You've already forked lazarus-ccr
LazStats: First refactoring of WLSUnit.
git-svn-id: https://svn.code.sf.net/p/lazarus-ccr/svn@7773 8e941d3f-bd1b-0410-a28a-d453659cc2b4
This commit is contained in:
wp_xxyyzz
@ -205,11 +205,7 @@ begin
|
||||
ser := FChartFrame.PlotXY(ptLines, XPoints, conf, nil, nil, 'Lower confidence band', clRed);
|
||||
rightLabels.Add(ser.yValue[ser.Count-1], ser.YValue[ser.Count-1], 'LCL');
|
||||
end;
|
||||
{
|
||||
FChartFrame.Chart.Prepare;
|
||||
FChartFrame.GetXRange(xmin, xmax, false);
|
||||
FChartFrame.GetYRange(ymin, ymax, false);
|
||||
}
|
||||
|
||||
// Draw means
|
||||
if MeansChk.Checked then
|
||||
with ARegressionResults do
|
||||
|
||||
@ -7,14 +7,14 @@ interface
|
||||
uses
|
||||
Classes, SysUtils, FileUtil, Forms, Controls, Graphics, Dialogs,
|
||||
StdCtrls, Buttons, ExtCtrls, ComCtrls,
|
||||
Globals, MainUnit, DictionaryUnit, Matrixlib,
|
||||
DataProcs, BlankFrmUnit, ReportFrameUnit, ChartFrameUnit, BasicStatsParamsFormUnit; //BasicStatsReportAndChartFormUnit;
|
||||
Globals, MainUnit, DictionaryUnit, Matrixlib, DataProcs,
|
||||
MathUnit, ReportFrameUnit, ChartFrameUnit, BasicStatsParamsFormUnit;
|
||||
|
||||
type
|
||||
|
||||
{ TWLSFrm }
|
||||
|
||||
TWLSFrm = class(TBasicStatsParamsForm) //TBasicStatsReportAndChartForm)
|
||||
TWLSFrm = class(TBasicStatsParamsForm)
|
||||
DepInBtn: TBitBtn;
|
||||
DepOutBtn: TBitBtn;
|
||||
IndInBtn: TBitBtn;
|
||||
@ -50,7 +50,7 @@ type
|
||||
procedure IndOutBtnClick(Sender: TObject);
|
||||
procedure IndVarListDblClick(Sender: TObject);
|
||||
procedure VarListDblClick(Sender: TObject);
|
||||
procedure VarListSelectionChange(Sender: TObject; User: boolean);
|
||||
procedure VarListSelectionChange(Sender: TObject; {%H-}User: boolean);
|
||||
procedure WghtInBtnClick(Sender: TObject);
|
||||
procedure WghtOutBtnClick(Sender: TObject);
|
||||
|
||||
@ -64,18 +64,20 @@ type
|
||||
|
||||
function GetPageCaption(AVarName: String): String;
|
||||
|
||||
procedure PlotSquaredResiduals(AIndepCols: IntDyneVec;
|
||||
ANumIndepCols, ADepCol: Integer; AConfLevel: Double);
|
||||
|
||||
procedure PlotXY(AChartFrame: TChartFrame; const XPoints, YPoints: DblDyneVec;
|
||||
const ARegressionResults: TBivariateRegressionResults; const XLabel, YLabel: String);
|
||||
|
||||
procedure PredictIt(ColNoSelected: IntDyneVec; NoVars: integer;
|
||||
Means, StdDevs, BetaWeights: DblDyneVec;
|
||||
StdErrEst: double; NoIndepVars: integer);
|
||||
|
||||
procedure PlotXY(AChartFrame: TChartFrame; const XPoints, YPoints, UpConf, LowConf: DblDyneVec;
|
||||
ConfBand, XMean, YMean, R, Slope, Intercept: Double; XLabel, YLabel: String);
|
||||
procedure WriteDescriptiveReport(AMemo: TMemo;
|
||||
const ARegressionResults: TBivariateRegressionResults;
|
||||
const XLabel, YLabel: String);
|
||||
|
||||
procedure PlotXY(Xpoints, Ypoints, UpConf, LowConf: DblDyneVec;
|
||||
ConfBand, Xmean, Ymean, R, Slope, Intercept: double;
|
||||
Xmax, Xmin, Ymax, Ymin: double;
|
||||
N: integer; XLabel, YLabel: string);
|
||||
|
||||
protected
|
||||
procedure AdjustConstraints; override;
|
||||
procedure Compute; override;
|
||||
@ -97,15 +99,14 @@ implementation
|
||||
{$R *.lfm}
|
||||
|
||||
uses
|
||||
TAChartUtils, TALegend,
|
