Examples with LongLongVector com.tencent.angel.ml.math2.vector.LongLongVector used on opensource projects

Example 56 with LongLongVector

use of com.tencent.angel.ml.math2.vector.LongLongVector in project angel by Tencent.

the class SimpleBinaryOutNonZAExecutor method apply.

public static Vector apply(LongLongVector v1, LongDummyVector v2, Binary op) {
    LongLongVectorStorage newStorage = (LongLongVectorStorage) StorageSwitch.apply(v1, v2, op);
    if (v1.isSparse()) {
        long[] v2Indices = v2.getIndices();
        if (((v1.size() + v2.size()) * Constant.intersectionCoeff > Constant.sparseDenseStorageThreshold * v1.getDim())) {
            long[] resValues = newStorage.getValues();
            ObjectIterator<Long2LongMap.Entry> iter = v1.getStorage().entryIterator();
            while (iter.hasNext()) {
                Long2LongMap.Entry entry = iter.next();
                newStorage.set(entry.getLongKey(), entry.getLongValue());
            }
            for (long idx : v2Indices) {
                newStorage.set(idx, op.apply(v1.get(idx), 1));
            }
        } else {
            // to avoid multi-rehash
            int capacity = 1 << (32 - Integer.numberOfLeadingZeros((int) (v1.size() / 0.75)));
            if (v1.size() + v2.size() < 1.5 * capacity) {
                long size = v2.size();
                for (int i = 0; i < size; i++) {
                    long idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), 1));
                }
            } else {
                ObjectIterator<Long2LongMap.Entry> iter1 = v1.getStorage().entryIterator();
                while (iter1.hasNext()) {
                    Long2LongMap.Entry entry = iter1.next();
                    long idx = entry.getLongKey();
                    newStorage.set(idx, entry.getLongValue());
                }
                long size = v2.size();
                for (int i = 0; i < size; i++) {
                    long idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), 1));
                }
            }
        }
    } else {
        // sorted
        long[] v1Indices = v1.getStorage().getIndices();
        long[] v2Indices = v2.getIndices();
        if (!op.isKeepStorage() && ((v1.size() + v2.size()) * Constant.intersectionCoeff > Constant.sortedDenseStorageThreshold * v1.getDim())) {
            long[] v1Values = v1.getStorage().getValues();
            long size = v1.size();
            for (int i = 0; i < size; i++) {
                newStorage.set(v1Indices[i], v1Values[i]);
            }
            size = v2.size();
            for (int i = 0; i < size; i++) {
                long idx = v2Indices[i];
                newStorage.set(idx, op.apply(newStorage.get(idx), 1));
            }
        } else {
            int v1Pointor = 0;
            int v2Pointor = 0;
            long size1 = v1.size();
            long size2 = v2.size();
            long[] v1Values = v1.getStorage().getValues();
            while (v1Pointor < size1 || v2Pointor < size2) {
                if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                    newStorage.set(v1Indices[v1Pointor], op.apply(v1Values[v1Pointor], 1));
                    v1Pointor++;
                    v2Pointor++;
                } else if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] < v2Indices[v2Pointor] || (v1Pointor < size1 && v2Pointor >= size2)) {
                    newStorage.set(v1Indices[v1Pointor], v1Values[v1Pointor]);
                    v1Pointor++;
                } else if (((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] >= v2Indices[v2Pointor]) || (v1Pointor >= size1 && v2Pointor < size2)) {
                    newStorage.set(v2Indices[v2Pointor], op.apply(0, 1));
                    v2Pointor++;
                }
            }
        }
    }
    return new LongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}

Example 57 with LongLongVector

use of com.tencent.angel.ml.math2.vector.LongLongVector in project angel by Tencent.

the class SimpleBinaryOutNonZAExecutor method apply.

