All Downloads are FREE. Search and download functionalities are using the official Maven repository.

no.uib.cipr.matrix.Vector Maven / Gradle / Ivy

Go to download

Matrix data structures, linear solvers, least squares methods, eigenvalue, and singular value decompositions. For larger random dense matrices (above ~ 350 x 350) matrix-matrix multiplication C = A.B is about 50% faster than MTJ.

There is a newer version: 1.1.0
Show newest version
/*
 * Copyright (C) 2003-2006 Bjørn-Ove Heimsund
 * 
 * This file is part of MTJ.
 * 
 * This library 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 2.1 of the License, or (at your
 * option) any later version.
 * 
 * This library 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 this library; if not, write to the Free Software Foundation,
 * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
 */

package no.uib.cipr.matrix;

import java.io.Serializable;

/**
 * Basic vector interface. It holds doubles in an array, and is
 * used alongside Matrix in numerical computations. Implementing
 * classes decides on the actual storage.
 * 
 * 

Basic operations

*

* Use size to get the vector size. get(int) gets an * element, and there are corresponding set(int,double) and * add(int,double) methods as well. Note that vector indices are * zero-based (typical for Java and C). This means that they range from 0 to * size-1. It is legal to have size equal zero. *

*

* Other basic operations are zero which zeros all the entries of * the vector, which can be cheaper than either zeroing the vector manually, or * creating a new vector, and the operation copy which creates a * deep copy of the vector. This copy has separate storage, but starts with the * same contents as the current vector. *

*

Iterators

*

* The vector interface extends Iterable, and the iterator returns * a VectorEntry which contains current index and entry value. Note * that the iterator may skip non-zero entries. Using an iterator, many simple * and efficient algorithms can be created. The iterator also permits changing * values in the vector, however only non-zero entries can be changed. *

*

Basic linear algebra

*

* A selection of basic linear algebra operations are available. To ensure high * efficiency, little or no internal memory allocation is done, and the user is * required to supply the output arguments. *

*

* The operations available include: *

*
*
Additions
*
Vectors can be added to each other, even if their underlying vector * structures are incompatible
*
Scaling
*
Scalar multiplication (scaling) of a whole vector
*
Norms
*
Both innerproducts and norms can be computed. Several common norms are * supported
*
*/ public interface Vector extends Iterable, Serializable { /** * Size of the vector */ int size(); /** * x(index) = value */ void set(int index, double value); /** * x(index) += value */ void add(int index, double value); /** * Returns x(index) */ double get(int index); /** * Creates a deep copy of the vector */ Vector copy(); /** * Zeros all the entries in the vector, while preserving any underlying * structure */ Vector zero(); /** * x=alpha*x * * @return x */ Vector scale(double alpha); /** * x=y * * @return x */ Vector set(Vector y); /** * x=alpha*y * * @return x */ Vector set(double alpha, Vector y); /** * x = y + x * * @return x */ Vector add(Vector y); /** * x = alpha*y + x * * @return x */ Vector add(double alpha, Vector y); /** * xT*y */ double dot(Vector y); /** * Computes the given norm of the vector * * @param type * The type of norm to compute */ double norm(Norm type); /** * Supported vector-norms. The difference between the two 2-norms is that * one is fast, but can overflow, while the robust version is overflow * resistant, but slower. */ enum Norm { /** * Sum of the absolute values of the entries */ One, /** * The root of sum of squares */ Two, /** * As the 2 norm may overflow, an overflow resistant version is also * available. Note that it may be slower. */ TwoRobust, /** * Largest entry in absolute value */ Infinity } }




© 2015 - 2024 Weber Informatics LLC | Privacy Policy