Neural Networks on C#

// AForge Framework
// Approximation using Mutli-Layer Neural Network
//
// Copyright � Andrew Kirillov, 2006
// andrew.kirillov@gmail.com
//

using System;
using System.Drawing;
using System.Collections;
using System.ComponentModel;
using System.Windows.Forms;
using System.Data;

using System.IO;
using System.Threading;

using AForge;
using AForge.Neuro;
using AForge.Neuro.Learning;
using AForge.Controls;

namespace Approximation
{
	/// <summary>
	/// Summary description for Form1.
	/// </summary>
	public class MainForm : System.Windows.Forms.Form
	{
		private System.Windows.Forms.GroupBox groupBox1;
		private System.Windows.Forms.ListView dataList;
		private System.Windows.Forms.Button loadDataButton;
		private System.Windows.Forms.ColumnHeader xColumnHeader;
		private System.Windows.Forms.ColumnHeader yColumnHeader;
		private System.Windows.Forms.OpenFileDialog openFileDialog;
		private System.Windows.Forms.GroupBox groupBox2;
		private AForge.Controls.Chart chart;
		private System.Windows.Forms.GroupBox groupBox3;
		private System.Windows.Forms.TextBox momentumBox;
		private System.Windows.Forms.Label label6;
		private System.Windows.Forms.TextBox alphaBox;
		private System.Windows.Forms.Label label2;
		private System.Windows.Forms.TextBox learningRateBox;
		private System.Windows.Forms.Label label1;
		private System.Windows.Forms.Label label8;
		private System.Windows.Forms.TextBox iterationsBox;
		private System.Windows.Forms.Label label10;
		private System.Windows.Forms.Label label9;
		private System.Windows.Forms.GroupBox groupBox4;
		private System.Windows.Forms.TextBox currentErrorBox;
		private System.Windows.Forms.Label label3;
		private System.Windows.Forms.TextBox currentIterationBox;
		private System.Windows.Forms.Label label5;
		private System.Windows.Forms.Button stopButton;
		private System.Windows.Forms.Button startButton;
		private System.Windows.Forms.Label label4;
		private System.Windows.Forms.TextBox neuronsBox;
		/// <summary>
		/// Required designer variable.
		/// </summary>
		private System.ComponentModel.Container components = null;

		private double[,] data = null;

		private double	learningRate = 0.1;
		private double	momentum = 0.0;
		private double	sigmoidAlphaValue = 2.0;
		private int		neuronsInFirstLayer = 20;
		private int		iterations = 1000;

		private Thread	workerThread = null;
		private bool	needToStop = false;

		// Constructor
		public MainForm( )
		{
			//
			// Required for Windows Form Designer support
			//
			InitializeComponent();

			// init chart control
			chart.AddDataSeries( "data", Color.Red, Chart.SeriesType.Dots, 5 );
			chart.AddDataSeries( "solution", Color.Blue, Chart.SeriesType.Line, 1 );

			// init controls
			UpdateSettings( );
		}

		/// <summary>
		/// Clean up any resources being used.
		/// </summary>
		protected override void Dispose( bool disposing )
		{
			if( disposing )
			{
				if (components != null) 
				{
					components.Dispose();
				}
			}
			base.Dispose( disposing );
		}