||||
Utils, GridProcs, MathUnit;
|
||||
TAChartUtils, TAChartAxisUtils, TALegend, TASources, TACustomSeries,
|
||||
Utils, GridProcs;
|
||||
|
||||
{ TWLSFrm }
|
||||
|
||||
constructor TWLSFrm.Create(AOwner: TComponent);
|
||||
begin
|
||||
inherited;
|
||||
if BlankFrm = nil then Application.CreateForm(TBlankFrm, BlankFrm);
|
||||
if DictionaryFrm = nil then Application.CreateForm(TDictionaryFrm, DictionaryFrm);
|
||||
|
||||
OLSReportFrame := TReportFrame.Create(self);
|
||||
@ -150,7 +151,7 @@ end;
|
||||
|
||||
procedure TWLSFrm.Compute;
|
||||
var
|
||||
i, ii, j, Noindep, DepCol, WghtCol, olddepcol, NCases, pos, col: integer;
|
||||
i, j, Noindep, DepCol, WghtCol, olddepcol, NCases, pos, col: integer;
|
||||
IndepCols: IntDyneVec = nil;
|
||||
RowLabels: StrDyneVec = nil;
|
||||
X, Y: double;
|
||||
@ -163,24 +164,14 @@ var
|
||||
BtTests: DblDyneVec = nil;
|
||||
tProbs: DblDyneVec = nil;
|
||||
PrintDesc: boolean = true;
|
||||
Xpoints: DblDyneVec = nil;
|
||||
Ypoints: DblDyneVec = nil;
|
||||
upConf: DblDyneVec = nil;
|
||||
lowConf: DblDyneVec = nil;
|
||||
Xmax, Xmin, Ymax, Ymin, Xmean, Ymean, Xvariance, Yvariance, R: double;
|
||||
temp, SEPred, Slope, Intercept, DF, SSx, t, ConfBand, sedata: double;
|
||||
Xstddev, Ystddev, predicted: double;
|
||||
ColNoSelected: IntDyneVec = nil;
|
||||
XLabel, YLabel: string;
|
||||
N, Xcol, Ycol, NoSelected: integer;
|
||||
predicted: Double;
|
||||
lReport: TStrings;
|
||||
StdErrEst: Double = 0.0;
|
||||
R2: Double = 0.0;
|
||||
errorcode: Boolean = false;
|
||||
C: TWinControl;
|
||||
msg: String;
|
||||
chartFrame: TChartFrame;
|
||||
memo: TMemo;
|
||||
begin
|
||||
if not Validate(msg, C) then
|
||||
begin
|
||||
@ -201,10 +192,6 @@ begin
|
||||
SetLength(tprobs, NoVariables + 2);
|
||||
SetLength(RowLabels, NoVariables + 2);
|
||||
SetLength(IndepCols, NoVariables + 2);
|
||||
// SetLength(Xpoints, NoCases + 1);
|
||||
// SetLength(Ypoints, NoCases + 1);
|
||||
// SetLength(UpConf, NoCases + 1);
|
||||
// SetLength(lowConf, NoCases + 1);
|
||||
SetLength(ColNoSelected, 2);
|
||||
|
||||
lReport := TStringList.Create;
|
||||
@ -298,11 +285,6 @@ begin
|
||||
|
||||
OLSReportFrame.DisplayReport(lReport);
|
||||
lReport.Clear;
|
||||
{
|
||||
lReport.Add('');
|
||||
lReport.Add(DIVIDER);
|
||||
lReport.Add('');
|
||||
}
|
||||
end;
|
||||
|
||||
if RegResChk.Checked and OLSChk.Checked then
|
||||
@ -318,13 +300,6 @@ begin
|
||||
|
||||
ResidualsRegReportFrame.DisplayReport(lReport);
|
||||
lReport.Clear;
|
||||
{
|
||||
lReport.Add(DIVIDER);
|
||||
lReport.Add('');
|
||||
}
|
||||
// FReportFrame.DisplayReport(lReport);
|
||||
// lReport.Clear;
|
||||
|
||||
end;
|
||||
|
||||
if WeightChk.Checked and RegResChk.Checked then
|
||||
@ -366,135 +341,9 @@ begin
|
||||
end; // next i
|
||||
end; // if regresChk
|
||||
|
||||
// Now, plot squared residuals against each independent variable
|
||||
// Display squared residuals for each independent variable
|
||||
if RegResChk.Checked then
|
||||
begin
|
||||
xCol := DepCol;
|
||||
for ii := 0 to NoIndep - 1 do
|
||||
begin
|
||||
SetLength(xPoints, NoCases);
|
||||
SetLength(yPoints, NoCases);
|
||||
yCol := IndepCols[ii];
|
||||
N := 0;
|
||||
ColNoSelected[0] := xCol;
|
||||
