77double HypoTestInverter::fgCLAccuracy = 0.005;
78unsigned int HypoTestInverter::fgNToys = 500;
80double HypoTestInverter::fgAbsAccuracy = 0.05;
81double HypoTestInverter::fgRelAccuracy = 0.05;
82std::string HypoTestInverter::fgAlgo =
"logSecant";
84bool HypoTestInverter::fgCloseProof =
false;
88template<
class HypoTestType>
91 static void SetToys(HypoTestType *
h,
int toyNull,
int toyAlt) {
h->SetToys(toyNull,toyAlt); }
98void HypoTestInverter::SetCloseProof(
bool flag) {
130 if (!modelSB || ! modelB)
132 assert(modelSB && modelB);
135 <<
"\t\t using as S+B (null) model : "
137 <<
"\t\t using as B (alternate) model : "
138 << modelB->
GetName() <<
"\n" << std::endl;
143 if (!bPdf || !bObs) {
144 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter - B model has no pdf or observables defined" << std::endl;
149 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter - pdf of B model has no parameters" << std::endl;
154 if (!poiB || !poiB->
find(scanVariable.
GetName()) ||
157 << scanVariable.
GetName() <<
" not equal to zero "
158 <<
" user must check input model configurations " << endl;
159 if (poiB)
delete poiB;
177 fCalcType(kUndefined),
178 fNBins(0), fXmin(1), fXmax(1),
197 fScannedVariable(scannedVariable),
203 fCalcType(kUndefined),
204 fNBins(0), fXmin(1), fXmax(1),
212 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter - Cannot guess the variable to scan " << std::endl;
234 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter - Type of hypotest calculator is not supported " <<std::endl;
250 fScannedVariable(scannedVariable),
257 fNBins(0), fXmin(1), fXmax(1),
265 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter - Cannot guess the variable to scan " << std::endl;
283 fScannedVariable(scannedVariable),
289 fCalcType(kFrequentist),
290 fNBins(0), fXmin(1), fXmax(1),
298 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter - Cannot guess the variable to scan " << std::endl;
315 fScannedVariable(scannedVariable),
321 fCalcType(kAsymptotic),
322 fNBins(0), fXmin(1), fXmax(1),
330 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter - Cannot guess the variable to scan " << std::endl;
348 fScannedVariable(scannedVariable),
355 fNBins(0), fXmin(1), fXmax(1),
367 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter - Cannot guess the variable to scan " << std::endl;
382 fCalculator0(0), fScannedVariable(0),
395 if (
this == &rhs)
return *
this;
460 TString results_name =
"result_";
463 TString title =
"HypoTestInverter Result For ";
494 oocoutI(
nullptr,
Eval) <<
"HypoTestInverter::GetInterval - return an already existing interval " << std::endl;
499 oocoutI(
nullptr,
Eval) <<
"HypoTestInverter::GetInterval - run a fixed scan" << std::endl;
502 oocoutE(
nullptr,
Eval) <<
"HypoTestInverter::GetInterval - error running a fixed scan " << std::endl;
505 oocoutI(
nullptr,
Eval) <<
"HypoTestInverter::GetInterval - run an automatic scan" << std::endl;
506 double limit(0),err(0);
509 oocoutE(
nullptr,
Eval) <<
"HypoTestInverter::GetInterval - error running an auto scan " << std::endl;
535 oocoutE(
nullptr,
Eval) <<
"HypoTestInverter::Eval - HypoTest failed" << std::endl;
563 while (clsMidErr >=
fgCLAccuracy && (clsTarget == -1 ||
std::abs(clsMid-clsTarget) < 3*clsMidErr) ) {
564 std::unique_ptr<HypoTestResult> more(hc.
GetHypoTest());
569 hcResult->
Append(more.get());
572 if (
fVerbose) std::cout << (
fUseCLs ?
