/*
*

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.
*/

package railo.runtime.img.filter;

/**
 * An image histogram.
 */
public class Histogram {

	public static final int RED = 0;
	public static final int GREEN = 1;
	public static final int BLUE = 2;
	public static final int GRAY = 3;

	protected int[][] histogram;
	protected int numSamples;
	protected int[] minValue;
	protected int[] maxValue;
	protected int[] minFrequency;
	protected int[] maxFrequency;
	protected float[] mean;
	protected boolean isGray;

	public Histogram() {
		histogram = null;
		numSamples = 0;
		isGray = true;
		minValue = null;
		maxValue = null;
		minFrequency = null;
		maxFrequency = null;
		mean = null;
	}

	public Histogram(int[] pixels, int w, int h, int offset, int stride) {
		histogram = new int[3][256];
		minValue = new int[4];
		maxValue = new int[4];
		minFrequency = new int[3];
		maxFrequency = new int[3];
		mean = new float[3];

		numSamples = w*h;
		isGray = true;

		int index = 0;
		for (int y = 0; y < h; y++) {
			index = offset+y*stride;
			for (int x = 0; x < w; x++) {
				int rgb = pixels[index++];
				int r = (rgb >> 16) & 0xff;
				int g = (rgb >> 8) & 0xff;
				int b = rgb & 0xff;
				histogram[RED][r]++;
				histogram[GREEN][g]++;
				histogram[BLUE][b]++;
			}
		}

		for (int i = 0; i < 256; i++) {
			if (histogram[RED][i] != histogram[GREEN][i] || histogram[GREEN][i] != histogram[BLUE][i]) {
				isGray = false;
				break;
			}
		}

		for (int i = 0; i < 3; i++) {
			for (int j = 0; j < 256; j++) {
				if (histogram[i][j] > 0) {
					minValue[i] = j;
					break;
				}
			}

			for (int j = 255; j >= 0; j--) {
				if (histogram[i][j] > 0) {
					maxValue[i] = j;
					break;
				}
			}

			minFrequency[i] = Integer.MAX_VALUE;
			maxFrequency[i] = 0;
			for (int j = 0; j < 256; j++) {
				minFrequency[i] = Math.min(minFrequency[i], histogram[i][j]);
				maxFrequency[i] = Math.max(maxFrequency[i], histogram[i][j]);
				mean[i] += (j*histogram[i][j]);
			}
			mean[i] /= numSamples;
		}
		minValue[GRAY] = Math.min(Math.min(minValue[RED], minValue[GREEN]), minValue[BLUE]);
		maxValue[GRAY] = Math.max(Math.max(maxValue[RED], maxValue[GREEN]), maxValue[BLUE]);
	}

	public boolean isGray() {
		return isGray;
	}

	public int getNumSamples() {
		return numSamples;
	}

	public int getFrequency(int value) {
		if (numSamples > 0 && isGray && value >= 0 && value <= 255)
			return histogram[0][value];
		return -1;
	}

	public int getFrequency(int channel, int value) {
		if (numSamples < 1 || channel < 0 || channel > 2 ||
		 value < 0 || value > 255)
			return -1;
		return histogram[channel][value];
	}

	public int getMinFrequency() {
		if (numSamples > 0 && isGray)
			return minFrequency[0];
		return -1;
	}

	public int getMinFrequency(int channel) {
		if (numSamples < 1 || channel < 0 || channel > 2)
			return -1;
		return minFrequency[channel];
	}


	public int getMaxFrequency() {
		if (numSamples > 0 && isGray)
			return maxFrequency[0];
		return -1;
	}

	public int getMaxFrequency(int channel) {
		if (numSamples < 1 || channel < 0 || channel > 2)
			return -1;
		return maxFrequency[channel];
	}


	public int getMinValue() {
		if (numSamples > 0 && isGray)
			return minValue[0];
		return -1;
	}

	public int getMinValue(int channel) {
		return minValue[channel];
	}

	public int getMaxValue() {
		if (numSamples > 0 && isGray)
			return maxValue[0];
		return -1;
	}

	public int getMaxValue(int channel) {
		return maxValue[channel];
	}

	public float getMeanValue() {
		if (numSamples > 0 && isGray)
			return mean[0];
		return -1.0F;
	}

	public float getMeanValue(int channel) {
		if (numSamples > 0 && RED <= channel && channel <= BLUE)
			return mean[channel];
		return -1.0F;
	}


}
