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NeuralNetwork.java
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NeuralNetwork.java
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import java.awt.Color;
import java.awt.Font;
import java.awt.datatransfer.Clipboard;
import java.awt.datatransfer.StringSelection;
import java.awt.event.ActionListener;
import java.awt.event.ActionEvent;
import java.io.File;
import java.io.IOException;
import java.text.DecimalFormat;
import java.util.ArrayList;
import java.util.Random;
import java.awt.*;
import javax.swing.*;
import javax.swing.filechooser.FileSystemView;
public class NeuralNetwork {
public static double[][] trainingData;
public static double[][] correctOutputs;
public static int amountInput;
public static int amountHidden;
public static int amountOutput;
public static double[] inputNeurons;
public static double[] hiddenNeurons;
public static double[] outputNeurons;
public static double[][] inputToHidden;
public static double[][] hiddenToOutput;
public static double[] hiddenNeuronBias;
public static double[] outputNeuronBias;
public static double learningRate;
public static double reps;
public static double[] outputError;
public static double[] hiddenError;
public static String inputTrainingDataFilepath;
public static String outputTrainingDataFilepath;
public static String[] outputNames;
public static String filepathTrain;
public static JFrame jframe;
public static JButton newButton;
public static JButton runButton;
public static JButton trainButton;
public static JTextArea startingName;
public static JTextArea startingBackground;
public static boolean done2;
public static Color backgroundColor;
public static JButton trainData;
public static JTextArea trainFile;
public static JButton inputData;
public static JTextArea inputFile;
public static JButton outputData;
public static JTextArea outputFile;
public static JScrollPane inputFileScroll;
public static JScrollPane outputFileScroll;
public static JScrollPane trainFileScroll;
public static JTextArea hiddenNeuronTitle;
public static JTextArea hiddenNeuronInput;
public static JScrollPane hiddenNeuronInputScroll;
public static JTextArea repsTitle;
public static JTextArea repsInput;
public static JScrollPane repsInputScroll;
public static JTextArea learningRateTitle;
public static JTextArea learningRateInput;
public static JScrollPane learningRateInputScroll;
public static JTextArea newTitle;
public static JButton helpButton;
public static JButton submitButton;
public static String[] restOfCommand;
public static String s;
public static boolean saveNetwork;
public static boolean yesOrNo;
public static boolean done;
public static boolean inputTxt;
public static String filepath;
public static JButton returnToHome;
public static boolean isReturn;
public static boolean bool;
public static ArrayList<Integer> highestNeurons;
public static ImageIcon img;
public static void main(String[] args) throws IOException {
boolean running = true;
java.net.URL url = NeuralNetwork.class.getResource("images/icon.png");
img = new ImageIcon(url);
JFrame errorframe = new JFrame("Error!");
errorframe.setIconImage(img.getImage());
isReturn = false;
returnToHome = new JButton("Return To Start");
returnToHome.setSize(100, 30);
returnToHome.setFont(new Font("Times New Roman", Font.PLAIN, 9));
while (running) {
try {
run();
} catch (Exception e) {
if (isReturn) {
isReturn = false;
} else {
JOptionPane.showMessageDialog(errorframe, e.getStackTrace());
}
}
}
}
public static void run() throws IOException {
jframe = new JFrame("Train A Brain");
jframe.setIconImage(img.getImage());
backgroundColor = jframe.getBackground();
s = "";
restOfCommand = new String[6];
initializeFrame();
jframe.setVisible(true);
jframe.setLocationRelativeTo(null);
amountHidden = 4;
learningRate = 0.2;
reps = 1000000;
String command = initialSetup();
if (command.equals("new") || command.equals("train")) {
if (command.equals("train")) {
runNeuralNet(filepathTrain);
} else {
dataExtractionFromFile();
amountInput = trainingData[0].length;
amountOutput = correctOutputs[0].length;
inputNeurons = new double[amountInput];
hiddenNeurons = new double[amountHidden];