"\tCLs = " :
"\tCLsplusb = ") << clsMid <<
" +/- " << clsMidErr << std::endl;
579 "\tCLs = " << hcResult->
CLs() <<
" +/- " << hcResult->
CLsError() <<
"\n" <<
580 "\tCLb = " << hcResult->
CLb() <<
" +/- " << hcResult->
CLbError() <<
"\n" <<
617 if ( nBins==1 && xMin!=xMax ) {
618 oocoutW(
nullptr,
InputArguments) <<
"HypoTestInverter::RunFixedScan - nBins==1 -> I will run for xMin (" << xMin <<
")\n";
620 if ( xMin==xMax && nBins>1 ) {
621 oocoutW(
nullptr,
InputArguments) <<
"HypoTestInverter::RunFixedScan - xMin==xMax -> I will enforce nBins==1\n";
626 << xMin <<
") smaller than xMax (" << xMax <<
")\n";
630 if (xMin < fScannedVariable->getMin()) {
632 oocoutW(
nullptr,
InputArguments) <<
"HypoTestInverter::RunFixedScan - xMin < lower bound, using xmin = "
633 << xMin << std::endl;
637 oocoutW(
nullptr,
InputArguments) <<
"HypoTestInverter::RunFixedScan - xMax > upper bound, using xmax = "
638 << xMax << std::endl;
641 if (xMin <= 0. && scanLog) {
642 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter::RunFixedScan - cannot go in log steps if xMin <= 0" << std::endl;
647 for (
int i=0; i<nBins; i++) {
651 thisX =
exp(
log(xMin) + i*(
log(xMax)-
log(xMin))/(nBins-1) );
653 thisX = xMin + i*(xMax-xMin)/(nBins-1);
659 if ( status==
false ) {
660 oocoutW(
nullptr,
Eval) <<
"HypoTestInverter::RunFixedScan - The hypo test for point " << thisX <<
" failed. Skipping." << std::endl;
676 if ( rVal < fScannedVariable->getMin() ) {
677 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter::RunOnePoint - Out of range: using the lower bound "
679 <<
" on the scanned variable rather than " << rVal<<
"\n";
685 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter::RunOnePoint - Out of range: using the upper bound "
687 <<
" on the scanned variable rather than " << rVal<<
"\n";
702 const_cast<ModelConfig*
>(sbModel)->SetSnapshot(poi);
715 const double nullPV =
result->NullPValue();
716 const double altPV =
result->AlternatePValue();
717 if (!std::isfinite(nullPV) || nullPV < 0. || nullPV > 1. || !std::isfinite(altPV) || altPV < 0. || altPV > 1.) {
725 else lastXtested = -999;
730 oocoutI(
nullptr,
Eval) <<
"HypoTestInverter::RunOnePoint - Merge with previous result for "
738 oocoutI(
nullptr,
Eval) <<
"HypoTestInverter::RunOnePoint - replace previous empty result\n";
777 if ((hint != 0) && (*hint >
r->getMin())) {
778 r->setMax(std::min<double>(3.0 * (*hint),
r->getMax()));
779 r->setMin(std::max<double>(0.3 * (*hint),
r->getMin()));
781 <<
" search in interval " <<
r->getMin() <<
" , " <<
r->getMax() << std::endl;
788 typedef std::pair<double,double> CLs_t;
789 double clsTarget =
fSize;
790 CLs_t clsMin(1,0), clsMax(0,0), clsMid(0,0);
791 double rMin =
r->getMin(), rMax =
r->getMax();
792 limit = 0.5*(rMax + rMin);
793 limitErr = 0.5*(rMax - rMin);
796 TF1 expoFit(
"expoFit",
"[0]*exp([1]*(x-[2]))", rMin, rMax);
798 fLimitPlot = std::make_unique<TGraphErrors>();
800 if (
fVerbose > 0) std::cout <<
"Search for upper limit to the limit" << std::endl;
801 for (
int tries = 0; tries < 6; ++tries) {
803 oocoutE(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - Hypotest failed at upper limit of scan range: " << rMax << std::endl;
808 if (clsMax.first == 0 || clsMax.first + 3 *
std::abs(clsMax.second) < clsTarget )
break;
811 oocoutE(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - Cannot determine upper limit of scan range. At " <<
r->GetName()
812 <<
" = " << rMax <<
" still getting "
813 << (
fUseCLs ?