public static Vector apply(LongDoubleVector v1, LongLongVector v2, Binary op) {
    LongDoubleVectorStorage newStorage = (LongDoubleVectorStorage) StorageSwitch.apply(v1, v2, op);
    if (v1.isSparse() && v2.isSparse()) {
        long v1Size = v1.size();
        long v2Size = v2.size();
        if (v1Size >= v2Size * Constant.sparseThreshold && (v1Size + v2Size) * Constant.intersectionCoeff <= Constant.sparseDenseStorageThreshold * v1.dim()) {
            // we gauss the indices of v2 maybe is a subset of v1, or overlap is very large
            ObjectIterator<Long2LongMap.Entry> iter = v2.getStorage().entryIterator();
            while (iter.hasNext()) {
                Long2LongMap.Entry entry = iter.next();
                long idx = entry.getLongKey();
                newStorage.set(idx, op.apply(v1.get(idx), entry.getLongValue()));
            }
        } else if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sparseDenseStorageThreshold * v1.dim()) {
            // we gauss dense storage is more efficient
            ObjectIterator<Long2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Long2DoubleMap.Entry entry = iter1.next();
                long idx = entry.getLongKey();
                newStorage.set(idx, entry.getDoubleValue());
            }
            ObjectIterator<Long2LongMap.Entry> iter2 = v2.getStorage().entryIterator();
            while (iter2.hasNext()) {
                Long2LongMap.Entry entry = iter2.next();
                long idx = entry.getLongKey();
                newStorage.set(idx, op.apply(v1.get(idx), entry.getLongValue()));
            }
        } else {
            // to avoid multi-rehash
            int capacity = 1 << (32 - Integer.numberOfLeadingZeros((int) (v1.size() / 0.75)));
            if (v1.size() + v2.size() <= 1.5 * capacity) {
                // no rehashor one onle rehash is required, nothing to optimization
                ObjectIterator<Long2LongMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Long2LongMap.Entry entry = iter.next();
                    long idx = entry.getLongKey();
                    newStorage.set(idx, op.apply(v1.get(idx), entry.getLongValue()));
                }
            } else {
                // multi-rehash
                ObjectIterator<Long2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
                while (iter1.hasNext()) {
                    Long2DoubleMap.Entry entry = iter1.next();
                    long idx = entry.getLongKey();
                    newStorage.set(idx, entry.getDoubleValue());
                }
                ObjectIterator<Long2LongMap.Entry> iter2 = v2.getStorage().entryIterator();
                while (iter2.hasNext()) {
                    Long2LongMap.Entry entry = iter2.next();
                    long idx = entry.getLongKey();
                    newStorage.set(idx, op.apply(v1.get(idx), entry.getLongValue()));
                }
            }
        }
    } else if (v1.isSparse() && v2.isSorted()) {
        long v1Size = v1.size();
        long v2Size = v2.size();
        if (v1Size >= v2Size * Constant.sparseThreshold && (v1Size + v2Size) * Constant.intersectionCoeff <= Constant.sparseDenseStorageThreshold * v1.dim()) {
            // we gauss the indices of v2 maybe is a subset of v1, or overlap is very large
            long[] v2Indices = v2.getStorage().getIndices();
            long[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < v2.size(); i++) {
                long idx = v2Indices[i];
                newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
            }
        } else if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sparseDenseStorageThreshold * v1.dim()) {
            ObjectIterator<Long2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Long2DoubleMap.Entry entry = iter1.next();
                long idx = entry.getLongKey();
                newStorage.set(idx, entry.getDoubleValue());
            }
            long[] v2Indices = v2.getStorage().getIndices();
            long[] v2Values = v2.getStorage().getValues();
            long size = v2.size();
            for (int i = 0; i < size; i++) {
                long idx = v2Indices[i];
                newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
            }
        } else {
            // to avoid multi-rehash
            int capacity = 1 << (32 - Integer.numberOfLeadingZeros((int) (v1.size() / 0.75)));
            if (v1.size() + v2.size() <= 1.5 * capacity) {
                long[] v2Indices = v2.getStorage().getIndices();
                long[] v2Values = v2.getStorage().getValues();
                for (int i = 0; i < v2.size(); i++) {
                    long idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
                }
            } else {
