/*-
 * Copyright (c) 2012 Diamond Light Source Ltd.
 *
 * All rights reserved. This program and the accompanying materials
 * are made available under the terms of the Eclipse Public License v1.0
 * which accompanies this distribution, and is available at
 * http://www.eclipse.org/legal/epl-v10.html
 */

package org.eclipse.dawnsci.analysis.dataset;


import static org.junit.Assert.assertEquals;

import org.eclipse.dawnsci.analysis.dataset.impl.Image;
import org.eclipse.january.dataset.Dataset;
import org.eclipse.january.dataset.DatasetFactory;
import org.eclipse.january.dataset.DatasetUtils;
import org.eclipse.january.dataset.DoubleDataset;
import org.eclipse.january.dataset.IntegerDataset;
import org.eclipse.january.dataset.Random;
import org.junit.Test;


public class ImageTest {

	@Test
	// TODO not really a test as such, but checks to make sure there are no execution errors
	public void testregrid() {
		
		Dataset ds = Random.rand(new int[] {100,100});
		Dataset pow = DatasetFactory.createRange(DoubleDataset.class, 100);
		pow.ipower(2);
		
		Dataset tile = pow.reshape(pow.getShape()[0],1);
		Dataset x = DatasetUtils.tile(tile, 100);
		
		Dataset y = DatasetUtils.transpose(x);
		
		Dataset lin = DatasetFactory.createRange(DoubleDataset.class, -100,900,10);
		
		// now apply the Transform
		@SuppressWarnings("unused")
		Dataset result = Image.regrid(ds, x, y, lin, lin);
		
	}
	
	@Test
	public void testMedianFilter() {
		Dataset ds = DatasetFactory.createRange(DoubleDataset.class, 1000);
		Dataset result = Image.medianFilter(ds, new int[] {3});
		assertEquals(result.getDouble(2), ds.getDouble(2), 0.001);
		
		ds = ds.reshape(new int[] {10,100});
		result = Image.medianFilter(ds, new int[] {3,3});
		assertEquals(result.getDouble(5,5), ds.getDouble(5,5), 0.001);
		
		ds = ds.reshape(new int[] {10,10,10});
		result = Image.medianFilter(ds, new int[] {3,3,3});
		assertEquals(result.getDouble(5,5,5), ds.getDouble(5,5,5), 0.001);
		
		ds = DatasetFactory.createRange(IntegerDataset.class, 1000);
		result = Image.medianFilter(ds, new int[] {3});
		assertEquals(result.getDouble(2), ds.getDouble(2), 0.001);
		
		ds = ds.reshape(new int[] {10,100});
		result = Image.medianFilter(ds, new int[] {3,3});
		assertEquals(result.getDouble(5,5), ds.getDouble(5,5), 0.001);
		
		ds = ds.reshape(new int[] {10,10,10});
		result = Image.medianFilter(ds, new int[] {3,3,3});
		assertEquals(result.getDouble(5,5,5), ds.getDouble(5,5,5), 0.001);
	}
	
	@Test
	public void testConvolutionFilter() {
		Dataset ds = DatasetFactory.createRange(DoubleDataset.class, 1000);
		Dataset kernel = DatasetFactory.ones(DoubleDataset.class, 27);
		Dataset result = Image.convolutionFilter(ds, kernel);
		assertEquals(120, result.getDouble(2), 0.001);
		
		ds = ds.reshape(new int[] {10,100});
		kernel = kernel.reshape(3,9);
		result = Image.convolutionFilter(ds, kernel);
		assertEquals(ds.getDouble(5,5)*27, result.getDouble(5,5), 0.001);
		
		ds = ds.reshape(new int[] {10,10,10});
		kernel = kernel.reshape(3,3,3);
		result = Image.convolutionFilter(ds, kernel);
		assertEquals(ds.getDouble(5,5,5)*27, result.getDouble(5,5,5), 0.001);
		
	}
	
	
	@Test
	public void testSobelFilter() {
		Dataset ds = Random.rand(new int[] {100,100});
		Image.sobelFilter(ds);
	}
}