Java Code Examples for weka.core.matrix.Matrix#getArray()

/** Generate matrix with standard-normally distributed random elements
     @param m    Number of rows.
     @param n    Number of colums.
     @return An m-by-n matrix with random elements.  */
 public static Matrix randomNormal( int m, int n ) {
   Random random = new Random();
    
   Matrix A = new Matrix(m,n);
   double[][] X = A.getArray();
   for (int i = 0; i < m; i++) {
     for (int j = 0; j < n; j++) {
X[i][j] = random.nextGaussian();
     }
   }
   return A;
 }
 

private double getLogDeterminant(Matrix L) {
  double logDeterminant;
  double detL = 0;
  int n = L.getRowDimension();
  double[][] matrixAsArray = L.getArray();
  for (int i = 0; i < n; i++) {

    detL += Math.log(matrixAsArray[i][i]);
  }
  logDeterminant = detL * 2;

  return logDeterminant;
}
 

/**
    * 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.
    */
   @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;
   }
 

/**
 * Helper method that transforms a Matrix object to an Instances object.
 *
 * @param mat The Matrix to transform.
 * @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;
}
 

/** Construct a PaceMatrix from a Matrix 
    @param X    Matrix 
*/
public PaceMatrix( Matrix X ) {
  super( X.getRowDimension(), X.getColumnDimension() );
  A = X.getArray();
}