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

Example 6 with LongDoubleVectorStorage

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

the class MixedBinaryInZAExecutor method apply.

private static Vector apply(CompLongDoubleVector v1, LongDoubleVector v2, Binary op) {
    LongDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isSparse()) {
        ObjectIterator<Long2DoubleMap.Entry> iter = v2.getStorage().entryIterator();
        if (v1.size() > v2.size()) {
            long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            while (iter.hasNext()) {
                Long2DoubleMap.Entry entry = iter.next();
                long idx = entry.getLongKey();
                int pidx = (int) (idx / subDim);
                long subidx = idx % subDim;
                if (parts[pidx].hasKey(subidx)) {
                    ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), entry.getDoubleValue()));
                }
            }
        } else {
            long base = 0;
            for (int i = 0; i < parts.length; i++) {
                LongDoubleVector part = parts[i];
                LongDoubleVectorStorage resPart = (LongDoubleVectorStorage) 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<Long2DoubleMap.Entry> piter = part.getStorage().entryIterator();
                    while (piter.hasNext()) {
                        Long2DoubleMap.Entry entry = piter.next();
                        long idx = entry.getLongKey();
                        if (v2.hasKey(idx + base)) {
                            resPart.set(idx, op.apply(entry.getDoubleValue(), v2.get(idx + base)));
                        }
                    }
                } else {
                    // sorted
                    if (op.isKeepStorage()) {
                        long[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        long[] resPartIndices = resPart.getIndices();
                        double[] resPartValues = resPart.getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            long idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPartIndices[j] = idx;
                                resPartValues[j] = op.apply(partValues[j], v2.get(idx + base));
                            }
                        }
                    } else {
                        long[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            long 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()) {
            long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            long[] v2Indices = v2.getStorage().getIndices();
            double[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < v2Indices.length; i++) {
                long idx = v2Indices[i];
                int pidx = (int) (idx / subDim);
                long subidx = idx % subDim;
                if (parts[pidx].hasKey(subidx)) {
                    ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
                }
            }
        } else {
            long base = 0;
            for (int i = 0; i < parts.length; i++) {
                LongDoubleVector part = parts[i];
                LongDoubleVectorStorage resPart = (LongDoubleVectorStorage) 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<Long2DoubleMap.Entry> piter = part.getStorage().entryIterator();
                    while (piter.hasNext()) {
                        Long2DoubleMap.Entry entry = piter.next();
                        long idx = entry.getLongKey();
                        if (v2.hasKey(idx + base)) {
                            resPart.set(idx, op.apply(entry.getDoubleValue(), v2.get(idx + base)));
                        }
                    }
                } else {
                    // sorted
                    if (op.isKeepStorage()) {
                        long[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        long[] resPartIndices = resPart.getIndices();
                        double[] resPartValues = resPart.getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            long idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPartIndices[j] = idx;
                                resPartValues[j] = op.apply(partValues[j], v2.get(idx + base));
                            }
                        }
                    } else {
                        long[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            long idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPart.set(idx, op.apply(partValues[j], v2.get(idx + base)));
                            }
                        }
                    }
                }
                base += part.getDim();
            }
        }
    }
    LongDoubleVector[] res = new LongDoubleVector[parts.length];
    int i = 0;
    for (LongDoubleVector part : parts) {
        res[i] = new LongDoubleVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (LongDoubleVectorStorage) resParts[i]);
        i++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 7 with LongDoubleVectorStorage

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

the class MixedBinaryInNonZAExecutor method apply.

