues = part.getStorage().getValues();
                    for (int j = 0; j < partIndices.length; j++) {
                        int idx = partIndices[j];
                        resPartIndices[j] = idx;
                        resPartValues[j] = op.apply(partValues[j], v2Values[idx + base]);
                    }
                } else {
                    int[] partIndices = part.getStorage().getIndices();
                    double[] partValues = part.getStorage().getValues();
                    for (int j = 0; j < partIndices.length; j++) {
                        int idx = partIndices[j];
                        resPart.set(idx, op.apply(partValues[j], v2Values[idx + base]));
                    }
                }
            }
            base += part.getDim();
        }
    } else if (v2.isSparse()) {
        ObjectIterator<Int2DoubleMap.Entry> iter = v2.getStorage().entryIterator();
        if (v1.size() > v2.size()) {
            int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            while (iter.hasNext()) {
                Int2DoubleMap.Entry entry = iter.next();
                int idx = entry.getIntKey();
                int pidx = (int) (idx / subDim);
                int subidx = idx % subDim;
                if (parts[pidx].hasKey(subidx)) {
                    ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), entry.getDoubleValue()));
                }
            }
        } else {
            int base = 0;
            for (int i = 0; i < parts.length; i++) {
                IntDoubleVector part = parts[i];
                IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[i];
                if (part.isDense()) {
                    double[] partValues = part.getStorage().getValues();
                    double[] resPartValues = resPart.getValues();
                    for (int j = 0; j < partValues.length; j++) {
                        if (v2.hasKey(j + base)) {
                            resPartValues[j] = op.apply(partValues[j], v2.get(j + base));
                        }
                    }
                } else if (part.isSparse()) {
                    ObjectIterator<Int2DoubleMap.Entry> piter = part.getStorage().entryIterator();
                    while (piter.hasNext()) {
                        Int2DoubleMap.Entry entry = piter.next();
                        int idx = entry.getIntKey();
                        if (v2.hasKey(idx + base)) {
                            resPart.set(idx, op.apply(entry.getDoubleValue(), v2.get(idx + base)));
                        }
                    }
                } else {
                    // sorted
                    if (op.isKeepStorage()) {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        int[] resPartIndices = resPart.getIndices();
                        double[] resPartValues = resPart.getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            int idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPartIndices[j] = idx;
                                resPartValues[j] = op.apply(partValues[j], v2.get(idx + base));
                            }
                        }
                    } else {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            int idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPart.set(idx, op.apply(partValues[j], v2.get(idx + base)));
                            }
                        }
                    }
                }
                base += part.getDim();
            }
        }
    } else {
        // sorted
        if (v1.size() > v2.size()) {
            int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            int[] v2Indices = v2.getStorage().getIndices();
            double[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < v2Indices.length; i++) {
                int idx = v2Indices[i];
                int pidx = (int) (idx / subDim);
                int subidx = idx % subDim;
                if (parts[pidx].hasKey(subidx)) {
                    ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
                }
            }
        } else {
            int base = 0;
            for (int i = 0; i < parts.length; i++) {
                IntDoubleVector part = parts[i];
                IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[i];
                if (part.isDense()) {
                    double[] partValues = part.getStorage().getValues();
                    double[] resPartValues = resPart.getValues();
                    for (int j = 0; j < partValues.length; j++) {
                        if (v2.hasKey(j + base)) {
                            resPartValues[j] = op.apply(partValues[j], v2.get(j + base));
                        }
                    }
                } else if (part.isSparse()) {
                    ObjectIterator<Int2DoubleMap.Entry> piter = part.getStorage().entryIterator();
                    while (piter.hasNext()) {
                        Int2DoubleMap.Entry entry = piter.next();
                        int idx = entry.getIntKey();
                        if (v2.hasKey(idx + base)) {
                            resPart.set(idx, op.apply(entry.getDoubleValue(), v2.get(idx + base)));
                        }
                    }
                } else {
                    // sorted
                    if (op.isKeepStorage()) {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        int[] resPartIndices = resPart.getIndices();
                        double[] resPartValues = resPart.getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            int idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPartIndices[j] = idx;
                                resPartValues[j] = op.apply(partValues[j], v2.get(idx + base));
                            }
                        }
                    } else {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            int idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPart.set(idx, op.apply(partValues[j], v2.get(idx + base)));
                            }
                        }
                    }
                }
                base += part.getDim();
            }
        }
    }
    IntDoubleVector[] res = new IntDoubleVector[parts.length];
    int i = 0;
    for (IntDoubleVector part : parts) {
        res[i] = new IntDoubleVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (IntDoubleVectorStorage) resParts[i]);
        i++;
    }
    return new CompIntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}