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

Example 51 with IntDoubleVectorStorage

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

the class MixedBinaryOutAllExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntDummyVector v2, Binary op) {
    IntDoubleVector[] 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 IntDoubleSortedVectorStorage) {
                resParts[i] = new IntDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
            }
        }
    }
    int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
    for (int i = 0; i < v1.getDim(); i++) {
        int pidx = (int) (i / subDim);
        int subidx = i % subDim;
        ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
    }
    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());
}

Example 52 with IntDoubleVectorStorage

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

the class MixedBinaryOutAllExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntFloatVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        float[] v2Values = v2.getStorage().getValues();
        int base = 0, k = 0;
        for (IntDoubleVector part : parts) {
            IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[k];
            if (part.isDense()) {
                double[] partValue = part.getStorage().getValues();
                double[] resPartValues = resPart.getValues();
                for (int i = 0; i < partValue.length; i++) {
                    int idx = i;
                    resPartValues[i] = op.apply(partValue[i], v2Values[idx + base]);
                }
            } else if (part.isSparse()) {
                if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                    for (int i = 0; i < part.getDim(); i++) {
                        resPart.set(i, op.apply(0, v2Values[i + base]));
                    }
                    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 {
                    for (int i = 0; i < resPart.size(); i++) {
                        if (part.getStorage().hasKey(i)) {
                            resPart.set(i, op.apply(part.get(i), v2Values[i + base]));
                        } else {
                            resPart.set(i, op.apply(0, v2Values[i + base]));
                        }
                    }
                }
            } else {
                // sorted
                if (op.isKeepStorage()) {
                    int[] resPartIndices = resPart.getIndices();
                    double[] resPartValues = resPart.getValues();
                    if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int i = 0; i < part.getDim(); i++) {
                            resPartIndices[i] = i;
                            resPartValues[i] = op.apply(0, v2Values[i + base]);
                        }
                        int size = part.size();
                        for (int i = 0; i < size; i++) {
                            int idx = partIndices[i];
                            resPartValues[idx] = op.apply(partValues[i], v2Values[idx + base]);
                        }
                    } else {
                        IntDoubleVectorStorage partStorage = part.getStorage();
                        for (int i = 0; i < resPartValues.length; i++) {
                            if (partStorage.hasKey(i)) {
                                resPartIndices[i] = i;
                                resPartValues[i] = op.apply(partStorage.get(i), v2Values[i + base]);
                            } else {
                                resPartIndices[i] = i;
                                resPartValues[i] = op.apply(0, v2Values[i + base]);
                            }
                        }
                    }
                } else {
                    double[] resPartValues = resPart.getValues();
                    if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int i = 0; i < part.getDim(); i++) {
                            resPartValues[i] = op.apply(0, v2Values[i + base]);
                        }
                        int size = part.size();
                        for (int i = 0; i < size; i++) {
                            int idx = partIndices[i];
                            resPartValues[idx] = op.apply(partValues[i], v2Values[idx + base]);
                        }
                    } else {
                        IntDoubleVectorStorage partStorage = part.getStorage();
                        for (int i = 0; i < resPartValues.length; i++) {
                            if (partStorage.hasKey(i)) {
                                resPartValues[i] = op.apply(partStorage.get(i), v2Values[i + base]);
                            } else {
                                resPartValues[i] = op.apply(0, v2Values[i + base]);
                            }
                        }
                    }
                }
            }
            base += part.getDim();
            k++;
        }
    } else {
        if (!op.isKeepStorage()) {
            for (int i = 0; i < parts.length; i++) {
                if (parts[i].getStorage() instanceof IntDoubleSortedVectorStorage) {
                    resParts[i] = new IntDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
                }
            }
        }
        int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
        for (int i = 0; i < v1.getDim(); i++) {
            int pidx = (int) (i / subDim);
            int subidx = i % subDim;
            if (v2.getStorage().hasKey(i)) {
                ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
            } else {
                ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), 0));
            }
        }
    }
    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());
}

Example 53 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, IntDummyVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v1.size() > v2.size()) {
        int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
        int[] v2Indices = v2.getIndices();
        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), 1));
            }
        }
    } 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());
}

Example 54 with IntDoubleVectorStorage

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

the class SimpleBinaryInAllExecutor method apply.

