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package hef.neuralnet.bitmap.v1;

import java.util.Arrays;
import java.util.LinkedHashMap;
import java.util.Map;



public class Neuron
{
    private int inputCount;
    private Map<int[], Integer> memory;

    /**
     * Constructs a neuron
     * 
     * @param inputCount Specifies how many inputs this neuron should accept when the <code>teach</code> or
     *        <code>use</code> methods are invoked
     */
    public Neuron(int inputCount) {
        this.inputCount = inputCount;
        this.memory = new LinkedHashMap<int[], Integer>();
    }

    public void teach(int[] inputs, int output) {
        assert inputs.length == this.inputCount;

        this.memory.put(Arrays.copyOf(inputs, inputs.length), output);
    }

    public int use(int[] inputs) {
        int bestDist = Integer.MAX_VALUE;
        int bestOut = -1;

        for (Map.Entry<int[], Integer> kv : this.memory.entrySet()) {
            int dist = distance(inputs, kv.getKey());
            if (dist <= bestDist) {
                bestDist = dist;
                bestOut = kv.getValue();
            }
        }

        if (bestDist != 0) this.teach(inputs, bestOut);

        return bestOut;
    }

    private static int distance(int[] a, int[] b) {
        assert a.length == b.length;

        int dist = 0;
        for (int i = 0; i < a.length; i += 1)
            dist += Math.abs(a[i] - b[i]);

        return dist;
    }
}