Merge branch 'master' of https://github.com/FBRDNLMS/NLMSvariants

bin/README.md

@@ -0,0 +1,31 @@
+# README
+
+### Short explenation of the c# .exe
+
+![alt text](https://github.com/FBRDNLMS/NLMSvariants/blob/master/img/CS_exe_screenshot_1.PNG "C# .exe with loaded picture")
+
+1. Choose the algorithm u want to calculate on and press "start" or "enter"
+
+2. Choose the number of pixels you want to go for
+
+3. Clears the screen and reprints the actual values of your picture or predefined values
+
+4. Choose the learnrate and window size you want, learnrate has to be over 0.0 and under or even 1.0.
+   The window size has to be an integer.
+
+5. Loads a picture, it has to be BMP, GIF, EXIF, JPG, PNG or TIFF
+
+6. Check this for generating outputfiles in the same direktory you started your .exe in
+   Outputfiles are : weights.txt, weights_after.txt, localMean|directPredecessorer|differentialPredecessorer.txt, results.txt
+
+7. Chart where the algorithems output is displayed
+
+
+![alt text](https://github.com/FBRDNLMS/NLMSvariants/blob/master/img/CS_exe_screenshot_2.PNG "C# .exe with loaded picture and calculated")
+
+1. Displays the average error of the calculated algorithm
+
+2. Displays the variance of the error of the calculated algorithm
+
+3. The history of graphs displayed in the chart, it is possible to have graphs of all 3 LMS algorithems in the history.
+   There is no way to hide graphs, simply use "Clear" and then calculate again.

src/c_sharp_implementation/NLMSvariants.cs

@@ -1,3 +1,10 @@
+/*
+===========================================================================
+
+Created by Kevin Becker on 19.04.2018
+
+===========================================================================
+*/
 using System;
 using System.Collections.Generic;
 using System.ComponentModel;
@@ -37,11 +44,52 @@ namespace NMLS_Graphisch
          * 
          *---------------------------------------------------*/
 
-        private void GO_btn_Click(object sender, EventArgs e)
+        private void Start_btn_Click(object sender, EventArgs e)
         {
 
-            /* Initializing the chart to display all values */
+            /* Initializing NumberOfSamples with the choosen pixelcount */
             NumberOfSamples = Int32.Parse(comboBox_pixel.SelectedItem.ToString());
+
+            /* Initializing the weights */
+
+            w = new double[windowSize, NumberOfSamples];
+            for (int i = 0; i < NumberOfSamples; i++)
+            {
+                for (int k = 0; k < windowSize; k++)
+                {
+                    w[k, i] = rnd.NextDouble();
+                }
+            }
+
+            /* Initializing the learnrate with the choosen one */
+            txtBox_learnrate.Text = txtBox_learnrate.Text.Replace(".", ",");
+            try
+            {
+                learnrate = Double.Parse(txtBox_learnrate.Text);
+            }
+            catch(Exception exep)
+            {
+                MessageBox.Show("Please choose a learnrate between >0.0 and <=1.0");
+                return;
+            }
+            
+            while(learnrate <= 0.0 || learnrate > 1.0)
+            {
+                MessageBox.Show("Please choose a learnrate between >0.0 and <=1.0");
+                var myValue = Microsoft.VisualBasic.Interaction.InputBox("Choose a learnrate between >0.0 and <=1.0", "Learnrate", "0,8");
+                if(myValue == "")
+                {
+                    return;
+                }
+                else
+                {
+                    learnrate = Double.Parse(myValue);
+                }
+            }
+
+            /* Initializing the windowsize with the choosen one*/
+
+            /* Initializing the chart to display all values */
             chart_main.ChartAreas[0].AxisX.Maximum = NumberOfSamples;
             chart_main.ChartAreas[0].AxisY.Maximum = 300;
             chart_main.ChartAreas[0].AxisY.Minimum = -100;
@@ -53,7 +101,7 @@ namespace NMLS_Graphisch
                 {
                     for (int k = 0; k < windowSize; k++)
                     {
-                        File.AppendAllText("weights.txt",
+                        File.AppendAllText(String.Format("weights_{0}.txt", comboBox_algorithem.SelectedItem.ToString().Replace(" ","")),
                             String.Format("[{0}][{1}] {2}\n", k, i, Math.Round(w[k, i], 2).ToString()),
                             Encoding.UTF8);
                     }
@@ -66,15 +114,15 @@ namespace NMLS_Graphisch
             switch (comboBox_algorithem.SelectedItem.ToString())
             {
 