private static Vector apply(CompLongDoubleVector v1, LongDoubleVector v2, Binary op) {
    LongDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isSparse()) {
        if (!op.isKeepStorage()) {
            for (int i = 0; i < parts.length; i++) {
                if (parts[i].getStorage() instanceof LongDoubleSortedVectorStorage) {
                    resParts[i] = new LongDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
                }
            }
        }
        long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
        ObjectIterator<Long2DoubleMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Long2DoubleMap.Entry entry = iter.next();
            long gidx = entry.getLongKey();
            int pidx = (int) (gidx / subDim);
            long subidx = gidx % subDim;
            ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), entry.getDoubleValue()));
        }
    } else {
        // sorted
        if (!op.isKeepStorage()) {
            for (int i = 0; i < parts.length; i++) {
                if (parts[i].getStorage() instanceof LongDoubleSortedVectorStorage) {
                    resParts[i] = new LongDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
                }
            }
        }
        long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
        long[] v2Indices = v2.getStorage().getIndices();
        double[] v2Values = v2.getStorage().getValues();
        for (int i = 0; i < v2Indices.length; i++) {
            long gidx = v2Indices[i];
            int pidx = (int) (gidx / subDim);
            long subidx = gidx % subDim;
            ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
        }
    }
    LongDoubleVector[] res = new LongDoubleVector[parts.length];
    int i = 0;
    for (LongDoubleVector part : parts) {
        res[i] = new LongDoubleVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (LongDoubleVectorStorage) resParts[i]);
        i++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 8 with LongDoubleVectorStorage

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

the class MixedBinaryInAllExecutor method apply.

private static Vector apply(CompLongDoubleVector v1, LongLongVector v2, Binary op) {
    LongDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (!op.isKeepStorage()) {
        for (int i = 0; i < parts.length; i++) {
            if (parts[i].getStorage() instanceof LongDoubleSortedVectorStorage) {
                resParts[i] = new LongDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
            }
        }
    }
    long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
    for (int i = 0; i < v1.getDim(); i++) {
        int pidx = (int) (i / subDim);
        long subidx = i % subDim;
        if (v2.getStorage().hasKey(i)) {
            ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
        } else {
            ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), 0));
        }
    }
    LongDoubleVector[] res = new LongDoubleVector[parts.length];
    int i = 0;
    for (LongDoubleVector part : parts) {
        res[i] = new LongDoubleVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (LongDoubleVectorStorage) resParts[i]);
        i++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 9 with LongDoubleVectorStorage

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

the class LongDoubleVector method argmin.

public long argmin() {
    LongDoubleVectorStorage idstorage = (LongDoubleVectorStorage) storage;
    if (idstorage.size() == 0)
        return -1;
    double minval = Double.MAX_VALUE;
    long minidx = -1;
    if (idstorage.isSparse()) {
        ObjectIterator<Long2DoubleMap.Entry> iter = idstorage.entryIterator();
        while (iter.hasNext()) {
            Long2DoubleMap.Entry entry = iter.next();
            long idx = entry.getLongKey();
            double val = entry.getDoubleValue();
            if (val < minval) {
                minval = val;
                minidx = idx;
            }
        }
    } else {
        long[] indices = idstorage.getIndices();
        double[] val = idstorage.getValues();
        long size = idstorage.size();
        for (int i = 0; i < size; i++) {
            long idx = indices[i];
            if (val[i] < minval) {
                minval = val[i];
                minidx = idx;
            }
        }
    }
    return minidx;
}

Example 10 with LongDoubleVectorStorage

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

the class LongDoubleVector method std.

public double std() {
    LongDoubleVectorStorage dstorage = (LongDoubleVectorStorage) storage;
    if (dstorage.size() == 0)
        return 0;
    double sumval = 0.0;
    double sumval2 = 0.0;
    if (dstorage.isSparse()) {
        DoubleIterator iter = dstorage.valueIterator();
        while (iter.hasNext()) {
            double val = iter.nextDouble();
            sumval += val;
            sumval2 += val * val;
        }
    } else {
        for (double val : dstorage.getValues()) {
            sumval += val;
            sumval2 += val * val;
        }
    }
    sumval /= getDim();
    sumval2 /= getDim();
    return Math.sqrt(sumval2 - sumval * sumval);
}