org.ujmp.parallelcolt.ParallelColtDenseDoubleMatrix2D Maven / Gradle / Ivy

Go to download
Show more of this group Show more artifacts with this name
Show all versions of ujmp-parallelcolt Show documentation
Plugin to incorporate dense and sparse matrix classes from ParallelColt
The newest version!
/*
 * Copyright (C) 2008-2015 by Holger Arndt
 *
 * This file is part of the Universal Java Matrix Package (UJMP).
 * See the NOTICE file distributed with this work for additional
 * information regarding copyright ownership and licensing.
 *
 * UJMP is free software; you can redistribute it and/or modify
 * it under the terms of the GNU Lesser General Public License as
 * published by the Free Software Foundation; either version 2
 * of the License, or (at your option) any later version.
 *
 * UJMP is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
 * GNU Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with UJMP; if not, write to the
 * Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
 * Boston, MA  02110-1301  USA
 */

package org.ujmp.parallelcolt;

import org.ujmp.core.Matrix;
import org.ujmp.core.doublematrix.DenseDoubleMatrix2D;
import org.ujmp.core.doublematrix.stub.AbstractDenseDoubleMatrix2D;
import org.ujmp.core.interfaces.HasRowMajorDoubleArray2D;
import org.ujmp.core.interfaces.Wrapper;
import org.ujmp.core.mapmatrix.MapMatrix;
import org.ujmp.parallelcolt.calculation.Solve;

import cern.colt.matrix.tdouble.DoubleFactory2D;
import cern.colt.matrix.tdouble.DoubleMatrix2D;
import cern.colt.matrix.tdouble.algo.DenseDoubleAlgebra;
import cern.colt.matrix.tdouble.algo.decomposition.DenseDoubleCholeskyDecomposition;
import cern.colt.matrix.tdouble.algo.decomposition.DenseDoubleEigenvalueDecomposition;
import cern.colt.matrix.tdouble.algo.decomposition.DenseDoubleLUDecomposition;
import cern.colt.matrix.tdouble.algo.decomposition.DenseDoubleQRDecomposition;
import cern.colt.matrix.tdouble.algo.decomposition.DenseDoubleSingularValueDecomposition;
import cern.jet.math.tdouble.DoubleFunctions;

public class ParallelColtDenseDoubleMatrix2D extends AbstractDenseDoubleMatrix2D implements
		Wrapper {
	private static final long serialVersionUID = -1941030601886654699L;

	public static final ParallelColtDenseDoubleMatrix2DFactory Factory = new ParallelColtDenseDoubleMatrix2DFactory();

	public static final DenseDoubleAlgebra ALG = new DenseDoubleAlgebra();

	private final cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D matrix;

	public ParallelColtDenseDoubleMatrix2D(int rows, int columns) {
		super(rows, columns);
		this.matrix = new cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D(rows, columns);
	}

	public ParallelColtDenseDoubleMatrix2D(DoubleMatrix2D m) {
		super(m.rows(), m.columns());
		if (m instanceof DenseDoubleMatrix2D) {
			this.matrix = (cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D) m;
		} else {
			this.matrix = new cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D(m.toArray());
			// this.matrix = new
			// cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D(
			// m.rows(), m.columns());
			// for (int r = 0; r < m.rows(); r++) {
			// for (int c = 0; c < m.columns(); c++) {
			// matrix.setQuick(r, c, m.getQuick(r, c));
			// }
			// }
		}
	}

	public ParallelColtDenseDoubleMatrix2D(cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D m) {
		super(m.rows(), m.columns());
		this.matrix = m;
	}

	public ParallelColtDenseDoubleMatrix2D(Matrix source) {
		super(source.getRowCount(), source.getColumnCount());
		if (source instanceof HasRowMajorDoubleArray2D) {
			final double[][] data = ((HasRowMajorDoubleArray2D) source).getRowMajorDoubleArray2D();
			this.matrix = new cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D(data);
		} else if (source instanceof DenseDoubleMatrix2D) {
			this.matrix = new cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D((int) source.getRowCount(),
					(int) source.getColumnCount());
			final DenseDoubleMatrix2D m2 = (DenseDoubleMatrix2D) source;
			for (int r = (int) source.getRowCount(); --r >= 0;) {
				for (int c = (int) source.getColumnCount(); --c >= 0;) {
					matrix.setQuick(r, c, m2.getDouble(r, c));
				}
			}
		} else {
			this.matrix = new cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D((int) source.getRowCount(),
					(int) source.getColumnCount());
			for (long[] c : source.availableCoordinates()) {
				setDouble(source.getAsDouble(c), c);
			}
		}
		if (source.getMetaData() != null) {
			setMetaData(source.getMetaData().clone());
		}
	}

	public double getDouble(long row, long column) {
		return matrix.getQuick((int) row, (int) column);
	}

	public double getDouble(int row, int column) {
		return matrix.getQuick(row, column);
	}

	public void setDouble(double value, long row, long column) {
		matrix.setQuick((int) row, (int) column, value);
	}

	public void setDouble(double value, int row, int column) {
		matrix.setQuick(row, column, value);
	}

	public cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D getWrappedObject() {
		return matrix;
	}

	public Matrix plus(double value) {
		Matrix result = new ParallelColtDenseDoubleMatrix2D((cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D) matrix
				.copy().assign(DoubleFunctions.plus(value)));
		MapMatrix a = getMetaData();
		if (a != null) {
			result.setMetaData(a.clone());
		}
		return result;
	}

	public Matrix inv() {
		return new ParallelColtDenseDoubleMatrix2D(
				(cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D) ALG.inverse(matrix));
	}