ColNoSelected[1] := yCol;
|
||||
NoSelected := 2;
|
||||
XLabel := OS3MainFrm.DataGrid.Cells[Xcol,0];
|
||||
YLabel := OS3MainFrm.DataGrid.Cells[Ycol,0];
|
||||
Xmax := -1.0e308;
|
||||
Xmin := 1.0e308;
|
||||
Ymax := -1.0e308;
|
||||
Ymin := 1.0e308;
|
||||
Xmean := 0.0;
|
||||
Ymean := 0.0;
|
||||
Xvariance := 0.0;
|
||||
Yvariance := 0.0;
|
||||
R := 0.0;
|
||||
for i := 1 to NoCases do
|
||||
begin
|
||||
if (not DataProcs.GoodRecord(i,NoSelected,ColNoSelected)) then continue;
|
||||
X := StrToFloat(OS3MainFrm.DataGrid.Cells[Xcol,i]);
|
||||
Y := StrToFloat(OS3MainFrm.DataGrid.Cells[Ycol,i]);
|
||||
Xpoints[N] := X;
|
||||
Ypoints[N] := Y;
|
||||
if (X > Xmax) then Xmax := X;
|
||||
if (X < Xmin) then Xmin := X;
|
||||
if (Y > Ymax) then Ymax := Y;
|
||||
if (Y < Ymin) then Ymin := Y;
|
||||
Xmean := Xmean + X;
|
||||
Ymean := Ymean + Y;
|
||||
Xvariance := Xvariance + X * X;
|
||||
Yvariance := Yvariance + Y * Y;
|
||||
R := R + X * Y;
|
||||
N := N + 1;
|
||||
end;
|
||||
SetLength(xPoints, N);
|
||||
SetLength(yPoints, N);
|
||||
|
||||
// sort on X
|
||||
SortOnX(xPoints, yPoints);
|
||||
|
||||
// calculate statistics
|
||||
Xvariance := Xvariance - Xmean * Xmean / N;
|
||||
SSx := Xvariance;
|
||||
Xvariance := Xvariance / (N - 1);
|
||||
Xstddev := sqrt(Xvariance);
|
||||
|
||||
Yvariance := Yvariance - Ymean * Ymean / N;
|
||||
Yvariance := Yvariance / (N - 1);
|
||||
Ystddev := sqrt(Yvariance);
|
||||
|
||||
R := R - Xmean * Ymean / N;
|
||||
R := R / (N - 1);
|
||||
R := R / (Xstddev * Ystddev);
|
||||
|
||||
SEPred := sqrt(1.0 - R * R) * Ystddev;
|
||||
SEPred := SEPred * sqrt((N - 1) / (N - 2));
|
||||
Xmean := Xmean / N;
|
||||
Ymean := Ymean / N;
|
||||
Slope := R * Ystddev / Xstddev;
|
||||
Intercept := Ymean - Slope * Xmean;
|
||||
|
||||
// Now, print the descriptive statistics if requested
|
||||
lReport.Clear;
|
||||
lReport.Add('Data file: %s', [OS3MainFrm.FileNameEdit.Text]);
|
||||
lReport.Add('');
|
||||
lReport.Add('Variables:');
|
||||
lReport.Add(' X: %s', [OS3MainFrm.DataGrid.Cells[xCol, 0]]);
|
||||
lReport.Add(' Y: %s', [OS3MainFrm.DataGrid.Cells[yCol, 0]]);
|
||||
lReport.Add('');
|
||||
lReport.Add('Variable Mean Variance Std.Dev.');
|
||||
lReport.Add('---------- -------- -------- --------');
|
||||
lReport.Add('%-10s %8.2f %8.2f %8.2f', [OS3MainFrm.DataGrid.Cells[xCol, 0], XMean, XVariance, XStdDev]);
|
||||
lReport.Add('%-10s %8.2f %8.2f %8.2f', [OS3MainFrm.DataGrid.Cells[ycol, 0], YMean, YVariance, YStdDev]);
|
||||
lReport.Add('');
|
||||
lReport.Add('Correlation: %8.4f', [R]);
|
||||
lReport.Add('Slope: %8.2f', [Slope]);
|
||||
lReport.Add('Intercept: %8.2f', [Intercept]);
|
||||
lReport.Add('Standard Error of Estimate: %8.2f', [SEPred]);
|
||||
lReport.Add('Number of good cases: %8d', [N]);
|
||||
|
||||
// Get upper and lower confidence points for each X value
|
||||
SetLength(UpConf, N);
|
||||
SetLength(LowConf, N);
|
||||
ConfBand := 0.95;
|
||||
DF := N - 2;
|
||||
t := inverset(ConfBand,DF);
|
||||
for i := 0 to N-1 do
|
||||
begin
|
||||
X := Xpoints[i];
|
||||
predicted := Slope * X + Intercept;
|
||||
sedata := SEPred * sqrt(1.0 + (1.0 / N) + ((X - Xmean) * (X - Xmean) / SSx));
|
||||
UpConf[i] := predicted + (t * sedata);
|
||||
