Examples with IComplexNDArray org.nd4j.linalg.api.complex.IComplexNDArray used on opensource projects

Example 41 with IComplexNDArray

use of org.nd4j.linalg.api.complex.IComplexNDArray in project nd4j by deeplearning4j.

the class VectorSerializer method serialize.

@Override
public void serialize(INDArray indArray, JsonGenerator jsonGenerator, SerializerProvider serializerProvider) throws IOException {
    if (indArray.isView())
        indArray = indArray.dup(indArray.ordering());
    jsonGenerator.writeStartObject();
    DataBuffer view = indArray.data();
    jsonGenerator.writeArrayFieldStart("dataBuffer");
    for (int i = 0; i < view.length(); i++) {
        jsonGenerator.writeNumber(view.getDouble(i));
    }
    jsonGenerator.writeEndArray();
    jsonGenerator.writeArrayFieldStart("shapeField");
    for (int i = 0; i < indArray.rank(); i++) {
        jsonGenerator.writeNumber(indArray.size(i));
    }
    jsonGenerator.writeEndArray();
    jsonGenerator.writeArrayFieldStart("strideField");
    for (int i = 0; i < indArray.rank(); i++) jsonGenerator.writeNumber(indArray.stride(i));
    jsonGenerator.writeEndArray();
    jsonGenerator.writeNumberField("offsetField", indArray.offset());
    jsonGenerator.writeStringField("typeField", indArray instanceof IComplexNDArray ? "complex" : "real");
    jsonGenerator.writeNumberField("rankField", indArray.rank());
    jsonGenerator.writeNumberField("numElements", view.length());
    jsonGenerator.writeStringField("orderingField", String.valueOf(indArray.ordering()));
    jsonGenerator.writeEndObject();
}

Example 42 with IComplexNDArray

use of org.nd4j.linalg.api.complex.IComplexNDArray in project nd4j by deeplearning4j.

the class NDArrayStrings method vectorToString.

private String vectorToString(INDArray arr, boolean summarize) {
    StringBuilder sb = new StringBuilder();
    sb.append("[");
    for (int i = 0; i < arr.length(); i++) {
        if (arr instanceof IComplexNDArray) {
            sb.append(((IComplexNDArray) arr).getComplex(i).toString());
        } else {
            if (summarize && i > 2 && i < arr.length() - 3) {
                if (i == 3)
                    sb.append("  ...");
            } else {
                double arrElement = arr.getDouble(i);
                if (!dontOverrideFormat && ((Math.abs(arrElement) < this.minToPrintWithoutSwitching && arrElement != 0) || (Math.abs(arrElement) >= this.maxToPrintWithoutSwitching))) {
                    // switch to scientific notation
                    String asString = new DecimalFormat(scientificFormat).format(arrElement);
                    // from E to small e
                    asString = asString.replace('E', 'e');
                    sb.append(String.format("%1$" + padding + "s", asString));
                } else {
                    if (arrElement == 0) {
                        sb.append(String.format("%1$" + padding + "s", 0));
                    } else {
                        sb.append(String.format("%1$" + padding + "s", decimalFormat.format(arrElement)));
                    }
                }
            }
        }
        if (i < arr.length() - 1) {
            if (!summarize || i < 2 || i > arr.length() - 3 || (summarize && arr.length() == 6)) {
                sb.append(colSep);
            }
        }
    }
    sb.append("]");
    return sb.toString();
}

Example 43 with IComplexNDArray

use of org.nd4j.linalg.api.complex.IComplexNDArray in project nd4j by deeplearning4j.

the class BaseLoader method doSave.

