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/*===============================================================================
 * Copyright (c) 2010-2012 University of Massachusetts.  All Rights Reserved.
 *
 * Use of the RankLib package is subject to the terms of the software license set
 * forth in the LICENSE file included with this software, and also available at
 * http://people.cs.umass.edu/~vdang/ranklib_license.html
 *===============================================================================
 */

package ciir.umass.edu.learning.neuralnet;

import java.util.ArrayList;
import java.util.List;

/**
 * @author vdang
 *
 * This class implements layers of neurons in neural networks.
 */
public class Layer {
    protected List neurons = null;

    public Layer(final int size) {
        neurons = new ArrayList<>();
        for (int i = 0; i < size; i++) {
            neurons.add(new Neuron());
        }
    }

    /**
     *
     * @param size
     * @param nType 0 for pair; 1 for list.
     */
    public Layer(final int size, final int nType) {
        neurons = new ArrayList<>();
        for (int i = 0; i < size; i++) {
            if (nType == 0) {
                neurons.add(new Neuron());
            } else {
                neurons.add(new ListNeuron());
            }
        }
    }

    public Neuron get(final int k) {
        return neurons.get(k);
    }

    public int size() {
        return neurons.size();
    }

    /**
     * Have all neurons in this layer compute its output
     */
    public void computeOutput(final int i) {
        for (int j = 0; j < neurons.size(); j++) {
            neurons.get(j).computeOutput(i);
        }
    }

    public void computeOutput() {
        for (int j = 0; j < neurons.size(); j++) {
            neurons.get(j).computeOutput();
        }
    }

    public void clearOutputs() {
        for (int i = 0; i < neurons.size(); i++) {
            neurons.get(i).clearOutputs();
        }
    }

    /**
     * [Only for output layers] Compute delta for all neurons in the this (output) layer
     * @param param
     */
    public void computeDelta(final PropParameter param) {
        for (int i = 0; i < neurons.size(); i++) {
            neurons.get(i).computeDelta(param);
        }
    }

    /**
     * Update delta from neurons in the previous layers
     */
    public void updateDelta(final PropParameter param) {
        for (int i = 0; i < neurons.size(); i++) {
            neurons.get(i).updateDelta(param);
        }
    }

    public void updateWeight(final PropParameter param) {
        for (int i = 0; i < neurons.size(); i++) {
            neurons.get(i).updateWeight(param);
        }
    }
}