-                case "lokaler Mittelwert":
+                case "local mean":
                     series = localMean();
                     break;
 
-                case "direkter Vorgänger":
+                case "direct predecessor":
                     series = directPredecessor();
                     break;
 
-                case "differenzieller Vorgänger":
+                case "differential predecessor":
                     series = diffPredecessor();
                     break;
 
@@ -104,7 +152,7 @@ namespace NMLS_Graphisch
                 {
                     for (int k = 0; k < windowSize; k++)
                     {
-                        File.AppendAllText("weights_after.txt",
+                        File.AppendAllText(String.Format("weights_after_{0}.txt", comboBox_algorithem.SelectedItem.ToString().Replace(" ", "")),
                             String.Format("[{0}][{1}] {2}\n", k, i, Math.Round(w[k, i], 2).ToString()),
                             Encoding.UTF8);
                     }
@@ -133,8 +181,8 @@ namespace NMLS_Graphisch
             x_error[0] = 0;
 
             /* Inizilazing series for the main chart */
-            Series localMeanError = new Series("Lokaler Mittelwert Error");
+            Series localMeanError = new Series("Local Mean Error");
-            Series localMeanPredict = new Series("Lokaler Mittelwert Prediction");
+            Series localMeanPredict = new Series("Local Mean Prediction");
             localMeanError.ChartType = SeriesChartType.Spline;
             localMeanPredict.ChartType = SeriesChartType.Spline;
 
@@ -155,7 +203,7 @@ namespace NMLS_Graphisch
 
                 double x_pred = 0.0;
                 double[] x_array = _x;
-                double x_actual = _x[x_count + 1];
+                double x_actual = _x[x_count];
 
                 /* Prediction algorithem */
 
@@ -169,11 +217,11 @@ namespace NMLS_Graphisch
 
                 if (checkBox_output.Checked)
                 {
-                    File.AppendAllText("lokalerMittelwert.txt",
+                    File.AppendAllText("localMean.txt",
                    String.Format("{0}. X_pred {1}\n", x_count, x_pred),
                    Encoding.UTF8);
 
-                    File.AppendAllText("lokalerMittelwert.txt",
+                    File.AppendAllText("localMean.txt",
                         String.Format("{0}. X_actual {1}\n", x_count, x_actual),
                         Encoding.UTF8);
                 }
@@ -187,7 +235,7 @@ namespace NMLS_Graphisch
                 /* Output */
                 if (checkBox_output.Checked)
                 {
-                    File.AppendAllText("lokalerMittelwert.txt",
+                    File.AppendAllText("localMean.txt",
                     String.Format("{0}. X_error {1}\n\n", x_count, x_error[x_count]),
                     Encoding.UTF8);
                 }
@@ -234,8 +282,8 @@ namespace NMLS_Graphisch
             /* Output the result */
             if (checkBox_output.Checked)
             {
-                File.AppendAllText("ergebnisse.txt",
+                File.AppendAllText("results_localMean.txt",
-                        String.Format("Quadratische Varianz(x_error): {0}\n Mittelwert(x_error): {1}\n\n", varianz, mittel),
+                        String.Format("Squared variance(x_error): {0}\n Average(x_error): {1}\n\n", varianz, mittel),
                         Encoding.UTF8);
             }
 
@@ -259,8 +307,8 @@ namespace NMLS_Graphisch
             int x_count = 0;
 