lowConf[i] := predicted - (t * sedata);
|
||||
if (UpConf[i] > Ymax) then Ymax := UpConf[i];
|
||||
if (lowConf[i] < Ymin) then Ymin := lowConf[i];
|
||||
end;
|
||||
|
||||
// Plot the values, line and confidence band
|
||||
CreateOrGetChartFrame(yCol, yLabel, memo, chartFrame);
|
||||
chartFrame.Clear;
|
||||
PlotXY(chartFrame, XPoints, YPoints, upConf, lowConf, confBand, xMean, yMean, R, slope, intercept, xLabel, yLabel);
|
||||
memo.Lines.Assign(lReport);
|
||||
lReport.Clear;
|
||||
{
|
||||
if NormPltChk.Checked then
|
||||
PlotNormalDist(chartFrame, normDistValue);
|
||||
PlotFreq(chartFrame, col, cellVal, xLabels, freq);
|
||||
}
|
||||
|
||||
|
||||
|
||||
if PlotChk.Checked then
|
||||
begin
|
||||
PlotXY(Xpoints, Ypoints, UpConf, lowConf, ConfBand, Xmean, Ymean, R,
|
||||
Slope, Intercept, Xmax, Xmin, Ymax, Ymin, N, XLabel, YLabel);
|
||||
BlankFrm.ShowModal;
|
||||
end;
|
||||
end;
|
||||
|
||||
// FReportFrame.DisplayReport(lReport);
|
||||
end;
|
||||
PlotSquaredResiduals(IndepCols, NoIndep, DepCol, 0.95);
|
||||
|
||||
if not UserWghtsChk.Checked then
|
||||
begin
|
||||
@ -516,7 +365,7 @@ begin
|
||||
// get means of variables and subtract from the values
|
||||
if OriginChk.Checked then
|
||||
begin
|
||||
for j := 0 to Noindep do
|
||||
for j := 0 to NoIndep do
|
||||
begin
|
||||
Means[j] := 0.0;
|
||||
NCases := 0;
|
||||
@ -647,6 +496,22 @@ begin
|
||||
AChartFrame.Chart.Legend.TextFormat := tfHTML;
|
||||
AChartFrame.Chart.BottomAxis.Intervals.MaxLength := 80;
|
||||
AChartFrame.Chart.BottomAxis.Intervals.MinLength := 30;
|
||||
with AChartFrame.Chart.AxisList.Add do
|
||||
begin
|
||||
Alignment := calRight;
|
||||
Marks.Source := TListChartSource.Create(self);
|
||||
Marks.Style := smsLabel;
|
||||
Grid.Visible := false;
|
||||
TickColor := clNone;
|
||||
end;
|
||||
with AChartFrame.Chart.AxisList.Add do
|
||||
begin
|
||||
Alignment := calTop;
|
||||
Marks.Source := TListChartSource.Create(self);
|
||||
Marks.Style := smsLabel;
|
||||
Grid.Visible := false;
|
||||
TickColor := clNone;
|
||||
end;
|
||||
|
||||
// ... and add memo
|
||||
AMemo := TMemo.Create(tabSheet);
|
||||
@ -749,6 +614,116 @@ begin
|
||||
end;
|
||||
end;
|
||||
|
||||
|
||||
procedure TWLSFrm.PlotSquaredResiduals(AIndepCols: IntDyneVec;
|
||||
ANumIndepCols, ADepCol: Integer; AConfLevel: Double);
|
||||
var
|
||||
xCol, yCol: Integer;
|
||||
xLabel, yLabel: String;
|
||||
i: Integer;
|
||||
colNoSelected: IntDyneVec = nil;
|
||||
xPoints: DblDyneVec = nil;
|
||||
yPoints: DblDyneVec = nil;
|
||||
regressionRes: TBivariateRegressionResults;
|
||||
memo: TMemo;
|
||||
chartFrame: TChartFrame;
|
||||
begin
|
||||
SetLength(colNoSelected, 2);
|
||||
xCol := ADepCol;
|
||||
|
||||
for i := 0 to ANumIndepCols-1 do
|
||||
begin
|
||||
// Get values
|
||||
yCol := AIndepCols[i];
|
||||
colNoSelected[0] := xCol;
|
||||
colNoSelected[1] := yCol;
|
||||
xLabel := OS3MainFrm.DataGrid.Cells[xCol, 0];
|
||||
yLabel := OS3MainFrm.DataGrid.Cells[yCol, 0];
|
||||
xPoints := CollectValues(OS3MainFrm.DataGrid, xCol, colNoSelected);
|
||||
yPoints := CollectValues(OS3MainFrm.DataGrid, yCol, colNoSelected);
|
||||
SortOnX(xPoints, yPoints);
|
||||
|
||||
// Regression
|
||||