outputNeurons = new double[amountOutput];
inputToHidden = new double[amountInput][amountHidden];
hiddenToOutput = new double[amountHidden][amountOutput];
hiddenNeuronBias = new double[amountHidden];
outputNeuronBias = new double[amountOutput];
}
outputError = new double[amountOutput];
hiddenError = new double[amountHidden];
if (command.equals("new")) {
randomize();
} else {
dataExtractionFromFile();
}
for (int i = 0; i < reps; i++) {
for (int j = 0; j < trainingData.length; j++) {
calculate(trainingData[j]);
backPropagate(j);
}
}
wouldYouLikeToSave();
if (saveNetwork) {
saved();
}
} else if (command.equals("run")) {
boolean running = true;
while (running) {
String[] inputs = runNetDataInputPage();
boolean wantAnotherInput = false;
for (int i = 0; i < amountInput; i++) {
inputNeurons[i] = Double.parseDouble(inputs[i]);
}
calculate(inputNeurons);
double highest = -1;
highestNeurons = new ArrayList<Integer>();
for (int i = 0; i < amountOutput; i++) {
if (outputNeurons[i] > highest) {
highest = outputNeurons[i];
highestNeurons.clear();
highestNeurons.add(i);
} else if (outputNeurons[i] == highest) {
highest = outputNeurons[i];
highestNeurons.add(i);
}
}
showOutputs(highestNeurons);
wantAnotherInput = doYouWantAnotherInput();
if (wantAnotherInput) {
running = true;
} else {
running = false;
}
}
}
}
public static void randomize() {
Random rd = new Random();
for (int i = 0; i < inputToHidden.length; i++) {
for (int j = 0; j < inputToHidden[i].length; j++) {
double num = rd.nextDouble();
num = num * 100;
num = Math.round(num);
inputToHidden[i][j] = (num / 100);
}
}
for (int i = 0; i < hiddenToOutput.length; i++) {
for (int j = 0; j < hiddenToOutput[i].length; j++) {
double num = rd.nextDouble();
num = num * 100;
num = Math.round(num);
hiddenToOutput[i][j] = (num / 100);
}
}
for (int i = 0; i < hiddenNeuronBias.length; i++) {
double num = rd.nextDouble();
num = num * 100;
num = Math.round(num);
hiddenNeuronBias[i] = (num / 100);
}
for (int i = 0; i < outputNeuronBias.length; i++) {
double num = rd.nextDouble();
num = num * 100;
num = Math.round(num);
outputNeuronBias[i] = (num / 100);
}
}
public static void calculate(double[] inputs) {
for (int i = 0; i < inputs.length; i++) {
inputNeurons[i] = inputs[i];
}
for (int i = 0; i < amountHidden; i++) {
for (int j = 0; j < inputToHidden.length; j++) {
hiddenNeurons[i] += inputNeurons[j] * inputToHidden[j][i];
}
hiddenNeurons[i] += hiddenNeuronBias[i];
hiddenNeurons[i] = sigmoid(hiddenNeurons[i]);
}
for (int i = 0; i < amountOutput; i++) {
for (int j = 0; j < hiddenToOutput.length; j++) {
outputNeurons[i] += hiddenNeurons[j] * hiddenToOutput[j][i];
}
outputNeurons[i] += outputNeuronBias[i];
outputNeurons[i] = sigmoid(outputNeurons[i]);
}
}
public static void backPropagate(int dataNumber) {
for (int i = 0; i < amountOutput; i++) {
outputError[i] = (correctOutputs[dataNumber][i] - outputNeurons[i]) * sigmoidDerivative(outputNeurons[i]);
}
for (int i = 0; i < amountHidden; i++) {
hiddenError[i] = 0.0;
for (int j = 0; j < amountOutput; j++) {
hiddenError[i] += outputError[j] * hiddenToOutput[i][j];
}
hiddenError[i] *= sigmoidDerivative(hiddenNeurons[i]);
}
for (int i = 0; i < amountOutput; i++) {
for (int j = 0; j < amountHidden; j++) {
hiddenToOutput[j][i] += (learningRate * outputError[i] * hiddenNeurons[j]);
}
outputNeuronBias[i] += (learningRate * outputError[i]);
}
for (int i = 0; i < amountHidden; i++) {
for (int j = 0; j < amountInput; j++) {
inputToHidden[j][i] += (learningRate * hiddenError[i] * inputNeurons[j]);
}
hiddenNeuronBias[i] += (learningRate * hiddenError[i]);
}
}
public static double sigmoid(double num) {
return (1.0 / (1.0 + Math.exp(-num)));
}
public static double sigmoidDerivative(double num) {
return (num * (1.0 - num));
}
public static String initialSetup() throws IOException {
boolean running = true;
String command1 = "";
while (running) {
String[] command = new String[7];
command[0] = addFirstButtonFunctionality();
secondPage();
for (int i = 1; i < command.length; i++) {
command[i] = restOfCommand[i - 1];
}
command1 = command[0].substring(0, command[0].length() - 1);
String currentCommand = "";
