C# Application to Create and Recognize Mouse Gestures (.NET)

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

namespace MouseGesture
{
	#region HiddenType enum
	//L'enumeratore serve per identificare se si vuole creare una rete con un numero
	//di default di neuroni o con un numero ben preciso di neuroni
	public enum HiddenType
	{
		Default,
		Fixed
	}
	#endregion

	#region NetTrainingForm class
	public class NetTrainingForm : System.Windows.Forms.Form
	{
		#region Visual objects
		private System.Windows.Forms.Label LearningRateLabel;
		private System.Windows.Forms.Label MaxErrorLabel;
		private System.Windows.Forms.Label MomentumLabel;
		private System.Windows.Forms.NumericUpDown LerningRateNumber;
		private System.Windows.Forms.NumericUpDown MomentumNumber;
		private System.Windows.Forms.NumericUpDown MaxErrorNumber;
		private System.Windows.Forms.Button Done;
		private System.Windows.Forms.Button Cancel;
		private System.ComponentModel.Container components = null;
		private System.Windows.Forms.GroupBox groupBox1;
		private System.Windows.Forms.RadioButton HiddenFixed;
		private System.Windows.Forms.RadioButton HiddenFixedDefault;
		private System.Windows.Forms.NumericUpDown HiddenFixedNumber;
		private System.Windows.Forms.NumericUpDown EpochsNumber;
		private System.Windows.Forms.Label EpochsLabel;
		#endregion

		#region Private members
		private double m_LearningRate;
		private double m_Momentum;
		private double m_MaxError;
		private MainBoard m_MainBoard;
		private int m_GestureIndex;
		private int m_HiddenNeurons;
		private HiddenType m_HiddenType=HiddenType.Default;
		private int m_Epochs;
		private Pattern[] m_Patterns;
		private System.Windows.Forms.CheckBox OnlyUntrainedCheck;
		private System.Windows.Forms.CheckBox SaveOnFinishedCheck;
		private System.Windows.Forms.CheckBox UseLoadedCheck;
		private int[] m_Indexes;
		#endregion
		
		#region Events and delegates
		//L'evento viene invocato appena viene addestrata una gesture
		public delegate void GestureTrainedDelegate();
		public event GestureTrainedDelegate GestureTrained;
		#endregion

		#region Contructor
		public NetTrainingForm(MainBoard board, int[] GesturesIndexes)
		{
			this.m_Indexes=GesturesIndexes;	//Vettore degli indici delle gesture con training set
			this.m_MainBoard=board;
			this.InitializeComponent();
			this.LinkHandlers();
		}
		#endregion

		#region Dispose function
		protected override void Dispose( bool disposing )
		{
			if( disposing )
			{
				if(components != null)
				{
					components.Dispose();
				}
			}
			base.Dispose( disposing );
		}
		#endregion

