public void SmartAlphaBetaFilter_FilterFewSamples()
{
Sample sample = new Sample(0, 1);
Sample filteredSample = new Sample(0, 0);
SmartAlphaBetaFilter abf = new SmartAlphaBetaFilter(0.0033, 10);
for (int i = 0; i < 50; i++)
{
filteredSample = abf.AddSample(new Sample(i * 0.5, -0.5 + (new Random()).NextDouble()));
sample.Time++;
}
Assert.AreEqual(1, Math.Round(sample.Value));
}
private void GenerateChart()
{
if (csv == null)
{
return;
}
WaitingScreen.Visible = true;
this.Refresh();
list1.Clear();
list2.Clear();
IFilter Filter;
string FilterType = FilterSelector.Text;
switch (FilterType)
{
case "FIR Filter":
Filter = new FIRFilter(new List <double>()
{
0.25, 0.25, 0.25, 0.25
});
break;
case "Alpha Beta Filter":
Filter = new AlphaBetaFilter(0.2, 0.3);
break;
case "Smart Alpha Beta Filter":
Filter = new SmartAlphaBetaFilter(0.003307643036326, 200);
break;
default:
Filter = null;
break;
}
int PreviousProgress = 0;
int Progress = 0;
int i = 0;
Integrator integrator = new Integrator();
foreach (KeyValuePair <double, List <double> > entry in csv.Data)
{
InertialNavigationSystem.Sample sample = new InertialNavigationSystem.Sample(entry.Key, entry.Value[ColumnSelector.SelectedIndex]);
if (Filter != null)
{
sample = Filter.AddSample(sample);
}
list1.Add(sample.Time, sample.Value);
integrator.AddSample(sample);
if (DrawIntegral.Checked)
{
list2.Add(sample.Time, integrator.Value);
}
i++;
Progress = i * 100 / csv.Data.Count;
if (PreviousProgress != Progress)
{
ProgressIndicator.Value = Progress;
Application.DoEvents();
}
PreviousProgress = Progress;
}
Chart1.AxisChange();
Chart1.Refresh();
WaitingScreen.Visible = false;
}