if (command[0].substring(0, command[0].length() - 1).equals("new") || command[0].equals("train ")) {
for (int i = 1; i < command.length - 1; i++) {
currentCommand = command[i].substring(0, command[i].length() - 1);
if (i == 1) {
inputTrainingDataFilepath = currentCommand;
} else if (i == 2) {
outputTrainingDataFilepath = currentCommand;
} else if (i == 3) {
amountHidden = Integer.parseInt(currentCommand);
} else if (i == 4) {
learningRate = Double.parseDouble(currentCommand);
} else if (i == 5) {
if (command[0].equals("new ")) {
reps = Integer.parseInt(command[5]);
} else {
reps = Integer.parseInt(currentCommand);
filepathTrain = command[6];
}
running = false;
}
}
} else if (command[0].equals("run ")) {
runNeuralNet(command[1]);
running = false;
}
}
return command1;
}
public static void dataExtractionFromFile() throws IOException {
String input = Scan.scan(inputTrainingDataFilepath);
input = input.replaceAll(" ", "");
input = input.replaceAll("\\}", "");
input = input.replaceAll("\\{", "");
String[] inputs = input.split(";");
String[][] inputsFinal = new String[inputs.length][inputs[1].split(",").length];
trainingData = new double[inputsFinal.length][inputsFinal[1].length];
for (int i = 0; i < inputsFinal.length; i++) {
inputsFinal[i] = inputs[i].split(",");
}
for (int i = 1; i < inputsFinal.length; i++) {
for (int j = 0; j < inputsFinal[1].length; j++) {
trainingData[i - 1][j] = Double.parseDouble(inputsFinal[i][j]);
}
}
outputNames = inputsFinal[0];
String output = Scan.scan(outputTrainingDataFilepath);
output = output.replaceAll(" ", "");
output = output.replaceAll("\\}", "");
output = output.replaceAll("\\{", "");
String[] outputs = output.split(";");
String[][] outputsFinal = new String[outputs.length][outputs[1].split(",").length];
correctOutputs = new double[outputsFinal.length][outputsFinal[1].length];
for (int i = 0; i < outputsFinal.length; i++) {
outputsFinal[i] = outputs[i].split(",");
}
for (int i = 1; i < outputsFinal.length; i++) {
for (int j = 0; j < outputsFinal[1].length; j++) {
correctOutputs[i - 1][j] = Double.parseDouble(outputsFinal[i][j]);
}
}
}
public static void save(String filepath) throws IOException {
String str = "";
// input to hidden, hidden to output, hidden bias, output bias, output names (0
// - x)
// input to hidden
for (int i = 0; i < inputToHidden.length; i++) {
for (int j = 0; j < inputToHidden[0].length; j++) {
if (j == (inputToHidden[0].length - 1)) {
str = str + inputToHidden[i][j];
} else {
str = str + inputToHidden[i][j] + ",";
}
}
if (!(i == (inputToHidden.length - 1))) {
str = str + ";";
}
}
str = str + ":";
// hidden to output
for (int i = 0; i < hiddenToOutput.length; i++) {
for (int j = 0; j < hiddenToOutput[0].length; j++) {
if (j == (hiddenToOutput[0].length - 1)) {
str = str + hiddenToOutput[i][j];
} else {
str = str + hiddenToOutput[i][j] + ",";
}
}
if (!(i == (hiddenToOutput.length - 1))) {
str = str + ";";
}
}
str = str + ":";
// hidden bias
for (int i = 0; i < hiddenNeuronBias.length; i++) {
if (i == (hiddenNeuronBias.length - 1)) {
str = str + hiddenNeuronBias[i];
} else {
str = str + hiddenNeuronBias[i] + ",";
}
}
str = str + ":";
// output bias
for (int i = 0; i < outputNeuronBias.length; i++) {
if (i == (outputNeuronBias.length - 1)) {
str = str + outputNeuronBias[i];
} else {
str = str + outputNeuronBias[i] + ",";
}
}
str = str + ":";
// output names (0 - x)
for (int i = 0; i < outputNames.length; i++) {
if (i == (outputNames.length - 1)) {
str = str + outputNames[i];
} else {
str = str + outputNames[i] + ",";
}
}
Writer.write(filepath, str);
}
public static void wouldYouLikeToSave() throws IOException {
String input = "";
jframe.setVisible(false);
jframe.setLocationRelativeTo(null);
saveScreen();
if (saveNetwork) {
input = getSaveFilePath();
}
boolean output = true;
boolean fileEmpty = false;
while (output) {
if (saveNetwork) {
String wantedFile = Scan.scan(input);
if (wantedFile.equals("")) {
fileEmpty = true;
} else {
boolean decision = fileNotEmptyOverwrite();
boolean deciding = true;
while (deciding) {
if (decision) {
fileEmpty = true;
deciding = false;
} else {
wouldYouLikeToSave();
fileEmpty = false;
deciding = false;
}
}
}
