private void doFit()
{
int l = _values.Length;
List <PointF> ps = new List <PointF>(l);
for (int i = 0; i < l; ++i)
{
var v = _values[i];
if (v > _average)
{
ps.Add(new PointF(i, _values[i]));
}
}
var fittedParamsTemp = CurveFunctions.FindPolynomialLeastSquaresFit(ps, 2);
var errorTemp = Math.Sqrt(CurveFunctions.ErrorSquared(ps, fittedParamsTemp));
_fittedParams = fittedParamsTemp;
_error = errorTemp;
// -b / 2a
_fittedMaxPos = (float)(-_fittedParams[1] / (2 * _fittedParams[2]));
lblError.Text = string.Format("{0:0.0000}", _error);
string pt = "";
foreach (var p in _fittedParams)
{
pt += p.ToString("0.000");
}
lblParams.Text = pt;
}
private void panel1_Paint(object sender, PaintEventArgs e)
{
bool first = true;
Point oldPoint = new Point();
Graphics g = e.Graphics;
var ca = (_average - _min) * _yk;
g.DrawLine(Pens.Green, 0, ca, _w, ca);
for (var i = 0; i < _count; ++i)
{
Point p = new Point((int)(i * _xk), (int)(_h + (_min - _values[i]) * _yk));
if (!first)
{
g.DrawLine(Pens.Black, oldPoint, p);
}
oldPoint = p;
first = false;
}
if (_fittedParams != null)
{
first = true;
for (var x = 0; x < _w; ++x)
{
Point p = new Point((int)(x * _xk), (int)(_h + (_min - CurveFunctions.F(_fittedParams, x)) * _yk));
if (!first)
{
g.DrawLine(Pens.Blue, oldPoint, p);
}
oldPoint = p;
first = false;
}
var fp = _fittedMaxPos * _xk;
g.DrawLine(Pens.Red, fp, 0, fp, _h);
}
}
float getDist(float[] values)
{
// this is basically trying to fit a parable
// to the points which focus rank is higher than average
// THIS IS A CHEAP TRICK soon to be substituted
// with RANSAC or RANSAC-like technique...
try
{
float min = 1000000;
int minPos = -1;
float max = 0;
int maxPos = -1;
int l = values.Length;
float v = 0;
float accu = 0;
for (int i = 0; i < l; ++i)
{
v = values[i];
accu += v;
if (v < min)
{
min = v;
minPos = i;
}
if (v > max)
{
max = v;
maxPos = i;
}
}
float average = accu / l;
List <PointF> ps = new List <PointF>(l);
for (int i = 0; i < l; ++i)
{
v = values[i];
if (v > average)
{
ps.Add(new PointF(i, values[i]));
}
}
var fittedParamsTemp = CurveFunctions.FindPolynomialLeastSquaresFit(ps, 2);
if (fittedParamsTemp[2] > 0)
{
return(-1);
}
var errorTemp = Math.Sqrt(CurveFunctions.ErrorSquared(ps, fittedParamsTemp));
//if (errorTemp > 0.5f)
//{
// return -1;
//}
if (max - average < CurveReliabilityTreshold)
{
return(-1);
}
// -b / 2a
float res = (float)(-fittedParamsTemp[1] / (2 * fittedParamsTemp[2]));
return((res >= l) || (res <= 0) ? -1 : res);
}
catch { return(-1); }
}