47#ifdef ROOFIT_LEGACY_EVAL_BACKEND
80 <<
"RooAbsPdf::fitTo(" << pdf.
GetName()
81 <<
") WARNING: Asymptotic error correction is requested for a binned data set. "
82 "This method is not designed to handle binned data. A standard chi2 fit will likely be more suitable.";
86 std::unique_ptr<RooFitResult>
rw(minimizer.
save());
90 <<
"RooAbsPdf::fitTo(" << pdf.
GetName()
91 <<
") Calculating covariance matrix according to the asymptotically correct approach. If you find this "
92 "method useful please consider citing https://arxiv.org/abs/1911.01303.\n";
104 std::vector<std::unique_ptr<RooDerivative>>
derivatives;
110 const double eps = 1.0e-4;
124 for (std::size_t k = 0; k <
floated.size(); k++) {
141 for (
int j = 0;
j <
data.numEntries();
j++) {
146 for (std::size_t k = 0; k <
floated.size(); k++) {
157 for (std::size_t k = 0; k <
floated.size(); k++) {
158 for (std::size_t
l = 0;
l <
floated.size();
l++) {
163 num.Similarity(
matV);
171 return rw->covQual();
189 std::unique_ptr<RooFitResult>
rw{minimizer.
save()};
190 nll.applyWeightSquared(
true);
192 <<
") Calculating sum-of-weights-squared correction matrix for covariance matrix\n";
194 std::unique_ptr<RooFitResult>
rw2{minimizer.
save()};
195 nll.applyWeightSquared(
false);
203 <<
") ERROR: Cannot apply sum-of-weights correction to covariance matrix: correction "
204 "matrix calculated with weight-squared is singular\n";
212 for (
int i = 0; i <
matC.GetNrows(); ++i) {
213 for (
int j = 0;
j < i; ++
j) {
222 return std::min(
rw->covQual(),
rw2->covQual());
228 double recoverFromNaN = 10.;
246 bool enableParallelGradient =
true;
247 bool enableParallelDescent =
false;
248 bool timingAnalysis =
false;
251 std::string
minAlg =
"minuit";
261 <<
"p.d.f. provides expected number of events, including extended term in likelihood." << std::endl;
272 std::string
errMsg =
"You used the Extended(false) option on a pdf where the fit MUST be extended! "
273 "The parameters are not well defined and you're getting nonsensical results.";
309 if (arg->isCategory())
311 auto &observable =
static_cast<RooRealVar &
>(*arg);
314 observable.getMax(
subrange.c_str()));
333 if (!rangeName.empty()) {
344 std::unique_ptr<RooArgSet> observables{
350 auto nll = std::make_unique<RooFit::Detail::RooNLLVarNew>(
name.c_str(),
name.c_str(), *pdf, *observables,
353 nll->setPrefix(std::string(
"_") +
catName +
"_");
363 auto nll = std::make_unique<RooAddition>(
"mynll",
"mynll",
nllTerms);
369 std::string
const &rangeName,
RooArgSet const &projDeps,
bool isExtended,
380 observables.
remove(projDeps,
true,
true);
383 <<
") fixing normalization set for coefficient determination to observables in data"
400 simPdf->wrapPdfsInBinSamplingPdfs(
data, integrateOverBinsPrecision);
403 nllTerms.addOwned(std::make_unique<RooFit::Detail::RooNLLVarNew>(
"RooNLLVarNew",
"RooNLLVarNew",
finalPdf,
404 observables, isExtended,
offset));
407 nllTerms.addOwned(std::move(constraints));
445 pc.
defineInt(
"doOffset",
"OffsetLikelihood", 0, 0);
446 pc.
defineInt(
"parallelize",
"Parallelize", 0, 0);
447 pc.
defineInt(
"enableParallelGradient",
"ParallelGradientOptions", 0, 0);
448 pc.
defineInt(
"enableParallelDescent",
"ParallelDescentOptions", 0, 0);
449 pc.
defineInt(
"timingAnalysis",
"TimingAnalysis", 0, 0);
469 cfg.recoverFromNaN = pc.
getDouble(
"RecoverFromUndefinedRegions");
470 cfg.optConst = pc.
getInt(
"optConst");
471 cfg.verbose = pc.
getInt(
"verbose");
472 cfg.doSave = pc.
