Examples with ObjectIterator it.unimi.dsi.fastutil.objects.ObjectIterator used on opensource projects

Example 26 with ObjectIterator

use of it.unimi.dsi.fastutil.objects.ObjectIterator in project angel by Tencent.

the class BinaryMatrixExecutor method apply.

private static Matrix apply(BlasFloatMatrix mat, IntLongVector v, int idx, boolean onCol, Binary op) {
    float[] data = mat.getData();
    int m = mat.getNumRows(), n = mat.getNumCols();
    int size = v.size();
    byte[] flag = null;
    if (!v.isDense()) {
        flag = new byte[v.getDim()];
    }
    if (onCol && op.isInplace()) {
        if (v.isDense()) {
            long[] values = v.getStorage().getValues();
            for (int i = 0; i < m; i++) {
                data[i * n + idx] = op.apply(data[i * n + idx], values[i]);
            }
        } else if (v.isSparse()) {
            ObjectIterator<Int2LongMap.Entry> iter = v.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2LongMap.Entry entry = iter.next();
                int i = entry.getIntKey();
                flag[i] = 1;
                data[i * n + idx] = op.apply(data[i * n + idx], entry.getLongValue());
            }
        } else {
            // sorted
            int[] idxs = v.getStorage().getIndices();
            long[] values = v.getStorage().getValues();
            for (int k = 0; k < size; k++) {
                int i = idxs[k];
                flag[i] = 1;
                data[i * n + idx] = op.apply(data[i * n + idx], values[k]);
            }
        }
        if (!v.isDense()) {
            switch(op.getOpType()) {
                case INTERSECTION:
                    for (int i = 0; i < m; i++) {
                        if (flag[i] == 0) {
                            data[i * n + idx] = 0;
                        }
                    }
                case UNION:
                    break;
                case ALL:
                    for (int i = 0; i < m; i++) {
                        if (flag[i] == 0) {
                            data[i * n + idx] = op.apply(data[i * n + idx], 0);
                        }
                    }
            }
        }
        return mat;
    } else if (onCol && !op.isInplace()) {
        float[] newData;
        if (op.getOpType() == INTERSECTION) {
            newData = new float[m * n];
        } else {
            newData = ArrayCopy.copy(data);
        }
        if (v.isDense()) {
            long[] values = v.getStorage().getValues();
            for (int i = 0; i < m; i++) {
                newData[i * n + idx] = op.apply(data[i * n + idx], values[i]);
            }
        } else if (v.isSparse()) {
            ObjectIterator<Int2LongMap.Entry> iter = v.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2LongMap.Entry entry = iter.next();
                int i = entry.getIntKey();
                flag[i] = 1;
                newData[i * n + idx] = op.apply(data[i * n + idx], entry.getLongValue());
            }
        } else {
            // sorted
            int[] idxs = v.getStorage().getIndices();
            long[] values = v.getStorage().getValues();
            for (int k = 0; k < size; k++) {
                int i = idxs[k];
                flag[i] = 1;
                newData[i * n + idx] = op.apply(data[i * n + idx], values[k]);
            }
        }
        if (!v.isDense()) {
            switch(op.getOpType()) {
                case INTERSECTION:
                    break;
                case UNION:
                    break;
                case ALL:
                    for (int i = 0; i < m; i++) {
                        if (flag[i] == 0) {
                            newData[i * n + idx] = op.apply(data[i * n + idx], 0);
                        }
                    }
            }
        }
        return new BlasFloatMatrix(mat.getMatrixId(), mat.getClock(), m, n, newData);
    } else if (!onCol && op.isInplace()) {
        if (v.isDense()) {
            long[] values = v.getStorage().getValues();
            for (int j = 0; j < n; j++) {
                data[idx * n + j] = op.apply(data[idx * n + j], values[j]);
            }
        } else if (v.isSparse()) {
            ObjectIterator<Int2LongMap.Entry> iter = v.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2LongMap.Entry entry = iter.next();
                int j = entry.getIntKey();
                flag[j] = 1;
                data[idx * n + j] = op.apply(data[idx * n + j], entry.getLongValue());
            }
        } else {
            // sorted
            int[] idxs = v.getStorage().getIndices();
            long[] values = v.getStorage().getValues();
            for (int k = 0; k < size; k++) {
                int j = idxs[k];
                flag[j] = 1;
                data[idx * n + j] = op.apply(data[idx * n + j], values[k]);
            }
        }
        if (!v.isDense()) {
            switch(op.getOpType()) {
                case INTERSECTION:
                    for (int j = 0; j < n; j++) {
                        if (flag[j] == 0) {
                            data[idx * n + j] = 0;
                        }
                    }
                case UNION:
                    break;
                case ALL:
                    for (int j = 0; j < n; j++) {
                        if (flag[j] == 0) {
                            data[idx * n + j] = op.apply(data[idx * n + j], 0);
                        }
                    }
            }
        }
        return mat;
    } else {
        float[] newData;
        if (op.getOpType() == INTERSECTION) {
            newData = new float[m * n];
        } else {
            newData = ArrayCopy.copy(data);
        }
        if (v.isDense()) {
            long[] values = v.getStorage().getValues();
            for (int j = 0; j < n; j++) {
                newData[idx * n + j] = op.apply(data[idx * n + j], values[j]);
            }
        } else if (v.isSparse()) {
            ObjectIterator<Int2LongMap.Entry> iter = v.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2LongMap.Entry entry = iter.next();
                int j = entry.getIntKey();
                flag[j] = 1;
                newData[idx * n + j] = op.apply(data[idx * n + j], entry.getLongValue());
            }
        } else {
            // sorted
            int[] idxs = v.getStorage().getIndices();
            long[] values = v.getStorage().getValues();
            for (int k = 0; k < size; k++) {
                int j = idxs[k];
                flag[j] = 1;
                newData[idx * n + j] = op.apply(data[idx * n + j], values[k]);
            }
        }
        if (!v.isDense()) {
            switch(op.getOpType()) {
                case INTERSECTION:
                    break;
                case UNION:
                    break;
                case ALL:
                    for (int j = 0; j < n; j++) {
                        if (flag[j] == 0) {
                            newData[idx * n + j] = op.apply(data[idx * n + j], 0);
                        }
                    }
            }
        }
        return new BlasFloatMatrix(mat.getMatrixId(), mat.getClock(), m, n, newData);
    }
}