		#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()
		{
			System.Resources.ResourceManager resources = new System.Resources.ResourceManager(typeof(NetTrainingForm));
			this.LearningRateLabel = new System.Windows.Forms.Label();
			this.MaxErrorLabel = new System.Windows.Forms.Label();
			this.MomentumLabel = new System.Windows.Forms.Label();
			this.LerningRateNumber = new System.Windows.Forms.NumericUpDown();
			this.MomentumNumber = new System.Windows.Forms.NumericUpDown();
			this.MaxErrorNumber = new System.Windows.Forms.NumericUpDown();
			this.Done = new System.Windows.Forms.Button();
			this.Cancel = new System.Windows.Forms.Button();
			this.groupBox1 = new System.Windows.Forms.GroupBox();
			this.HiddenFixedDefault = new System.Windows.Forms.RadioButton();
			this.HiddenFixed = new System.Windows.Forms.RadioButton();
			this.HiddenFixedNumber = new System.Windows.Forms.NumericUpDown();
			this.EpochsNumber = new System.Windows.Forms.NumericUpDown();
			this.EpochsLabel = new System.Windows.Forms.Label();
			this.OnlyUntrainedCheck = new System.Windows.Forms.CheckBox();
			this.SaveOnFinishedCheck = new System.Windows.Forms.CheckBox();
			this.UseLoadedCheck = new System.Windows.Forms.CheckBox();
			((System.ComponentModel.ISupportInitialize)(this.LerningRateNumber)).BeginInit();
			((System.ComponentModel.ISupportInitialize)(this.MomentumNumber)).BeginInit();
			((System.ComponentModel.ISupportInitialize)(this.MaxErrorNumber)).BeginInit();
			this.groupBox1.SuspendLayout();
			((System.ComponentModel.ISupportInitialize)(this.HiddenFixedNumber)).BeginInit();
			((System.ComponentModel.ISupportInitialize)(this.EpochsNumber)).BeginInit();
			this.SuspendLayout();
			// 
			// LearningRateLabel
			// 
			this.LearningRateLabel.Location = new System.Drawing.Point(8, 10);
			this.LearningRateLabel.Name = "LearningRateLabel";
			this.LearningRateLabel.Size = new System.Drawing.Size(80, 17);
			this.LearningRateLabel.TabIndex = 0;
			this.LearningRateLabel.Text = "Learning rate:";
			// 
			// MaxErrorLabel
			// 
			this.MaxErrorLabel.Location = new System.Drawing.Point(184, 8);
			this.MaxErrorLabel.Name = "MaxErrorLabel";
			this.MaxErrorLabel.Size = new System.Drawing.Size(56, 17);
			this.MaxErrorLabel.TabIndex = 3;
			this.MaxErrorLabel.Text = "Max error:";
			// 
			// MomentumLabel
			// 
			this.MomentumLabel.Location = new System.Drawing.Point(8, 42);
			this.MomentumLabel.Name = "MomentumLabel";
			this.MomentumLabel.Size = new System.Drawing.Size(80, 17);
			this.MomentumLabel.TabIndex = 4;
			this.MomentumLabel.Text = "Momentum:";
			// 
			// LerningRateNumber
			// 
			this.LerningRateNumber.DecimalPlaces = 4;
			this.LerningRateNumber.Increment = new System.Decimal(new int[] {
																				1,
																				0,
																				0,
																				262144});
			this.LerningRateNumber.Location = new System.Drawing.Point(88, 8);
			this.LerningRateNumber.Maximum = new System.Decimal(new int[] {
																			  1,
																			  0,
																			  0,
																			  0});
			this.LerningRateNumber.Minimum = new System.Decimal(new int[] {
																			  1,
																			  0,
																			  0,
																			  262144});
			this.LerningRateNumber.Name = "LerningRateNumber";
			this.LerningRateNumber.Size = new System.Drawing.Size(72, 20);
			this.LerningRateNumber.TabIndex = 1;
			this.LerningRateNumber.Value = new System.Decimal(new int[] {
																			5,
																			0,
																			0,
																			65536});
			// 
			// MomentumNumber
			// 
			this.MomentumNumber.DecimalPlaces = 4;
			this.MomentumNumber.Increment = new System.Decimal(new int[] {
																			 1,
																			 0,
																			 0,
																			 262144});
			this.MomentumNumber.Location = new System.Drawing.Point(88, 40);
