public RegressionGraphPane(RegressionGraphData graphData)
{
_graphData = graphData;
Title.Text = graphData.Title;
XAxis.Title.Text = graphData.LabelX;
YAxis.Title.Text = graphData.LabelY;
Border.IsVisible = false;
Title.IsVisible = true;
Chart.Border.IsVisible = false;
XAxis.Scale.MaxAuto = true;
XAxis.Scale.MinAuto = true;
YAxis.Scale.MaxAuto = true;
YAxis.Scale.MinAuto = true;
Y2Axis.IsVisible = false;
X2Axis.IsVisible = false;
XAxis.MajorTic.IsOpposite = false;
YAxis.MajorTic.IsOpposite = false;
XAxis.MinorTic.IsOpposite = false;
YAxis.MinorTic.IsOpposite = false;
IsFontsScaled = false;
YAxis.Scale.MaxGrace = 0.1;
// Legend.FontSpec.Size = 12;
var curve = AddCurve(Resources.RegressionGraphPane_RegressionGraphPane_Values, graphData.XValues, graphData.YValues,
Color.Black, SymbolType.Diamond);
curve.Line.IsVisible = false;
curve.Symbol.Border.IsVisible = false;
curve.Symbol.Fill = new Fill(COLOR_REGRESSION);
// Find maximum points for drawing the regression line
var lineX = new[] { double.MaxValue, double.MinValue };
var lineY = new[] { double.MaxValue, double.MinValue };
for (int i = 0; i < graphData.XValues.Length; i++)
{
double xValue = graphData.XValues[i];
double yValue = graphData.YValues[i];
if (xValue < lineX[0])
{
lineX[0] = xValue;
lineY[0] = yValue;
}
if (xValue > lineX[1])
{
lineX[1] = xValue;
lineY[1] = yValue;
}
}
if (graphData.RegressionLine != null)
{
// Recalculate the y values based on the maximum x values
// and the regression.
lineY[0] = graphData.RegressionLine.GetY(lineX[0]);
lineY[1] = graphData.RegressionLine.GetY(lineX[1]);
curve = AddCurve(Resources.RegressionGraphPane_RegressionGraphPane_Regression, lineX, lineY, COLOR_LINE_REGRESSION);
curve.Line.IsAntiAlias = true;
curve.Line.IsOptimizedDraw = true;
Statistics statsX = new Statistics(_graphData.XValues);
Statistics statsY = new Statistics(_graphData.YValues);
double slope = statsY.Slope(statsX);
double intercept = statsY.Intercept(statsX);
_labelRegression = string.Format("{0} = {1:F04}, {2} = {3:F04}\n" + "r = {4:F02}", // Not L10N
Resources.Regression_slope,
slope,
Resources.Regression_intercept,
intercept,
statsY.R(statsX));
}
var regressionLineCurrent = graphData.RegressionLineCurrent;
if (regressionLineCurrent != null)
{
lineY[0] = regressionLineCurrent.GetY(lineX[0]);
lineY[1] = regressionLineCurrent.GetY(lineX[1]);
curve = AddCurve(Resources.RegressionGraphPane_RegressionGraphPane_Current, lineX, lineY, COLOR_LINE_REGRESSION_CURRENT);
curve.Line.IsAntiAlias = true;
curve.Line.IsOptimizedDraw = true;
curve.Line.Style = DashStyle.Dash;
_labelRegressionCurrent = string.Format("{0} = {1:F04}, {2} = {3:F04}", // Not L10N
Resources.Regression_slope,
regressionLineCurrent.Slope,
Resources.Regression_intercept,
regressionLineCurrent.Intercept);
}
}
public void OkDialog()
{
double minIrt;
double maxIrt;
var helper = new MessageBoxHelper(this);
if (!helper.ValidateDecimalTextBox(textMinIrt, null, null, out minIrt))
return;
if (!helper.ValidateDecimalTextBox(textMaxIrt, minIrt, null, out maxIrt))
return;
var peptide1 = (DbIrtPeptide) comboFixedPoint1.SelectedItem;
var peptide2 = (DbIrtPeptide) comboFixedPoint2.SelectedItem;
double minCurrent = Math.Min(peptide1.Irt, peptide2.Irt);
double maxCurrent = Math.Max(peptide1.Irt, peptide2.Irt);
var statX = new Statistics(minCurrent, maxCurrent);
var statY = new Statistics(minIrt, maxIrt);
LinearEquation = new RegressionLine(statY.Slope(statX), statY.Intercept(statX));
// Convert all of the peptides to the new scale.
foreach (var peptide in _irtPeptides)
{
peptide.Irt = LinearEquation.GetY(peptide.Irt);
}
DialogResult = DialogResult.OK;
}
public static bool TryGetRegressionLine(IList<double> listIndependent, IList<double> listDependent, int minPoints, out RegressionLine line)
{
line = null;
if (listIndependent.Count != listDependent.Count || listIndependent.Count < minPoints)
return false;
double correlation;
while (true)
{
var statIndependent = new Statistics(listIndependent);
var statDependent = new Statistics(listDependent);
line = new RegressionLine(statDependent.Slope(statIndependent), statDependent.Intercept(statIndependent));
correlation = statDependent.R(statIndependent);
if (correlation >= MIN_IRT_TO_TIME_CORRELATION || listIndependent.Count <= minPoints)
break;
var furthest = 0;
var maxDistance = 0.0;
for (var i = 0; i < listDependent.Count; i++)
{
var distance = Math.Abs(line.GetY(listDependent[i]) - listIndependent[i]);
if (distance > maxDistance)
{
furthest = i;
maxDistance = distance;
}
}
listIndependent.RemoveAt(furthest);
listDependent.RemoveAt(furthest);
}
return correlation >= MIN_IRT_TO_TIME_CORRELATION;
}
private static RegressionLine CalcConversion(IList<TimeScorePair> listPepCorr, int minCount)
{
var listTime = listPepCorr.Select(p => p.Time).ToList();
var listScore = listPepCorr.Select(p => p.Score).ToList();
RegressionLine line;
if (RCalcIrt.TryGetRegressionLine(listScore, listTime, minCount, out line))
return line;
// TODO: Figure out something better here
var statTime = new Statistics(listTime);
var statScore = new Statistics(listScore);
return new RegressionLine(statTime.Slope(statScore), statTime.Intercept(statScore));
}
