private void testForData_Click(object sender, EventArgs e)
{
if (worker != null && worker.IsBusy)
{
info = Resource.Inst.Get("r189");
return;
}
var file = Common.Dialog.Open(Resource.Inst.Get("r190"), Resource.Inst.Get("r191"), "dat");
if (file.Length > 0 && File.Exists(file))
{
RepeatWindowChoice rwc = new RepeatWindowChoice();
rwc.Text = Resource.Inst.Get("r192");
rwc.FormClosing += (owner, args) =>
{
var w = (RepeatWindowChoice)owner;
if (w.Repeat)
{
var repeats = w.NumberOfRepeats;
NeuronNumberWindow nnw = new NeuronNumberWindow();
nnw.FormClosing += (nnnwOwner, nnwArgs) => {
var nw = (NeuronNumberWindow)nnnwOwner;
if (nw.IsSelected)
{
var neurons = nw.NumberOfNeurons;
worker = new BackgroundWorker();
worker.WorkerReportsProgress = true;
worker.WorkerSupportsCancellation = true;
worker.DoWork += (a, b) =>
{
var data = ((String)b.Argument).Split(";".ToCharArray());
var inputFile = data[0];
var numberRepeats = int.Parse(data[1]);
var maxNeurons = int.Parse(data[2]);
List<LearnResult> results = new List<LearnResult>();
int counter = 0;
for (int nn = 1; nn < maxNeurons; nn++)
{
for (int r = 0; r < numberRepeats; r++)
{
NBN nbn = new NBN(nn, file);
results.Add(nbn.Run(1));
((BackgroundWorker)a).ReportProgress(++counter);
}
}
List<ReportData> items = new List<ReportData>();
for (int nn = 2; nn <= maxNeurons; nn++)
{
var list = results.Where(q => q.Info != null && q.Info.nn == nn).ToList();
var avgLearnRMSE = list.Average(q => q.AverageLearnRMSE);
var avgTestRMSE = list.Average(q => q.AverageTestRMSE);
ReportData r = new ReportData();
r.LearnData = file;
r.LearnRMSE = avgLearnRMSE.ToString();
r.NeuronNumber = nn.ToString();
r.TestRMSE = avgTestRMSE.ToString();
r.Trials = numberRepeats.ToString();
r.LearnTime = list.GetLearnTime();
r.TestTime = list.GetTestTime();
items.Add(r);
}
b.Result = items;
};
worker.ProgressChanged += (a, b) =>
{
info = b.ProgressPercentage.ToString() + " z " + maxTmp;
};
worker.RunWorkerCompleted += (a, b) =>
{
info = Resource.Inst.Get("r193");
var report = ((List<ReportData>)b.Result);
GridWindow gw = new GridWindow();
gw.SetData(Resource.Inst.Get("r194"), report);
gw.ShowDialog();
};
var arguments = String.Format("{0};{1};{2}", file, repeats, neurons);
maxTmp = (repeats * neurons).ToString();
worker.RunWorkerAsync(arguments);
}
else
{
info = Resource.Inst.Get("r195");
}
};
nnw.ShowDialog();
}
else
{
info = Resource.Inst.Get("r195");
}
};
rwc.ShowDialog();
}
else
{
info = Resource.Inst.Get("r196");
}
}
private void testForData_Click(object sender, EventArgs e)
{
if (worker != null && worker.IsBusy)
{
info = Resource.Inst.Get("r189");
return;
}
var file = Common.Dialog.Open(Resource.Inst.Get("r190"), Resource.Inst.Get("r191"), "dat");
if (file.Length > 0 && File.Exists(file))
{
RepeatWindowChoice rwc = new RepeatWindowChoice();
rwc.Text = Resource.Inst.Get("r192");
rwc.FormClosing += (owner, args) =>
{
var w = (RepeatWindowChoice)owner;
if (w.Repeat)
{
var repeats = w.NumberOfRepeats;
NeuronNumberWindow nnw = new NeuronNumberWindow();
nnw.FormClosing += (nnnwOwner, nnwArgs) => {
var nw = (NeuronNumberWindow)nnnwOwner;
if (nw.IsSelected)
{
var neurons = nw.NumberOfNeurons;
worker = new BackgroundWorker();
worker.WorkerReportsProgress = true;
worker.WorkerSupportsCancellation = true;
worker.DoWork += (a, b) =>
{
var data = ((String)b.Argument).Split(";".ToCharArray());
var inputFile = data[0];
var numberRepeats = int.Parse(data[1]);
var maxNeurons = int.Parse(data[2]);
List <LearnResult> results = new List <LearnResult>();
int counter = 0;
for (int nn = 1; nn < maxNeurons; nn++)
{
for (int r = 0; r < numberRepeats; r++)
{
NBN nbn = new NBN(nn, file);
results.Add(nbn.Run(1));
((BackgroundWorker)a).ReportProgress(++counter);
}
}
List <ReportData> items = new List <ReportData>();
for (int nn = 2; nn <= maxNeurons; nn++)
{
var list = results.Where(q => q.Info != null && q.Info.nn == nn).ToList();
var avgLearnRMSE = list.Average(q => q.AverageLearnRMSE);
var avgTestRMSE = list.Average(q => q.AverageTestRMSE);
ReportData r = new ReportData();
r.LearnData = file;
r.LearnRMSE = avgLearnRMSE.ToString();
r.NeuronNumber = nn.ToString();
r.TestRMSE = avgTestRMSE.ToString();
r.Trials = numberRepeats.ToString();
r.LearnTime = list.GetLearnTime();
r.TestTime = list.GetTestTime();
items.Add(r);
}
b.Result = items;
};
worker.ProgressChanged += (a, b) =>
{
info = b.ProgressPercentage.ToString() + " z " + maxTmp;
};
worker.RunWorkerCompleted += (a, b) =>
{
info = Resource.Inst.Get("r193");
var report = ((List <ReportData>)b.Result);
GridWindow gw = new GridWindow();
gw.SetData(Resource.Inst.Get("r194"), report);
gw.ShowDialog();
};
var arguments = String.Format("{0};{1};{2}", file, repeats, neurons);
maxTmp = (repeats * neurons).ToString();
worker.RunWorkerAsync(arguments);
}
else
{
info = Resource.Inst.Get("r195");
}
};
nnw.ShowDialog();
}
else
{
info = Resource.Inst.Get("r195");
}
};
rwc.ShowDialog();
}
else
{
info = Resource.Inst.Get("r196");
}
}
