void UnitTestGaussNoise(){
//
// Unit Test pulls Gauss
// Compare 2 Regression objects obtained from 2 indpendent training sample
//
// Test:
// Bias < 10 *error
// Pull < 1+ 3*error
//
TCanvas * canvasUnitGausNoise = new TCanvas("canvasUnitGausNoise","canvasUnitGausNoise",800,800);
treeIn->Draw("(AliNDLocalRegression::GetCorrND(3,xyz0,xyz1)-AliNDLocalRegression::GetCorrND(2,xyz0,xyz1))/sqrt(AliNDLocalRegression::GetCorrNDError(3,xyz0,xyz1)**2+AliNDLocalRegression::GetCorrNDError(2,xyz0,xyz1)**2)>>pullsGaus32(401,-20.5,20.5)","","");
TH1F *pullsGaus32 = (TH1F*)gPad->GetPrimitive("pullsGaus32");
Double_t meanPullsGaus01 = treeIn->GetHistogram()->GetMean();
Double_t meanPullsGaus01Err = treeIn->GetHistogram()->GetMeanError();
Double_t rmsPullsGaus01 = treeIn->GetHistogram()->GetRMS();
Double_t rmsPullsGaus01Err = treeIn->GetHistogram()->GetRMSError();
if (TMath::Abs(meanPullsGaus01)<10*meanPullsGaus01Err) {
::Info( "AliNDLocalRegressionTest","mean pull OK %3.3f\t+-%3.3f", meanPullsGaus01, meanPullsGaus01Err);
}else{
::Error( "AliNDLocalRegressionTest","mean pull NOT OK %3.3f\t+-%3.3f", meanPullsGaus01, meanPullsGaus01Err);
}
if (rmsPullsGaus01<1+rmsPullsGaus01Err) {
::Info( "AliNDLocalRegressionTest"," rms pull OK %3.3f\t+-%3.3f", rmsPullsGaus01, rmsPullsGaus01Err);
}else{
::Error( "AliNDLocalRegressionTest"," rms pull NOT OK %3.3f\t+-%3.3f", rmsPullsGaus01, rmsPullsGaus01Err);
}
//
//
//
PlotData(pullsGaus32,"Gaus pulls","counts (arb. units)",kRed+2,"zTitle",rmsPullsGaus01,rmsPullsGaus01Err,meanPullsGaus01,meanPullsGaus01Err);
canvasUnitGausNoise->SaveAs("AliNDLocalRegressionTest.canvasUnitTestGaussNoise.png");
}
void UnitTestBreitWignerNoise(){
//
// Unit Test pulls BreitWigner
// Compare 2 Regression objects obtained from 2 independent training sample
//
// Test:
// Bias < 10 *error
// Pull < 1+ 3*error
//
TCanvas * canvasUnitBreitWigner = new TCanvas("canvasUnitBretWigner","canvasUnitBreitWigner",800,800);
treeIn->Draw("(AliNDLocalRegression::GetCorrND(5,xyz0,xyz1)-AliNDLocalRegression::GetCorrND(4,xyz0,xyz1))/sqrt(AliNDLocalRegression::GetCorrNDError(4,xyz0,xyz1)**2+AliNDLocalRegression::GetCorrNDError(5,xyz0,xyz1)**2)>>pullsBreiWigner54(401,-20.5,20.5)","","");
TH1F *pullsBreiWigner54 = (TH1F*)gPad->GetPrimitive("pullsBreiWigner54");
Double_t meanPullsBreitWigner = treeIn->GetHistogram()->GetMean();
Double_t meanPullsBreitWignerErr = treeIn->GetHistogram()->GetMeanError();
Double_t rmsPullsBreitWigner = treeIn->GetHistogram()->GetRMS();
Double_t rmsPullsBreitWignerErr = treeIn->GetHistogram()->GetRMSError();
if (TMath::Abs(meanPullsBreitWigner)<10*meanPullsBreitWignerErr) {
::Info( "AliNDLocalRegressionTest::UnitTestBreitWignerNoise","mean pull OK %3.3f\t+-%3.3f", meanPullsBreitWigner, meanPullsBreitWignerErr);
}else{
::Error( "AliNDLocalRegressionTest::UnitTestBreitWignerNoise","mean pull NOT OK %3.3f\t+-%3.3f", meanPullsBreitWigner, meanPullsBreitWignerErr);
}