getInt(
"doSave");
473 cfg.doTimer = pc.
getInt(
"doTimer");
474 cfg.printLevel = pc.
getInt(
"printLevel");
475 cfg.strategy = pc.
getInt(
"strategy");
476 cfg.initHesse = pc.
getInt(
"initHesse");
477 cfg.hesse = pc.
getInt(
"hesse");
478 cfg.minos = pc.
getInt(
"minos");
479 cfg.numee = pc.
getInt(
"numee");
480 cfg.doEEWall = pc.
getInt(
"doEEWall");
481 cfg.doWarn = pc.
getInt(
"doWarn");
482 cfg.doSumW2 = pc.
getInt(
"doSumW2");
483 cfg.doAsymptotic = pc.
getInt(
"doAsymptoticError");
484 cfg.maxCalls = pc.
getInt(
"maxCalls");
485 cfg.minosSet = pc.
getSet(
"minosSet");
486 cfg.minType = pc.
getString(
"mintype",
"");
487 cfg.minAlg = pc.
getString(
"minalg",
"minuit");
488 cfg.doOffset = pc.
getInt(
"doOffset");
489 cfg.parallelize = pc.
getInt(
"parallelize");
490 cfg.enableParallelGradient = pc.
getInt(
"enableParallelGradient");
491 cfg.enableParallelDescent = pc.
getInt(
"enableParallelDescent");
492 cfg.timingAnalysis = pc.
getInt(
"timingAnalysis");
497 std::string
msgPrefix = std::string{
"RooAbsPdf::fitTo("} + pdf.
GetName() +
"): ";
500 if (
weightedData && cfg.doSumW2 == -1 && cfg.doAsymptotic == -1) {
502 R
"(WARNING: a likelihood fit is requested of what appears to be weighted data.
503 While the estimated values of the parameters will always be calculated taking the weights into account,
504 there are multiple ways to estimate the errors of the parameters. You are advised to make an
505 explicit choice for the error calculation:
506 - Either provide SumW2Error(true), to calculate a sum-of-weights-corrected HESSE error matrix
507 (error will be proportional to the number of events in MC).
508 - Or provide SumW2Error(false), to return errors from original HESSE error matrix
509 (which will be proportional to the sum of the weights, i.e., a dataset with <sum of weights> events).
510 - Or provide AsymptoticError(true), to use the asymptotically correct expression
511 (for details see https://arxiv.org/abs/1911.01303)."
515 if (cfg.minos && (cfg.doSumW2 == 1 || cfg.doAsymptotic == 1)) {
518 <<
" sum-of-weights and asymptotic error correction do not work with MINOS errors. Not fitting.\n";
521 if (cfg.doAsymptotic == 1 && cfg.minos) {
522 oocoutW(&pdf, InputArguments) <<
msgPrefix <<
"WARNING: asymptotic correction does not apply to MINOS errors\n";
526 if (cfg.doSumW2 == 1 && cfg.doAsymptotic == 1) {
528 <<
"ERROR: Cannot compute both asymptotically correct and SumW2 errors.\n";
541 m.setMinimizerType(cfg.minType);
542 m.setEvalErrorWall(cfg.doEEWall);
543 m.setRecoverFromNaNStrength(cfg.recoverFromNaN);
544 m.setPrintEvalErrors(cfg.numee);
545 if (cfg.maxCalls > 0)
546 m.setMaxFunctionCalls(cfg.maxCalls);
547 if (cfg.printLevel != 1)
548 m.setPrintLevel(cfg.printLevel);
550 m.optimizeConst(cfg.optConst);
555 if (cfg.strategy != 1)
556 m.setStrategy(cfg.strategy);
559 m.minimize(cfg.minType.c_str(), cfg.minAlg.c_str());
565 if (
m.getNPar() > 0) {
566 if (cfg.doAsymptotic == 1)
568 if (cfg.doSumW2 == 1)
573 cfg.minosSet ?
m.minos(*cfg.minosSet) :
m.minos();
576 std::unique_ptr<RooFitResult>
ret;
578 auto name = std::string(
"fitresult_") + pdf.
GetName() +
"_" +
data.GetName();
579 auto title = std::string(
"Result of fit of p.d.f. ") + pdf.