	public Matrix times(double value) {
		Matrix result = new ParallelColtDenseDoubleMatrix2D((cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D) matrix
				.copy().assign(DoubleFunctions.mult(value)));
		MapMatrix a = getMetaData();
		if (a != null) {
			result.setMetaData(a.clone());
		}
		return result;
	}

	public Matrix transpose() {
		return new ParallelColtDenseDoubleMatrix2D((cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D) matrix
				.viewDice().copy());
	}

	public Matrix plus(Matrix m) {
		if (m instanceof ParallelColtDenseDoubleMatrix2D) {
			DoubleMatrix2D result = matrix.copy();
			result.assign(((ParallelColtDenseDoubleMatrix2D) m).getWrappedObject(), DoubleFunctions.plus);
			Matrix ret = new ParallelColtDenseDoubleMatrix2D(result);
			MapMatrix a = getMetaData();
			if (a != null) {
				ret.setMetaData(a.clone());
			}
			return ret;
		} else {
			return super.plus(m);
		}
	}

	public Matrix minus(Matrix m) {
		if (m instanceof ParallelColtDenseDoubleMatrix2D) {
			DoubleMatrix2D result = matrix.copy();
			result.assign(((ParallelColtDenseDoubleMatrix2D) m).getWrappedObject(), DoubleFunctions.minus);
			Matrix ret = new ParallelColtDenseDoubleMatrix2D(result);
			MapMatrix a = getMetaData();
			if (a != null) {
				ret.setMetaData(a.clone());
			}
			return ret;
		} else {
			return super.minus(m);
		}
	}

	public Matrix mtimes(Matrix m) {
		if (m instanceof ParallelColtDenseDoubleMatrix2D) {
			cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D ret = new cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D(
					(int) getRowCount(), (int) m.getColumnCount());
			matrix.zMult(((ParallelColtDenseDoubleMatrix2D) m).matrix, ret);
			Matrix result = new ParallelColtDenseDoubleMatrix2D(ret);
			MapMatrix a = getMetaData();
			if (a != null) {
				result.setMetaData(a.clone());
			}
			return result;
		} else {
			return super.mtimes(m);
		}
	}

	public Matrix[] svd() {
		DenseDoubleSingularValueDecomposition svd = new DenseDoubleSingularValueDecomposition(matrix, true, false);
		Matrix u = new ParallelColtDenseDoubleMatrix2D(svd.getU());
		Matrix s = new ParallelColtDenseDoubleMatrix2D(svd.getS());
		Matrix v = new ParallelColtDenseDoubleMatrix2D(svd.getV());
		return new Matrix[] { u, s, v };
	}

	public Matrix[] eig() {
		DenseDoubleEigenvalueDecomposition eig = new DenseDoubleEigenvalueDecomposition(matrix);
		Matrix v = new ParallelColtDenseDoubleMatrix2D(eig.getV());
		Matrix d = new ParallelColtDenseDoubleMatrix2D(eig.getD());
		return new Matrix[] { v, d };
	}

	public Matrix[] qr() {
		DenseDoubleQRDecomposition qr = new DenseDoubleQRDecomposition(matrix);
		Matrix q = new ParallelColtDenseDoubleMatrix2D(qr.getQ(false));
		Matrix r = new ParallelColtDenseDoubleMatrix2D(qr.getR(false));
		return new Matrix[] { q, r };
	}

	public Matrix[] lu() {
		if (getRowCount() >= getColumnCount()) {
			DenseDoubleLUDecomposition lu = new DenseDoubleLUDecomposition(matrix);
			Matrix l = new ParallelColtDenseDoubleMatrix2D(lu.getL());
			Matrix u = new ParallelColtDenseDoubleMatrix2D(lu.getU().viewPart(0, 0, (int) getColumnCount(),
					(int) getColumnCount()));
			int m = (int) getRowCount();
			int[] piv = lu.getPivot();
			Matrix p = new ParallelColtDenseDoubleMatrix2D(m, m);
			for (int i = 0; i < m; i++) {
				p.setAsDouble(1, i, piv[i]);
			}
			return new Matrix[] { l, u, p };
		} else {
			throw new RuntimeException("only supported for matrices m>=n");
		}
	}

	public Matrix chol() {
		DenseDoubleCholeskyDecomposition chol = new DenseDoubleCholeskyDecomposition(matrix);
		Matrix r = new ParallelColtDenseDoubleMatrix2D(chol.getL());
		return r;
	}

	public Matrix copy() {
		Matrix m = new ParallelColtDenseDoubleMatrix2D(
				(cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D) matrix.copy());
		if (getMetaData() != null) {
			m.setMetaData(getMetaData().clone());
		}
		return m;
	}

	public Matrix solve(Matrix b) {
		return Solve.INSTANCE.calc(this, b);
	}

	public Matrix solveSPD(Matrix b) {
		if (b instanceof ParallelColtDenseDoubleMatrix2D) {
			ParallelColtDenseDoubleMatrix2D b2 = new ParallelColtDenseDoubleMatrix2D(b);
			DenseDoubleCholeskyDecomposition chol = new DenseDoubleCholeskyDecomposition(matrix);
			chol.solve(b2.matrix);
			return b2;
		} else {
			return super.solve(b);
		}
	}

	public Matrix invSPD() {
		DenseDoubleCholeskyDecomposition chol = new DenseDoubleCholeskyDecomposition(matrix);
		DoubleMatrix2D ret = DoubleFactory2D.dense.identity(matrix.rows());
		chol.solve(ret);
		return new ParallelColtDenseDoubleMatrix2D(ret);
	}

	public ParallelColtDenseDoubleMatrix2DFactory getFactory() {
		return Factory;
	}
}