private void doSave(INDArray save, String id) throws SQLException, IOException {
    Connection c = dataSource.getConnection();
    ByteArrayOutputStream bos = new ByteArrayOutputStream();
    DataOutputStream dos = new DataOutputStream(bos);
    if (save instanceof IComplexNDArray) {
        IComplexNDArray c2 = (IComplexNDArray) save;
        Nd4j.writeComplex(c2, dos);
    } else {
        BinarySerde.writeArrayToOutputStream(save, bos);
    }
    byte[] bytes = bos.toByteArray();
    PreparedStatement preparedStatement = c.prepareStatement(insertStatement());
    preparedStatement.setString(1, id);
    preparedStatement.setBytes(2, bytes);
    preparedStatement.executeUpdate();
}

Example 44 with IComplexNDArray

use of org.nd4j.linalg.api.complex.IComplexNDArray in project nd4j by deeplearning4j.

the class Eigen method eigenvectors.

/**
 * Computes the eigenvalues and eigenvectors of a general matrix.
 * <p/>
 * For matlab users note the following from their documentation:
 * The columns of V present eigenvectors of A. The diagonal matrix D contains eigenvalues.
 * <p/>
 * This is in reverse order of the matlab eig(A) call.
 *
 * @param A the ndarray to getFloat the eigen vectors for
 * @return 2 arrays representing W (eigen vectors) and V (normalized eigen vectors)
 */
public static IComplexNDArray[] eigenvectors(INDArray A) {
    assert A.columns() == A.rows();
    // setting up result arrays
    INDArray WR = Nd4j.create(A.rows());
    INDArray WI = WR.dup();
    INDArray VR = Nd4j.create(A.rows(), A.rows());
    INDArray VL = Nd4j.create(A.rows(), A.rows());
    Nd4j.getBlasWrapper().geev('v', 'v', A.dup(), WR, WI, VL, VR);
    // transferring the result
    IComplexNDArray E = Nd4j.createComplex(WR, WI);
    IComplexNDArray V = Nd4j.createComplex(A.rows(), A.rows());
    for (int i = 0; i < A.rows(); i++) {
        if (E.getComplex(i).isReal()) {
            IComplexNDArray column = Nd4j.createComplex(VR.getColumn(i));
            V.putColumn(i, column);
        } else {
            IComplexNDArray v = Nd4j.createComplex(VR.getColumn(i), VR.getColumn(i + 1));
            V.putColumn(i, v);
            V.putColumn(i + 1, v.conji());
            i += 1;
        }
    }
    return new IComplexNDArray[] { Nd4j.diag(E), V };
}

Example 45 with IComplexNDArray

use of org.nd4j.linalg.api.complex.IComplexNDArray in project nd4j by deeplearning4j.

the class Nd4j method sort.

/**
 * Sort an ndarray along a particular dimension
 *
 * @param ndarray   the ndarray to sort
 * @param dimension the dimension to sort
 * @return the sorted ndarray
 */
public static IComplexNDArray sort(IComplexNDArray ndarray, int dimension, boolean ascending) {
    for (int i = 0; i < ndarray.vectorsAlongDimension(dimension); i++) {
        IComplexNDArray vec = ndarray.vectorAlongDimension(i, dimension);
        IComplexNumber[] data = new IComplexNumber[vec.length()];
        for (int j = 0; j < vec.length(); j++) {
            data[j] = vec.getComplex(j);
        }
        if (ascending)
            Arrays.sort(data, new Comparator<IComplexNumber>() {

                @Override
                public int compare(IComplexNumber o1, IComplexNumber o2) {
                    return Double.compare(o1.asDouble().absoluteValue().doubleValue(), o2.asDouble().absoluteValue().doubleValue());
                }
            });
        else
            Arrays.sort(data, new Comparator<IComplexNumber>() {

                @Override
                public int compare(IComplexNumber o1, IComplexNumber o2) {
                    return -Double.compare(o1.asDouble().absoluteValue().doubleValue(), o2.asDouble().absoluteValue().doubleValue());
                }
            });
        for (int j = 0; j < vec.length(); j++) vec.putScalar(j, data[j]);
    }
    return ndarray;
}