		#region Windows Form Designer generated code
		/// <summary>
		/// Required method for Designer support - do not modify
		/// the contents of this method with the code editor.
		/// </summary>
		private void InitializeComponent()
		{
			this.groupBox1 = new System.Windows.Forms.GroupBox();
			this.dataList = new System.Windows.Forms.ListView();
			this.loadDataButton = new System.Windows.Forms.Button();
			this.xColumnHeader = new System.Windows.Forms.ColumnHeader();
			this.yColumnHeader = new System.Windows.Forms.ColumnHeader();
			this.openFileDialog = new System.Windows.Forms.OpenFileDialog();
			this.groupBox2 = new System.Windows.Forms.GroupBox();
			this.chart = new AForge.Controls.Chart();
			this.groupBox3 = new System.Windows.Forms.GroupBox();
			this.momentumBox = new System.Windows.Forms.TextBox();
			this.label6 = new System.Windows.Forms.Label();
			this.alphaBox = new System.Windows.Forms.TextBox();
			this.label2 = new System.Windows.Forms.Label();
			this.learningRateBox = new System.Windows.Forms.TextBox();
			this.label1 = new System.Windows.Forms.Label();
			this.label8 = new System.Windows.Forms.Label();
			this.iterationsBox = new System.Windows.Forms.TextBox();
			this.label10 = new System.Windows.Forms.Label();
			this.label9 = new System.Windows.Forms.Label();
			this.groupBox4 = new System.Windows.Forms.GroupBox();
			this.currentErrorBox = new System.Windows.Forms.TextBox();
			this.label3 = new System.Windows.Forms.Label();
			this.currentIterationBox = new System.Windows.Forms.TextBox();
			this.label5 = new System.Windows.Forms.Label();
			this.stopButton = new System.Windows.Forms.Button();
			this.startButton = new System.Windows.Forms.Button();
			this.label4 = new System.Windows.Forms.Label();
			this.neuronsBox = new System.Windows.Forms.TextBox();
			this.groupBox1.SuspendLayout();
			this.groupBox2.SuspendLayout();
			this.groupBox3.SuspendLayout();
			this.groupBox4.SuspendLayout();
			this.SuspendLayout();
			// 
			// groupBox1
			// 
			this.groupBox1.Controls.Add(this.dataList);
			this.groupBox1.Controls.Add(this.loadDataButton);
			this.groupBox1.Location = new System.Drawing.Point(10, 10);
			this.groupBox1.Name = "groupBox1";
			this.groupBox1.Size = new System.Drawing.Size(180, 320);
			this.groupBox1.TabIndex = 1;
			this.groupBox1.TabStop = false;
			this.groupBox1.Text = "Data";
			// 
			// dataList
			// 
			this.dataList.Columns.AddRange(new System.Windows.Forms.ColumnHeader[] {
																					   this.xColumnHeader,
																					   this.yColumnHeader});
			this.dataList.FullRowSelect = true;
			this.dataList.GridLines = true;
			this.dataList.Location = new System.Drawing.Point(10, 20);
			this.dataList.Name = "dataList";
			this.dataList.Size = new System.Drawing.Size(160, 255);
			this.dataList.TabIndex = 0;
			this.dataList.View = System.Windows.Forms.View.Details;
			// 
			// loadDataButton
			// 
			this.loadDataButton.Location = new System.Drawing.Point(10, 285);
			this.loadDataButton.Name = "loadDataButton";
			this.loadDataButton.TabIndex = 1;
			this.loadDataButton.Text = "&Load";
			this.loadDataButton.Click += new System.EventHandler(this.loadDataButton_Click);
			// 
			// xColumnHeader
			// 
			this.xColumnHeader.Text = "X";
			// 
			// yColumnHeader
			// 
			this.yColumnHeader.Text = "Y";
			// 
			// openFileDialog
			// 
			this.openFileDialog.Filter = "CSV (Comma delimited) (*.csv)|*.csv";
			this.openFileDialog.Title = "Select data file";
			// 
			// groupBox2
			// 
			this.groupBox2.Controls.Add(this.chart);
			this.groupBox2.Location = new System.Drawing.Point(200, 10);
			this.groupBox2.Name = "groupBox2";
			this.groupBox2.Size = new System.Drawing.Size(300, 320);
			this.groupBox2.TabIndex = 2;
			this.groupBox2.TabStop = false;