GetName() +
" to dataset " +
data.GetName();
580 ret = std::unique_ptr<RooFitResult>{
m.save(
name.c_str(), title.c_str())};
581 if ((cfg.doSumW2 == 1 || cfg.doAsymptotic == 1) &&
m.getNPar() > 0)
597 pc.
defineString(
"rangeName",
"RangeWithName", 0,
"",
true);
599 pc.
defineString(
"globstag",
"GlobalObservablesTag", 0,
"");
600 pc.
defineString(
"globssource",
"GlobalObservablesSource", 0,
"data");
603 pc.
defineInt(
"splitRange",
"SplitRange", 0, 0);
606 pc.
defineInt(
"interleave",
"NumCPU", 1, 0);
607 pc.
defineInt(
"verbose",
"Verbose", 0, 0);
608 pc.
defineInt(
"optConst",
"Optimize", 0, 0);
609 pc.
defineInt(
"cloneData",
"CloneData", 0, 2);
610 pc.
defineSet(
"projDepSet",
"ProjectedObservables", 0,
nullptr);
611 pc.
defineSet(
"cPars",
"Constrain", 0,
nullptr);
612 pc.
defineSet(
"glObs",
"GlobalObservables", 0,
nullptr);
613 pc.
defineInt(
"doOffset",
"OffsetLikelihood", 0, 0);
614 pc.
defineSet(
"extCons",
"ExternalConstraints", 0,
nullptr);
616 pc.
defineDouble(
"IntegrateBins",
"IntegrateBins", 0, -1.);
618 pc.
defineMutex(
"GlobalObservables",
"GlobalObservablesTag");
619 pc.
defineInt(
"ModularL",
"ModularL", 0, 0);
634 if (pc.
getInt(
"ModularL")) {
635 int lut[3] = {2, 1, 0};
643 if (
auto tmp = pc.
getSet(
"cPars"))
646 if (
auto tmp = pc.
getSet(
"extCons"))
649 if (
auto tmp = pc.
getSet(
"glObs"))
652 const std::string rangeName = pc.
getString(
"globstag",
"",
false);
655 builder.Extended(
ext)
659 .GlobalObservablesTag(rangeName.c_str());
661 return std::make_unique<RooFit::TestStatistics::RooRealL>(
"likelihood",
"", builder.build());
665 const char *rangeName = pc.
getString(
"rangeName",
nullptr,
true);
666 const char *addCoefRangeName = pc.
getString(
"addCoefRange",
nullptr,
true);
680 double rangeLo = pc.
getDouble(
"rangeLo");
681 double rangeHi = pc.
getDouble(
"rangeHi");
686 for (
auto arg : obs) {
689 rrv->setRange(
"fit", rangeLo, rangeHi);
707 std::string
errMsg =
"RooAbsPdf::fitTo: GlobalObservablesSource can only be \"data\" or \"model\"!";
709 throw std::invalid_argument(
errMsg);
716 auto createConstr = [&]() -> std::unique_ptr<RooAbsReal> {
724 takeGlobalObservablesFromData);
742 normSet.remove(projDeps,
true,
true);
748 ctx.setLikelihoodMode(
true);
750 std::unique_ptr<RooAbsPdf>
pdfClone = std::unique_ptr<RooAbsPdf>{
static_cast<RooAbsPdf *
>(head.release())};
759 if (addCoefRangeName) {
761 <<
") fixing interpretation of coefficients of any component to range "
762 << addCoefRangeName <<
"\n";
763 pdfClone->fixAddCoefRange(addCoefRangeName,
false);
773 pc.getDouble(
"IntegrateBins"),
offset);
781 nllWrapper = std::make_unique<RooFit::Experimental::RooFuncWrapper>(
"nll_func_wrapper",
"nll_func_wrapper",
784 static_cast<Experimental::RooFuncWrapper &
>(*nllWrapper).createGradient();
786 nllWrapper = std::make_unique<RooEvaluatorWrapper>(
788 takeGlobalObservablesFromData);
791 nllWrapper->addOwnedComponents(std::move(nll));
796 std::unique_ptr<RooAbsReal>
nll;
798#ifdef ROOFIT_LEGACY_EVAL_BACKEND
805 oocoutW(&pdf, Minimization) <<
"Cannot use a NumCpu Strategy = 3 when the pdf is not a RooSimultaneous, "
806 "falling back to default strategy = 0"
827 cfg.
