public void Test()
{
var filter = new ScalarKF(1, 0, 3, 0, 1);
IList<StepOutput<float>> result =
filter.Filter(new List<float>(new float[] {1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}));
Assert.That(result.Count > 0);
}
public void Test()
{
var filter = new ScalarKF(1, 0, 3, 0, 1);
IList <StepOutput <float> > result =
filter.Filter(new List <float>(new float[] { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 }));
Assert.That(result.Count > 0);
}
/// <summary>
/// According to
/// http://www.swarthmore.edu/NatSci/echeeve1/Ref/Kalman/Ex2ScalarKalman.html
/// </summary>
public void FirstOrderOutputTest()
{
try
{
if (Chart == null)
{
return;
}
// Add test Lines to demonstrate the control
Chart.Primitives.Clear();
const float a = 0.85f, b = 0, h = 3, Q = 0.1f, R = 1;
var filter = new ScalarKF(a, b, h, Q, R);
float[] inValues = SwordfishGraphHelper.CreateFloatArray(100, 1);
IList <StepOutput <float> > outValues = filter.Filter(inValues);
var originalZValues = new List <float>(outValues.Select(element => element.Z));
// var smoothedZValues = new List<float>();
int halfWindowLength = inValues.Length / 10;
for (int i = halfWindowLength; i < originalZValues.Count - halfWindowLength; i++)
{
float windowMean = 0;
for (int j = -halfWindowLength; j <= halfWindowLength; j++)
{
int windowIndex = i + j;
windowMean += originalZValues[windowIndex];
}
windowMean /= halfWindowLength * 2;
// smoothedZValues.Add(windowMean);
originalZValues[i] = windowMean;
}
// AddLineXY("N-Window Smoothing", Colors.DarkGoldenrod, originalZValues);//smoothedZValues);
// AddLineXY("Noise W", Colors.White, outValues.Select(element => element.W));
// AddLineXY("Noise V", Colors.LightGray, outValues.Select(element => element.V));
// AddLineXY("k", Colors.Cyan, outValues.Select(element => element.K));
SwordfishGraphHelper.AddLineXY(Chart, "A Posteriori X", Colors.YellowGreen,
outValues.Select(element => element.PostX));
SwordfishGraphHelper.AddLineXY(Chart, "A Priori X", Colors.Blue,
outValues.Select(element => element.PriX));
SwordfishGraphHelper.AddLineXY(Chart, "X", Colors.Red, outValues.Select(element => element.X));
Chart.Title = "FirstOrderOutputTest()";
Chart.XAxisLabel = "X Axis";
Chart.YAxisLabel = "Y Axis";
Chart.RedrawPlotLines();
}
catch (Exception e)
{
MessageBox.Show(e.ToString());
}
}
/// <summary>
/// According to
/// http://www.swarthmore.edu/NatSci/echeeve1/Ref/Kalman/Ex1ScalarKalman.html
/// </summary>
public void ConstantOutputTest()
{
try
{
if (Chart == null)
return;
// Add test Lines to demonstrate the control
Chart.Primitives.Clear();
const float a = 1, b = 0, h = 3, Q = 0, R = 1;
var filter = new ScalarKF(a, b, h, Q, R);
float[] inValues = SwordfishGraphHelper.CreateFloatArray(100, 1);
IList<StepOutput<float>> outValues = filter.Filter(inValues);
var smoothedZValues = new List<float>(outValues.Select(element => element.Z));
int halfWindowLength = inValues.Length/10;
for (int i = halfWindowLength; i < smoothedZValues.Count - halfWindowLength; i++)
{
float windowMean = 0;
for (int j = -halfWindowLength; j <= halfWindowLength; j++)
{
int windowIndex = i + j;
windowMean += smoothedZValues[windowIndex];
}
windowMean /= halfWindowLength*2;
smoothedZValues[i] = windowMean;
}
SwordfishGraphHelper.AddLineXY(Chart, "N-Window Smoothing", Colors.DarkGoldenrod, smoothedZValues);
SwordfishGraphHelper.AddLineXY(Chart, "Noise V", Colors.LightGray,
outValues.Select(element => element.V));
SwordfishGraphHelper.AddLineXY(Chart, "k", Colors.Cyan, outValues.Select(element => element.K));
SwordfishGraphHelper.AddLineXY(Chart, "A Posteriori X", Colors.YellowGreen,
outValues.Select(element => element.PostX));
SwordfishGraphHelper.AddLineXY(Chart, "A Priori X", Colors.Blue,
outValues.Select(element => element.PriX));
SwordfishGraphHelper.AddLineXY(Chart, "X", Colors.Red, outValues.Select(element => element.X));
Chart.Title = "ConstantOutputTest()";
Chart.XAxisLabel = "X Axis";
Chart.YAxisLabel = "Y Axis";
Chart.RedrawPlotLines();
}
catch (Exception e)
{
MessageBox.Show(e.ToString());
}
}