			this.groupBox2.Text = "Function";
			// 
			// chart
			// 
			this.chart.Location = new System.Drawing.Point(10, 20);
			this.chart.Name = "chart";
			this.chart.Size = new System.Drawing.Size(280, 290);
			this.chart.TabIndex = 0;
			// 
			// groupBox3
			// 
			this.groupBox3.Controls.Add(this.neuronsBox);
			this.groupBox3.Controls.Add(this.label4);
			this.groupBox3.Controls.Add(this.momentumBox);
			this.groupBox3.Controls.Add(this.label6);
			this.groupBox3.Controls.Add(this.alphaBox);
			this.groupBox3.Controls.Add(this.label2);
			this.groupBox3.Controls.Add(this.learningRateBox);
			this.groupBox3.Controls.Add(this.label1);
			this.groupBox3.Controls.Add(this.label8);
			this.groupBox3.Controls.Add(this.iterationsBox);
			this.groupBox3.Controls.Add(this.label10);
			this.groupBox3.Controls.Add(this.label9);
			this.groupBox3.Location = new System.Drawing.Point(510, 10);
			this.groupBox3.Name = "groupBox3";
			this.groupBox3.Size = new System.Drawing.Size(195, 195);
			this.groupBox3.TabIndex = 4;
			this.groupBox3.TabStop = false;
			this.groupBox3.Text = "Settings";
			// 
			// momentumBox
			// 
			this.momentumBox.Location = new System.Drawing.Point(125, 45);
			this.momentumBox.Name = "momentumBox";
			this.momentumBox.Size = new System.Drawing.Size(60, 20);
			this.momentumBox.TabIndex = 3;
			this.momentumBox.Text = "";
			// 
			// label6
			// 
			this.label6.Location = new System.Drawing.Point(10, 47);
			this.label6.Name = "label6";
			this.label6.Size = new System.Drawing.Size(82, 17);
			this.label6.TabIndex = 2;
			this.label6.Text = "Momentum:";
			// 
			// alphaBox
			// 
			this.alphaBox.Location = new System.Drawing.Point(125, 70);
			this.alphaBox.Name = "alphaBox";
			this.alphaBox.Size = new System.Drawing.Size(60, 20);
			this.alphaBox.TabIndex = 5;
			this.alphaBox.Text = "";
			// 
			// label2
			// 
			this.label2.Location = new System.Drawing.Point(10, 72);
			this.label2.Name = "label2";
			this.label2.Size = new System.Drawing.Size(120, 15);
			this.label2.TabIndex = 4;
			this.label2.Text = "Sigmoid\'s alpha value:";
			// 
			// learningRateBox
			// 
			this.learningRateBox.Location = new System.Drawing.Point(125, 20);
			this.learningRateBox.Name = "learningRateBox";
			this.learningRateBox.Size = new System.Drawing.Size(60, 20);
			this.learningRateBox.TabIndex = 1;
			this.learningRateBox.Text = "";
			// 
			// label1
			// 
			this.label1.Location = new System.Drawing.Point(10, 22);
			this.label1.Name = "label1";
			this.label1.Size = new System.Drawing.Size(78, 14);
			this.label1.TabIndex = 0;
			this.label1.Text = "Learning rate:";
			// 
			// label8
			// 
			this.label8.BorderStyle = System.Windows.Forms.BorderStyle.Fixed3D;
			this.label8.Location = new System.Drawing.Point(10, 147);
			this.label8.Name = "label8";
			this.label8.Size = new System.Drawing.Size(175, 2);
			this.label8.TabIndex = 22;
			// 
			// iterationsBox
			// 
			this.iterationsBox.Location = new System.Drawing.Point(125, 155);
			this.iterationsBox.Name = "iterationsBox";
			this.iterationsBox.Size = new System.Drawing.Size(60, 20);
			this.iterationsBox.TabIndex = 9;
			this.iterationsBox.Text = "";
			// 
			// label10
			// 
			this.label10.Font = new System.Drawing.Font("Microsoft Sans Serif", 6.75F, System.Drawing.FontStyle.Regular, System.Drawing.GraphicsUnit.Point, ((System.Byte)(0)));
			this.label10.Location = new System.Drawing.Point(126, 175);
			this.label10.Name = "label10";
			this.label10.Size = new System.Drawing.Size(58, 14);
			this.label10.TabIndex = 25;
			this.label10.Text = "( 0 - inifinity )";
			// 
			// label9
			// 
			this.label9.Location = new System.Drawing.Point(10, 157);
			this.label9.Name = "label9";