"CLs" :
"CLsplusb") <<
" = " << clsMax.first << std::endl;
818 oocoutI(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - Search for lower limit to the limit" << std::endl;
826 oocoutE(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - Hypotest failed at lower limit of scan range: " << rMin << std::endl;
831 if (clsMin.first != 1 && clsMin.first - 3 *
std::abs(clsMin.second) < clsTarget) {
837 for (
int tries = 0; tries < 6; ++tries) {
839 oocoutE(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - Hypotest failed at lower limit of scan range: " << rMin << std::endl;
840 rMin = rMin == 0. ? 0.1 : rMin * 1.1;
844 if (clsMin.first == 1 || clsMin.first - 3 *
std::abs(clsMin.second) > clsTarget)
break;
847 oocoutE(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - Cannot determine lower limit of scan range. At " <<
r->GetName()
848 <<
" = " << rMin <<
" still get " << (
fUseCLs ?
"CLs" :
"CLsplusb")
849 <<
" = " << clsMin.first << std::endl;
857 oocoutI(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - Now doing proper bracketing & bisection" << std::endl;
862 oocoutW(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - maximum number of toys reached " << std::endl;
868 limit = 0.5*(rMin+rMax); limitErr = 0.5*(rMax-rMin);
869 if (
fgAlgo ==
"logSecant" && clsMax.first != 0) {
870 double logMin =
log(clsMin.first), logMax =
log(clsMax.first), logTarget =
log(clsTarget);
871 limit = rMin + (rMax-rMin) * (logTarget - logMin)/(logMax - logMin);
872 if (clsMax.second != 0 && clsMin.second != 0) {
873 limitErr =
hypot((logTarget-logMax) * (clsMin.second/clsMin.first), (logTarget-logMin) * (clsMax.second/clsMax.first));
874 limitErr *= (rMax-rMin)/((logMax-logMin)*(logMax-logMin));
877 r->setError(limitErr);
880 if (limitErr < std::max(absAccuracy, relAccuracy * limit)) {
882 oocoutI(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - reached accuracy " << limitErr
883 <<
" below " << std::max(absAccuracy, relAccuracy * limit) << std::endl;
889 oocoutE(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - Hypo test failed at x=" << limit <<
" when trying to find limit." << std::endl;
894 if (clsMid.second == -1) {
895 std::cerr <<
"Hypotest failed" << std::endl;
900 if (
std::abs(clsMid.first-clsTarget) >= 2*clsMid.second) {
901 if ((clsMid.first>clsTarget) == (clsMax.first>clsTarget)) {
902 rMax = limit; clsMax = clsMid;
904 rMin = limit; clsMin = clsMid;
907 if (
fVerbose > 0) std::cout <<
"Trying to move the interval edges closer" << std::endl;
908 double rMinBound = rMin, rMaxBound = rMax;
910 while (clsMin.second == 0 ||
std::abs(rMin-limit) > std::max(absAccuracy, relAccuracy * limit)) {
911 rMin = 0.5*(rMin+limit);
913 oocoutE(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - Hypo test failed at x=" << rMin <<
" when trying to find limit from below." << std::endl;
917 if (
std::abs(clsMin.first-clsTarget) <= 2*clsMin.second)
break;
920 while (clsMax.second == 0 ||
std::abs(rMax-limit) > std::max(absAccuracy, relAccuracy * limit)) {
921 rMax = 0.5*(rMax+limit);
923 oocoutE(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - Hypo test failed at x=" << rMin <<
" when trying to find limit from above." << std::endl;
927 if (
std::abs(clsMax.first-clsTarget) <= 2*clsMax.second)
break;
930 expoFit.
SetRange(rMinBound,rMaxBound);
937 oocoutI(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - Before fit --- \n";
938 std::cout <<
"Limit: " <<
r->GetName() <<
" < " << limit <<
" +/- " << limitErr <<
" [" << rMin <<
", " << rMax <<
"]\n";
944 double rMinBound, rMaxBound; expoFit.
