public static MatrixBlock unaryOperations(MatrixObject inj, String opcode)
throws DMLRuntimeException {
Array2DRowRealMatrix matrixInput = DataConverter.convertToArray2DRowRealMatrix(inj);
if (opcode.equals("inverse")) return computeMatrixInverse(matrixInput);
else if (opcode.equals("cholesky")) return computeCholesky(matrixInput);
return null;
}
/**
* Function to perform LU decomposition on a given matrix.
*
* @param in matrix object
* @return array of matrix blocks
* @throws DMLRuntimeException if DMLRuntimeException occurs
*/
private static MatrixBlock[] computeLU(MatrixObject in) throws DMLRuntimeException {
if (in.getNumRows() != in.getNumColumns()) {
throw new DMLRuntimeException(
"LU Decomposition can only be done on a square matrix. Input matrix is rectangular (rows="
+ in.getNumRows()
+ ", cols="
+ in.getNumColumns()
+ ")");
}
Array2DRowRealMatrix matrixInput = DataConverter.convertToArray2DRowRealMatrix(in);
// Perform LUP decomposition
LUDecomposition ludecompose = new LUDecomposition(matrixInput);
RealMatrix P = ludecompose.getP();
RealMatrix L = ludecompose.getL();
RealMatrix U = ludecompose.getU();
// Read the results into native format
MatrixBlock mbP = DataConverter.convertToMatrixBlock(P.getData());
MatrixBlock mbL = DataConverter.convertToMatrixBlock(L.getData());
MatrixBlock mbU = DataConverter.convertToMatrixBlock(U.getData());
return new MatrixBlock[] {mbP, mbL, mbU};
}
/**
* Function to solve a given system of equations.
*
* @param in1 matrix object 1
* @param in2 matrix object 2
* @return matrix block
* @throws DMLRuntimeException if DMLRuntimeException occurs
*/
private static MatrixBlock computeSolve(MatrixObject in1, MatrixObject in2)
throws DMLRuntimeException {
Array2DRowRealMatrix matrixInput = DataConverter.convertToArray2DRowRealMatrix(in1);
Array2DRowRealMatrix vectorInput = DataConverter.convertToArray2DRowRealMatrix(in2);
/*LUDecompositionImpl ludecompose = new LUDecompositionImpl(matrixInput);
DecompositionSolver lusolver = ludecompose.getSolver();
RealMatrix solutionMatrix = lusolver.solve(vectorInput);*/
// Setup a solver based on QR Decomposition
QRDecomposition qrdecompose = new QRDecomposition(matrixInput);
DecompositionSolver solver = qrdecompose.getSolver();
// Invoke solve
RealMatrix solutionMatrix = solver.solve(vectorInput);
return DataConverter.convertToMatrixBlock(solutionMatrix.getData());
}
/**
* Function to perform QR decomposition on a given matrix.
*
* @param in matrix object
* @return array of matrix blocks
* @throws DMLRuntimeException if DMLRuntimeException occurs
*/
private static MatrixBlock[] computeQR(MatrixObject in) throws DMLRuntimeException {
Array2DRowRealMatrix matrixInput = DataConverter.convertToArray2DRowRealMatrix(in);
// Perform QR decomposition
QRDecomposition qrdecompose = new QRDecomposition(matrixInput);
RealMatrix H = qrdecompose.getH();
RealMatrix R = qrdecompose.getR();
// Read the results into native format
MatrixBlock mbH = DataConverter.convertToMatrixBlock(H.getData());
MatrixBlock mbR = DataConverter.convertToMatrixBlock(R.getData());
return new MatrixBlock[] {mbH, mbR};
}
/**
* Function to perform Eigen decomposition on a given matrix. Input must be a symmetric matrix.
*
* @param in matrix object
* @return array of matrix blocks
* @throws DMLRuntimeException if DMLRuntimeException occurs
*/
private static MatrixBlock[] computeEigen(MatrixObject in) throws DMLRuntimeException {
if (in.getNumRows() != in.getNumColumns()) {
throw new DMLRuntimeException(
"Eigen Decomposition can only be done on a square matrix. Input matrix is rectangular (rows="
+ in.getNumRows()
+ ", cols="
+ in.getNumColumns()
+ ")");
}
Array2DRowRealMatrix matrixInput = DataConverter.convertToArray2DRowRealMatrix(in);
EigenDecomposition eigendecompose = new EigenDecomposition(matrixInput);
RealMatrix eVectorsMatrix = eigendecompose.getV();
double[][] eVectors = eVectorsMatrix.getData();
double[] eValues = eigendecompose.getRealEigenvalues();
// Sort the eigen values (and vectors) in increasing order (to be compatible w/ LAPACK.DSYEVR())
int n = eValues.length;
for (int i = 0; i < n; i++) {
int k = i;
double p = eValues[i];
for (int j = i + 1; j < n; j++) {
if (eValues[j] < p) {
k = j;
p = eValues[j];
}
}
if (k != i) {
eValues[k] = eValues[i];
eValues[i] = p;
for (int j = 0; j < n; j++) {
p = eVectors[j][i];
eVectors[j][i] = eVectors[j][k];
eVectors[j][k] = p;
}
}
}
MatrixBlock mbValues = DataConverter.convertToMatrixBlock(eValues, true);
MatrixBlock mbVectors = DataConverter.convertToMatrixBlock(eVectors);
return new MatrixBlock[] {mbValues, mbVectors};
}
