/*
 * #%L,
 * ImageJ software for multidimensional image processing and analysis.
 * %%
 * Copyright (C) 2014 - 2015 Board of Regents of the University of
 * Wisconsin-Madison, University of Konstanz and Brian Northan.
 * %%
 * 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
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 * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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 * #L%
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package net.imagej.ops.filter.dog;

import java.util.concurrent.Executors;

import net.imagej.ops.AbstractOpTest;
import net.imglib2.Cursor;
import net.imglib2.RandomAccessibleInterval;
import net.imglib2.algorithm.dog.DifferenceOfGaussian;
import net.imglib2.img.Img;
import net.imglib2.type.numeric.integer.ByteType;
import net.imglib2.view.Views;

import org.junit.Test;

/**
 * Tests Difference of Gaussians (DoG) implementations.
 * 
 * @author Christian Dietz, University of Konstanz
 */
public class DoGTest extends AbstractOpTest {

	@Test
	public void dogRAITest() {

		final double[] sigmas1 = new double[] { 1, 1 };
		final double[] sigmas2 = new double[] { 2, 2 };
		final long[] dims = new long[] { 10, 10 };

		final Img<ByteType> in = generateByteTestImg(true, dims);
		final Img<ByteType> out1 = generateByteTestImg(false, dims);
		final Img<ByteType> out2 = generateByteTestImg(false, dims);

		ops.filter().dog(out1, in, sigmas1, sigmas2);

		// test against native imglib2 implementation
		net.imglib2.algorithm.dog.DifferenceOfGaussian.DoG(sigmas1, sigmas2, Views
			.extendMirrorSingle(in), out2, Executors.newFixedThreadPool(10));

		final Cursor<ByteType> out1Cursor = out1.cursor();
		final Cursor<ByteType> out2Cursor = out2.cursor();

		while (out1Cursor.hasNext()) {
			org.junit.Assert.assertEquals(out1Cursor.next().getRealDouble(),
				out2Cursor.next().getRealDouble(), 0);
		}
	}

	@Test
	public void dogRAISingleSigmasTest() {
		final RandomAccessibleInterval<ByteType> res =
			ops.filter().dog(generateByteTestImg(true, new long[] { 10, 10 }), 1, 2);

		org.junit.Assert.assertNotNull(res);
	}
}

@@ -2548,34 +2548,8 @@
 n%0A%09%09
-net.imglib2.algorithm.dog.
 Diff
@@ -2592,20 +2592,16 @@
 2, Views
-%0A%09%09%09
 .extendM
@@ -2616,17 +2616,20 @@
 gle(in),
- 
+%0A%09%09%09
 out2, Ex

remove unneeded fully qualified reference