			this.label9.Size = new System.Drawing.Size(70, 16);
			this.label9.TabIndex = 8;
			this.label9.Text = "Iterations:";
			// 
			// groupBox4
			// 
			this.groupBox4.Controls.Add(this.currentErrorBox);
			this.groupBox4.Controls.Add(this.label3);
			this.groupBox4.Controls.Add(this.currentIterationBox);
			this.groupBox4.Controls.Add(this.label5);
			this.groupBox4.Location = new System.Drawing.Point(510, 210);
			this.groupBox4.Name = "groupBox4";
			this.groupBox4.Size = new System.Drawing.Size(195, 75);
			this.groupBox4.TabIndex = 6;
			this.groupBox4.TabStop = false;
			this.groupBox4.Text = "Current iteration";
			// 
			// currentErrorBox
			// 
			this.currentErrorBox.Location = new System.Drawing.Point(125, 45);
			this.currentErrorBox.Name = "currentErrorBox";
			this.currentErrorBox.ReadOnly = true;
			this.currentErrorBox.Size = new System.Drawing.Size(60, 20);
			this.currentErrorBox.TabIndex = 3;
			this.currentErrorBox.Text = "";
			// 
			// label3
			// 
			this.label3.Location = new System.Drawing.Point(10, 47);
			this.label3.Name = "label3";
			this.label3.Size = new System.Drawing.Size(70, 16);
			this.label3.TabIndex = 2;
			this.label3.Text = "Error:";
			// 
			// currentIterationBox
			// 
			this.currentIterationBox.Location = new System.Drawing.Point(125, 20);
			this.currentIterationBox.Name = "currentIterationBox";
			this.currentIterationBox.ReadOnly = true;
			this.currentIterationBox.Size = new System.Drawing.Size(60, 20);
			this.currentIterationBox.TabIndex = 1;
			this.currentIterationBox.Text = "";
			// 
			// label5
			// 
			this.label5.Location = new System.Drawing.Point(10, 22);
			this.label5.Name = "label5";
			this.label5.Size = new System.Drawing.Size(70, 16);
			this.label5.TabIndex = 0;
			this.label5.Text = "Iteration:";
			// 
			// stopButton
			// 
			this.stopButton.Enabled = false;
			this.stopButton.Location = new System.Drawing.Point(630, 305);
			this.stopButton.Name = "stopButton";
			this.stopButton.TabIndex = 8;
			this.stopButton.Text = "S&top";
			this.stopButton.Click += new System.EventHandler(this.stopButton_Click);
			// 
			// startButton
			// 
			this.startButton.Enabled = false;
			this.startButton.Location = new System.Drawing.Point(540, 305);
			this.startButton.Name = "startButton";
			this.startButton.TabIndex = 7;
			this.startButton.Text = "&Start";
			this.startButton.Click += new System.EventHandler(this.startButton_Click);
			// 
			// label4
			// 
			this.label4.Location = new System.Drawing.Point(10, 97);
			this.label4.Name = "label4";
			this.label4.Size = new System.Drawing.Size(115, 15);
			this.label4.TabIndex = 6;
			this.label4.Text = "Neurons in first layer:";
			// 
			// neuronsBox
			// 
			this.neuronsBox.Location = new System.Drawing.Point(125, 95);
			this.neuronsBox.Name = "neuronsBox";
			this.neuronsBox.Size = new System.Drawing.Size(60, 20);
			this.neuronsBox.TabIndex = 7;
			this.neuronsBox.Text = "";
			// 
			// MainForm
			// 
			this.AutoScaleBaseSize = new System.Drawing.Size(5, 13);
			this.ClientSize = new System.Drawing.Size(714, 338);
			this.Controls.Add(this.stopButton);
			this.Controls.Add(this.startButton);
			this.Controls.Add(this.groupBox4);
			this.Controls.Add(this.groupBox3);
			this.Controls.Add(this.groupBox2);
			this.Controls.Add(this.groupBox1);
			this.FormBorderStyle = System.Windows.Forms.FormBorderStyle.FixedDialog;
			this.MaximizeBox = false;
			this.Name = "MainForm";
			this.Text = "Approximation using Multi-Layer Neural Network";
			this.Closing += new System.ComponentModel.CancelEventHandler(this.MainForm_Closing);
			this.groupBox1.ResumeLayout(false);
			this.groupBox2.ResumeLayout(false);
			this.groupBox3.ResumeLayout(false);
			this.groupBox4.ResumeLayout(false);
			this.ResumeLayout(false);

