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NLMSvariants
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update

This commit is contained in:
kbecke23 2018-05-24 10:46:20 +02:00
parent 25251cd572
commit 0ce7848833
1 changed files with 21 additions and 33 deletions
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54
src/c_sharp_implementation/NLMSvariants.cs
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@ -27,15 +27,15 @@ namespace NMLS_Graphisch
}
static int NumberOfSamples = 1000;
static int NumberOfSamples = 20000;
const int tracking = 40;
static Stack<double> x = new Stack<double>();
static Random rnd = new Random();
static int windowSize = 6;
static double[,] w = new double[windowSize, NumberOfSamples];
static double[] _x = new double[NumberOfSamples];
static double[,] w = new double[NumberOfSamples, NumberOfSamples];
static double learnrate = 0.2;
static double[] pixel_array;
static int windowSize = 6;
/*---------------------------------------------------
* GO_btn_click()
@ -67,17 +67,17 @@ namespace NMLS_Graphisch
{
learnrate = Double.Parse(txtBox_learnrate.Text);
}
catch(Exception exep)
catch (Exception exep)
{
MessageBox.Show("Please choose a learnrate between >0.0 and <=1.0");
return;
}
while(learnrate <= 0.0 || learnrate > 1.0)
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 == "")
if (myValue == "")
{
return;
}
@ -101,7 +101,7 @@ namespace NMLS_Graphisch
{
for (int k = 0; k < windowSize; k++)
{
File.AppendAllText(String.Format("weights_{0}.txt", comboBox_algorithem.SelectedItem.ToString().Replace(" ","")),
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);
}
@ -200,8 +200,8 @@ namespace NMLS_Graphisch
Array.Copy(_x, _sourceIndex, x_part_Array, 0, _arrayLength);
double x_middle = (x_count > 0) ? (x_part_Array.Sum() / _arrayLength) : 0;
double x_pred = 0.0;
double[] x_array = _x;
double x_actual = _x[x_count];
@ -265,9 +265,9 @@ namespace NMLS_Graphisch
}
/* Calculating the avearage of the error and the variance of the error */
double mittel = x_error.Where(d => !double.IsNaN(d)).Sum() / x_error.Length;
double mittel = x_error.Where(d => !double.IsNaN(d)).Skip(windowSize).Sum() / x_error.Length;
double varianz = 0.0;
foreach (double x_e in x_error)
foreach (double x_e in x_error.Skip(windowSize))
{
if (!double.IsNaN(x_e))
varianz += Math.Pow(x_e - mittel, 2);
@ -381,9 +381,9 @@ namespace NMLS_Graphisch
}
/* Calculating the avearage of the error and the variance of the error */
double mittel = x_error.Where(d => !double.IsNaN(d)).Sum() / x_error.Length;
double mittel = x_error.Where(d => !double.IsNaN(d)).Skip(windowSize).Sum() / x_error.Length;
double varianz = 0.0;
foreach (double x_e in x_error)
foreach (double x_e in x_error.Skip(windowSize))
{
if (!double.IsNaN(x_e))
varianz += Math.Pow(x_e - mittel, 2);
@ -499,9 +499,9 @@ namespace NMLS_Graphisch
}
/* Calculating the avearage of the error and the variance of the error */
double mittel = x_error.Where(d => !double.IsNaN(d)).Sum() / x_error.Length;
double mittel = x_error.Where(d => !double.IsNaN(d)).Skip(windowSize).Sum() / x_error.Length;
double varianz = 0.0;
foreach (double x_e in x_error)
foreach (double x_e in x_error.Skip(windowSize))
{
if (!double.IsNaN(x_e))
varianz += Math.Pow(x_e - mittel, 2);
@ -535,7 +535,7 @@ namespace NMLS_Graphisch
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.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);
@ -549,9 +549,9 @@ namespace NMLS_Graphisch
/* Initializing weights and actual values
In case no picture is loaded, actual values are generated
Then printing them on a chart */
for (int i = 0; i < NumberOfSamples; i++)
for (int i = 0; i < NumberOfSamples / 2; i++)
{
_x[i] += ((255.0 / NumberOfSamples) * i);
_x[i] += ((255.0 / NumberOfSamples / 2) * i);
for (int k = 0; k < windowSize; k++)
{
w[k, i] = rnd.NextDouble();
@ -637,19 +637,6 @@ namespace NMLS_Graphisch
}
}
/* If NuberOfSamples is greater then 2147483591 its size is over
* the limit of C# possible indexes in an array, so we have to decrease
* the size of NumberOfSamples */
NumberOfSamples = (img.Width * img.Height) / 2;
if (NumberOfSamples > 2147483591 / 5)
NumberOfSamples = 2147483591 / 5;
/* Add every 10% a number into comboBox_pixel for calculating */
for (int i = 1; i < 11; i++)
comboBox_pixel.Items.Add((int)(NumberOfSamples * 0.1 * i));
_x = pixel_array;
/* Recreating the weights with the new size of NumberOfSamples */
@ -686,11 +673,12 @@ namespace NMLS_Graphisch
{
try
{
if(txtBox_windowSize.Text.Length > 0)
if (txtBox_windowSize.Text.Length > 0)
{
windowSize = Int32.Parse(txtBox_windowSize.Text);
}
}catch(Exception excep)
}
catch (Exception excep)
{
MessageBox.Show("Not a valid window size");
txtBox_windowSize.Text = "";