			this.MomentumNumber.Maximum = new System.Decimal(new int[] {
																		   1,
																		   0,
																		   0,
																		   0});
			this.MomentumNumber.Minimum = new System.Decimal(new int[] {
																		   1,
																		   0,
																		   0,
																		   262144});
			this.MomentumNumber.Name = "MomentumNumber";
			this.MomentumNumber.Size = new System.Drawing.Size(72, 20);
			this.MomentumNumber.TabIndex = 3;
			this.MomentumNumber.Value = new System.Decimal(new int[] {
																		 5000,
																		 0,
																		 0,
																		 262144});
			// 
			// MaxErrorNumber
			// 
			this.MaxErrorNumber.DecimalPlaces = 4;
			this.MaxErrorNumber.Increment = new System.Decimal(new int[] {
																			 1,
																			 0,
																			 0,
																			 262144});
			this.MaxErrorNumber.Location = new System.Drawing.Point(240, 8);
			this.MaxErrorNumber.Maximum = new System.Decimal(new int[] {
																		   1,
																		   0,
																		   0,
																		   0});
			this.MaxErrorNumber.Minimum = new System.Decimal(new int[] {
																		   1,
																		   0,
																		   0,
																		   262144});
			this.MaxErrorNumber.Name = "MaxErrorNumber";
			this.MaxErrorNumber.Size = new System.Drawing.Size(72, 20);
			this.MaxErrorNumber.TabIndex = 2;
			this.MaxErrorNumber.Value = new System.Decimal(new int[] {
																		 1,
																		 0,
																		 0,
																		 196608});
			// 
			// Done
			// 
			this.Done.Location = new System.Drawing.Point(232, 232);
			this.Done.Name = "Done";
			this.Done.Size = new System.Drawing.Size(80, 24);
			this.Done.TabIndex = 0;
			this.Done.Text = "&Train";
			// 
			// Cancel
			// 
			this.Cancel.Location = new System.Drawing.Point(8, 232);
			this.Cancel.Name = "Cancel";
			this.Cancel.Size = new System.Drawing.Size(80, 24);
			this.Cancel.TabIndex = 10;
			this.Cancel.Text = "&Cancel";
			this.Cancel.Click += new System.EventHandler(this.OnCancel);
			// 
			// groupBox1
			// 
			this.groupBox1.Controls.Add(this.HiddenFixedDefault);
			this.groupBox1.Controls.Add(this.HiddenFixed);
			this.groupBox1.Controls.Add(this.HiddenFixedNumber);
			this.groupBox1.Location = new System.Drawing.Point(8, 72);
			this.groupBox1.Name = "groupBox1";
			this.groupBox1.Size = new System.Drawing.Size(304, 72);
			this.groupBox1.TabIndex = 11;
			this.groupBox1.TabStop = false;
			this.groupBox1.Text = "Hidden neurons:";
			// 
			// HiddenFixedDefault
			// 
			this.HiddenFixedDefault.Checked = true;
			this.HiddenFixedDefault.Location = new System.Drawing.Point(16, 16);
			this.HiddenFixedDefault.Name = "HiddenFixedDefault";
			this.HiddenFixedDefault.Size = new System.Drawing.Size(144, 24);
			this.HiddenFixedDefault.TabIndex = 5;
			this.HiddenFixedDefault.TabStop = true;
			this.HiddenFixedDefault.Text = "Default hidden neurons";
			this.HiddenFixedDefault.CheckedChanged += new System.EventHandler(this.OnHiddenFixedDefaultChanged);
			// 
			// HiddenFixed
			// 
			this.HiddenFixed.Location = new System.Drawing.Point(16, 40);
			this.HiddenFixed.Name = "HiddenFixed";
			this.HiddenFixed.Size = new System.Drawing.Size(136, 24);
			this.HiddenFixed.TabIndex = 6;
			this.HiddenFixed.Text = "Fixed hidden neurons";
			this.HiddenFixed.CheckedChanged += new System.EventHandler(this.OnHiddenFixedChanged);
			// 
			// HiddenFixedNumber
			// 
			this.HiddenFixedNumber.Enabled = false;
			this.HiddenFixedNumber.Location = new System.Drawing.Point(160, 40);
			this.HiddenFixedNumber.Maximum = new System.Decimal(new int[] {
																			  1000,
																			  0,
																			  0,
																			  0});
			this.HiddenFixedNumber.Minimum = new System.Decimal(new int[] {
																			  1,
																			  0,