Example 27 with ObjectIterator

use of it.unimi.dsi.fastutil.objects.ObjectIterator in project angel by Tencent.

the class BinaryMatrixExecutor method apply.

private static Matrix apply(BlasDoubleMatrix mat, IntLongVector v, boolean onCol, Binary op) {
    double[] data = mat.getData();
    int m = mat.getNumRows(), n = mat.getNumCols();
    int size = v.size();
    byte[] flag = null;
    if (!v.isDense()) {
        flag = new byte[v.getDim()];
    }
    if (onCol && op.isInplace()) {
        if (v.isDense()) {
            long[] values = v.getStorage().getValues();
            for (int i = 0; i < m; i++) {
                long value = values[i];
                for (int j = 0; j < n; j++) {
                    data[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else if (v.isSparse()) {
            ObjectIterator<Int2LongMap.Entry> iter = v.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2LongMap.Entry entry = iter.next();
                int i = entry.getIntKey();
                flag[i] = 1;
                double value = entry.getLongValue();
                for (int j = 0; j < n; j++) {
                    data[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else {
            // sorted
            int[] idxs = v.getStorage().getIndices();
            long[] values = v.getStorage().getValues();
            for (int k = 0; k < size; k++) {
                int i = idxs[k];
                flag[i] = 1;
                long value = values[k];
                for (int j = 0; j < n; j++) {
                    data[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        }
        if (!v.isDense()) {
            switch(op.getOpType()) {
                case INTERSECTION:
                    for (int i = 0; i < m; i++) {
                        if (flag[i] == 0) {
                            for (int j = 0; j < n; j++) {
                                data[i * n + j] = 0;
                            }
                        }
                    }
                case UNION:
                    break;
                case ALL:
                    for (int i = 0; i < m; i++) {
                        if (flag[i] == 0) {
                            for (int j = 0; j < n; j++) {
                                data[i * n + j] = op.apply(data[i * n + j], 0);
                            }
                        }
                    }
            }
        }
        return mat;
    } else if (onCol && !op.isInplace()) {
        double[] newData;
        if (op.getOpType() == INTERSECTION) {
            newData = new double[m * n];
        } else {
            newData = ArrayCopy.copy(data);
        }
        if (v.isDense()) {
            long[] values = v.getStorage().getValues();
            for (int i = 0; i < m; i++) {
                long value = values[i];
                for (int j = 0; j < n; j++) {
                    newData[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else if (v.isSparse()) {
            ObjectIterator<Int2LongMap.Entry> iter = v.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2LongMap.Entry entry = iter.next();
                int i = entry.getIntKey();
                flag[i] = 1;
                double value = entry.getLongValue();
                for (int j = 0; j < n; j++) {
                    newData[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else {
            // sorted
            int[] idxs = v.getStorage().getIndices();
            long[] values = v.getStorage().getValues();
            for (int k = 0; k < size; k++) {
                int i = idxs[k];
                flag[i] = 1;
                long value = values[k];
                for (int j = 0; j < n; j++) {
                    newData[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        }
        if (!v.isDense()) {
            switch(op.getOpType()) {
                case INTERSECTION:
                    break;
                case UNION:
                    break;
                case ALL:
                    for (int i = 0; i < m; i++) {
                        if (flag[i] == 0) {
                            for (int j = 0; j < n; j++) {
                                newData[i * n + j] = op.apply(data[i * n + j], 0);
                            }
