private void Textlist_CollectionChanged(object sender, System.Collections.Specialized.NotifyCollectionChangedEventArgs e)
{
this.Invoke(new MethodInvoker(delegate()
{
string newtxt = e.NewItems[0].ToString();
listBox1.Items.Add(e.NewItems[0]);
if (newtxt.Contains("Iteration"))
{
label7.Text = e.NewItems[0].ToString();
}
if (newtxt.Contains("Sequence "))
{
// var lista = MainGA.fitness.Where(x => x.Individual.Contains(textBox1.Text)).ToList();
var lista = MainGA.fitness.Where(x => x.Histogramdistance == MainGA.fitness.Max(r => r.Histogramdistance)).ToList();
if (lista.Count > 0)
{
// string s=textlist.Where(l => l.Contains(textBox1.Text+"x")).FirstOrDefault();
testfitness = lista[0];
textBox1.Text = lista[0].Individual;
textBox2.Text = lista[0].Histogramdistance + "";
textBox3.Text = lista[0].Cleanupperrange + "";
textBox5.Text = lista[0].Lowerupperrange + "";
textBox4.Text = lista[0].Crossentropy + "";
textBox7.Text = lista[0].Crossentropy_PDE + "";
textBox6.Text = lista[0].Lvalue + "";
test = true;
testac();
}
}
}));
}
private Fitnessvalues DifferenceMethod()
{
Lvalueavg = Math.Abs(Lcleanvalueavg - Ladvvalueavg);
// Lvalueavg = 1 / Lvalueavg;
double distance = 0.0;
double distancepercentage = 0.0;
if (cleanupperrange > adversupperrange && cleanlowerrange > adversupperrange)
{
distance = cleanlowerrange - adversupperrange;
distancepercentage = distance / cleanlowerrange;
distance = distance * distance;
}
else if (adversupperrange > cleanupperrange && adverselowerrange > cleanupperrange)
{
distance = adverselowerrange - cleanupperrange;
distancepercentage = distance / adverselowerrange;
distance = distance * distance;
}
else
{
distance = Math.Abs(adversupperrange + adverselowerrange - cleanupperrange - cleanlowerrange);
distancepercentage = distance / adversupperrange;
}
// diff = distance;
double lbp_distance = 0.0;
if (lbp_cleanupperrange > lbp_adversupperrange && lbp_cleanlowerrange > lbp_adversupperrange)
{
lbp_distance = lbp_cleanlowerrange - lbp_adversupperrange;
lbp_distance = lbp_distance * lbp_distance;
}
else if (lbp_adversupperrange > lbp_cleanupperrange && lbp_adverselowerrange > lbp_cleanupperrange)
{
lbp_distance = lbp_adverselowerrange - lbp_cleanupperrange;
lbp_distance = lbp_distance * lbp_distance;
}
else
{
lbp_distance = Math.Abs(lbp_adversupperrange + lbp_adverselowerrange - lbp_cleanupperrange - lbp_cleanlowerrange);
}
Accord.Math.Distances.Euclidean euclidean = new Accord.Math.Distances.Euclidean();
var p = Array.ConvertAll <int, double>(adv_histogram.ToArray(), x => (double)x / (double)adv_histogram.Max);
var q = Array.ConvertAll <int, double>(clean_histogram.ToArray(), x => (double)x / (double)clean_histogram.Max);
// foreach(var b in q)
// Console.Write(b + "");
var plist = p.ToList();
var qlist = q.ToList();
double ecu_distance = euclidean.Distance(p, q);
double crossentropyp = CEL.Crossentropy(plist, plist);
double crossentropyq = CEL.Crossentropy(qlist, qlist);
double crossentropy = CEL.Crossentropy(plist, qlist);
// Console.WriteLine(sta + " crossentropy " + crossentropyp + " " + crossentropyq + " " + crossentropy);
// var adv_normal = new NormalDistribution(mean: plist.Average(), stdDev: plist.StdDev);
// var clean_normal = new NormalDistribution(mean: clean_histogram.Mean, stdDev: clean_histogram.StdDev);
double crossentropyppde = CEL.CrossentropyPDE(plist, plist);
double crossentropyqpde = CEL.CrossentropyPDE(qlist, qlist);
double crossentropypde = CEL.CrossentropyPDE(qlist, plist);;
// Console.WriteLine(sta + " crossentropypde " + crossentropyppde + " " + crossentropyqpde + " " + crossentropypde);
double deltax = 0 - lbp_distance;// point1[0];
double deltay = 0 - distance;
double deltaz = 0 - ecu_distance;
diff = (double)Math.Sqrt(
(deltax * deltax) +
(deltay * deltay) +
(deltaz * deltaz));
// Console.WriteLine(sta+ " fitness " + diff+"-"+ ecu_distance + "-"+ lbp_distance);
euc_cleanupperrange = clean_histogram.Mean + clean_histogram.StdDev;
euc_cleanlowerrange = clean_histogram.Mean - clean_histogram.StdDev;
string sa = sta + ", LVALUE, " + Lvalueavg + " fitness ," + diff + "," + ecu_distance + "," + lbp_distance + " ," + crossentropy + " ," + crossentropypde;
// if (!MainGA.recodedfilters.Contains(sta + "," + diff + "," + cleanupperrange + "," + cleanlowerrange + "," + lbp_cleanupperrange + "," + lbp_cleanlowerrange + "," + euc_cleanupperrange + "," + euc_cleanlowerrange));
// MainGA.recodedfilters.Add(sta + "," + diff + "," + cleanupperrange + "," + cleanlowerrange + "," + lbp_cleanupperrange + "," + lbp_cleanlowerrange + "," + euc_cleanupperrange + "," + euc_cleanlowerrange);
Fitnessvalues fitnessvalues = new Fitnessvalues();
fitnessvalues.Individual = sta;
fitnessvalues.Histogramdistance = diff;
fitnessvalues.Cleanupperrange = cleanupperrange;
fitnessvalues.Lowerupperrange = cleanlowerrange;
fitnessvalues.Lbp_distance = lbp_distance;
fitnessvalues.Lbp_cleanupperrange = lbp_cleanupperrange;
fitnessvalues.Lbp_lowerupperrange = lbp_cleanlowerrange;
fitnessvalues.Ecu_distance = Math.Abs(ecu_distance);
fitnessvalues.Ecu_histogram_clean = clean_histogram;
fitnessvalues.Ecu_histogram_adv = adv_histogram;
fitnessvalues.Lvalue = Lvalueavg;
fitnessvalues.Crossentropy = crossentropy;
fitnessvalues.Crossentropy_clean = crossentropyq;
fitnessvalues.Crossentropy_adv = crossentropyp;
fitnessvalues.Crossentropy_PDE = crossentropypde;
fitnessvalues.Crossentropy_PDE_clean = crossentropyqpde;
fitnessvalues.Crossentropy_PDE_adv = Math.Abs(crossentropyppde);
MainGA.fitness.Add(fitnessvalues);
return(fitnessvalues);
}