                ObjectIterator<Long2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
                while (iter1.hasNext()) {
                    Long2DoubleMap.Entry entry = iter1.next();
                    long idx = entry.getLongKey();
                    newStorage.set(idx, entry.getDoubleValue());
                }
                long[] v2Indices = v2.getStorage().getIndices();
                long[] v2Values = v2.getStorage().getValues();
                long size = v2.size();
                for (int i = 0; i < size; i++) {
                    long idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
                }
            }
        }
    } else if (v1.isSorted() && v2.isSparse()) {
        long v1Size = v1.size();
        long v2Size = v2.size();
        if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sortedDenseStorageThreshold * v1.dim()) {
            if (op.isKeepStorage()) {
                long[] v1Indices = v1.getStorage().getIndices();
                long[] idxiter = v2.getStorage().indexIterator().toLongArray();
                long[] indices = new long[(int) (v1Size + v2Size)];
                System.arraycopy(v1Indices, 0, indices, 0, (int) v1.size());
                System.arraycopy(idxiter, 0, indices, (int) v1.size(), (int) v2.size());
                LongAVLTreeSet avl = new LongAVLTreeSet(indices);
                LongBidirectionalIterator iter = avl.iterator();
                double[] values = new double[indices.length];
                int i = 0;
                while (iter.hasNext()) {
                    long idx = iter.nextLong();
                    indices[i] = idx;
                    values[i] = op.apply(v1.get(idx), v2.get(idx));
                    i++;
                }
                while (i < indices.length) {
                    indices[i] = 0;
                    i++;
                }
                newStorage = new LongDoubleSortedVectorStorage(v1.getDim(), (int) avl.size(), indices, values);
            } else {
                long[] v1Indices = v1.getStorage().getIndices();
                double[] v1Values = v1.getStorage().getValues();
                long size = v1.size();
                for (int i = 0; i < size; i++) {
                    long idx = v1Indices[i];
                    newStorage.set(idx, v1Values[i]);
                }
                ObjectIterator<Long2LongMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Long2LongMap.Entry entry = iter.next();
                    long idx = entry.getLongKey();
                    newStorage.set(idx, op.apply(newStorage.get(idx), entry.getLongValue()));
                }
            }
        } else {
            if (op.isKeepStorage()) {
                long[] v1Indices = v1.getStorage().getIndices();
                long[] idxiter = v2.getStorage().indexIterator().toLongArray();
                long[] indices = new long[(int) (v1Size + v2Size)];
                System.arraycopy(v1Indices, 0, indices, 0, (int) v1.size());
                System.arraycopy(idxiter, 0, indices, (int) v1.size(), (int) v2.size());
                LongAVLTreeSet avl = new LongAVLTreeSet(indices);
                LongBidirectionalIterator iter = avl.iterator();
                double[] values = new double[indices.length];
                int i = 0;
                while (iter.hasNext()) {
                    long idx = iter.nextLong();
                    indices[i] = idx;
                    values[i] = op.apply(v1.get(idx), v2.get(idx));
                    i++;
                }
                while (i < indices.length) {
                    indices[i] = 0;
                    i++;
                }
                newStorage = new LongDoubleSortedVectorStorage(v1.getDim(), (int) avl.size(), indices, values);
            } else {
                long[] v1Indices = v1.getStorage().getIndices();
                double[] v1Values = v1.getStorage().getValues();
                long size = v1.size();
                for (int i = 0; i < size; i++) {
                    long idx = v1Indices[i];
                    newStorage.set(idx, v1Values[i]);
                }
                ObjectIterator<Long2LongMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Long2LongMap.Entry entry = iter.next();
                    long idx = entry.getLongKey();
                    newStorage.set(idx, op.apply(newStorage.get(idx), entry.getLongValue()));
                }
            }
        }
    } else if (v1.isSorted() && v2.isSorted()) {
        int v1Pointor = 0;
        int v2Pointor = 0;
        long size1 = v1.size();
        long size2 = v2.size();
        long[] v1Indices = v1.getStorage().getIndices();
        double[] v1Values = v1.getStorage().getValues();
        long[] v2Indices = v2.getStorage().getIndices();
