org.ejml.simple.SimpleMatrix Maven / Gradle / Ivy
/*
* Copyright (c) 2009-2014, Peter Abeles. All Rights Reserved.
*
* This file is part of Efficient Java Matrix Library (EJML).
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.ejml.simple;
import org.ejml.alg.generic.GenericMatrixOps;
import org.ejml.data.DenseMatrix64F;
import org.ejml.data.RealMatrix64F;
import org.ejml.ops.CommonOps;
import org.ejml.ops.CovarianceRandomDraw;
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( RealMatrix64F orig ) {
this.mat = new DenseMatrix64F(orig.getNumRows(),orig.getNumCols());
GenericMatrixOps.copy(orig,mat);
}
/**
* Constructor for internal library use only. Nothing is configured and is intended for serialization.
*/
public 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;
}
/**
*
* Creates a new vector which is drawn from a multivariate normal distribution with zero mean
* and the provided covariance.
*
*
* @see CovarianceRandomDraw
*
* @param covariance Covariance of the multivariate normal distribution
* @return Vector randomly drawn from the distribution
*/
public static SimpleMatrix randomNormal( SimpleMatrix covariance , Random random ) {
CovarianceRandomDraw draw = new CovarianceRandomDraw(random,covariance.getMatrix());
SimpleMatrix found = new SimpleMatrix(covariance.numRows(),1);
draw.next(found.getMatrix());
return found;
}
/**
* @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;
// }
}