GetRange(rMinBound, rMaxBound);
952 for (
int j = 0; j <
fLimitPlot->GetN(); ++j) {
955 for (
int i = 0, imax = 8; i <= imax; ++i, ++npoints) {
965 if (limitErr < std::max(absAccuracy, relAccuracy * limit))
break;
970 if (!
RunOnePoint(rTry,
true,clsTarget) )
return false;
982 double xmin =
r->getMin(),
xmax =
r->getMax();
983 for (
int j = 0; j <
fLimitPlot->GetN(); ++j) {
989 fLimitPlot->GetYaxis()->SetRangeUser(0.5*clsTarget, 1.5*clsTarget);
991 expoFit.
Draw(
"SAME");
1001 oocoutI(
nullptr,
Eval) <<
"HypoTestInverter::RunLimit - Result: \n"
1002 <<
"\tLimit: " <<
r->GetName() <<
" < " << limit <<
" +/- " << limitErr <<
" @ " << (1-
fSize) * 100 <<
"% CL\n";
1027 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter::GetLowerLimitDistribution(false) - result not existing\n";
1033 TList * clsDist = 0;
1034 TList * clsbDist = 0;
1054 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter::GetUpperLimitDistribution(false) - result not existing\n";
1060 TList * clsDist = 0;
1061 TList * clsbDist = 0;
1089 if (!bModel || ! sbModel)
return 0;
1096 oocoutW(
nullptr,
InputArguments) <<
"HypoTestInverter::RebuildDistribution - background snapshot not existing"
1097 <<
" assume is for POI = 0" << std::endl;
1102 paramPoint.
assign(*poibkg);
1106 if (!toymcSampler) {
1107 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter::RebuildDistribution - no toy MC sampler existing" << std::endl;
1125 bool storePValues = clsDist || clsbDist || clbDist;
1126 if (
fNBins <=0 && storePValues) {
1127 oocoutW(
nullptr,
InputArguments) <<
"HypoTestInverter::RebuildDistribution - cannot return p values distribution with the auto scan" << std::endl;
1128 storePValues =
false;
1135 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter - result is not existing and number of point to scan is not set"
1141 if (nToys <= 0) nToys = 100;
1143 std::vector<std::vector<double> > CLs_values(nPoints);
1144 std::vector<std::vector<double> > CLsb_values(nPoints);
1145 std::vector<std::vector<double> > CLb_values(nPoints);
1148 for (
int i = 0; i < nPoints; ++i) {
1149 CLs_values[i].reserve(nToys);
1150 CLb_values[i].reserve(nToys);
1151 CLsb_values[i].reserve(nToys);
1155 std::vector<double> limit_values; limit_values.reserve(nToys);
1157 oocoutI(
nullptr,
InputArguments) <<
"HypoTestInverter - rebuilding the p value distributions by generating ntoys = "
1158 << nToys << std::endl;
1168 assert(bModel->
GetPdf() );
1174 std::unique_ptr<TFile> fileOut{
TFile::Open(outputfile,
"RECREATE")};
1176 oocoutE(
nullptr,
InputArguments) <<
"HypoTestInverter - RebuildDistributions - Error opening file " << outputfile
1177 <<
" - the resulting limits will not be stored" << std::endl;
1180 TH1D * hL =
new TH1D(
"lowerLimitDist",
"Rebuilt lower limit distribution",100,1.,0.);
1181 TH1D * hU =
new TH1D(
"upperLimitDist",
"Rebuilt upper limit distribution",100,1.,0.);
1182 TH1D * hN =
new TH1D(
"nObs",
"Observed events",100,1.,0.);
1185 std::vector<TH1*> hCLb;
1186 std::vector<TH1*> hCLsb;
1187 std::vector<TH1*> hCLs;
1189 for (
int i = 0; i < nPoints; ++i) {
1190 hCLb.push_back(
new TH1D(
TString::Format(
"CLbDist_bin%d",i),
"CLb distribution",100,1.,0.));
1191 hCLs.push_back(
new TH1D(
TString::Format(
"ClsDist_bin%d",i),
"CLs distribution",100,1.,0.));
1192 hCLsb.push_back(
new TH1D(
TString::Format(
"CLsbDist_bin%d",i),
"CLs+b distribution",100,1.,0.));
1198 for (
int itoy = 0; itoy < nToys; ++itoy) {
1200 oocoutP(
nullptr,
Eval) <<
"\nHypoTestInverter - RebuildDistributions - running toy # " << itoy <<
" / "
1201 << nToys << std::endl;
1204 printf(
"\n\nshnapshot of s+b model \n");
1209 allParams->
assign(saveParams);
1226 for (
int i = 0; i < genObs.