Calc_BivariateRegression(xPoints, yPoints, AConfLevel, regressionRes);
|
||||
|
||||
// Create tab with chart and report controls
|
||||
CreateOrGetChartFrame(yCol, yLabel, memo, chartFrame);
|
||||
|
||||
// Plot
|
||||
PlotXY(chartFrame, xPoints, yPoints, regressionRes, xLabel, yLabel);
|
||||
|
||||
// Print the descriptive statistics
|
||||
WriteDescriptiveReport(memo, regressionRes, xLabel, yLabel);
|
||||
end;
|
||||
end;
|
||||
|
||||
|
||||
procedure TWLSFrm.PlotXY(AChartFrame: TChartFrame; const XPoints, YPoints: DblDyneVec;
|
||||
const ARegressionResults: TBivariateRegressionResults; const XLabel, YLabel: String);
|
||||
var
|
||||
xpts: DblDyneVec = nil;
|
||||
ypts: DblDyneVec = nil;
|
||||
conf: DblDyneVec = nil;
|
||||
ext: TDoubleRect;
|
||||
i: Integer;
|
||||
rightLabels, topLabels: TListChartSource;
|
||||
ser: TChartSeries;
|
||||
begin
|
||||
rightLabels := AChartFrame.Chart.AxisList[2].Marks.Source as TListChartSource;
|
||||
rightLabels.Clear;
|
||||
topLabels := AChartFrame.Chart.AxisList[3].Marks.Source as TListChartSource;
|
||||
topLabels.Clear;
|
||||
AChartFrame.Clear;
|
||||
|
||||
with ARegressionResults do
|
||||
AChartFrame.SetFooter(Format('R(X,Y) = %.3f, Slope = %.3f, Intercept = %.3f', [
|
||||
R, Slope, Intercept
|
||||
]));
|
||||
|
||||
// Data points
|
||||
AChartFrame.SetXTitle(XLabel);
|
||||
AChartFrame.SetYTitle(YLabel);
|
||||
AChartFrame.PlotXY(ptSymbols, XPoints, YPoints, nil, nil, 'Data', DATA_COLORS[0]);
|
||||
|
||||
// Regression line
|
||||
SetLength(xpts, 2);
|
||||
SetLengtH(ypts, 2);
|
||||
ext := AChartFrame.Chart.GetFullExtent;
|
||||
xpts[0] := ext.a.x;
|
||||
xpts[1] := ext.b.x;
|
||||
with ARegressionResults do
|
||||
begin
|
||||
ypts[0] := Intercept + Slope * xpts[0];
|
||||
ypts[1] := Intercept + Slope * xpts[1];
|
||||
end;
|
||||
AChartFrame.PlotXY(ptLines, xpts, ypts, nil, nil, 'Predicted', clBlack);
|
||||
rightLabels.Add(ypts[1], ypts[1], 'Predicted');
|
||||
|
||||
// Upper ...
|
||||
SetLength(conf, ARegressionResults.Count);
|
||||
for i := 0 to High(conf) do
|
||||
conf[i] := ARegressionResults.ConfidenceLimits(XPoints[i], true);
|
||||
ser := AChartFrame.PlotXY(ptLines, XPoints, conf, nil, nil, 'Upper confidence band', clRed);
|
||||
rightLabels.Add(ser.yValue[ser.Count-1], ser.yValue[ser.Count-1], 'UCL');
|
||||
|
||||
// ... and lower confidence limit curves
|
||||
for i := 0 to High(conf) do
|
||||
conf[i] := ARegressionResults.ConfidenceLimits(XPoints[i], false);
|
||||
ser := AChartFrame.PlotXY(ptLines, XPoints, conf, nil, nil, 'Lower confidence band', clRed);
|
||||
rightLabels.Add(ser.yValue[ser.Count-1], ser.yValue[ser.Count-1], 'LCL');
|
||||
|
||||
// Mean lines
|
||||
with ARegressionResults do
|
||||
begin
|
||||
AChartFrame.VertLine(XMean, clGreen, psDashDot, 'Mean ' + XLabel);
|
||||
topLabels.Add(XMean, XMean, 'Mean ' + XLabel);
|
||||
|
||||
AChartFrame.HorLine(YMean, clGreen, psDash, 'Mean ' + YLabel);
|
||||
rightLabels.Add(YMean, YMean, 'Mean ' + YLabel);
|
||||
end;
|
||||
end;
|
||||
|
||||
|
||||
{ Routine obtains predicted raw and standardized scores and their
|
||||
residuals. It is assumed that the dependent variable is last in the
|
||||
list of variable column pointers stored in the ColNoSelected vector.