        long[] v2Values = v2.getStorage().getValues();
        if ((size1 + size2) * Constant.intersectionCoeff >= Constant.sortedDenseStorageThreshold * v1.dim()) {
            if (op.isKeepStorage()) {
                // sorted
                long[] resIndices = newStorage.getIndices();
                double[] resValues = newStorage.getValues();
                int global = 0;
                while (v1Pointor < size1 && v2Pointor < size2) {
                    if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        resIndices[global] = v1Indices[v1Pointor];
                        resValues[global] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
                        global++;
                        v1Pointor++;
                        v2Pointor++;
                    } else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
                        resIndices[global] = v1Indices[v1Pointor];
                        resValues[global] = v1Values[v1Pointor];
                        global++;
                        v1Pointor++;
                    } else {
                        // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                        resIndices[global] = v2Indices[v2Pointor];
                        resValues[global] = op.apply(0, v2Values[v2Pointor]);
                        global++;
                        v2Pointor++;
                    }
                }
            } else {
                // dense
                while (v1Pointor < size1 || v2Pointor < size2) {
                    if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        newStorage.set(v1Indices[v1Pointor], op.apply(v1Values[v1Pointor], v2Values[v2Pointor]));
                        v1Pointor++;
                        v2Pointor++;
                    } else if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] < v2Indices[v2Pointor] || (v1Pointor < size1 && v2Pointor >= size2)) {
                        newStorage.set(v1Indices[v1Pointor], v1Values[v1Pointor]);
                        v1Pointor++;
                    } else if (((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] >= v2Indices[v2Pointor]) || (v1Pointor >= size1 && v2Pointor < size2)) {
                        newStorage.set(v2Indices[v2Pointor], op.apply(0, v2Values[v2Pointor]));
                        v2Pointor++;
                    }
                }
            }
        } else {
            if (op.isKeepStorage()) {
                long[] resIndices = newStorage.getIndices();
                double[] resValues = newStorage.getValues();
                int globalPointor = 0;
                while (v1Pointor < size1 && v2Pointor < size2) {
                    if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        resIndices[globalPointor] = v1Indices[v1Pointor];
                        resValues[globalPointor] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
                        v1Pointor++;
                        v2Pointor++;
                        globalPointor++;
                    } else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
                        resIndices[globalPointor] = v1Indices[v1Pointor];
                        resValues[globalPointor] = v1Values[v1Pointor];
                        v1Pointor++;
                        globalPointor++;
                    } else {
                        // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                        resIndices[globalPointor] = v2Indices[v2Pointor];
                        resValues[globalPointor] = op.apply(0, v2Values[v2Pointor]);
                        v2Pointor++;
                        globalPointor++;
                    }
                }
            } else {
                while (v1Pointor < size1 || v2Pointor < size2) {
                    if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        newStorage.set(v1Indices[v1Pointor], op.apply(v1Values[v1Pointor], v2Values[v2Pointor]));
                        v1Pointor++;
                        v2Pointor++;
                    } else if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] < v2Indices[v2Pointor] || (v1Pointor < size1 && v2Pointor >= size2)) {
                        newStorage.set(v1Indices[v1Pointor], v1Values[v1Pointor]);
                        v1Pointor++;
                    } else if (((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] >= v2Indices[v2Pointor]) || (v1Pointor >= size1 && v2Pointor < size2)) {
                        newStorage.set(v2Indices[v2Pointor], op.apply(0, v2Values[v2Pointor]));
                        v2Pointor++;
                    }
                }
            }
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return new LongDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}

