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Fast double-precision vector and matrix maths library for Java, supporting N-dimensional numeric arrays.

There is a newer version: 0.67.0

package mikera.vectorz.util;

import mikera.arrayz.INDArray;
import mikera.util.Rand;
import mikera.util.Random;
import mikera.vectorz.AVector;
import mikera.vectorz.Vector;
import mikera.vectorz.Vectorz;
import mikera.vectorz.impl.Vector0;

/**
 * Utility function for testing arrays / matrix implementations
 * @author Mike
 */
public class Testing {

	private Testing(){}

	public static AVector createTestVector(int length) {
		return createTestVector(length,new Random());
	} 
	
	public static AVector createTestVector(int length, Random r) {
		if (length<0) throw new IllegalArgumentException("Negative vector length!");
		if (length==0) {
			switch (r.nextInt(2)) {
				case 0: return Vector0.INSTANCE;
				case 1: return Vector.createLength(0);
				default: return Vector0.INSTANCE;
			}
		}
		if ((length<=5)&&r.nextInt(100)<50) {
			return Vectorz.newVector(length);
		}
		if (r.nextInt(100)<50) {
			int mid=r.nextInt(length+1);
			return createTestVector(mid,r).join(createTestVector(length-mid,r));
		}
		return Vector.createLength(length);
	} 
	
	/**
	 * Fills an array with random values in the [0..1) range. Returns the mutated array.
	 * @param a
	 * @param r
	 * @return
	 */
	public static INDArray fillRandom(INDArray a, Random r) {
		int dims=a.dimensionality();
		if (dims==0) {
			a.set(r.nextDouble());
		} else if (dims==1) {
			int len=a.getShape(0);
			for (int i=0; i0)) return false;	
		
		for (int i=0; i