		}
		#endregion

		/// <summary>
		/// The main entry point for the application.
		/// </summary>
		[STAThread]
		static void Main( ) 
		{
			Application.Run( new MainForm( ) );
		}

		// On main form closing
		private void MainForm_Closing(object sender, System.ComponentModel.CancelEventArgs e)
		{
			// check if worker thread is running
			if ( ( workerThread != null ) && ( workerThread.IsAlive ) )
			{
				needToStop = true;
				workerThread.Join( );
			}
		}

		// Update settings controls
		private void UpdateSettings( )
		{
			learningRateBox.Text	= learningRate.ToString( );
			momentumBox.Text		= momentum.ToString( );
			alphaBox.Text			= sigmoidAlphaValue.ToString( );
			neuronsBox.Text			= neuronsInFirstLayer.ToString( );
			iterationsBox.Text		= iterations.ToString( );
		}
		
		// Load data
		private void loadDataButton_Click(object sender, System.EventArgs e)
		{
			// show file selection dialog
			if ( openFileDialog.ShowDialog( ) == DialogResult.OK )
			{
				StreamReader reader = null;
				// read maximum 50 points
				double[,] tempData = new double[50, 2];
				double minX = double.MaxValue;
				double maxX = double.MinValue;

				try
				{
					// open selected file
					reader = File.OpenText( openFileDialog.FileName );
					string	str = null;
					int		i = 0;

					// read the data
					while ( ( i < 50 ) && ( ( str = reader.ReadLine( ) ) != null ) )
					{
						string[] strs = str.Split( ';' );
						if ( strs.Length == 1 )
							strs = str.Split( ',' );
						// parse X
						tempData[i, 0] = double.Parse( strs[0] );
						tempData[i, 1] = double.Parse( strs[1] );

						// search for min value
						if ( tempData[i, 0] < minX )
							minX = tempData[i, 0];
						// search for max value
						if ( tempData[i, 0] > maxX )
							maxX = tempData[i, 0];

						i++;
					}

					// allocate and set data
					data = new double[i, 2];
					Array.Copy( tempData, 0, data, 0, i * 2 );
				}
				catch (Exception)
				{
					MessageBox.Show( "Failed reading the file", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error );
					return;
				}
				finally
				{
					// close file
					if ( reader != null )
						reader.Close( );
				}

				// update list and chart
				UpdateDataListView( );
				chart.RangeX = new DoubleRange( minX, maxX );
				chart.UpdateDataSeries( "data", data );
				chart.UpdateDataSeries( "solution", null );
				// enable "Start" button
				startButton.Enabled = true;
			}
		}

		// Update data in list view
		private void UpdateDataListView( )
		{
			// remove all current records
			dataList.Items.Clear( );
			// add new records
			for ( int i = 0, n = data.GetLength( 0 ); i < n; i++ )
			{
				dataList.Items.Add( data[i, 0].ToString( ) );
				dataList.Items[i].SubItems.Add( data[i, 1].ToString( ) );
			}
		}

		// Enable/disale controls
		private void EnableControls( bool enable )
		{
			loadDataButton.Enabled		= enable;
			learningRateBox.Enabled		= enable;
			momentumBox.Enabled			= enable;
			alphaBox.Enabled			= enable;
			neuronsBox.Enabled			= enable;
			iterationsBox.Enabled		= enable;