             /* Inizilazing series for the main chart */
-            Series directPredecessorError = new Series("Direkter Vorgänger Error");
+            Series directPredecessorError = new Series("Direct predecessor Error");
-            Series directPredecessorPrediction = new Series("Direkter Vorgänger Prediction");
+            Series directPredecessorPrediction = new Series("Direct predecessor Prediction");
             directPredecessorError.ChartType = SeriesChartType.Spline;
             directPredecessorPrediction.ChartType = SeriesChartType.Spline;
 
@@ -268,7 +316,7 @@ namespace NMLS_Graphisch
             while (x_count < NumberOfSamples - 1)
             {
                 double x_pred = 0.0;
-                double x_actual = _x[x_count + 1];
+                double x_actual = _x[x_count];
 
                 if (x_count > 0)
                 {
@@ -285,11 +333,11 @@ namespace NMLS_Graphisch
                     /* If output is checked a file is produced with prediction, actual and the error */
                     if (checkBox_output.Checked)
                     {
-                        File.AppendAllText("direkterVorgaenger.txt",
+                        File.AppendAllText("directpredecessor.txt",
                        String.Format("{0}. X_pred {1}\n", x_count, x_pred),
                        Encoding.UTF8);
 
-                        File.AppendAllText("direkterVorgaenger.txt",
+                        File.AppendAllText("directpredecessor.txt",
                             String.Format("{0}. X_actual {1}\n", x_count, x_actual),
                             Encoding.UTF8);
                     }
@@ -300,7 +348,7 @@ namespace NMLS_Graphisch
                     /* Output */
                     if (checkBox_output.Checked)
                     {
-                        File.AppendAllText("direkterVorgaenger.txt",
+                        File.AppendAllText("directpredecessor.txt",
                         String.Format("{0}. X_error {1}\n\n", x_count, x_error[x_count]),
                         Encoding.UTF8);
                     }
@@ -350,8 +398,8 @@ namespace NMLS_Graphisch
             /* Output the result */
             if (checkBox_output.Checked)
             {
-                File.AppendAllText("ergebnisse.txt",
+                File.AppendAllText("results_directpredecessor.txt",
-                        String.Format("Quadratische Varianz(x_error): {0}\n Mittelwert(x_error): {1}\n\n", varianz, mittel),
+                        String.Format("Squared variance(x_error): {0}\n Average(x_error): {1}\n\n", varianz, mittel),
                         Encoding.UTF8);
             }
 
@@ -375,8 +423,8 @@ namespace NMLS_Graphisch
             int x_count = 0;
 
             /* Inizilazing series for the main chart */
-            Series diffPredecessorError = new Series("Differenzieller Vorgänger Error");
+            Series diffPredecessorError = new Series("Differential predecessor Error");
-            Series diffPredecessorPrediction = new Series("Differenzieller Vorgänger Prediction");
+            Series diffPredecessorPrediction = new Series("Differential predecessor Prediction");
             diffPredecessorError.ChartType = SeriesChartType.Spline;
             diffPredecessorPrediction.ChartType = SeriesChartType.Spline;
 
@@ -384,7 +432,7 @@ namespace NMLS_Graphisch
             while (x_count < NumberOfSamples - 1)
             {
                 double x_pred = 0.0;
-                double x_actual = _x[x_count + 1];
+                double x_actual = _x[x_count];
                 if (x_count > 0)
                 {
 
@@ -401,11 +449,11 @@ namespace NMLS_Graphisch
                     /* If output is checked a file is produced with prediction, actual and the error */
                     if (checkBox_output.Checked)
                     {
-                        File.AppendAllText("differenziellerVorgaenger.txt",
+                        File.AppendAllText("differentialpredecessor .txt",
                        String.Format("{0}. X_pred {1}\n", x_count, x_pred),
                        Encoding.UTF8);
 