if (fileEmpty) {
try {
save(input);
} catch (Exception e) {
boolean output1 = error();
if (output1) {
wouldYouLikeToSave();
} else {
//System.exit(0);
}
}
}
output = false;
} else {
output = false;
//System.exit(0);
}
}
}
public static void runNeuralNet(String filepath) throws IOException {
String str = Scan.scan(filepath);
String[] splitStr = str.split(":");
inputToHidden = new double[splitStr[0].split(";").length][splitStr[0].split(";")[0].split(",").length];
for (int i = 0; i < splitStr[0].split(";").length; i++) {
for (int j = 0; j < splitStr[0].split(";")[0].split(",").length; j++) {
inputToHidden[i][j] = Double.parseDouble(splitStr[0].split(";")[i].split(",")[j]);
}
}
hiddenToOutput = new double[splitStr[1].split(";").length][splitStr[1].split(";")[0].split(",").length];
for (int i = 0; i < splitStr[1].split(";").length; i++) {
for (int j = 0; j < splitStr[1].split(";")[0].split(",").length; j++) {
hiddenToOutput[i][j] = Double.parseDouble(splitStr[1].split(";")[i].split(",")[j]);
}
}
inputNeurons = new double[inputToHidden.length];
hiddenNeurons = new double[hiddenToOutput.length];
outputNeurons = new double[hiddenToOutput[0].length];
amountInput = inputNeurons.length;
amountHidden = hiddenNeurons.length;
amountOutput = outputNeurons.length;
hiddenNeuronBias = new double[splitStr[2].split(",").length];
outputNeuronBias = new double[splitStr[3].split(",").length];
outputNames = new String[splitStr[4].split(",").length];
for (int i = 0; i < splitStr[2].split(",").length; i++) {
hiddenNeuronBias[i] = Double.parseDouble(splitStr[2].split(",")[i]);
}
for (int i = 0; i < splitStr[3].split(",").length; i++) {
outputNeuronBias[i] = Double.parseDouble(splitStr[3].split(",")[i]);
}
outputNames = splitStr[4].split(",");
}
public static void initializeFrame() throws IOException {
jframe.setResizable(false);
jframe.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
newButton = new JButton("New");
newButton.setBounds(30, 350, 100, 40);
jframe.add(newButton);
runButton = new JButton("Run");
runButton.setBounds(160, 350, 100, 40);
jframe.add(runButton);
trainButton = new JButton("Cont. Train");
trainButton.setBounds(290, 350, 100, 40);
jframe.add(trainButton);
startingName = new JTextArea();
startingName.setEditable(false);
startingName.setText("Train\n A\n Brain!");
startingName.setFont(new Font("Denmark", Font.PLAIN, 50));
startingName.setOpaque(false);
startingName.setBounds(82, 75, 265, 200);
jframe.add(startingName);
startingBackground = new JTextArea();
startingBackground.setEditable(false);
startingBackground.setText("01010110010101011101010101110111010101011010101011001010101110101010111011101010101110\n101010100011001011001010101010100001010101010100101000100111110001010101010101000101110\n001110010101010101001110000101010100110101001110010110101010001010111010101101110011101\n01010110010101011101010101110111010101011010101011001010101110101010111011101010101110\n101010100011001011001010101010100001010101010100101000100111110001010101010101000101110\n001110010101010101001110000101010100110101001110010110101010001010111010101101110011101\n01010110010101011101010101110111010101011010101011001010101110101010111011101010101110\n101010100011001011001010101010100001010101010100101000100111110001010101010101000101110\n001110010101010101001110000101010100110101001110010110101010001010111010101101110011101\n01010110010101011101010101110111010101011010101011001010101110101010111011101010101110\n101010100011001011001010101010100001010101010100101000100111110001010101010101000101110\n001110010101010101001110000101010100110101001110010110101010001010111010101101110011101\n01010110010101011101010101110111010101011010101011001010101110101010111011101010101110\n101010100011001011001010101010100001010101010100101000100111110001010101010101000101110\n001110010101010101001110000101010100110101001110010110101010001010111010101101110011101\n01010110010101011101010101110111010101011010101011001010101110101010111011101010101110\n101010100011001011001010101010100001010101010100101000100111110001010101010101000101110\n001110010101010101001110000101010100110101001110010110101010001010111010101101110011101\n01010