Example 58 with LongLongVector

use of com.tencent.angel.ml.math2.vector.LongLongVector in project angel by Tencent.

the class SimpleBinaryOutAllExecutor method apply.

public static Vector apply(LongLongVector v1, LongDummyVector v2, Binary op) {
    LongLongVector res;
    if (v1.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            // multi-rehash
            LongLongVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongLongVectorStorage v1Storage = v1.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                }
            }
            res = new LongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else {
        // sorted
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongLongVectorStorage newStorage = new LongLongSparseVectorStorage(v1.getDim());
            LongLongVectorStorage v1Storage = v1.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                }
            }
            res = new LongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    }
    return res;
}

Example 59 with LongLongVector

use of com.tencent.angel.ml.math2.vector.LongLongVector in project angel by Tencent.

the class SimpleBinaryOutAllExecutor method apply.

public static Vector apply(LongDoubleVector v1, LongLongVector v2, Binary op) {
    LongDoubleVector res;
    if (v1.isSparse() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            // multi-rehash
            LongDoubleVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongDoubleVectorStorage v1Storage = v1.getStorage();
            LongLongVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0.0, 0));
                }
            }
            res = new LongDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSparse() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongDoubleVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongDoubleVectorStorage v1Storage = v1.getStorage();
            LongLongVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0.0, 0));
                }
            }
            res = new LongDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSorted() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongDoubleVectorStorage newStorage = new LongDoubleSparseVectorStorage(v1.getDim());
            LongDoubleVectorStorage v1Storage = v1.getStorage();
            LongLongVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0.0, 0));
                }
            }
            res = new LongDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSorted() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongDoubleVectorStorage newStorage = v1.getStorage().emptySorted((int) (v1.getDim()));
            long[] resIndices = newStorage.getIndices();
            double[] resValues = newStorage.getValues();
            int v1Pointor = 0;
            int v2Pointor = 0;
            long size1 = v1.size();
            long size2 = v2.size();
            long[] v1Indices = v1.getStorage().getIndices();
            double[] v1Values = v1.getStorage().getValues();
            long[] v2Indices = v2.getStorage().getIndices();
            long[] v2Values = v2.getStorage().getValues();
            if (!op.isCompare()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = Double.NaN;
                }
            }
            int globalPointor = 0;
            while (v1Pointor < size1 && v2Pointor < size2) {
                if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                    resIndices[globalPointor] = v1Indices[v1Pointor];
                    resValues[globalPointor] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
                    v1Pointor++;
                    v2Pointor++;
                    globalPointor++;
                } else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
                    resIndices[globalPointor] = v1Indices[v1Pointor];
                    resValues[globalPointor] = op.apply(v2Values[v2Pointor], 0);
                    v1Pointor++;
                    globalPointor++;
                } else {
                    // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                    resIndices[globalPointor] = v2Indices[v2Pointor];
                    resValues[globalPointor] = op.apply(0, v2Values[v2Pointor]);
                    v2Pointor++;
                    globalPointor++;
                }
            }
            res = new LongDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return res;
}

Example 60 with LongLongVector

use of com.tencent.angel.ml.math2.vector.LongLongVector in project angel by Tencent.

the class SimpleBinaryOutAllExecutor method apply.

public static Vector apply(LongLongVector v1, LongIntVector v2, Binary op) {
    LongLongVector res;
    if (v1.isSparse() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            // multi-rehash
            LongLongVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongLongVectorStorage v1Storage = v1.getStorage();
            LongIntVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0, 0));
                }
            }
            res = new LongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSparse() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongLongVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongLongVectorStorage v1Storage = v1.getStorage();
            LongIntVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0, 0));
                }
            }
            res = new LongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSorted() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongLongVectorStorage newStorage = new LongLongSparseVectorStorage(v1.getDim());
            LongLongVectorStorage v1Storage = v1.getStorage();
            LongIntVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0, 0));
                }
            }
            res = new LongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSorted() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongLongVectorStorage newStorage = v1.getStorage().emptySorted((int) (v1.getDim()));
            long[] resIndices = newStorage.getIndices();
            long[] resValues = newStorage.getValues();
            int v1Pointor = 0;
            int v2Pointor = 0;
            long size1 = v1.size();
            long size2 = v2.size();
            long[] v1Indices = v1.getStorage().getIndices();
            long[] v1Values = v1.getStorage().getValues();
            long[] v2Indices = v2.getStorage().getIndices();
            int[] v2Values = v2.getStorage().getValues();
            if (!op.isCompare()) {
                if (size1 != v1.getDim() && size2 != v2.getDim()) {
                    for (int i = 0; i < v1.getDim(); i++) {
                        resValues[i] = 0 / 0;
                    }
                }
            }
            int globalPointor = 0;
            while (v1Pointor < size1 && v2Pointor < size2) {
                if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                    resIndices[globalPointor] = v1Indices[v1Pointor];
                    resValues[globalPointor] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
                    v1Pointor++;
                    v2Pointor++;
                    globalPointor++;
                } else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
                    resIndices[globalPointor] = v1Indices[v1Pointor];
                    resValues[globalPointor] = op.apply(v2Values[v2Pointor], 0);
                    v1Pointor++;
                    globalPointor++;
                } else {
                    // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                    resIndices[globalPointor] = v2Indices[v2Pointor];
                    resValues[globalPointor] = op.apply(0, v2Values[v2Pointor]);
                    v2Pointor++;
                    globalPointor++;
                }
            }
            res = new LongLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return res;
}