getSize(); ++i) {
1228 if (
x) nObs +=
x->getVal();
1243 if (
r == 0)
continue;
1245 double value = (isUpper) ?
r->UpperLimit() :
r->LowerLimit();
1246 limit_values.push_back(
value );
1247 hU->
Fill(
r->UpperLimit() );
1248 hL->
Fill(
r->LowerLimit() );
1251 std::cout <<
"The computed upper limit for toy #" << itoy <<
" is " <<
value << std::endl;
1254 if (itoy%10 == 0 || itoy == nToys-1) {
1260 if (!storePValues)
continue;
1265 else if (nPoints >
r->ArraySize()) {
1270 for (
int ipoint = 0; ipoint < nPoints; ++ipoint) {
1273 CLs_values[ipoint].push_back( hr->
CLs() );
1274 CLsb_values[ipoint].push_back( hr->
CLsplusb() );
1275 CLb_values[ipoint].push_back( hr->
CLb() );
1276 hCLs[ipoint]->Fill( hr->
CLs() );
1277 hCLb[ipoint]->Fill( hr->
CLb() );
1278 hCLsb[ipoint]->Fill( hr->
CLsplusb() );
1286 if (itoy%10 == 0 || itoy == nToys-1) {
1287 for (
int ipoint = 0; ipoint < nPoints; ++ipoint) {
1301 if (clsDist) clsDist->
SetOwner(
true);
1302 if (clbDist) clbDist->
SetOwner(
true);
1303 if (clsbDist) clsbDist->
SetOwner(
true);
1307 for (
int ipoint = 0; ipoint < nPoints; ++ipoint) {
1327 for (
int i = 0; i < nPoints && storePValues; ++i) {
1334 const char * disName = (isUpper) ?
"upperLimit_dist" :
"lowerLimit_dist";
size_t size(const MatrixT &matrix)
retrieve the size of a square matrix
winID h TVirtualViewer3D TVirtualGLPainter char TVirtualGLPainter plot
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void data
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t r
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t Int_t Int_t UInt_t UInt_t Rectangle_t result
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void value
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t Int_t Int_t UInt_t UInt_t Rectangle_t Int_t Int_t Window_t TString Int_t GCValues_t GetPrimarySelectionOwner GetDisplay GetScreen GetColormap GetNativeEvent const char const char dpyName wid window const char font_name cursor keysym reg const char only_if_exist regb h Point_t winding char text const char depth char const char Int_t count const char ColorStruct_t color const char Pixmap_t Pixmap_t PictureAttributes_t attr const char char ret_data h unsigned char height h Atom_t Int_t ULong_t ULong_t unsigned char prop_list Atom_t Atom_t Atom_t Time_t type
RooArgSet * getVariables(bool stripDisconnected=true) const
Return RooArgSet with all variables (tree leaf nodes of expresssion tree)
RooArgSet * getParameters(const RooAbsData *data, bool stripDisconnected=true) const
Create a list of leaf nodes in the arg tree starting with ourself as top node that don't match any of...
Int_t getSize() const
Return the number of elements in the collection.
virtual bool add(const RooAbsArg &var, bool silent=false)
Add the specified argument to list.
void assign(const RooAbsCollection &other) const
Sets the value, cache and constant attribute of any argument in our set that also appears in the othe...
RooAbsArg * first() const
bool selectCommon(const RooAbsCollection &refColl, RooAbsCollection &outColl) const
Create a subset of the current collection, consisting only of those elements that are contained as we...
