Examples with NdIndexIterator org.nd4j.linalg.api.iter.NdIndexIterator used on opensource projects

Example 6 with NdIndexIterator

use of org.nd4j.linalg.api.iter.NdIndexIterator in project deeplearning4j by deeplearning4j.

the class BackPropMLPTest method asFloat.

public static float[] asFloat(INDArray arr) {
    int len = arr.length();
    float[] f = new float[len];
    NdIndexIterator iterator = new NdIndexIterator('c', arr.shape());
    for (int i = 0; i < len; i++) {
        f[i] = arr.getFloat(iterator.next());
    }
    return f;
}

Example 7 with NdIndexIterator

use of org.nd4j.linalg.api.iter.NdIndexIterator in project nd4j by deeplearning4j.

the class BaseNDArray method put.

@Override
public INDArray put(INDArray indices, INDArray element) {
    if (indices.rank() > 2) {
        throw new ND4JIllegalArgumentException("Indices must be a vector or matrix.");
    }
    if (indices.rows() == rank()) {
        NdIndexIterator ndIndexIterator = new NdIndexIterator(element.shape());
        for (int i = 0; i < indices.columns(); i++) {
            int[] specifiedIndex = indices.getColumn(i).dup().data().asInt();
            putScalar(specifiedIndex, element.getDouble(ndIndexIterator.next()));
        }
    } else {
        List<INDArray> arrList = new ArrayList<>();
        if (indices.isMatrix() || indices.isColumnVector()) {
            for (int i = 0; i < indices.rows(); i++) {
                INDArray row = indices.getRow(i);
                for (int j = 0; j < row.length(); j++) {
                    INDArray slice = slice(row.getInt(j));
                    Nd4j.getExecutioner().exec(new Assign(new INDArray[] { slice, element }, new INDArray[] { slice }));
                    arrList.add(slice(row.getInt(j)));
                }
            }
        } else if (indices.isRowVector()) {
            for (int i = 0; i < indices.length(); i++) {
                arrList.add(slice(indices.getInt(i)));
            }
        }
    }
    return this;
}

Example 8 with NdIndexIterator

use of org.nd4j.linalg.api.iter.NdIndexIterator in project nd4j by deeplearning4j.

the class NormalDistribution method sample.

@Override
public INDArray sample(INDArray ret) {
    if (random.getStatePointer() != null) {
        if (means != null) {
            return Nd4j.getExecutioner().exec(new GaussianDistribution(ret, means, standardDeviation), random);
        } else {
            return Nd4j.getExecutioner().exec(new GaussianDistribution(ret, mean, standardDeviation), random);
        }
    } else {
        // For consistent values irrespective of c vs. fortran ordering
        Iterator<int[]> idxIter = new NdIndexIterator(ret.shape());
        int len = ret.length();
        if (means != null) {
            for (int i = 0; i < len; i++) {
                int[] idx = idxIter.next();
                ret.putScalar(idx, standardDeviation * random.nextGaussian() + means.getDouble(idx));
            }
        } else {
            for (int i = 0; i < len; i++) {
                ret.putScalar(idxIter.next(), standardDeviation * random.nextGaussian() + mean);
            }
        }
        return ret;
    }
}

Example 9 with NdIndexIterator

use of org.nd4j.linalg.api.iter.NdIndexIterator in project nd4j by deeplearning4j.

the class LapackTest method testEv.

void testEv(int N, char matrixOrder) {
    INDArray A = Nd4j.rand(N, N, matrixOrder);
    for (int r = 1; r < N; r++) {
        for (int c = 0; c < r; c++) {
            double v = A.getDouble(r, c);
            A.putScalar(c, r, v);
        }
    }
    INDArray Aorig = A.dup();
    INDArray V = Nd4j.create(N);
    Nd4j.getBlasWrapper().lapack().syev('V', 'U', A, V);
    INDArray VV = Nd4j.create(N, N);
    for (int i = 0; i < N; i++) {
        VV.put(i, i, V.getDouble(i));
    }
    INDArray L = Aorig.mmul(A);
    INDArray R = A.mmul(VV);
    NdIndexIterator iter = new NdIndexIterator(L.shape());
    while (iter.hasNext()) {
        int[] pos = iter.next();
        assertEquals("SVD did not factorize properly", L.getDouble(pos), R.getDouble(pos), 1e-5);
    }
}

Example 10 with NdIndexIterator

use of org.nd4j.linalg.api.iter.NdIndexIterator in project nd4j by deeplearning4j.

the class LapackTest method testSvd.

// 
// Helper functions - not direct test cases
// 
void testSvd(int M, int N, char matrixOrder) {
    INDArray A = Nd4j.rand(M, N, matrixOrder);
    INDArray Aorig = A.dup();
    INDArray U = Nd4j.create(M, M, matrixOrder);
    INDArray S = Nd4j.create(N, matrixOrder);
    INDArray VT = Nd4j.create(N, N, matrixOrder);
    Nd4j.getBlasWrapper().lapack().gesvd(A, S, U, VT);
    INDArray SS = Nd4j.create(M, N);
    for (int i = 0; i < Math.min(M, N); i++) {
        SS.put(i, i, S.getDouble(i));
    }
    INDArray AA = U.mmul(SS).mmul(VT);
    NdIndexIterator iter = new NdIndexIterator(AA.shape());
    while (iter.hasNext()) {
        int[] pos = iter.next();
        assertEquals("SVD did not factorize properly", AA.getDouble(pos), Aorig.getDouble(pos), 1e-5);
    }
}