                        }
                    }
            }
        }
        return new BlasDoubleMatrix(mat.getMatrixId(), mat.getClock(), m, n, newData);
    } else if (!onCol && op.isInplace()) {
        if (v.isDense()) {
            long[] values = v.getStorage().getValues();
            for (int i = 0; i < m; i++) {
                for (int j = 0; j < n; j++) {
                    data[i * n + j] = op.apply(data[i * n + j], values[j]);
                }
            }
        } else if (v.isSparse()) {
            ObjectIterator<Int2LongMap.Entry> iter = v.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2LongMap.Entry entry = iter.next();
                int j = entry.getIntKey();
                double value = entry.getLongValue();
                flag[j] = 1;
                for (int i = 0; i < m; i++) {
                    data[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else {
            // sorted
            int[] idxs = v.getStorage().getIndices();
            long[] values = v.getStorage().getValues();
            for (int k = 0; k < size; k++) {
                int j = idxs[k];
                long value = values[k];
                flag[j] = 1;
                for (int i = 0; i < m; i++) {
                    data[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        }
        if (!v.isDense()) {
            switch(op.getOpType()) {
                case INTERSECTION:
                    for (int j = 0; j < n; j++) {
                        if (flag[j] == 0) {
                            for (int i = 0; i < m; i++) {
                                data[i * n + j] = 0;
                            }
                        }
                    }
                case UNION:
                    break;
                case ALL:
                    for (int j = 0; j < n; j++) {
                        if (flag[j] == 0) {
                            for (int i = 0; i < m; i++) {
                                data[i * n + j] = op.apply(data[i * n + j], 0);
                            }
                        }
                    }
            }
        }
        return mat;
    } else {
        double[] newData;
        if (op.getOpType() == INTERSECTION) {
            newData = new double[m * n];
        } else {
            newData = ArrayCopy.copy(data);
        }
        if (v.isDense()) {
            long[] values = v.getStorage().getValues();
            for (int j = 0; j < n; j++) {
                long value = values[j];
                for (int i = 0; i < m; i++) {
                    newData[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else if (v.isSparse()) {
            ObjectIterator<Int2LongMap.Entry> iter = v.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2LongMap.Entry entry = iter.next();
                int j = entry.getIntKey();
                flag[j] = 1;
                double value = entry.getLongValue();
                for (int i = 0; i < m; i++) {
                    newData[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else {
            // sorted
            int[] idxs = v.getStorage().getIndices();
            long[] values = v.getStorage().getValues();
            for (int k = 0; k < size; k++) {
                int j = idxs[k];
                flag[j] = 1;
                long value = values[k];
                for (int i = 0; i < m; i++) {
                    newData[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        }
        if (!v.isDense()) {
            switch(op.getOpType()) {
                case INTERSECTION:
                    break;
                case UNION:
                    break;
                case ALL:
                    for (int j = 0; j < n; j++) {
                        if (flag[j] == 0) {
                            for (int i = 0; i < m; i++) {
                                newData[i * n + j] = op.apply(data[i * n + j], 0);
                            }
                        }
                    }
            }
        }
        return new BlasDoubleMatrix(mat.getMatrixId(), mat.getClock(), m, n, newData);
    }
}

Example 28 with ObjectIterator

use of it.unimi.dsi.fastutil.objects.ObjectIterator in project angel by Tencent.

the class MixedBinaryInAllExecutor method apply.

