anndl.Anndl.java Source code

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Here is the source code for anndl.Anndl.java

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/*
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 * and open the template in the editor.
 */
package anndl;

/**
 *
 * @author Asus
 */

import anndl.lang.*;
import anndl.model.ModelClassifier;
import java.io.BufferedReader;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileReader;
import java.io.InputStream;
import java.util.Scanner;
import java.util.logging.Level;
import java.util.logging.Logger;
import org.antlr.v4.runtime.ANTLRInputStream;
import org.antlr.v4.runtime.CommonTokenStream;
import org.antlr.v4.runtime.tree.ParseTree;
import weka.classifiers.Classifier;
import weka.classifiers.functions.MultilayerPerceptron;
import weka.core.Debug;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.converters.ConverterUtils.DataSource;

public class Anndl {

    public Scanner scanner;

    /**
     * @param args the command line arguments
     */
    public static void main(String[] args) throws Exception {
        int pilihan = 0;
        Anndl anndl = new Anndl();

        do {
            anndl.PrintMenu();
            pilihan = anndl.scanner.nextInt();
            anndl.doAction(pilihan);
        } while (pilihan != 3);
        System.out.println("Bye .. !");
        // TODO code application logic here
        /*if(args.length == 1){*/
        //String namafile = "tes.anndl";
        //            buildModel(new FileInputStream(new File(args[0])));
        //buildModel(new FileInputStream(new File(namafile)));
        /*}else{
        System.out.println("Wrong Command, usage  : java -jar ANNDL.jar <ANNDL File> ");
        }*/
    }

    public Anndl() {
        scanner = new Scanner(System.in);
    }

    private void PrintMenu() {
        System.out.println("\n");
        System.out.println("=== MENU ANN Description Langguage ===");
        System.out.println("1. Build Model");
        System.out.println("2. Classify Data");
        System.out.println("3. Exit");
        System.out.println("Your Choice \t : ");
        System.out.println("======================================");
    }

    private void doAction(int pilihan) throws Exception {
        switch (pilihan) {
        case 1:
            System.out.println("Pilihan 1 Dipilih");
            makeModel();
            break;
        case 2:
            System.out.println("Pilihan 2 dipilih");
            classifyTest();
            break;
        case 3:
            break;
        default:
            System.out.println("\n-- XX -- XX -- XX -- XX -- XX -- XX -- XX -- XX -- XX ");
            System.out.println("Tidak Terdapat Pilihan yang anda pilih.. ulangi lagi..");
            System.out.println("-- XX -- XX -- XX -- XX -- XX -- XX -- XX -- XX -- XX \n");
            break;
        }

    }

    private void makeModel() {
        System.out.println("Masukan Nama File *.anndl (Artificial Neural Network Description Langguagge)");
        String inputfile = scanner.nextLine();
        try {
            buildModel(new FileInputStream(new File(inputfile)));
        } catch (Exception e) {
            System.out.println("\n-- XX -- XX -- XX -- XX -- XX -- XX -- XX -- XX -- XX");
            System.out.println("Terjadi Kesalahan, mungkin karena file tersebut tidak ada atau kesalahan lainya");
            System.out.println("-- XX -- XX -- XX -- XX -- XX -- XX -- XX -- XX -- XX \n");
        }
    }

    private static void buildModel(InputStream input) throws Exception {
        ANNDLLexer lexer = new ANNDLLexer(new ANTLRInputStream(input));
        CommonTokenStream tokens = new CommonTokenStream(lexer);
        ANNDLParser parser = new ANNDLParser(tokens);
        ParseTree tree = parser.model();

        ModelVisitor visitor = new ModelVisitor();

        ModelClassifier themodel = (ModelClassifier) visitor.visit(tree);
        //themodel.PrintInfo();
        themodel.extracthidden();

        System.out.println("Membaca File Training...");
        DataSource trainingsoure = new DataSource(themodel.filetraining);
        Instances trainingdata = trainingsoure.getDataSet();
        if (trainingdata.classIndex() == -1) {
            trainingdata.setClassIndex(trainingdata.numAttributes() - 1);
        }

        System.out.println("Melakukan konfigurasi ANN ... ");
        MultilayerPerceptron mlp = new MultilayerPerceptron();
        mlp.setLearningRate(themodel.learningrate);
        mlp.setMomentum(themodel.momentum);
        mlp.setTrainingTime(themodel.epoch);
        mlp.setHiddenLayers(themodel.hidden);

        System.out.println("Melakukan Training data ...");
        mlp.buildClassifier(trainingdata);

        Debug.saveToFile(themodel.namamodel + ".model", mlp);

        System.out.println("\n~~ .. ~~ .. ~~ .. ~~ .. ~~ .. ~~ .. ~~ .. ~~ .. ~~ ..");
        System.out.println("Model ANN Berhasil Diciptakan dengan nama file : " + themodel.namamodel + ".model");
        System.out.println("~~ .. ~~ .. ~~ .. ~~ .. ~~ .. ~~ .. ~~ .. ~~ .. ~~ .. \n");

    }

    private void classifyTest() throws Exception {
        System.out.println("Masukan nama file model yang akan dijadikan Classifier :");
        String fileinput = scanner.next();
        //try {
        ClassifyInstance(fileinput);
        //} catch (Exception ex) {
        System.out.println("\n-- XX -- XX -- XX -- XX -- XX -- XX -- XX -- XX -- XX");
        System.out.println("Terjadi Kesalahan, mungkin karena file tersebut tidak ada atau kesalahan lainya");
        System.out.println("Silahkan load di Weka .. ");
        System.out.println("-- XX -- XX -- XX -- XX -- XX -- XX -- XX -- XX -- XX \n");
        //}

    }

    private void ClassifyInstance(String fileinput) throws Exception {
        System.out.println("Membaca File Model ..");
        Classifier cls = (Classifier) weka.core.SerializationHelper.read(fileinput);

        System.out.println("Masukan Data yang ingin diklasifikasikan, pisahkan dengan spasi :");
        String testset = scanner.nextLine();
        testset = "1 1 0";
        String[] exploded = testset.split(" ");

        Instance newinstance = new Instance(exploded.length);
        for (int i = 0; i < exploded.length; i++) {
            String exploded1 = exploded[i];
            System.out.println(exploded[i] + ";");

            newinstance.setValue(i, Integer.valueOf(exploded[i]));
        }

        System.out.println("Melakukan klasifikasi ... ");
        double result = cls.classifyInstance(newinstance);
        System.out.println("Data ini:");
        System.out.println(testset);
        System.out.println("memiliki label :");
        System.out.println(newinstance.value(newinstance.classIndex()));
    }
}