|
||||
@ -837,230 +812,6 @@ begin
|
||||
end;
|
||||
|
||||
|
||||
procedure TWLSFrm.PlotXY(AChartFrame: TChartFrame;
|
||||
const XPoints, YPoints, UpConf, LowConf: DblDyneVec;
|
||||
ConfBand, XMean, YMean, R, Slope, Intercept: Double; XLabel, YLabel: String);
|
||||
var
|
||||
xpts: DblDyneVec = nil;
|
||||
ypts: DblDyneVec = nil;
|
||||
ext: TDoubleRect;
|
||||
begin
|
||||
AChartFrame.SetFooter(Format('R(X,Y) = %.3f, Slope = %.3f, Intercept = %.3f', [
|
||||
R, Slope, Intercept
|
||||
]));
|
||||
|
||||
// Data points
|
||||
AChartFrame.SetXTitle(XLabel);
|
||||
AChartFrame.SetYTitle(YLabel);
|
||||
AChartFrame.PlotXY(ptSymbols, XPoints, YPoints, nil, nil, 'Data', DATA_COLORS[0]);
|
||||
|
||||
// Regression line
|
||||
SetLength(xpts, 2);
|
||||
SetLengtH(ypts, 2);
|
||||
ext := AChartFrame.Chart.GetFullExtent;
|
||||
xpts[0] := ext.a.x;
|
||||
xpts[0] := ext.b.x;
|
||||
ypts[0] := Intercept + Slope * xpts[0];
|
||||
ypts[1] := Intercept + Slope * xpts[1];
|
||||
AChartFrame.PlotXY(ptLines, xpts, ypts, nil, nil, 'Predicted', clBlack);
|
||||
|
||||
// Upper and lower confidence limit curves
|
||||
AChartFrame.PlotXY(ptLines, XPoints, UpConf, nil, nil, 'UCL', clRed);
|
||||
AChartFrame.PlotXY(ptLines, XPoints, LowConf, nil, nil, 'LCL', clRed);
|
||||
|
||||
// Mean lines
|
||||
AChartFrame.VertLine(XMean, clGreen, psDashDot, 'Mean ' + XLabel);
|
||||
// topLabels.Add(XMean, XMean, 'Mean ' + XLabel);
|
||||
|
||||
AChartFrame.HorLine(YMean, clGreen, psDash, 'Mean ' + YLabel);
|
||||
// rightLabels.Add(YMean, YMean, 'Mean ' + YLabel);
|
||||
end;
|
||||
|
||||
|
||||
procedure TWLSFrm.PlotXY(Xpoints, Ypoints, UpConf, LowConf : DblDyneVec;
|
||||
ConfBand, Xmean, Ymean, R, Slope, Intercept : double;
|
||||
Xmax, Xmin, Ymax, Ymin : double;
|
||||
N : integer; XLabel, YLabel : string);
|
||||
VAR
|
||||
i, xpos, ypos, hleft, hright, vtop, vbottom, imagewide : integer;
|
||||
vhi, hwide, offset, strhi, imagehi : integer;
|
||||
valincr, Yvalue, Xvalue, value : double;
|
||||
Title, outline : string;
|
||||
|
||||
begin
|
||||
BlankFrm.Image1.Canvas.Clear;
|
||||
Title := 'X versus Y PLOT Using File: ' + OS3MainFrm.FileNameEdit.Text;
|
||||
BlankFrm.Caption := Title;
|
||||
imagewide := BlankFrm.Image1.Width;
|
||||
imagehi := BlankFrm.Image1.Height;
|
||||
BlankFrm.Image1.Canvas.Pen.Color := clBlack;
|
||||
BlankFrm.Image1.Canvas.Brush.Color := clWhite;
|
||||
BlankFrm.Image1.Canvas.Rectangle(0,0,imagewide,imagehi);
|
||||
BlankFrm.Image1.Canvas.FloodFill(0,0,clWhite,fsBorder);
|
||||
vtop := 20;
|
||||
vbottom := round(imagehi) - 80;
|
||||
vhi := vbottom - vtop;
|
||||
hleft := 100;
|
||||
hright := imagewide - 80;
|
||||
hwide := hright - hleft;
|
||||
BlankFrm.Image1.Canvas.Pen.Color := clBlack;
|
||||
BlankFrm.Image1.Canvas.Brush.Color := clWhite;
|
||||
|
||||
// Draw chart border
|
||||
BlankFrm.Image1.Canvas.Rectangle(0,0,imagewide,imagehi);
|
||||
|
||||
// draw Means
|
||||
ypos := round(vhi * ( (Ymax - Ymean) / (Ymax - Ymin)));
|
||||
ypos := ypos + vtop;
|
||||
xpos := hleft;
|
||||
BlankFrm.Image1.Canvas.MoveTo(xpos,ypos);
|
||||
xpos := hright;
|
||||
BlankFrm.Image1.Canvas.Pen.Color := clGreen;
|
||||
BlankFrm.Image1.Canvas.LineTo(xpos,ypos);
|
||||
Title := 'MEAN ';
|
||||
Title := Title + YLabel;
|
||||
strhi := BlankFrm.Image1.Canvas.TextHeight(Title);
|
||||
ypos := ypos - strhi div 2;
|
||||
BlankFrm.Image1.Canvas.Brush.Color := clWhite;
|
||||
BlankFrm.Image1.Canvas.TextOut(xpos,ypos,Title);
|
||||
|
||||