public static Vector apply(IntDoubleVector v1, IntLongVector v2, Binary op) {
    if (v1.isDense() && v2.isDense()) {
        double[] resValues = v1.getStorage().getValues();
        long[] v2Values = v2.getStorage().getValues();
        for (int idx = 0; idx < resValues.length; idx++) {
            resValues[idx] = op.apply(resValues[idx], v2Values[idx]);
        }
    } else if (v1.isDense() && v2.isSparse()) {
        double[] resValues = v1.getStorage().getValues();
        if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
            for (int i = 0; i < resValues.length; i++) {
                resValues[i] = op.apply(resValues[i], 0);
            }
            ObjectIterator<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2LongMap.Entry entry = iter.next();
                int idx = entry.getIntKey();
                resValues[idx] = op.apply(v1.get(idx), entry.getLongValue());
            }
        } else {
            IntLongVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < resValues.length; i++) {
                if (v2Storage.hasKey(i)) {
                    resValues[i] = op.apply(resValues[i], v2.get(i));
                } else {
                    resValues[i] = op.apply(resValues[i], 0);
                }
            }
        }
    } else if (v1.isDense() && v2.isSorted()) {
        double[] resValues = v1.getStorage().getValues();
        if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
            int[] v2Indices = v2.getStorage().getIndices();
            long[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < resValues.length; i++) {
                resValues[i] = op.apply(resValues[i], 0);
            }
            int size = v2.size();
            for (int i = 0; i < size; i++) {
                int idx = v2Indices[i];
                resValues[idx] = op.apply(v1.get(idx), v2Values[i]);
            }
        } else {
            IntLongVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < resValues.length; i++) {
                if (v2Storage.hasKey(i)) {
                    resValues[i] = op.apply(resValues[i], v2.get(i));
                } else {
                    resValues[i] = op.apply(resValues[i], 0);
                }
            }
        }
    } else if (v1.isSparse() && v2.isDense()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
            double[] resValues = newStorage.getValues();
            long[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(0, v2Values[i]);
                }
                ObjectIterator<Int2DoubleMap.Entry> iter = v1.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2DoubleMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    resValues[idx] = op.apply(entry.getDoubleValue(), v2Values[idx]);
                }
            } else {
                for (int i = 0; i < resValues.length; i++) {
                    if (v1.getStorage().hasKey(i)) {
                        resValues[i] = op.apply(v1.get(i), v2Values[i]);
                    } else {
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                }
            }
            v1.setStorage(newStorage);
        }
    } else if (v1.isSorted() && v2.isDense()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
            double[] resValues = newStorage.getValues();
            long[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                int[] v1Indices = v1.getStorage().getIndices();
                double[] v1Values = v1.getStorage().getValues();
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(0, v2Values[i]);
                }
                int size = v1.size();
                for (int i = 0; i < size; i++) {
                    int idx = v1Indices[i];
                    resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
                }
            } else {
                IntDoubleVectorStorage v1Storage = v1.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v1Storage.hasKey(i)) {
                        resValues[i] = op.apply(v1.get(i), v2Values[i]);
                    } else {
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                }
            }
            v1.setStorage(newStorage);
        }
    } else if (v1.isSparse() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
            double[] resValues = newStorage.getValues();
            ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Int2DoubleMap.Entry entry = iter1.next();
                int idx = entry.getIntKey();
                resValues[idx] = entry.getDoubleValue();
            }
            if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(resValues[i], 0);
                }
                ObjectIterator<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2LongMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    if (v1.getStorage().hasKey(idx)) {
                        resValues[idx] = op.apply(v1.get(idx), entry.getLongValue());
                    }
                }
            } else {
                IntLongVectorStorage v2Storage = v2.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v2Storage.hasKey(i)) {
                        resValues[i] = op.apply(resValues[i], v2.get(i));
                    } else {
                        resValues[i] = op.apply(resValues[i], 0);
                    }
                }
            }
            v1.setStorage(newStorage);
        }
    } else if (v1.isSparse() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
            double[] resValues = newStorage.getValues();
            ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Int2DoubleMap.Entry entry = iter1.next();
                int idx = entry.getIntKey();
                resValues[idx] = entry.getDoubleValue();
            }
            if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
                int[] v2Indices = v2.getStorage().getIndices();
                long[] v2Values = v2.getStorage().getValues();
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(resValues[i], 0);
                }
                int size = v2.size();
                for (int i = 0; i < size; i++) {
                    int idx = v2Indices[i];
                    if (v1.getStorage().hasKey(idx)) {
                        resValues[idx] = op.apply(v1.get(idx), v2Values[i]);
                    }
                }
            } else {
                IntLongVectorStorage v2Storage = v2.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v2Storage.hasKey(i)) {
                        resValues[i] = op.apply(resValues[i], v2.get(i));
                    } else {
                        resValues[i] = op.apply(resValues[i], 0);
                    }
                }
            }
            v1.setStorage(newStorage);
        }
    } else if (v1.isSorted() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
            double[] resValues = newStorage.getValues();
            int[] v1Indices = v1.getStorage().getIndices();
            double[] v1Values = v1.getStorage().getValues();
            int size = v1.size();
            for (int i = 0; i < size; i++) {
                int idx = v1Indices[i];
                resValues[idx] = v1Values[i];
            }
            if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(resValues[i], 0);
                }
                ObjectIterator<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2LongMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    if (v1.getStorage().hasKey(idx)) {
                        resValues[idx] = op.apply(v1.get(idx), entry.getLongValue());
                    }
                }
            } else {
                IntLongVectorStorage v2Storage = v2.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v2Storage.hasKey(i)) {
                        resValues[i] = op.apply(resValues[i], v2.get(i));
                    } else {
                        resValues[i] = op.apply(resValues[i], 0);
                    }
                }
            }
            v1.setStorage(newStorage);
        }
    } else if (v1.isSorted() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
            double[] resValues = newStorage.getValues();
            int v1Pointor = 0;
            int v2Pointor = 0;
            int size1 = v1.size();
            int size2 = v2.size();
            int[] v1Indices = v1.getStorage().getIndices();
            double[] v1Values = v1.getStorage().getValues();
            int[] v2Indices = v2.getStorage().getIndices();
            long[] v2Values = v2.getStorage().getValues();
            if (!op.isCompare()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = Double.NaN;
                }
            }
            while (v1Pointor < size1 && v2Pointor < size2) {
                if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                    resValues[v1Indices[v1Pointor]] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
                    v1Pointor++;
                    v2Pointor++;
                } else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
                    resValues[v1Indices[v1Pointor]] = op.apply(v1Values[v1Pointor], 0);
                    v1Pointor++;
                } else {
                    // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                    resValues[v2Indices[v2Pointor]] = op.apply(0, v2Values[v2Pointor]);
                    v2Pointor++;
                }
            }
            v1.setStorage(newStorage);
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return v1;
}