RooAbsArg * find(const char *name) const
Find object with given name in list.
void Print(Option_t *options=nullptr) const override
This method must be overridden when a class wants to print itself.
RooAbsData is the common abstract base class for binned and unbinned datasets.
virtual double sumEntries() const =0
Return effective number of entries in dataset, i.e., sum all weights.
virtual const RooArgSet * get() const
virtual Int_t numEntries() const
Return number of entries in dataset, i.e., count unweighted entries.
bool canBeExtended() const
If true, PDF can provide extended likelihood term.
virtual double getMax(const char *name=nullptr) const
Get maximum of currently defined range.
virtual double getMin(const char *name=nullptr) const
Get minimum of currently defined range.
double getVal(const RooArgSet *normalisationSet=nullptr) const
Evaluate object.
RooArgList is a container object that can hold multiple RooAbsArg objects.
RooArgSet is a container object that can hold multiple RooAbsArg objects.
RooArgSet * snapshot(bool deepCopy=true) const
Use RooAbsCollection::snapshot(), but return as RooArgSet.
static double uniform(TRandom *generator=randomGenerator())
Return a number uniformly distributed from (0,1)
RooRealVar represents a variable that can be changed from the outside.
void setVal(double value) override
Set value of variable to 'value'.
Hypothesis Test Calculator based on the asymptotic formulae for the profile likelihood ratio.
Does a frequentist hypothesis test.
Same purpose as HybridCalculatorOriginal, but different implementation.
Common base class for the Hypothesis Test Calculators.
const ModelConfig * GetNullModel(void) const
void SetData(RooAbsData &data) override
Set the DataSet.
HypoTestResult * GetHypoTest() const override
inherited methods from HypoTestCalculator interface
const ModelConfig * GetAlternateModel(void) const
TestStatSampler * GetTestStatSampler(void) const
Returns instance of TestStatSampler.
Class to plot a HypoTestInverterResult, the output of the HypoTestInverter calculator.
HypoTestInverterResult class holds the array of hypothesis test results and compute a confidence inte...
SamplingDistribution * GetLowerLimitDistribution() const
get expected lower limit distributions implemented using interpolation The size for the sampling dist...
HypoTestResult * GetResult(int index) const
return a pointer to the i^th result object
int ArraySize() const
number of entries in the results array
std::vector< double > fXValues
void UseCLs(bool on=true)
flag to switch between using CLsb (default) or CLs as confidence level
double GetXValue(int index) const
function to return the value of the parameter of interest for the i^th entry in the results
double GetLastYError() const
TList fExpPValues
list of expected sampling distribution for each point
bool fIsTwoSided
two sided scan (look for lower/upper limit)
double GetLastYValue() const
TList fYObjects
list of HypoTestResult for each point
void SetConfidenceLevel(double cl) override
set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval)
SamplingDistribution * GetUpperLimitDistribution() const
get expected upper limit distributions implemented using interpolation
A class for performing a hypothesis test inversion by scanning the hypothesis test results of a HypoT...
static void CheckInputModels(const HypoTestCalculatorGeneric &hc, const RooRealVar &scanVar)
check the model given the given hypotestcalculator
RooRealVar * fScannedVariable
pointer to the constrained variable
static double fgCLAccuracy
std::unique_ptr< HypoTestCalculatorGeneric > fHC
! pointer to the generic hypotest calculator used
bool RunLimit(double &limit, double &limitErr, double absTol=0, double relTol=0, const double *hint=nullptr) const
Run an automatic scan until the desired accuracy is reached.
void SetData(RooAbsData &) override
Set the DataSet ( add to the workspace if not already there ?)
HypoTestInverterResult * fResults
pointer to the result
SamplingDistribution * RebuildDistributions(bool isUpper=true, int nToys=100, TList *clsDist=nullptr, TList *clsbDist=nullptr, TList *clbDist=nullptr, const char *outputfile="HypoTestInverterRebuiltDist.root")
function to rebuild the distributions
int fMaxToys
maximum number of toys to run
HypoTestInverter()
default constructor (used only for I/O)
~HypoTestInverter() override
destructor
double ConfidenceLevel() const override
Get the Confidence level for the test.
bool SetTestStatistic(TestStatistic &stat)
set the test statistic
HypoTestInverterResult * GetInterval() const override
Run a fixed scan or the automatic scan depending on the configuration.