xpos := round(hwide * ( (Xmean - Xmin) / (Xmax - Xmin)));
|
||||
xpos := xpos + hleft;
|
||||
ypos := vtop;
|
||||
BlankFrm.Image1.Canvas.MoveTo(xpos,ypos);
|
||||
ypos := vbottom;
|
||||
BlankFrm.Image1.Canvas.Pen.Color := clGreen;
|
||||
BlankFrm.Image1.Canvas.LineTo(xpos,ypos);
|
||||
Title := 'MEAN ';
|
||||
Title := Title + XLabel;
|
||||
strhi := BlankFrm.Image1.Canvas.TextWidth(Title);
|
||||
xpos := xpos - strhi div 2;
|
||||
ypos := vtop - BlankFrm.Image1.Canvas.TextHeight(Title);
|
||||
BlankFrm.Image1.Canvas.Brush.Color := clWhite;
|
||||
BlankFrm.Image1.Canvas.TextOut(xpos,ypos,Title);
|
||||
|
||||
// draw slope line
|
||||
BlankFrm.Image1.Canvas.Pen.Color := clBlack;
|
||||
Yvalue := (Xpoints[1] * Slope) + Intercept; // predicted score
|
||||
ypos := round(vhi * ( (Ymax - Yvalue) / (Ymax - Ymin)));
|
||||
ypos := ypos + vtop;
|
||||
xpos := round(hwide * ( (Xpoints[1]- Xmin) / (Xmax - Xmin)));
|
||||
xpos := xpos + hleft;
|
||||
BlankFrm.Image1.Canvas.MoveTo(xpos,ypos);
|
||||
Yvalue := (Xpoints[N] * Slope) + Intercept; // predicted score
|
||||
ypos := round(vhi * ( (Ymax - Yvalue) / (Ymax - Ymin)));
|
||||
ypos := ypos + vtop;
|
||||
xpos := round(hwide * ( (Xpoints[N] - Xmin) / (Xmax - Xmin)));
|
||||
xpos := xpos + hleft;
|
||||
BlankFrm.Image1.Canvas.LineTo(xpos,ypos);
|
||||
|
||||
// draw horizontal axis
|
||||
BlankFrm.Image1.Canvas.Pen.Color := clBlack;
|
||||
BlankFrm.Image1.Canvas.MoveTo(hleft,vbottom);
|
||||
BlankFrm.Image1.Canvas.LineTo(hright,vbottom);
|
||||
valincr := (Xmax - Xmin) / 10.0;
|
||||
for i := 1 to 11 do
|
||||
begin
|
||||
ypos := vbottom;
|
||||
Xvalue := Xmin + valincr * (i - 1);
|
||||
xpos := round(hwide * ((Xvalue - Xmin) / (Xmax - Xmin)));
|
||||
xpos := xpos + hleft;
|
||||
BlankFrm.Image1.Canvas.MoveTo(xpos,ypos);
|
||||
ypos := ypos + 10;
|
||||
BlankFrm.Image1.Canvas.LineTo(xpos,ypos);
|
||||
outline := format('%6.2f',[Xvalue]);
|
||||
Title := outline;
|
||||
offset := BlankFrm.Image1.Canvas.TextWidth(Title) div 2;
|
||||
xpos := xpos - offset;
|
||||
BlankFrm.Image1.Canvas.Pen.Color := clBlack;
|
||||
BlankFrm.Image1.Canvas.TextOut(xpos,ypos,Title);
|
||||
end;
|
||||
xpos := hleft + (hwide div 2) - (BlankFrm.Image1.Canvas.TextWidth(XLabel) div 2);
|
||||
ypos := vbottom + 20;
|
||||
BlankFrm.Image1.Canvas.TextOut(xpos,ypos,XLabel);
|
||||
outline := format('R(X,Y) := %5.3f, Slope := %6.2f, Intercept := %6.2f',
|
||||
[R,Slope,Intercept]);
|
||||
Title := outline;
|
||||
xpos := hleft + (hwide div 2) - (BlankFrm.Image1.Canvas.TextWidth(Title) div 2);
|
||||
ypos := ypos + 15;
|
||||
BlankFrm.Image1.Canvas.TextOut(xpos,ypos,Title);
|
||||
|
||||
// Draw vertical axis
|
||||
Title := YLabel;
|
||||
// xpos := hleft - 10 - BlankFrm.Image1.Canvas.TextWidth(Title) / 2;
|
||||
xpos := 10;
|
||||
ypos := vtop - 8 - BlankFrm.Image1.Canvas.TextHeight(Title);
|
||||
BlankFrm.Image1.Canvas.TextOut(xpos,ypos,YLabel);
|
||||
xpos := hleft;
|
||||
ypos := vtop;
|
||||
BlankFrm.Image1.Canvas.MoveTo(xpos,ypos);
|
||||
ypos := vbottom;
|
||||
BlankFrm.Image1.Canvas.LineTo(xpos,ypos);
|
||||
valincr := (Ymax - Ymin) / 10.0;
|
||||
for i := 1 to 11 do
|
||||
begin
|
||||
value := Ymax - ((i-1) * valincr);
|
||||
outline := format('%8.2f',[value]);
|
||||
Title := outline;
|
||||
strhi := BlankFrm.Image1.Canvas.TextHeight(Title);
|
||||
xpos := 10;
|
||||
Yvalue := Ymax - (valincr * (i-1));
|
||||
ypos := round(vhi * ( (Ymax - Yvalue) / (Ymax - Ymin)));
|
||||
ypos := ypos + vtop - strhi div 2;
|
||||