Example 55 with IntDoubleVectorStorage

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

the class SimpleBinaryInAllExecutor method apply.

public static Vector apply(IntDoubleVector v1, IntDoubleVector v2, Binary op) {
    if (v1.isDense() && v2.isDense()) {
        double[] resValues = v1.getStorage().getValues();
        double[] v2Values = v2.getStorage().getValues();
        for (int idx = 0; idx < resValues.length; idx++) {
            resValues[idx] = op.apply(resValues[idx], v2Values[idx]);
        }
    } else if (v1.isDense() && v2.isSparse()) {
        double[] resValues = v1.getStorage().getValues();
        if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
            for (int i = 0; i < resValues.length; i++) {
                resValues[i] = op.apply(resValues[i], 0);
            }
            ObjectIterator<Int2DoubleMap.Entry> iter = v2.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2DoubleMap.Entry entry = iter.next();
                int idx = entry.getIntKey();
                resValues[idx] = op.apply(v1.get(idx), entry.getDoubleValue());
            }
        } else {
            IntDoubleVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < resValues.length; i++) {
                if (v2Storage.hasKey(i)) {
                    resValues[i] = op.apply(resValues[i], v2.get(i));
                } else {
                    resValues[i] = op.apply(resValues[i], 0);
                }
            }
        }
    } else if (v1.isDense() && v2.isSorted()) {
        double[] resValues = v1.getStorage().getValues();
        if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
            int[] v2Indices = v2.getStorage().getIndices();
            double[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < resValues.length; i++) {
                resValues[i] = op.apply(resValues[i], 0);
            }
            int size = v2.size();
            for (int i = 0; i < size; i++) {
                int idx = v2Indices[i];
                resValues[idx] = op.apply(v1.get(idx), v2Values[i]);
            }
        } else {
            IntDoubleVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < resValues.length; i++) {
                if (v2Storage.hasKey(i)) {
                    resValues[i] = op.apply(resValues[i], v2.get(i));
                } else {
                    resValues[i] = op.apply(resValues[i], 0);
                }
            }
        }
    } else if (v1.isSparse() && v2.isDense()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
            double[] resValues = newStorage.getValues();
            double[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(0, v2Values[i]);
                }
                ObjectIterator<Int2DoubleMap.Entry> iter = v1.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2DoubleMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    resValues[idx] = op.apply(entry.getDoubleValue(), v2Values[idx]);
                }
            } else {
                for (int i = 0; i < resValues.length; i++) {
                    if (v1.getStorage().hasKey(i)) {
                        resValues[i] = op.apply(v1.get(i), v2Values[i]);
                    } else {
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                }
            }
            v1.setStorage(newStorage);
        }
    } else if (v1.isSorted() && v2.isDense()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
            double[] resValues = newStorage.getValues();
            double[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                int[] v1Indices = v1.getStorage().getIndices();
                double[] v1Values = v1.getStorage().getValues();
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(0, v2Values[i]);
                }
                int size = v1.size();
                for (int i = 0; i < size; i++) {
                    int idx = v1Indices[i];
                    resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
                }
            } else {
                IntDoubleVectorStorage v1Storage = v1.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v1Storage.hasKey(i)) {
                        resValues[i] = op.apply(v1.get(i), v2Values[i]);
                    } else {
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                }
            }
            v1.setStorage(newStorage);
        }
    } else if (v1.isSparse() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
            double[] resValues = newStorage.getValues();
            ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Int2DoubleMap.Entry entry = iter1.next();
                int idx = entry.getIntKey();
                resValues[idx] = entry.getDoubleValue();
            }
            if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(resValues[i], 0);
                }