if (rmsPullsBreitWigner<1+rmsPullsBreitWignerErr) {
::Info( "AliNDLocalRegressionTest::UnitTestBreitWignerNoise"," rms pull OK %3.3f\t+-%3.3f", rmsPullsBreitWigner, rmsPullsBreitWignerErr);
}else{
::Error( "AliNDLocalRegressionTest::UnitTestBreitWignerNoise"," rms pull NOT OK %3.3f\t+-%3.3f", rmsPullsBreitWigner, rmsPullsBreitWignerErr);
}
PlotData(pullsBreiWigner54,"BreitWigner pulls","counts (arb. units)",kBlue+2,"zTitle",rmsPullsBreitWigner,rmsPullsBreitWignerErr,meanPullsBreitWigner,meanPullsBreitWignerErr);
canvasUnitBreitWigner->SaveAs("AliNDLocalRegressionTest.canvasUnitBreitWigner.png");
}
void LinePlot::readFromInport() {
// create local copy of data and assign it to property
if (dynamic_cast<PlotData*>(inport_.getData())) {
data_ = *dynamic_cast<PlotData*>(inport_.getData());
if (!data_.sorted())
data_.sortRows();
dataProp_.set(&data_);
plotEntitiesProp_.setPlotData(&data_);
selectionProp_.setPlotData(&data_);
plotPickingManager_.setColumnCount(data_.getColumnCount());
inportHasPlotFunction_ = false;
discreteStep_.setVisible(false);
}
else if (dynamic_cast<PlotFunction*>(inport_.getData()) && inport_.getData()->getKeyColumnCount() == 1) {
function_ = *dynamic_cast<PlotFunction*>(inport_.getData());
inportHasPlotFunction_ = true;
selectDataFromFunction();
createSimpleZoomState();
discreteStep_.setVisible(true);
}
else {
LWARNINGC("LinePlot", "LinePlot can only handle PlotData objects and PlotFunction objects with one key column");
data_ = PlotData(0,0);
dataProp_.set(&data_);
plotEntitiesProp_.setPlotData(&data_);
selectionProp_.setPlotData(&data_);
plotPickingManager_.setColumnCount(data_.getColumnCount());
}
}
void BarPlot::readFromInport() {
// create local copy of data and assign it to property
if (dynamic_cast<PlotData*>(inport_.getData())) {
data_ = *dynamic_cast<PlotData*>(inport_.getData());
if (!data_.sorted())
data_.sortRows();
dataProp_.set(&data_);
plotEntitiesProp_.setPlotData(&data_);
selectionProp_.setPlotData(&data_);
plotPickingManager_.setColumnCount(data_.getColumnCount());
}
else {
LWARNINGC("BarPlot", "BarPlot can only handle PlotData objects");
data_ = PlotData(0,0);
dataProp_.set(&data_);
plotEntitiesProp_.setPlotData(&data_);
selectionProp_.setPlotData(&data_);
plotPickingManager_.setColumnCount(data_.getColumnCount());
}
}
void UnitTestStreamer(){
//
// Check consistency of streamer
//
TCanvas * canvasUnitTestStreamer = new TCanvas("canvasUnitTestStreamer","canvasUnitTestStreamer",800,800);
TFile * f = TFile::Open("fitNDLocalTestStreamer.root","recreate");
pfitNDGaus0->Write("pfitNDGaus0");
f->Close();
f = TFile::Open("fitNDLocalTestStreamer.root");
AliNDLocalRegression *streamTest1 = (AliNDLocalRegression *)f->Get("pfitNDGaus0");
streamTest1->AddVisualCorrection(streamTest1,100);
Int_t entries = treeIn->Draw("AliNDLocalRegression::GetCorrND(100,xyz0,xyz1)-AliNDLocalRegression::GetCorrND(2,xyz0,xyz1)>>streamerTest(201,-1.05,1.05)","");