private static Vector apply(CompIntFloatVector v1, IntIntVector v2, Binary op) {
    IntFloatVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        int[] v2Values = v2.getStorage().getValues();
        int base = 0, k = 0;
        for (IntFloatVector part : parts) {
            IntFloatVectorStorage resPart = (IntFloatVectorStorage) resParts[k];
            if (part.isDense()) {
                float[] partValue = part.getStorage().getValues();
                float[] resPartValues = resPart.getValues();
                for (int i = 0; i < partValue.length; i++) {
                    int idx = i + base;
                    resPartValues[i] = op.apply(partValue[i], v2Values[idx]);
                }
            } else if (part.isSparse()) {
                float[] resPartValues = resPart.getValues();
                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<Int2FloatMap.Entry> iter = part.getStorage().entryIterator();
                    while (iter.hasNext()) {
                        Int2FloatMap.Entry entry = iter.next();
                        int idx = entry.getIntKey();
                        resPart.set(idx, op.apply(entry.getFloatValue(), v2Values[idx + base]));
                    }
                } else {
                    for (int i = 0; i < resPartValues.length; 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
                int[] resPartIndices = resPart.getIndices();
                float[] resPartValues = resPart.getValues();
                if (op.isKeepStorage()) {
                    if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                        int[] partIndices = part.getStorage().getIndices();
                        float[] 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 {
                        IntFloatVectorStorage 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 {
                    if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                        int[] partIndices = part.getStorage().getIndices();
                        float[] 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 {
                        IntFloatVectorStorage 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 IntFloatSortedVectorStorage) {
                    resParts[i] = new IntFloatSparseVectorStorage(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)) {
                ((IntFloatVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
            } else {
                ((IntFloatVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), 0));
            }
        }
    }
    IntFloatVector[] res = new IntFloatVector[parts.length];
    int i = 0;
    for (IntFloatVector part : parts) {
        res[i] = new IntFloatVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (IntFloatVectorStorage) resParts[i]);
        i++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 29 with ObjectIterator

use of it.unimi.dsi.fastutil.objects.ObjectIterator in project angel by Tencent.

the class MixedBinaryInAllExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntIntVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        int[] 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 + base;
                    resPartValues[i] = op.apply(partValue[i], v2Values[idx]);
                }
            } else if (part.isSparse()) {
                double[] resPartValues = resPart.getValues();
                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 < resPartValues.length; 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
                int[] resPartIndices = resPart.getIndices();
                double[] resPartValues = resPart.getValues();
                if (op.isKeepStorage()) {
                    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 {
                    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++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 30 with ObjectIterator

use of it.unimi.dsi.fastutil.objects.ObjectIterator in project angel by Tencent.

the class BinaryMatrixExecutor method apply.

