Example usage for weka.core.matrix Matrix getArray

Introduction

In this page you can find the example usage for weka.core.matrix Matrix getArray.

Prototype

public double[][] getArray() 

Source Link

Document

Access the internal two-dimensional array.

Usage

From source file:adams.data.instancesanalysis.pls.MatrixHelper.java

License:Open Source License

/**
 * Turns a Weka matrix into a Jama one.//from   w  w w  .j av  a2  s .co m
 *
 * @param weka   the Weka matrix to convert
 * @return      the converted matrix
 */
public static Jama.Matrix wekaToJama(weka.core.matrix.Matrix weka) {
    return new Jama.Matrix(weka.getArray());
}

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From source file:adams.data.instancesanalysis.pls.MatrixHelper.java

License:Open Source License

/**
 * Turns a Weka matrix into a matrix-algorithm one.
 *
 * @param weka   the Weka matrix to convert
 * @return      the converted matrix/*from   w  w w .  j a  v  a 2s  .  co m*/
 */
public static com.github.waikatodatamining.matrix.core.Matrix wekaToMatrixAlgo(weka.core.matrix.Matrix weka) {
    return MatrixFactory.fromRaw(weka.getArray());
}

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From source file:adams.data.instancesanalysis.pls.SIMPLS.java

License:Open Source License

/**
 * Zeroes the coefficients of the W matrix beyond the specified number of
 * coefficients./*  w  ww. j av a  2s  .  c  om*/
 *
 * @param in      the matrix to process in-place
 */
protected void slim(Matrix in) {
    double[][] B = in.getArray();

    for (int i = 0; i < in.getColumnDimension(); i++) {
        Matrix l = in.getMatrix(0, in.getRowDimension() - 1, i, i);
        double[] ld = l.getRowPackedCopy();
        for (int t = 0; t < ld.length; t++) {
            ld[t] = Math.abs(ld[t]);
        }
        int[] srt = weka.core.Utils.sort(ld);
        //int index = srt.length - 1 - srt[Math.min(getNumCoefficients(),srt.length-1)]; //nonono
        int index = srt[Math.max(srt.length - 1 - getNumCoefficients(), 0)];

        double val = ld[index];
        for (int c = 0; c < in.getRowDimension(); c++) {
            if (Math.abs(B[c][i]) < val) {
                B[c][i] = 0;
            }
        }
    }
}

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From source file:meka.classifiers.multilabel.PLST.java

License:Open Source License

/**
 * Transforms the predictions of the internal classifier back to the original labels.
 *
 * @param y The predictions that should be transformed back. The array consists only of
 * the predictions as they are returned from the internal classifier.
 * @return The transformed predictions.//  w ww  .  ja  v a 2 s  . co m
 */
@Override
public double[] transformPredictionsBack(double[] y) {
    // y consists of predictions and maxindex, we need only predictions
    double[] predictions = new double[y.length / 2];

    for (int i = 0; i < predictions.length; i++) {
        predictions[i] = y[predictions.length + i];
    }

    double[][] dataArray = new double[1][predictions.length];

    dataArray[0] = predictions;

    Matrix yMat = new Matrix(dataArray);

    Matrix multiplied = yMat.times(this.m_v.transpose()).plus(m_Shift);

    double[] res = new double[multiplied.getColumnDimension()];

    // change back from -1/1 coding to 0/1
    for (int i = 0; i < res.length; i++) {
        res[i] = multiplied.getArray()[0][i] < 0.0 ? 0.0 : 1.0;
    }

    return res;
}

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From source file:meka.core.MatrixUtils.java

License:Open Source License

/**
 * Helper method that transforms a Matrix object to an Instances object.
 *
 * @param mat The Matrix to transform.// w w w.j av a  2s .  c  o  m
 * @param patternInst the Instances template to use
 * @return  The resulting Instances object.
 */
public static Instances matrixToInstances(Matrix mat, Instances patternInst) {
    Instances result = new Instances(patternInst);
    for (int i = 0; i < mat.getRowDimension(); i++) {
        double[] row = mat.getArray()[i];
        DenseInstance denseInst = new DenseInstance(1.0, row);
        result.add(denseInst);
    }

    return result;
}

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