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Parallel Colt is a multithreaded version of Colt - a library for high performance scientific computing in Java. It contains efficient algorithms for data analysis, linear algebra, multi-dimensional arrays, Fourier transforms, statistics and histogramming.

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/*
Copyright (C) 1999 CERN - European Organization for Nuclear Research.
Permission to use, copy, modify, distribute and sell this software and its documentation for any purpose 
is hereby granted without fee, provided that the above copyright notice appear in all copies and 
that both that copyright notice and this permission notice appear in supporting documentation. 
CERN makes no representations about the suitability of this software for any purpose. 
It is provided "as is" without expressed or implied warranty.
 */
package cern.colt.matrix.tdouble;

import cern.colt.matrix.tdouble.impl.DenseDoubleMatrix3D;
import cern.colt.matrix.tdouble.impl.SparseDoubleMatrix3D;
import cern.jet.math.tdouble.DoubleFunctions;

/**
 * Factory for convenient construction of 3-d matrices holding double
 * cells. Use idioms like DoubleFactory3D.dense.make(4,4,4) to
 * construct dense matrices, DoubleFactory3D.sparse.make(4,4,4) to
 * construct sparse matrices.
 * 
 * If the factory is used frequently it might be useful to streamline the
 * notation. For example by aliasing:
 * 
 * 
 * 
* *
 *  DoubleFactory3D F = DoubleFactory3D.dense;
 *  F.make(4,4,4);
 *  F.descending(10,20,5);
 *  F.random(4,4,5);
 *  ...
 * 
* *
* * @author [email protected] * @version 1.0, 09/24/99 */ public class DoubleFactory3D extends cern.colt.PersistentObject { private static final long serialVersionUID = 1L; /** * A factory producing dense matrices. */ public static final DoubleFactory3D dense = new DoubleFactory3D(); /** * A factory producing sparse matrices. */ public static final DoubleFactory3D sparse = new DoubleFactory3D(); /** * Makes this class non instantiable, but still let's others inherit from * it. */ protected DoubleFactory3D() { } /** * Constructs a matrix with cells having ascending values. For debugging * purposes. */ public DoubleMatrix3D ascending(int slices, int rows, int columns) { return descending(slices, rows, columns).assign( DoubleFunctions.chain(DoubleFunctions.neg, DoubleFunctions.minus(slices * rows * columns))); } /** * Constructs a matrix with cells having descending values. For debugging * purposes. */ public DoubleMatrix3D descending(int slices, int rows, int columns) { DoubleMatrix3D matrix = make(slices, rows, columns); int v = 0; for (int slice = slices; --slice >= 0;) { for (int row = rows; --row >= 0;) { for (int column = columns; --column >= 0;) { matrix.setQuick(slice, row, column, v++); } } } return matrix; } /** * Constructs a matrix with the given cell values. values is * required to have the form values[slice][row][column] and have * exactly the same number of slices, rows and columns as the receiver. *

* The values are copied. So subsequent changes in values are not * reflected in the matrix, and vice-versa. * * @param values * the values to be filled into the cells. * @return this (for convenience only). * @throws IllegalArgumentException * if * values.length != slices() || for any 0 <= slice < slices(): values[slice].length != rows() * . * @throws IllegalArgumentException * if * for any 0 <= column < columns(): values[slice][row].length != columns() * . */ public DoubleMatrix3D make(double[][][] values) { if (this == sparse) return new SparseDoubleMatrix3D(values); return new DenseDoubleMatrix3D(values); } /** * Constructs a matrix with the given shape, each cell initialized with * zero. */ public DoubleMatrix3D make(int slices, int rows, int columns) { if (this == sparse) return new SparseDoubleMatrix3D(slices, rows, columns); return new DenseDoubleMatrix3D(slices, rows, columns); } /** * Constructs a matrix with the given shape, each cell initialized with the * given value. */ public DoubleMatrix3D make(int slices, int rows, int columns, double initialValue) { return make(slices, rows, columns).assign(initialValue); } /** * Constructs a matrix with uniformly distributed values in (0,1) * (exclusive). */ public DoubleMatrix3D random(int slices, int rows, int columns) { return make(slices, rows, columns).assign(cern.jet.math.tdouble.DoubleFunctions.random()); } }





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