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/**
* Jun 4, 2007
*
* @author Samuel Halliday, ThinkTank Maths Limited
* @copyright ThinkTank Maths Limited 2007
*/
package org.netlib.blas;
import java.util.Random;
import junit.framework.TestCase;
/**
* @author Samuel Halliday, ThinkTank Maths Limited
*/
public class BLASTest extends TestCase {
private final BLAS jBLAS = JBLAS.INSTANCE;
private final NativeBLAS nativeBLAS = NativeBLAS.INSTANCE;
public void testDot() {
testDot1(jBLAS);
testDot1(nativeBLAS);
}
/**
* We test the JNI and the Java code at the same time so that we can compare results.
* Future JUnit tests should probably test against prior results so that we can write
* tests for the BLAS interface and then send the appropriate implementation to it.
*
* @see #testDot()
*/
public void testDotSpeed() {
assert nativeBLAS.isLoaded;
int[] sizes = new int[]{10, 100, 1000, 10000, 20000, 50000, 75000,
100000, 200000, 500000, 1000000, 10000000
}; // , 50000000 };
for (int size : sizes) {
final double[] array1 = randomArray(size);
final double[] array2 = randomArray(size);
long start = System.currentTimeMillis();
double outJ = jBLAS.ddot(size, array1, 1, array2, 1);
long endJ = System.currentTimeMillis();
double outN = nativeBLAS.ddot(size, array1, 1, array2, 1);
long endN = System.currentTimeMillis();
assert Math.abs(outJ - outN) < 0.00001d;
System.out.println("Array size: " + size + ", jLAPACK took: " +
(endJ - start) / 1000.0 + ", nativeLAPACK took: " +
(endN - endJ) / 1000.0);
}
}
// return array of size n with normally distributed elements
// this is a bottleneck when running the tests
private double[] randomArray(int n) {
assert n > 0;
Random random = new Random();
double[] array = new double[n];
for (int i = 0; i < n; i++) {
array[i] = random.nextGaussian();
}
return array;
}
private void testDot1(BLAS blas) {
double[] dx = {1.1, 2.2, 3.3, 4.4};
double[] dy = {1.1, 2.2, 3.3, 4.4};
int n = dx.length;
double answer = blas.ddot(n, dx, 1, dy, 1);
assert Math.abs(answer - 36.3) < 0.00001d;
}
}
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