package org.neuroph.samples.convolution;

import org.neuroph.nnet.ConvolutionalNetwork;
import org.neuroph.nnet.comp.layer.FeatureMapLayer;
import org.neuroph.core.data.DataSet;
import org.neuroph.nnet.comp.Dimension2D;
import org.neuroph.nnet.comp.layer.FeatureMapsLayer;


/**
 * This is simple sample to show that learning procedure works
 */
public class SimpleLearningExample {

    public static void testLearningOneLayer() {
        Dimension2D inputDimension = new Dimension2D(5, 5);

        Dimension2D convolutionKernel = new Dimension2D(3, 3);

        ConvolutionalNetwork convolutionNet = new ConvolutionalNetwork.Builder()
                .withInputLayer(5, 5, 1)
                .withConvolutionLayer(3, 3, 2)
                .withFullConnectedLayer(2)
                .build();
        

        // CREATE DATA SET

        DataSet dataSet = new DataSet(25, 2);
        dataSet.addRow(new double[]{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
                new double[]{1, 0});
        dataSet.addRow(new double[]{0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0},
                new double[]{0, 1});

        // TRAIN NETWORK

        convolutionNet.getLearningRule().setMaxError(0.00001);
        convolutionNet.learn(dataSet);
                
        System.out.println("Done training!");
        
        FeatureMapLayer featureMap1 = ((FeatureMapsLayer)convolutionNet.getLayerAt(1)).getFeatureMap(0);
        FeatureMapLayer featureMap2 = ((FeatureMapsLayer)convolutionNet.getLayerAt(1)).getFeatureMap(1);
        
//        WeightVisualiser visualiser1 = new WeightVisualiser(featureMap1, convolutionKernel);
//        visualiser1.displayWeights();
//
//        WeightVisualiser visualiser2 = new WeightVisualiser(featureMap2, convolutionKernel);
//        visualiser2.displayWeights();

        
        // CREATE TEST SET

        DataSet testSet = new DataSet(25, 2);
        testSet.addRow(new double[]{0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
                new double[]{1, 0});
        testSet.addRow(new double[]{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0},
                new double[]{1, 0});
        testSet.addRow(new double[]{0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0},
                new double[]{0, 1});

    }

    public static void main(String[] args) {
        testLearningOneLayer();
        System.out.println("done!");
    }
}