																			  0,
																			  0});
			this.HiddenFixedNumber.Name = "HiddenFixedNumber";
			this.HiddenFixedNumber.Size = new System.Drawing.Size(48, 20);
			this.HiddenFixedNumber.TabIndex = 7;
			this.HiddenFixedNumber.Value = new System.Decimal(new int[] {
																			1,
																			0,
																			0,
																			0});
			// 
			// EpochsNumber
			// 
			this.EpochsNumber.Location = new System.Drawing.Point(240, 40);
			this.EpochsNumber.Maximum = new System.Decimal(new int[] {
																		 100000,
																		 0,
																		 0,
																		 0});
			this.EpochsNumber.Minimum = new System.Decimal(new int[] {
																		 1,
																		 0,
																		 0,
																		 0});
			this.EpochsNumber.Name = "EpochsNumber";
			this.EpochsNumber.Size = new System.Drawing.Size(72, 20);
			this.EpochsNumber.TabIndex = 4;
			this.EpochsNumber.Value = new System.Decimal(new int[] {
																	   1,
																	   0,
																	   0,
																	   0});
			// 
			// EpochsLabel
			// 
			this.EpochsLabel.Location = new System.Drawing.Point(184, 40);
			this.EpochsLabel.Name = "EpochsLabel";
			this.EpochsLabel.Size = new System.Drawing.Size(48, 17);
			this.EpochsLabel.TabIndex = 12;
			this.EpochsLabel.Text = "Epochs:";
			// 
			// OnlyUntrainedCheck
			// 
			this.OnlyUntrainedCheck.Location = new System.Drawing.Point(8, 152);
			this.OnlyUntrainedCheck.Name = "OnlyUntrainedCheck";
			this.OnlyUntrainedCheck.Size = new System.Drawing.Size(296, 16);
			this.OnlyUntrainedCheck.TabIndex = 8;
			this.OnlyUntrainedCheck.Text = "Train only untrained gestures";
			// 
			// SaveOnFinishedCheck
			// 
			this.SaveOnFinishedCheck.Location = new System.Drawing.Point(8, 176);
			this.SaveOnFinishedCheck.Name = "SaveOnFinishedCheck";
			this.SaveOnFinishedCheck.Size = new System.Drawing.Size(296, 16);
			this.SaveOnFinishedCheck.TabIndex = 9;
			this.SaveOnFinishedCheck.Text = "Save net at the end of the training process";
			// 
			// UseLoadedCheck
			// 
			this.UseLoadedCheck.Location = new System.Drawing.Point(8, 200);
			this.UseLoadedCheck.Name = "UseLoadedCheck";
			this.UseLoadedCheck.Size = new System.Drawing.Size(296, 16);
			this.UseLoadedCheck.TabIndex = 13;
			this.UseLoadedCheck.Text = "Use loaded values (if available)";
			// 
			// NetTrainingForm
			// 
			this.AutoScaleBaseSize = new System.Drawing.Size(5, 13);
			this.ClientSize = new System.Drawing.Size(322, 264);
			this.Controls.Add(this.UseLoadedCheck);
			this.Controls.Add(this.SaveOnFinishedCheck);
			this.Controls.Add(this.OnlyUntrainedCheck);
			this.Controls.Add(this.EpochsNumber);
			this.Controls.Add(this.EpochsLabel);
			this.Controls.Add(this.groupBox1);
			this.Controls.Add(this.Cancel);
			this.Controls.Add(this.Done);
			this.Controls.Add(this.MaxErrorNumber);
			this.Controls.Add(this.MomentumNumber);
			this.Controls.Add(this.LerningRateNumber);
			this.Controls.Add(this.MomentumLabel);
			this.Controls.Add(this.MaxErrorLabel);
			this.Controls.Add(this.LearningRateLabel);
			this.FormBorderStyle = System.Windows.Forms.FormBorderStyle.FixedSingle;
			this.Icon = ((System.Drawing.Icon)(resources.GetObject("$this.Icon")));
			this.MaximizeBox = false;
			this.MinimizeBox = false;
			this.Name = "NetTrainingForm";
			this.ShowInTaskbar = false;
			this.Text = "Training parameters";
			((System.ComponentModel.ISupportInitialize)(this.LerningRateNumber)).EndInit();
			((System.ComponentModel.ISupportInitialize)(this.MomentumNumber)).EndInit();
			((System.ComponentModel.ISupportInitialize)(this.MaxErrorNumber)).EndInit();
			this.groupBox1.ResumeLayout(false);
			((System.ComponentModel.ISupportInitialize)(this.HiddenFixedNumber)).EndInit();
			((System.ComponentModel.ISupportInitialize)(this.EpochsNumber)).EndInit();
			this.ResumeLayout(false);