BlankFrm.Image1.Canvas.TextOut(xpos,ypos,Title);
|
||||
xpos := hleft;
|
||||
ypos := ypos + strhi div 2;
|
||||
BlankFrm.Image1.Canvas.MoveTo(xpos,ypos);
|
||||
xpos := hleft - 10;
|
||||
BlankFrm.Image1.Canvas.LineTo(xpos,ypos);
|
||||
end;
|
||||
|
||||
// draw points for x and y pairs
|
||||
for i := 0 to N-1 do
|
||||
begin
|
||||
ypos := round(vhi * ( (Ymax - Ypoints[i]) / (Ymax - Ymin)));
|
||||
ypos := ypos + vtop;
|
||||
xpos := round(hwide * ( (Xpoints[i] - Xmin) / (Xmax - Xmin)));
|
||||
xpos := xpos + hleft;
|
||||
BlankFrm.Image1.Canvas.Brush.Color := clNavy;
|
||||
BlankFrm.Image1.Canvas.Brush.Style := bsSolid;
|
||||
BlankFrm.Image1.Canvas.Pen.Color := clNavy;
|
||||
BlankFrm.Image1.Canvas.Ellipse(xpos,ypos,xpos+5,ypos+5);
|
||||
end;
|
||||
|
||||
// draw confidence bands if requested
|
||||
if not (ConfBand = 0.0) then
|
||||
begin
|
||||
BlankFrm.Image1.Canvas.Pen.Color := clRed;
|
||||
ypos := round(vhi * ((Ymax - UpConf[0]) / (Ymax - Ymin)));
|
||||
ypos := ypos + vtop;
|
||||
xpos := round(hwide * ( (Xpoints[0] - Xmin) / (Xmax - Xmin)));
|
||||
xpos := xpos + hleft;
|
||||
BlankFrm.Image1.Canvas.MoveTo(xpos,ypos);
|
||||
for i := 1 to N-1 do
|
||||
begin
|
||||
ypos := round(vhi * ((Ymax - UpConf[i]) / (Ymax - Ymin)));
|
||||
ypos := ypos + vtop;
|
||||
xpos := round(hwide * ( (Xpoints[i] - Xmin) / (Xmax - Xmin)));
|
||||
xpos := xpos + hleft;
|
||||
BlankFrm.Image1.Canvas.LineTo(xpos,ypos);
|
||||
end;
|
||||
ypos := round(vhi * ((Ymax - LowConf[0]) / (Ymax - Ymin)));
|
||||
ypos := ypos + vtop;
|
||||
xpos := round(hwide * ( (Xpoints[0] - Xmin) / (Xmax - Xmin)));
|
||||
xpos := xpos + hleft;
|
||||
BlankFrm.Image1.Canvas.MoveTo(xpos,ypos);
|
||||
for i := 1 to N-1 do
|
||||
begin
|
||||
ypos := round(vhi * ((Ymax - LowConf[i]) / (Ymax - Ymin)));
|
||||
ypos := ypos + vtop;
|
||||
xpos := round(hwide * ( (Xpoints[i] - Xmin) / (Xmax - Xmin)));
|
||||
xpos := xpos + hleft;
|
||||
BlankFrm.Image1.Canvas.LineTo(xpos,ypos);
|
||||
end;
|
||||
end;
|
||||
end;
|
||||
|
||||
procedure TWLSFrm.Reset;
|
||||
var
|
||||
i: integer;
|
||||
@ -1191,5 +942,41 @@ begin
|
||||
UpdateBtnStates;
|
||||
end;
|
||||
|
||||
|
||||
procedure TWLSFrm.WriteDescriptiveReport(AMemo: TMemo;
|
||||
const ARegressionResults: TBivariateRegressionResults;
|
||||
const XLabel, YLabel: String);
|
||||
var
|
||||
lReport: TStrings;
|
||||
begin
|
||||
lReport := TStringList.Create;
|
||||
try
|
||||
lReport.Add('Data file: %s', [OS3MainFrm.FileNameEdit.Text]);
|
||||
lReport.Add('');
|
||||
lReport.Add('Variables:');
|
||||
lReport.Add(' X: %s', [xLabel]);
|
||||
lReport.Add(' Y: %s', [yLabel]);
|
||||
lReport.Add('');
|
||||
lReport.Add('Variable Mean Variance Std.Dev.');
|
||||
lReport.Add('---------- -------- -------- --------');
|
||||
with ARegressionResults do
|
||||
begin
|
||||
lReport.Add('%-10s %8.2f %8.2f %8.2f', [xLabel, XMean, XVariance, XStdDev]);
|
||||
lReport.Add('%-10s %8.2f %8.2f %8.2f', [yLabel, YMean, YVariance, YStdDev]);
|
||||
lReport.Add('');
|
||||
lReport.Add('Regression:');
|
||||
lReport.Add(' Correlation: %8.3f', [R]);
|
||||
lReport.Add(' Slope: %8.3f', [Slope]);
|
||||
lReport.Add(' Intercept: %8.3f', [Intercept]);
|
||||
lReport.Add(' Standard Error of Estimate: %8.3f', [StdErrorPredicted]);
|
||||
lReport.Add(' Number of good cases: %8d', [Count]);
|
||||
end;
|
||||
AMemo.Lines.Assign(lReport);
|
||||
finally
|
||||
lReport.Free;
|
||||
end;
|
||||
end;
|
||||
|
||||
|
||||
end.
|
||||
|
||||
|
||||
Reference in New Issue
Block a user