                ObjectIterator<Int2DoubleMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2DoubleMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    if (v1.getStorage().hasKey(idx)) {
                        resValues[idx] = op.apply(v1.get(idx), entry.getDoubleValue());
                    }
                }
            } else {
                IntDoubleVectorStorage v2Storage = v2.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v2Storage.hasKey(i)) {
                        resValues[i] = op.apply(resValues[i], v2.get(i));
                    } else {
                        resValues[i] = op.apply(resValues[i], 0);
                    }
                }
            }
            v1.setStorage(newStorage);
        }
    } else if (v1.isSparse() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
            double[] resValues = newStorage.getValues();
            ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Int2DoubleMap.Entry entry = iter1.next();
                int idx = entry.getIntKey();
                resValues[idx] = entry.getDoubleValue();
            }
            if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
                int[] v2Indices = v2.getStorage().getIndices();
                double[] v2Values = v2.getStorage().getValues();
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(resValues[i], 0);
                }
                int size = v2.size();
                for (int i = 0; i < size; i++) {
                    int idx = v2Indices[i];
                    if (v1.getStorage().hasKey(idx)) {
                        resValues[idx] = op.apply(v1.get(idx), v2Values[i]);
                    }
                }
            } else {
                IntDoubleVectorStorage v2Storage = v2.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v2Storage.hasKey(i)) {
                        resValues[i] = op.apply(resValues[i], v2.get(i));
                    } else {
                        resValues[i] = op.apply(resValues[i], 0);
                    }
                }
            }
            v1.setStorage(newStorage);
        }
    } else if (v1.isSorted() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
            double[] resValues = newStorage.getValues();
            int[] v1Indices = v1.getStorage().getIndices();
            double[] v1Values = v1.getStorage().getValues();
            int size = v1.size();
            for (int i = 0; i < size; i++) {
                int idx = v1Indices[i];
                resValues[idx] = v1Values[i];
            }
            if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(resValues[i], 0);
                }
                ObjectIterator<Int2DoubleMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2DoubleMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    if (v1.getStorage().hasKey(idx)) {
                        resValues[idx] = op.apply(v1.get(idx), entry.getDoubleValue());
                    }
                }
            } else {
                IntDoubleVectorStorage v2Storage = v2.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v2Storage.hasKey(i)) {
                        resValues[i] = op.apply(resValues[i], v2.get(i));
                    } else {
                        resValues[i] = op.apply(resValues[i], 0);
                    }
                }
            }
            v1.setStorage(newStorage);
        }
    } else if (v1.isSorted() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntDoubleVectorStorage newStorage = v1.getStorage().emptyDense();
            double[] resValues = newStorage.getValues();
            int v1Pointor = 0;
            int v2Pointor = 0;
            int size1 = v1.size();
            int size2 = v2.size();
            int[] v1Indices = v1.getStorage().getIndices();
            double[] v1Values = v1.getStorage().getValues();
            int[] v2Indices = v2.getStorage().getIndices();
            double[] v2Values = v2.getStorage().getValues();
            if (!op.isCompare()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = Double.NaN;
                }
            }
            while (v1Pointor < size1 && v2Pointor < size2) {
                if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                    resValues[v1Indices[v1Pointor]] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
                    v1Pointor++;
                    v2Pointor++;
                } else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
                    resValues[v1Indices[v1Pointor]] = op.apply(v1Values[v1Pointor], 0);
                    v1Pointor++;
                } else {
                    // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                    resValues[v2Indices[v2Pointor]] = op.apply(0, v2Values[v2Pointor]);
                    v2Pointor++;
                }
            }
            v1.setStorage(newStorage);
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return v1;
}