private static Matrix apply(BlasDoubleMatrix mat, IntIntVector v, boolean onCol, Binary op) {
    double[] data = mat.getData();
    int m = mat.getNumRows(), n = mat.getNumCols();
    int size = v.size();
    byte[] flag = null;
    if (!v.isDense()) {
        flag = new byte[v.getDim()];
    }
    if (onCol && op.isInplace()) {
        if (v.isDense()) {
            int[] values = v.getStorage().getValues();
            for (int i = 0; i < m; i++) {
                int value = values[i];
                for (int j = 0; j < n; j++) {
                    data[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else if (v.isSparse()) {
            ObjectIterator<Int2IntMap.Entry> iter = v.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2IntMap.Entry entry = iter.next();
                int i = entry.getIntKey();
                flag[i] = 1;
                double value = entry.getIntValue();
                for (int j = 0; j < n; j++) {
                    data[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else {
            // sorted
            int[] idxs = v.getStorage().getIndices();
            int[] values = v.getStorage().getValues();
            for (int k = 0; k < size; k++) {
                int i = idxs[k];
                flag[i] = 1;
                int value = values[k];
                for (int j = 0; j < n; j++) {
                    data[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        }
        if (!v.isDense()) {
            switch(op.getOpType()) {
                case INTERSECTION:
                    for (int i = 0; i < m; i++) {
                        if (flag[i] == 0) {
                            for (int j = 0; j < n; j++) {
                                data[i * n + j] = 0;
                            }
                        }
                    }
                case UNION:
                    break;
                case ALL:
                    for (int i = 0; i < m; i++) {
                        if (flag[i] == 0) {
                            for (int j = 0; j < n; j++) {
                                data[i * n + j] = op.apply(data[i * n + j], 0);
                            }
                        }
                    }
            }
        }
        return mat;
    } else if (onCol && !op.isInplace()) {
        double[] newData;
        if (op.getOpType() == INTERSECTION) {
            newData = new double[m * n];
        } else {
            newData = ArrayCopy.copy(data);
        }
        if (v.isDense()) {
            int[] values = v.getStorage().getValues();
            for (int i = 0; i < m; i++) {
                int value = values[i];
                for (int j = 0; j < n; j++) {
                    newData[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else if (v.isSparse()) {
            ObjectIterator<Int2IntMap.Entry> iter = v.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2IntMap.Entry entry = iter.next();
                int i = entry.getIntKey();
                flag[i] = 1;
                double value = entry.getIntValue();
                for (int j = 0; j < n; j++) {
                    newData[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else {
            // sorted
            int[] idxs = v.getStorage().getIndices();
            int[] values = v.getStorage().getValues();
            for (int k = 0; k < size; k++) {
                int i = idxs[k];
                flag[i] = 1;
                int value = values[k];
                for (int j = 0; j < n; j++) {
                    newData[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        }
        if (!v.isDense()) {
            switch(op.getOpType()) {
                case INTERSECTION:
                    break;
                case UNION:
                    break;
                case ALL:
                    for (int i = 0; i < m; i++) {
                        if (flag[i] == 0) {
                            for (int j = 0; j < n; j++) {
                                newData[i * n + j] = op.apply(data[i * n + j], 0);
                            }
                        }
                    }
            }
        }
        return new BlasDoubleMatrix(mat.getMatrixId(), mat.getClock(), m, n, newData);
    } else if (!onCol && op.isInplace()) {
        if (v.isDense()) {
            int[] values = v.getStorage().getValues();
            for (int i = 0; i < m; i++) {
                for (int j = 0; j < n; j++) {
                    data[i * n + j] = op.apply(data[i * n + j], values[j]);
                }
            }
        } else if (v.isSparse()) {
            ObjectIterator<Int2IntMap.Entry> iter = v.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2IntMap.Entry entry = iter.next();
                int j = entry.getIntKey();
                double value = entry.getIntValue();
                flag[j] = 1;
                for (int i = 0; i < m; i++) {
                    data[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else {
            // sorted
            int[] idxs = v.getStorage().getIndices();
            int[] values = v.getStorage().getValues();
            for (int k = 0; k < size; k++) {
                int j = idxs[k];
                int value = values[k];
                flag[j] = 1;
                for (int i = 0; i < m; i++) {
                    data[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        }
        if (!v.isDense()) {
            switch(op.getOpType()) {
                case INTERSECTION:
                    for (int j = 0; j < n; j++) {
                        if (flag[j] == 0) {
                            for (int i = 0; i < m; i++) {
                                data[i * n + j] = 0;
                            }
                        }
                    }
                case UNION:
                    break;
                case ALL:
                    for (int j = 0; j < n; j++) {
                        if (flag[j] == 0) {
                            for (int i = 0; i < m; i++) {
                                data[i * n + j] = op.apply(data[i * n + j], 0);
                            }
                        }
                    }
            }
        }
        return mat;
    } else {
        double[] newData;
        if (op.getOpType() == INTERSECTION) {
            newData = new double[m * n];
        } else {
            newData = ArrayCopy.copy(data);
        }
        if (v.isDense()) {
            int[] values = v.getStorage().getValues();
            for (int j = 0; j < n; j++) {
                int value = values[j];
                for (int i = 0; i < m; i++) {
                    newData[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else if (v.isSparse()) {
            ObjectIterator<Int2IntMap.Entry> iter = v.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2IntMap.Entry entry = iter.next();
                int j = entry.getIntKey();
                flag[j] = 1;
                double value = entry.getIntValue();
                for (int i = 0; i < m; i++) {
                    newData[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        } else {
            // sorted
            int[] idxs = v.getStorage().getIndices();
            int[] values = v.getStorage().getValues();
            for (int k = 0; k < size; k++) {
                int j = idxs[k];
                flag[j] = 1;
                int value = values[k];
                for (int i = 0; i < m; i++) {
                    newData[i * n + j] = op.apply(data[i * n + j], value);
                }
            }
        }
        if (!v.isDense()) {
            switch(op.getOpType()) {
                case INTERSECTION:
                    break;
                case UNION:
                    break;
                case ALL:
                    for (int j = 0; j < n; j++) {
                        if (flag[j] == 0) {
                            for (int i = 0; i < m; i++) {
                                newData[i * n + j] = op.apply(data[i * n + j], 0);
                            }
                        }
                    }
            }
        }
        return new BlasDoubleMatrix(mat.getMatrixId(), mat.getClock(), m, n, newData);
    }
}