SamplingDistribution * GetUpperLimitDistribution(bool rebuild=false, int nToys=100)
get the distribution of lower limit if rebuild = false (default) it will re-use the results of the sc...
static unsigned int fgNToys
void Clear()
delete contained result and graph
TestStatistic * GetTestStatistic() const
get the test statistic
static std::string fgAlgo
std::unique_ptr< TGraphErrors > fLimitPlot
! plot of limits
bool RunFixedScan(int nBins, double xMin, double xMax, bool scanLog=false) const
Run a fixed scan.
bool RunOnePoint(double thisX, bool adaptive=false, double clTarget=-1) const
run only one point at the given POI value
ECalculatorType fCalcType
SamplingDistribution * GetLowerLimitDistribution(bool rebuild=false, int nToys=100)
get the upper/lower limit distribution
HypoTestInverter & operator=(const HypoTestInverter &rhs)
assignment
HypoTestCalculatorGeneric * fCalculator0
pointer to the calculator passed in the constructor
static double fgRelAccuracy
void CreateResults() const
create a new HypoTestInverterResult to hold all computed results
static double fgAbsAccuracy
static RooRealVar * GetVariableToScan(const HypoTestCalculatorGeneric &hc)
helper functions
HypoTestResult * Eval(HypoTestCalculatorGeneric &hc, bool adaptive, double clsTarget) const
run the hybrid at a single point
HypoTestResult is a base class for results from hypothesis tests.
virtual double CLsplusb() const
Convert AlternatePValue into a "confidence level".
double GetTestStatisticData(void) const
virtual void Append(const HypoTestResult *other)
add values from another HypoTestResult
double CLsError() const
The error on the ratio .
void SetBackgroundAsAlt(bool l=true)
bool GetPValueIsRightTail(void) const
double CLbError() const
The error on the "confidence level" of the null hypothesis.
void SetTestStatisticData(const double tsd)
double CLsplusbError() const
The error on the "confidence level" of the alternative hypothesis.
SamplingDistribution * GetNullDistribution(void) const
virtual double CLs() const
is simply (not a method, but a quantity)
virtual double CLb() const
Convert NullPValue into a "confidence level".
SamplingDistribution * GetAltDistribution(void) const
IntervalCalculator is an interface class for a tools which produce RooStats ConfIntervals.
ModelConfig is a simple class that holds configuration information specifying how a model should be u...
const RooArgSet * GetGlobalObservables() const
get RooArgSet for global observables (return nullptr if not existing)
const RooArgSet * GetParametersOfInterest() const
get RooArgSet containing the parameter of interest (return nullptr if not existing)
const RooArgSet * GetNuisanceParameters() const
get RooArgSet containing the nuisance parameters (return nullptr if not existing)
const RooArgSet * GetObservables() const
get RooArgSet for observables (return nullptr if not existing)
const RooArgSet * GetSnapshot() const
get RooArgSet for parameters for a particular hypothesis (return nullptr if not existing)
RooAbsPdf * GetPdf() const
get model PDF (return nullptr if pdf has not been specified or does not exist)
ProfileLikelihoodTestStat is an implementation of the TestStatistic interface that calculates the pro...
static void CloseProof(Option_t *option="s")
close all proof connections
This class simply holds a sampling distribution of some test statistic.
Int_t GetSize() const
size of samples
double fUpperLimit
upper interval limit
double fLowerLimit
lower interval limit
TestStatSampler is an interface class for a tools which produce RooStats SamplingDistributions.
virtual TestStatistic * GetTestStatistic() const =0
Get the TestStatistic.
virtual void SetTestStatistic(TestStatistic *testStatistic)=0
Set the TestStatistic (want the argument to be a function of the data & parameter points.
TestStatistic is an interface class to provide a facility for construction test statistics distributi...