		}
		#endregion

		#region Linking handlers
		//La funzione collega gli eventi ai relativi handlers
		private void LinkHandlers()
		{
			this.Done.Click+=new EventHandler(OnDone);
			this.GestureTrained+=new GestureTrainedDelegate( this.m_MainBoard.OnGestureTrained);
			this.Closed+=new EventHandler(this.OnClose);
		}
		#endregion

		#region Event Handlers
		
		#region OnDone handler
		//La funzione da inizio al training della funzione
		private void OnDone(object sender, EventArgs e)
		{
			//Caricogli input impostati dall'utente
			this.m_LearningRate=(double)this.LerningRateNumber.Value;
			this.m_Momentum=(double)this.MomentumNumber.Value;
			this.m_MaxError=(double)this.MaxErrorNumber.Value;
			this.m_Epochs=(int)this.EpochsNumber.Value;
			if(this.m_HiddenType==HiddenType.Fixed)
				this.m_HiddenNeurons=(int)(this.HiddenFixedNumber.Value);
			else
				this.m_HiddenNeurons=-1;

			this.Enabled=false;
			this.Visible=false;
			//Do inizio al thread di training
			Thread TrainTread=new Thread(new ThreadStart(this.StartBatchTraining));
			TrainTread.Start();
		}
		#endregion

		#region OnCancel handler
		private void OnCancel(object sender, System.EventArgs e)
		{
			this.Close();
		}
		#endregion
		
		#region OnHiddenFixedDefaultChanged handler
		//La funzione aggiorna la modalit� di generazione dei neuroni in default
		private void OnHiddenFixedDefaultChanged(object sender, System.EventArgs e)
		{
			if(this.HiddenFixedDefault.Checked)
			{
				this.m_HiddenType=HiddenType.Default;
				this.HiddenFixedNumber.Enabled=false;
			}
		}
		#endregion

		#region OnHiddenFixedChanged handler
		//La funzione aggiorna la modalit� di generazione dei neuroni in fixed
		private void OnHiddenFixedChanged(object sender, System.EventArgs e)
		{
			if(this.HiddenFixed.Checked)
			{
				this.m_HiddenType=HiddenType.Fixed;
				this.HiddenFixedNumber.Enabled=true;
			}
		}
		#endregion

		#region OnClose handler
		private void OnClose(object obj, EventArgs e)
		{
			this.m_MainBoard.ShowMessageToBar("Training form: closed",MessageType.Normal);
		}
		#endregion

		#endregion

		#region Training functions
		
		#region Batch training start function
		//La funzione esegue il training su tutte le gestures con training set
		private void StartBatchTraining()
		{
			int Trained=0;
			//Metto la main board in training mode
			this.m_MainBoard.StartTrainingMode(this.m_Epochs);
			for(int i=0; i<this.m_Indexes.Length; i++)
			{
				//Addestro tutte le gestures, a meno che non si sia scelto di addestrare solo quelle non addestrate
				if(!this.OnlyUntrainedCheck.Checked || !((Gesture)this.m_MainBoard.KnownGestures[this.m_Indexes[i]]).Trained)
				{
					Trained++;
					this.m_GestureIndex=this.m_Indexes[i];
					//Inserisco nel RecognizedPanel la gesture di cui sto facendo il training
					this.m_MainBoard.InsertRecognizedGesture(((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Points);
					//Do inizio al training della rete della gesture
					this.StartLearning();
				}
				if(this.GestureTrained!=null)
					this.GestureTrained();
			}

			if(Trained==0)
				MessageBox.Show("Every gesture is already trained.","Info",MessageBoxButtons.OK,MessageBoxIcon.Information);

