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A fast and easy to use dense matrix linear algebra library written in Java.

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/*
 * Copyright (c) 2009-2012, Peter Abeles. All Rights Reserved.
 *
 * This file is part of Efficient Java Matrix Library (EJML).
 *
 * EJML 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 3
 * of the License, or (at your option) any later version.
 *
 * EJML 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 EJML.  If not, see .
 */

package org.ejml.simple;

import org.ejml.alg.generic.GenericMatrixOps;
import org.ejml.data.DenseMatrix64F;
import org.ejml.data.Matrix64F;
import org.ejml.ops.CommonOps;
import org.ejml.ops.RandomMatrices;

import java.util.Random;


/**
 * 

* {@link SimpleMatrix} is a wrapper around {@link org.ejml.data.DenseMatrix64F} that provides an * easy to use object oriented interface for performing matrix operations. It is designed to be * more accessible to novice programmers and provide a way to rapidly code up solutions by simplifying * memory management and providing easy to use functions. *

* *

* Most functions in SimpleMatrix do not modify the original matrix. Instead they * create a new SimpleMatrix instance which is modified and returned. This greatly simplifies memory * management and writing of code in general. It also allows operations to be chained, as is shown * below:
*
* SimpleMatrix K = P.mult(H.transpose().mult(S.invert())); *

* *

* Working with both {@link org.ejml.data.DenseMatrix64F} and SimpleMatrix in the same code base is easy. * To access the internal DenseMatrix64F in a SimpleMatrix simply call {@link SimpleMatrix#getMatrix()}. * To turn a DenseMatrix64F into a SimpleMatrix use {@link SimpleMatrix#wrap(org.ejml.data.DenseMatrix64F)}. Not * all operations in EJML are provided for SimpleMatrix, but can be accessed by extracting the internal * DenseMatrix64F. *

* *

* EXTENDING: SimpleMatrix contains a list of narrowly focused functions for linear algebra. To harness * the functionality for another application and to the number of functions it supports it is recommended * that one extends {@link SimpleBase} instead. This way the returned matrix type's of SimpleMatrix functions * will be of the appropriate types. See StatisticsMatrix inside of the examples directory. *

* *

* PERFORMANCE: The disadvantage of using this class is that it is more resource intensive, since * it creates a new matrix each time an operation is performed. This makes the JavaVM work harder and * Java automatically initializes the matrix to be all zeros. Typically operations on small matrices * or operations that have a runtime linear with the number of elements are the most affected. More * computationally intensive operations have only a slight unnoticeable performance loss. MOST PEOPLE * SHOULD NOT WORRY ABOUT THE SLIGHT LOSS IN PERFORMANCE. *

* *

* It is hard to judge how significant the performance hit will be in general. Often the performance * hit is insignificant since other parts of the application are more processor intensive or the bottle * neck is a more computationally complex operation. The best approach is benchmark and then optimize the code. *

* *

* If SimpleMatrix is extended then the protected function {link #createMatrix} should be extended and return * the child class. The results of SimpleMatrix operations will then be of the correct matrix type. *

* *

* The object oriented approach used in SimpleMatrix was originally inspired by Jama. * http://math.nist.gov/javanumerics/jama/ *

* * @author Peter Abeles */ public class SimpleMatrix extends SimpleBase { /** * A simplified way to reference the last row or column in the matrix for some functions. */ public static final int END = Integer.MAX_VALUE; /** *

* Creates a new matrix which has the same value as the matrix encoded in the * provided array. The input matrix's format can either be row-major or * column-major. *

* *

* Note that 'data' is a variable argument type, so either 1D arrays or a set of numbers can be * passed in:
* SimpleMatrix a = new SimpleMatrix(2,2,true,new double[]{1,2,3,4});
* SimpleMatrix b = new SimpleMatrix(2,2,true,1,2,3,4);
*
* Both are equivalent. *

* * @see DenseMatrix64F#DenseMatrix64F(int, int, boolean, double...) * * @param numRows The number of rows. * @param numCols The number of columns. * @param rowMajor If the array is encoded in a row-major or a column-major format. * @param data The formatted 1D array. Not modified. */ public SimpleMatrix(int numRows, int numCols, boolean rowMajor, double ...data) { mat = new DenseMatrix64F(numRows,numCols, rowMajor, data); } /** *

* Creates a matrix with the values and shape defined by the 2D array 'data'. * It is assumed that 'data' has a row-major formatting:
*
* data[ row ][ column ] *