TH1F *streamerTest = (TH1F*)gPad->GetPrimitive("streamerTest");
Int_t rms = TMath::RMS(entries,treeIn->GetV1());
if (rms!=0){
::Error( "AliNDLocalRegressionTest::UnitTestStreamer","Streamer problem");
}else{
::Info( "AliNDLocalRegressionTest::UnitTestStreamer","Streamer OK");
}
PlotData(streamerTest,"streamer test","counts (arb. units)",kGreen+2,"zTitle",rms);
canvasUnitTestStreamer->SaveAs(" AliNDLocalRegressionTest.UnitTestStreamer.png");
}
void PlotHandler()
{
unsigned int i,j,k;
int classIdx1,levelIdx1,classIdx2,levelIdx2;
boolean found, addCellcountToLine;
switch(PlotOption)
{
case PLOTNOPROPSELECTED:
CNsave.cellcount[1] = 0.0;
for(i=1;i<=(unsigned int)active_ntypes;i++)
{
if (SubsetOption == SUBSETALLCELLSSELECTED)
//if all cells selected, no need to check in cellindicesToPlot
{
CNsave.cellcount[1] = CNsave.cellcount[1] + CN[i];
}
else
{
k=1;
found = false;
while((k<=numCellIndicesToPlot) && (!found))
{
if(LookUp[i].LookUpId == cellIndicesToPlot[k])
{
found = true;
CNsave.cellcount[1] = CNsave.cellcount[1] + CN[i];
}
else
{
k++;
}
}
}
}
break;
case PLOTALLPROPSELECTED:
for(i=1;i<=(unsigned int)active_ntypes;i++)
{
if (SubsetOption == SUBSETALLCELLSSELECTED)
//if all cells selected, no need to check in cellindicesToPlot
{
CNsave.cellcount[LookUp[i].LookUpId] = CN[i];
}
else
{
k=1;
found = false;
while((k<=numCellIndicesToPlot) && (!found))
{
if(LookUp[i].LookUpId == cellIndicesToPlot[k])
{
found = true;
CNsave.cellcount[LookUp[i].LookUpId] = CN[i];
}
else
{
k++;
}
}
}
}
break;
case PLOTSOMEPROPSELECTED:
// for each line
for(i=1;i<=numPlotLines;i++)
{
CNsave.cellcount[i] = 0.0;
if (SubsetOption == SUBSETALLCELLSSELECTED)
//if all cells selected, no need to check in cellindicesToPlot
{
// for each celltype in the subset
for(j=1;j<=(unsigned int)active_ntypes;j++)
{
addCellcountToLine = true;
for(k=1;k<=numPlotProperty;k++)
{
classIdx1 = PlotProperty[k];
levelIdx1 = getCellLevelbyClassforPlotting(i,k-1);
classIdx2 = classIdx1;
levelIdx2 = getcelllevelbyclass(LookUp[j].LookUpId,classIdx2);
//if the level of the line does not match the level of the celltype then
//do not add this celltype to the line
if(levelIdx2 != levelIdx1)
{
addCellcountToLine = false;
}
}
if (addCellcountToLine == true)
{
CNsave.cellcount[i]=CNsave.cellcount[i] + getcellcounts(LookUp[j].LookUpId,!VEGF);
}
}
}
else
{
// for each celltype in the subset
for(j=1;j<=numCellIndicesToPlot;j++)
{
addCellcountToLine = true;
for(k=1;k<=numPlotProperty;k++)
{
classIdx1 = PlotProperty[k];
levelIdx1 = getCellLevelbyClassforPlotting(i,k-1);
classIdx2 = classIdx1;
levelIdx2 = getcelllevelbyclass(cellIndicesToPlot[j],classIdx2);
//if the level of the line does not match the level of the celltype then
//do not add this celltype to the line
if(levelIdx2 != levelIdx1)
{
addCellcountToLine = false;
}
}
if (addCellcountToLine == true)
{
CNsave.cellcount[i]=CNsave.cellcount[i] + getcellcounts(cellIndicesToPlot[j],!VEGF);
}
}
}
}
break;
}
PlotData();
}