			//Termino la fase di training
			this.m_MainBoard.Parent.Enabled=true;
			this.m_MainBoard.EndTrainingMode();
			this.Close();
		}
		#endregion

		#region Start learning on current gesture
		//La funzione esegue effettivamente ilt raining della rete neurale
		private void StartLearning()
		{
			//La variabile conterr� il numero di gestures riconosciute
			double Recognized=0d;
			//La vriabile conterr� l'ultimo errore prodotto dal training della rete
			double LastError=0d;
			//La variabile indica il risultato del dialog box alla fine del ciclo while
			DialogResult result;
			//La variabile si occupa di mantenere lo stato originale della rete, prima di qualunque interventosulla stessa
			MultiLayerPerceptron OldNet=((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Net;

			do
			{
				Recognized=0d;
				LastError=0d;

				//Ripulisco la main board dai grafici precedenti
				this.m_MainBoard.ClearError();

				//Popolo il vettore del training set definitivo con ilt raining set della gesture (gli esempi)
				this.m_Patterns=new Pattern[((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).GestureTrainingSet.Length];
				((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).GestureTrainingSet.CopyTo(this.m_Patterns,0);

				//Memorizzo la grandezza del vettore, che � l'inidce del primo non esempio
				int NotExampleIndex=this.m_Patterns.Length;
				//Genero i non esempi per la gesture corrente
				this.GenerateNotExamples();

				//Se sto addestrando una rete gi� addestrata, e l'utente ha scelto di addestrare la rete con i valori usati
				//in precendeza, non ricreo la rete
				if(((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Trained && this.UseLoadedCheck.Checked)
				{
					this.m_MainBoard.ShowMessageToBar("Training \'"+((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Name+"\' net by current values",MessageType.Info);
				}
				else
				{
					//Se la rete non era addestrata, o l'utente ha deciso di uasre i nuovi settaggi, controllo
					//se l'utente abbia specificato o meno il numero di neuroni hidden
					if(this.m_HiddenType==HiddenType.Default)
						((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Net=new MultiLayerPerceptron(MainBoard.MaximumFeatures,1d,this.m_LearningRate,this.m_Momentum,this.m_Epochs,this.m_MaxError);
					else
						((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Net=new MultiLayerPerceptron(this.m_HiddenNeurons,MainBoard.MaximumFeatures,1d,this.m_LearningRate,this.m_Momentum,this.m_Epochs,this.m_MaxError);
					
					this.m_MainBoard.ShowMessageToBar("Training \'"+((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Name+"\' net by specified values values",MessageType.Info);
				}

				//Imposto il training set della rete
				((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Net.SetTrainingSet(this.m_Patterns,NotExampleIndex);

				//Creo il delegate alla funzione e collego l'evento all'handler
				MouseGesture.MultiLayerPerceptron.TrainedPatternDelegate Delegate=new MouseGesture.MultiLayerPerceptron.TrainedPatternDelegate(this.m_MainBoard.OnEpochEnded);
				((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Net.EpochEnded+=Delegate;

				LastError=((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Net.StartTraining(Gesture.ExtractFeatures(((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Points));

				double expected=0;

				//Dopo aver mandato il pattern, mando l'insieme delle gestures stesse, che rappresenta un
				//insieme di features non utilizzate nel training, applico la funzione di soglia e controllo
				//la percentuale di gestures che � stato in grado di riconoscere correttamente
				for(int g=0; g<this.m_Indexes.Length; g++)
				{
					expected=(this.m_Indexes[g]==this.m_GestureIndex)?(1d):(0d);
					if(Neuron.CheckThreashold(((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Net.Run(((Gesture)this.m_MainBoard.KnownGestures[this.m_Indexes[g]]).ExtractFeatures()))==expected)
						Recognized++;
				}

