/*
 * Zorbage: an algebraic data hierarchy for use in numeric processing.
 *
 * Copyright (C) 2016-2018 Barry DeZonia
 * 
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 * 
 * 1. Redistributions of source code must retain the above copyright notice,
 *    this list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 *    this list of conditions and the following disclaimer in the documentation
 *    and/or other materials provided with the distribution.
 * 
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
 * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
 * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
 * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
 * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
 * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
 * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
 * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 * POSSIBILITY OF SUCH DAMAGE.
 */
package nom.bdezonia.zorbage.algorithm;

import static org.junit.Assert.assertTrue;

import java.util.concurrent.ThreadLocalRandom;

import org.junit.Test;

import nom.bdezonia.zorbage.groups.G;
import nom.bdezonia.zorbage.type.data.int32.SignedInt32Member;
import nom.bdezonia.zorbage.type.data.point.Point;
import nom.bdezonia.zorbage.type.data.point.PointGroup;
import nom.bdezonia.zorbage.type.storage.IndexedDataSource;
import nom.bdezonia.zorbage.type.storage.array.ArrayStorage;

/**
 * 
 * @author Barry DeZonia
 *
 */
public class TestKMeans {

	@Test
	public void run() {
		
		int NUMELEMS = 100;
		
		PointGroup group = new PointGroup();

		Point point = new Point(2); // we will work in 2 dimensions
		
		SignedInt32Member num = G.INT32.construct();
		
		int numClusters = 3;
		
		IndexedDataSource<?, Point> points = ArrayStorage.allocate(NUMELEMS, point);

		IndexedDataSource<?, SignedInt32Member> clusterIndices = ArrayStorage.allocate(NUMELEMS, num);

		for (int i = 0; i < NUMELEMS; i++) {
			points.get(i, point);
			group.random().call(point);
		}
		
		KMeans.compute(group, numClusters, points, clusterIndices);
		
		assertTrue(true);
	}
}

@@ -1513,56 +1513,8 @@
 e;%0A%0A
-import java.util.concurrent.ThreadLocalRandom;%0A%0A
 impo

Eliminate a warning