ToyMCSampler is an implementation of the TestStatSampler interface.
void SetParametersForTestStat(const RooArgSet &nullpoi) override
Set the Pdf, add to the workspace if not already there.
void SetObservables(const RooArgSet &o) override
specify the observables in the dataset (needed to evaluate the test statistic)
virtual RooAbsData * GenerateToyData(RooArgSet ¶mPoint, RooAbsPdf &pdf) const
generates toy data without weight
void SetNuisanceParameters(const RooArgSet &np) override
specify the nuisance parameters (eg. the rest of the parameters)
void SetPdf(RooAbsPdf &pdf) override
Set the Pdf, add to the workspace if not already there.
void SetGlobalObservables(const RooArgSet &o) override
specify the conditional observables
virtual void SetNEventsPerToy(const Int_t nevents)
Forces the generation of exactly n events even for extended PDFs.
virtual void SetLineStyle(Style_t lstyle)
Set the line style.
virtual void SetLineWidth(Width_t lwidth)
Set the line width.
virtual void SetLineColor(Color_t lcolor)
Set the line color.
virtual void SetOwner(Bool_t enable=kTRUE)
Set whether this collection is the owner (enable==true) of its content.
virtual Double_t GetParError(Int_t ipar) const
Return value of parameter number ipar.
virtual void SetRange(Double_t xmin, Double_t xmax)
Initialize the upper and lower bounds to draw the function.
void Draw(Option_t *option="") override
Draw this function with its current attributes.
virtual void GetRange(Double_t *xmin, Double_t *xmax) const
Return range of a generic N-D function.
virtual void SetParameter(Int_t param, Double_t value)
virtual void FixParameter(Int_t ipar, Double_t value)
Fix the value of a parameter for a fit operation The specified value will be used in the fit and the ...
virtual Double_t GetParameter(Int_t ipar) const
static TFile * Open(const char *name, Option_t *option="", const char *ftitle="", Int_t compress=ROOT::RCompressionSetting::EDefaults::kUseCompiledDefault, Int_t netopt=0)
Create / open a file.
1-D histogram with a double per channel (see TH1 documentation)}
virtual Int_t Fill(Double_t x)
Increment bin with abscissa X by 1.
virtual void SetBuffer(Int_t buffersize, Option_t *option="")
Set the maximum number of entries to be kept in the buffer.
Use the TLine constructor to create a simple line.
virtual TLine * DrawLine(Double_t x1, Double_t y1, Double_t x2, Double_t y2)
Draw this line with new coordinates.
void Add(TObject *obj) override
TObject * Remove(TObject *obj) override
Remove object from the list.
TObject * Clone(const char *newname="") const override
Make a clone of an object using the Streamer facility.
virtual void SetTitle(const char *title="")
Set the title of the TNamed.
const char * GetName() const override
Returns name of object.
virtual void SetName(const char *name)
Set the name of the TNamed.
@ kOverwrite
overwrite existing object with same name
virtual Int_t Write(const char *name=nullptr, Int_t option=0, Int_t bufsize=0)
Write this object to the current directory.
virtual void Draw(Option_t *option="")
Default Draw method for all objects.
static TString Format(const char *fmt,...)
Static method which formats a string using a printf style format descriptor and return a TString.
RVec< PromoteType< T > > abs(const RVec< T > &v)
RVec< PromoteTypes< T0, T1 > > hypot(const T0 &x, const RVec< T1 > &v)
RVec< PromoteType< T > > log(const RVec< T > &v)
RVec< PromoteType< T > > exp(const RVec< T > &v)
Py_ssize_t ArraySize(const std::string &name)
Namespace for the RooStats classes.
void PrintListContent(const RooArgList &l, std::ostream &os=std::cout)
useful function to print in one line the content of a set with their values
Bool_t AreEqualRel(Double_t af, Double_t bf, Double_t relPrec)
Comparing floating points.
Bool_t AreEqualAbs(Double_t af, Double_t bf, Double_t epsilon)
Comparing floating points.
static void SetToys(HypoTestType *h, int toyNull, int toyAlt)