				//Rimuovo il delegate alla funzione creato in rpecedenza
				((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Net.EpochEnded-=Delegate;
				
				//Calcolo al percentuale di riconoscimento
				Recognized/=(double)this.m_Indexes.Length;

				//Faccio apparire il message box relativo al termine del training, l'utente pu�
				//rispondere 'Yes' per accettare il training e salvare la rete, 'No' per ripetere il
				//training o 'Cancel' per evitare il salvataggio della rete appena creata (quella 
				//salvata rester� quella addestrata in precedenza)
				result=MessageBox.Show("The gesture \'"+((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Name+"\' has been successfully trained (Recognized gestures: "+((double)(Recognized*100d))+"%, Last training error: "+LastError+").\nDo you want to accept this net?\n(Press \'YES\' to accept, \'NO\' to re-train and \'CANCEL\' to ignore this net)","Accept and save net?",MessageBoxButtons.YesNoCancel,MessageBoxIcon.Question);
			}
			while(result==DialogResult.No);

			//Se il risultato � stato 'Yes' salvo la rete
			if(result==DialogResult.Yes)
			{
				((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Trained=true;
				if(this.SaveOnFinishedCheck.Checked)
					((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).SaveGesture(false,true);
			}
			else
			{
				//In caso contrario ripristino lo stato della rete attuale (se era untrained rester� tale)
				((Gesture)this.m_MainBoard.KnownGestures[this.m_GestureIndex]).Net=OldNet;
			}
		}
		#endregion

		#region Not examples generation
		//La funzione si occupa della generazione dei non-esempi
		private void GenerateNotExamples()
		{
			//Il numero di pattern da generare in maniera random � pari alla dimensione del training set di
			//esempi della rete
			int TotRandom=this.m_Patterns.Length;
			//Fisso il numero di pattern da prendere da ogni training set
			//delle altre gestures
			int HowMany=(int)(TotRandom/this.m_MainBoard.KnownGestures.Count);
			HowMany=(HowMany<=0)?(1):(HowMany);
			//Inizializzo l'array del training set
			ArrayList RealTrainingSet=new ArrayList(this.m_Patterns);
            
			for(int i=0; i<this.m_MainBoard.KnownGestures.Count; i++)
			{
				if(i!=this.m_GestureIndex && ((Gesture)this.m_MainBoard.KnownGestures[i]).TrainingSetCreated)
				{
					int TotPerGesture=0;		
					for(int j=0; j<((Gesture)this.m_MainBoard.KnownGestures[i]).GestureTrainingSet.Length && TotPerGesture<HowMany; j++)
					{
						RealTrainingSet.Add(((Gesture)this.m_MainBoard.KnownGestures[i]).GestureTrainingSet[j]);
						TotPerGesture++;
					}
				}
			}

			//Aggiungo tanti contro-esempi random quanti sono i pattern positivi del training set
			for(int j=0; j<TotRandom; j++)
				RealTrainingSet.Add(this.GenerateRandomPattern());
			
			//Converto il training set finale da dinamico a statico (salvando nella variabile membro apposita)
			this.m_Patterns=new Pattern[RealTrainingSet.Count];
			RealTrainingSet.CopyTo(this.m_Patterns);
		}

		#region Random features
		//La funzione genera dei pattern con delle features comprese nell'intervallo [-1,1]
		//Anche se esiste la possibilit� di creare dei pattern simili a quello
		//da riconoscere, il fatto che gli esempi positivi siano pari al training set, rende
		//una tale eventualit� (fortuita) piuttosto ininfluente
		private Pattern GenerateRandomPattern()
		{
			Random r=new Random(DateTime.Now.Millisecond);
			double[] Features=new double[MainBoard.MaximumFeatures];
			for(int i=0; i<MainBoard.MaximumFeatures; i++)
				Features[i]=((double)r.Next(-1000,1001))/1000d;

			return new Pattern(Features);
		}
		#endregion

		#endregion
		
		#endregion
	}
	#endregion
}