110010101011101010101110111010101011010101011001010101110101010111011101010101110\n101010100011001011001010101010100001010101010100101000100111110001010101010101000101110\n001110010101010101001110000101010100110101001110010110101010001010111010101101110011101\n01010110010101011101010101110111010101011010101011001010101110101010111011101010101110\n101010100011001011001010101010100001010101010100101000100111110001010101010101000101110\n01010110010101011101010101110111010101011010101011001010101110101010111011101010101110\n101010100011001011001010101010100001010101010100101000100111110001010101010101000101110\n001110010101010101001110000101010100110101001110010110101010001010111010101101110011101\n01010110010101011101010101110111010101011010101011001010101110101010111011101010101110\n101010100011001011001010101010100001010101010100101000100111110001010101010101000101110\n01010110010101011101010101110111010101011010101011001010101110101010111011101010101110\n101010100011001011001010101010100001010101010100101000100111110001010101010101000101110\n001110010101010101001110000101010100110101001110010110101010001010111010101101110011101\n01010110010101011101010101110111010101011010101011001010101110101010111011101010101110\n101010100011001011001010101010100001010101010100101000100111110001010101010101000101110\n001110010101010101001110000101010100110101001110010110101010001010111010101101110011101\n01010110010101011101010101110111010101011010101011001010101110101010111011101010101110\n101010100011001011001010101010100001010101010100101000100111110001010101010101000101110\n001110010101010101001110000101010100110101001110010110101010001010111010101101110011101\n001110010101010101001110000101010100110101001110010110101010001010111010101101110011101\n001110010101010101001110000101010100110101001110010110101010001010111010101101110011101\n");
startingBackground.setFont(new Font("Times New Roman", Font.PLAIN, 10));
startingBackground.setOpaque(false);
startingBackground.setBounds(0, 0, 430, 450);
jframe.add(startingBackground);
jframe.setSize(430, 450);
jframe.setLayout(null);
}
public static String addFirstButtonFunctionality() {
s = "";
done2 = true;
Object obj = new Object();
newButton.addActionListener(new ActionListener() {
public void actionPerformed(ActionEvent e) {
s = "new ";
synchronized (obj) {
obj.notify();
}
}
});
runButton.addActionListener(new ActionListener() {
public void actionPerformed(ActionEvent e) {
s = "run ";
synchronized (obj) {
obj.notify();
}
}
});
trainButton.addActionListener(new ActionListener() {
public void actionPerformed(ActionEvent e) {
s = "train ";
synchronized (obj) {
obj.notify();
}
}
});
synchronized (obj) {
try {
obj.wait();
} catch (InterruptedException e) {
}
}
return s;
}
public static void secondPage() {
if (s.equals("new ")) {
newNetScreen();
} else if (s.equals("run ")) {
runNetScreen();
} else if (s.equals("train ")) {
trainNetScreen();
}
}
public static void newNetScreen() {
Object obj = new Object();
jframe.getContentPane().removeAll();
jframe.setSize(430, 450);
returnToHome.setBounds(158, 365, 100, 30);
jframe.add(returnToHome);
newTitle = new JTextArea();
newTitle.setBounds(25, 25, 375, 40);
newTitle.setText(" New Neural Network Page; Please Enter Info\n Press \"help\" button for information about this page.");
newTitle.setFont(new Font("Times New Roman", Font.BOLD, 15));
newTitle.setEditable(false);
newTitle.setOpaque(false);
jframe.add(newTitle);
inputData = new JButton("Input Data");
inputData.setBounds(25, 90, 105, 40);
jframe.add(inputData);
inputFile = new JTextArea();
inputFile.setEditable(false);
inputFileScroll = new JScrollPane(inputFile);
inputFileScroll.setBounds(155, 93, 235, 34);
inputFileScroll.setFont(new Font("Times New Roman", Font.PLAIN, 20));
jframe.add(inputFileScroll);
outputData = new JButton("Output Data");
outputData.setBounds(25, 160, 105, 40);
jframe.add(outputData);
outputFile = new JTextArea();
outputFile.setEditable(false);
outputFileScroll = new JScrollPane(outputFile);
outputFileScroll.setBounds(155, 163, 235, 34);
outputFileScroll.setFont(new Font("Times New Roman", Font.PLAIN, 20));
jframe.add(outputFileScroll);