* * @see org.ejml.data.DenseMatrix64F#DenseMatrix64F(double[][]) * * @param data 2D array representation of the matrix. Not modified. */ public SimpleMatrix(double data[][]) { mat = new DenseMatrix64F(data); } /** * Creates a new matrix that is initially set to zero with the specified dimensions. * * @see org.ejml.data.DenseMatrix64F#DenseMatrix64F(int, int) * * @param numRows The number of rows in the matrix. * @param numCols The number of columns in the matrix. */ public SimpleMatrix(int numRows, int numCols) { mat = new DenseMatrix64F(numRows, numCols); } /** * Creats a new SimpleMatrix which is identical to the original. * * @param orig The matrix which is to be copied. Not modified. */ public SimpleMatrix( SimpleMatrix orig ) { this.mat = orig.mat.copy(); } /** * Creates a new SimpleMatrix which is a copy of the DenseMatrix64F. * * @param orig The original matrix whose value is copied. Not modified. */ public SimpleMatrix( DenseMatrix64F orig ) { this.mat = orig.copy(); } /** * Creates a new SimpleMatrix which is a copy of the Matrix64F. * * @param orig The original matrix whose value is copied. Not modified. */ public SimpleMatrix( Matrix64F orig ) { this.mat = new DenseMatrix64F(orig.numRows,orig.numCols); GenericMatrixOps.copy(orig,mat); } protected SimpleMatrix(){} /** * Creates a new SimpleMatrix with the specified DenseMatrix64F used as its internal matrix. This means * that the reference is saved and calls made to the returned SimpleMatrix will modify the passed in DenseMatrix64F. * * @param internalMat The internal DenseMatrix64F of the returned SimpleMatrix. Will be modified. */ public static SimpleMatrix wrap( DenseMatrix64F internalMat ) { SimpleMatrix ret = new SimpleMatrix(); ret.mat = internalMat; return ret; } /** * Creates a new identity matrix with the specified size. * * @see org.ejml.ops.CommonOps#identity(int) * * @param width The width and height of the matrix. * @return An identity matrix. */ public static SimpleMatrix identity( int width ) { SimpleMatrix ret = new SimpleMatrix(width,width); CommonOps.setIdentity(ret.mat); return ret; } /** *

* Creates a matrix where all but the diagonal elements are zero. The values * of the diagonal elements are specified by the parameter 'vals'. *

* *

* To extract the diagonal elements from a matrix see {@link #extractDiag()}. *

* * @see org.ejml.ops.CommonOps#diag(double...) * * @param vals The values of the diagonal elements. * @return A diagonal matrix. */ public static SimpleMatrix diag( double ...vals ) { DenseMatrix64F m = CommonOps.diag(vals); SimpleMatrix ret = wrap(m); return ret; } /** *

* Creates a new SimpleMatrix with random elements drawn from a uniform distribution from minValue to maxValue. *

* * @see org.ejml.ops.RandomMatrices#setRandom(DenseMatrix64F,java.util.Random) * * @param numRows The number of rows in the new matrix * @param numCols The number of columns in the new matrix * @param minValue Lower bound * @param maxValue Upper bound * @param rand The random number generator that's used to fill the matrix. @return The new random matrix. */ public static SimpleMatrix random(int numRows, int numCols, double minValue, double maxValue, Random rand) { SimpleMatrix ret = new SimpleMatrix(numRows,numCols); RandomMatrices.setRandom(ret.mat,minValue,maxValue,rand); return ret; } /** * @inheritdoc */ @Override protected SimpleMatrix createMatrix( int numRows , int numCols ) { return new SimpleMatrix(numRows,numCols); } // TODO should this function be added back? It makes the code hard to read when its used // /** // *

// * Performs one of the following matrix multiplication operations:
// *
// * c = a * b
// * c = aT * b
// * c = a * b T
// * c = aT * b T
// *
// * where c is the returned matrix, a is this matrix, and b is the passed in matrix. // *

// * // * @see CommonOps#mult(DenseMatrix64F, DenseMatrix64F, DenseMatrix64F) // * @see CommonOps#multTransA(DenseMatrix64F, DenseMatrix64F, DenseMatrix64F) // * @see CommonOps#multTransB(DenseMatrix64F, DenseMatrix64F, DenseMatrix64F) // * @see CommonOps#multTransAB(DenseMatrix64F, DenseMatrix64F, DenseMatrix64F) // * // * @param tranA If true matrix A is transposed. // * @param tranB If true matrix B is transposed. // * @param b A matrix that is n by bn. Not modified. // * // * @return The results of this operation. // */ // public SimpleMatrix mult( boolean tranA , boolean tranB , SimpleMatrix b) { // SimpleMatrix ret; // // if( tranA && tranB ) { // ret = createMatrix(mat.numCols,b.mat.numRows); // CommonOps.multTransAB(mat,b.mat,ret.mat); // } else if( tranA ) { // ret = createMatrix(mat.numCols,b.mat.numCols); // CommonOps.multTransA(mat,b.mat,ret.mat); // } else if( tranB ) { // ret = createMatrix(mat.numRows,b.mat.numRows); // CommonOps.multTransB(mat,b.mat,ret.mat); // } else { // ret = createMatrix(mat.numRows,b.mat.numCols); // CommonOps.mult(mat,b.mat,ret.mat); // } // // return ret; // } }




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