/*
 * Encog(tm) Core v2.5 - Java Version
 * http://www.heatonresearch.com/encog/
 * http://code.google.com/p/encog-java/
 
 * Copyright 2008-2010 Heaton Research, Inc.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *   
 * For more information on Heaton Research copyrights, licenses 
 * and trademarks visit:
 * http://www.heatonresearch.com/copyright
 */

package org.encog.neural.data.image;

import java.awt.Image;

import org.encog.neural.data.basic.BasicNeuralData;
import org.encog.normalize.output.OutputFieldRangeMapped;
import org.encog.util.downsample.Downsample;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/**
 * An extension of the BasicNeuralData class that is designed to hold images for
 * input into a neural network. This class should only be used with the
 * ImageNeuralDataSet collection.
 *
 * This class provides the ability to associate images with the elements of a
 * dataset. These images will be downsampled to the resolution specified in the
 * ImageNeuralData set class that they are added to.
 *
 * @author jheaton
 *
 */
public class ImageNeuralData extends BasicNeuralData {

	/**
	 * The serial id.
	 */
	private static final long serialVersionUID = -4645971270240180450L;
	/**
	 * The image associated with this class.
	 */
	private Image image;

	/**
	 * The logging object.
	 */
	@SuppressWarnings("unused")
	private final Logger logger = LoggerFactory.getLogger(this.getClass());

	/**
	 * Construct an object based on an image.
	 *
	 * @param image
	 *            The image to use.
	 */
	public ImageNeuralData(final Image image) {
		super(1);
		this.image = image;
	}

	/**
	 * Downsample, and copy, the image contents into the data of this object.
	 * Calling this method has no effect on the image, as the same image can be
	 * downsampled multiple times to different resolutions.
	 *
	 * @param downsampler
	 *            The downsampler object to use.
	 * @param findBounds
	 *            Should the bounds be located and cropped.
	 * @param height
	 *            The height to downsample to.
	 * @param width
	 *            The width to downsample to.
	 * @param hi
	 *            The high value to normalize to.
	 * @param lo
	 *            The low value to normalize to.
	 */
	public void downsample(final Downsample downsampler,
			final boolean findBounds, final int height, final int width,
			final double hi, final double lo) {
		if (findBounds) {
			downsampler.findBounds();
		}
		final double[] sample = downsampler.downSample(this.image, height,
				width);

		for (int i = 0; i < sample.length; i++) {
			sample[i] = OutputFieldRangeMapped.calculate(sample[i], 0,
					255, hi,lo);
		}

		this.setData(sample);
	}

	/**
	 * @return the image
	 */
	public Image getImage() {
		return this.image;
	}

	/**
	 * @param image
	 *            the image to set
	 */
	public void setImage(final Image image) {
		this.image = image;
	}

	/**
	 * {@inheritDoc}
	 */
	@Override
	public String toString() {
		final StringBuilder builder = new StringBuilder("[ImageNeuralData:");
		for (int i = 0; i < this.getData().length; i++) {
			if (i != 0) {
				builder.append(',');
			}
			builder.append(this.getData(i));
		}
		builder.append("]");
		return builder.toString();
	}

}