-                        File.AppendAllText("differenziellerVorgaenger.txt",
+                        File.AppendAllText("differentialpredecessor.txt",
                             String.Format("{0}. X_actual {1}\n", x_count, x_actual),
                             Encoding.UTF8);
                     }
@@ -416,7 +464,7 @@ namespace NMLS_Graphisch
                     /* Output */
                     if (checkBox_output.Checked)
                     {
-                        File.AppendAllText("differenziellerVorgaenger.txt",
+                        File.AppendAllText("differentialpredecessor.txt",
                         String.Format("{0}. X_error {1}\n\n", x_count, x_error[x_count]),
                         Encoding.UTF8);
                     }
@@ -468,8 +516,8 @@ namespace NMLS_Graphisch
             /* Output the result */
             if (checkBox_output.Checked)
             {
-                File.AppendAllText("ergebnisse.txt",
+                File.AppendAllText("results_differentialpredecessor.txt",
-                        String.Format("Quadratische Varianz(x_error): {0}\n Mittelwert(x_error): {1}\n\n", varianz, mittel),
+                        String.Format("Squared variance(x_error): {0}\n Average(x_error): {1}\n\n", varianz, mittel),
                         Encoding.UTF8);
             }
 
@@ -484,15 +532,24 @@ namespace NMLS_Graphisch
         *---------------------------------------------------*/
         private void Form1_Load(object sender, EventArgs e)
         {
+            /* Initializing some diffrent combo-/textboxes and the main chart */
             comboBox_algorithem.SelectedIndex = 0;
             comboBox_pixel.SelectedIndex = 0;
+            // sets an eventhandler on the gotFocus event
+            txtBox_learnrate.GotFocus += new EventHandler(txtBox_learnrate_gotFocus); 
+            txtBox_learnrate.Text = ">0.0 & <=1.0";
+            // sets an eventhandler on the gotFocus event
+            txtBox_windowSize.GotFocus += new EventHandler(txtBox_windowSize_gotFocus);
             chart_main.Series.Clear();
             Series x_actual = new Series("Actual x Value");
             x_actual.ChartType = SeriesChartType.Spline;
 
+            // sets the accept button to Start_btn
+            this.AcceptButton = Start_btn;
+
             /*  Initializing weights and actual values
                 In case no picture is loaded, actual values are generated
-                And printing them on a chart */
+                Then printing them on a chart */
             for (int i = 0; i < NumberOfSamples; i++)
             {
                 _x[i] += ((255.0 / NumberOfSamples) * i);
@@ -505,6 +562,30 @@ namespace NMLS_Graphisch
             chart_main.Series.Add(x_actual);
         }
 
+        /*--------------------------------------------------
+         *  txtBox_learnrate_gotFocus()
+         * 
+         *  sets the default text to "" if gotFocus is raised
+         * 
+         * -------------------------------------------------*/
+
+        protected void txtBox_learnrate_gotFocus(Object sender, EventArgs e)
+        {
+            txtBox_learnrate.Text = "";
+        }
+
+        /*--------------------------------------------------
+         *  txtBox_windowSize_gotFocus()
+         * 
+         *  sets the default text to "" if gotFocus is raised
+         * 
+         * -------------------------------------------------*/
+
+        protected void txtBox_windowSize_gotFocus(Object sender, EventArgs e)
+        {
+            txtBox_windowSize.Text = "";
+        }
+
         /*---------------------------------------------------
         *  Clear_btn_Click()
         * 
@@ -594,6 +675,28 @@ namespace NMLS_Graphisch
                 }
             }
         }
+
+        /*---------------------------------------------------
+        *  txtBox_windowSize_TextChanged()
+        * 
+        *  proofs if window size textbox is a valid number
+        * 
+        *---------------------------------------------------*/
+
+        private void txtBox_windowSize_TextChanged(object sender, EventArgs e)
+        {
+            try
+            {
+                if(txtBox_windowSize.Text.Length > 0)
+                {
+                    windowSize = Int32.Parse(txtBox_windowSize.Text);
+                }
+            }catch(Exception excep)
+            {
+                MessageBox.Show("Not a valid window size");
+                txtBox_windowSize.Text = "";
+            }
+        }
     }
 
 }