			startButton.Enabled	= enable;
			stopButton.Enabled	= !enable;
		}

		// On button "Start"
		private void startButton_Click( object sender, System.EventArgs e )
		{
			// get learning rate
			try
			{
				learningRate = Math.Max( 0.00001, Math.Min( 1, double.Parse( learningRateBox.Text ) ) );
			}
			catch
			{
				learningRate = 0.1;
			}
			// get momentum
			try
			{
				momentum = Math.Max( 0, Math.Min( 0.5, double.Parse( momentumBox.Text ) ) );
			}
			catch
			{
				momentum = 0;
			}
			// get sigmoid's alpha value
			try
			{
				sigmoidAlphaValue = Math.Max( 0.001, Math.Min( 50, double.Parse( alphaBox.Text ) ) );
			}
			catch
			{
				sigmoidAlphaValue = 2;
			}
			// get neurons count in first layer
			try
			{
				neuronsInFirstLayer = Math.Max( 5, Math.Min( 50, int.Parse( neuronsBox.Text ) ) );
			}
			catch
			{
				neuronsInFirstLayer = 20;
			}
			// iterations
			try
			{
				iterations = Math.Max( 0, int.Parse( iterationsBox.Text ) );
			}
			catch
			{
				iterations = 1000;
			}
			// update settings controls
			UpdateSettings( );
		
			// disable all settings controls except "Stop" button
			EnableControls( false );

			// run worker thread
			needToStop = false;
			workerThread = new Thread( new ThreadStart( SearchSolution ) );
			workerThread.Start( );
		}

		// On button "Stop"
		private void stopButton_Click( object sender, System.EventArgs e )
		{
			// stop worker thread
			needToStop = true;
			workerThread.Join( );
			workerThread = null;
		}

		// Worker thread
		void SearchSolution( )
		{
			// number of learning samples
			int samples = data.GetLength( 0 );
			// data transformation factor
			double yFactor = 1.7 / chart.RangeY.Length;
			double yMin = chart.RangeY.Min;
			double xFactor = 2.0 / chart.RangeX.Length;
			double xMin = chart.RangeX.Min;

			// prepare learning data
			double[][] input = new double[samples][];
			double[][] output = new double[samples][];

			for ( int i = 0; i < samples; i++ )
			{
				input[i] = new double[1];
				output[i] = new double[1];

				// set input
				input[i][0] = ( data[i, 0] - xMin ) * xFactor - 1.0;
				// set output
				output[i][0] = ( data[i, 1] - yMin ) * yFactor - 0.85;
			}

			// create multi-layer neural network
			ActivationNetwork	network = new ActivationNetwork(
				new BipolarSigmoidFunction( sigmoidAlphaValue ),
				1, neuronsInFirstLayer, 1 );
			// create teacher
			BackPropagationLearning teacher = new BackPropagationLearning( network );
			// set learning rate and momentum
			teacher.LearningRate	= learningRate;
			teacher.Momentum		= momentum;

			// iterations
			int iteration = 1;

			// solution array
			double[,]	solution = new double[50, 2];
			double[]	networkInput = new double[1];

			// calculate X values to be used with solution function
			for ( int j = 0; j < 50; j++ )
			{
				solution[j, 0] = chart.RangeX.Min + (double) j * chart.RangeX.Length / 49;
			}

			// loop
			while ( !needToStop )
			{
				// run epoch of learning procedure
				double error = teacher.RunEpoch( input, output ) / samples;

				// calculate solution
				for ( int j = 0; j < 50; j++ )
				{
					networkInput[0] = ( solution[j, 0] - xMin ) * xFactor - 1.0;
					solution[j, 1] = ( network.Compute( networkInput )[0] + 0.85 ) / yFactor + yMin;
				}
				chart.UpdateDataSeries( "solution", solution );
				// calculate error
				double learningError = 0.0;
				for ( int j = 0, k = data.GetLength( 0 ); j < k; j++ )
				{
					networkInput[0] = input[j][0];
					learningError += Math.Abs( data[j, 1] - ( ( network.Compute( networkInput )[0] + 0.85 ) / yFactor + yMin ) );
				}
			
				// set current iteration's info
				currentIterationBox.Text = iteration.ToString( );
				currentErrorBox.Text = learningError.ToString( "F3" );

				// increase current iteration
				iteration++;

				// check if we need to stop
				if ( ( iterations != 0 ) && ( iteration > iterations ) )
					break;
			}


			// enable settings controls
			EnableControls( true );
		}
	}
}