rangeName = rangeName ? rangeName :
"";
828 auto nllVar = std::make_unique<RooNLLVar>(
baseName.c_str(),
"-log(likelihood)",
actualPdf,
data, projDeps,
ext, cfg);
830 nll = std::move(nllVar);
834 if (std::unique_ptr<RooAbsReal> constraintTerm =
createConstr()) {
846 constraintTerm->setData(
data,
false);
853 nll = std::make_unique<RooAddition>((
baseName +
"_with_constr").c_str(),
"nllWithCons",
855 nll->addOwnedComponents(std::move(
orignll), std::move(constraintTerm));
863 nll->enableOffsetting(
true);
866 throw std::runtime_error(
"RooFit was not built with the legacy evaluation backend");
874#ifdef ROOFIT_LEGACY_EVAL_BACKEND
880 pc.
defineInt(
"verbose",
"Verbose", 0, 0);
887 std::string
baseName =
"chi2_" + std::string(
real.GetName()) +
"_" +
data.GetName();
890 real.removeStringAttribute(
"fitrange");
894 pc.
defineInt(
"split_range",
"SplitRange", 0, 0);
895 pc.
defineDouble(
"integrate_bins",
"IntegrateBins", 0, -1);
911 const char *rangeName = pc.
getString(
"rangeName",
nullptr,
true);
912 const char *addCoefRangeName = pc.
getString(
"addCoefRange",
nullptr,
true);
914 cfg.
rangeName = rangeName ? rangeName :
"";
929 pc.
defineInt(
"integrate",
"Integrate", 0, 0);
931 pc.
defineString(
"rangeName",
"RangeWithName", 0,
"",
true);
932 pc.
defineInt(
"interleave",
"NumCPU", 1, 0);
941 bool integrate = pc.
getInt(
"integrate");
943 const char *rangeName = pc.
getString(
"rangeName",
nullptr,
true);
948 oocoutW(&
real, Minimization) <<
"Cannot use a NumCpu Strategy = 3 when the pdf is not a RooSimultaneous, "
949 "falling back to default strategy = 0"
956 cfg.
rangeName = rangeName ? rangeName :
"";
962 std::string
name =
"chi2_" + std::string(
real.GetName()) +
"_" +
data.GetName();
968 throw std::runtime_error(
"createChi2() is not supported without the legacy evaluation backend");
983 "RangeWithName,SumCoefRange,NumCPU,SplitRange,Constrained,Constrain,ExternalConstraints,"
984 "CloneData,GlobalObservables,GlobalObservablesSource,GlobalObservablesTag,"
985 "EvalBackend,IntegrateBins,ModularL";
992 "AddCoefRange,SplitRange,DataError,Extended";
1009 if (pc.
getInt(
"timingAnalysis") && !
real.InheritsFrom(
"RooSimultaneous")) {
1010 oocoutW(&
real, Minimization) <<
"The timingAnalysis feature was built for minimization with RooSimultaneous "
1011 "and is not implemented for other PDF's. Please create a RooSimultaneous to "
1012 "enable this feature."
1020 size_t nEvents =
static_cast<size_t>(
prefit *
data.numEntries());
1021 if (
prefit > 0.5 || nEvents < 100) {
1022 oocoutW(&
real, InputArguments) <<
"PrefitDataFraction should be in suitable range."
1023 <<
"With the current PrefitDataFraction=" <<
prefit
1024 <<
", the number of events would be " << nEvents <<
" out of "
1025 <<
data.numEntries() <<
". Skipping prefit..." << std::endl;
1027 size_t step =
data.numEntries() / nEvents;
1031 for (
int i = 0; i <
data.numEntries(); i += step) {
1048 if (pc.
getInt(
"parallelize") != 0 || pc.
getInt(
"enableParallelGradient") || pc.
getInt(
"enableParallelDescent")) {
1054 std::unique_ptr<RooAbsReal>
nll;
1062 return RooFit::FitHelpers::minimize(
real, *nll,
data, pc);
header file containing the templated implementation of matrix inversion routines for use with ROOT's ...
std::unique_ptr< RooAbsReal > createConstraintTerm(std::string const &name, RooAbsPdf const &pdf, RooAbsData const &data, RooArgSet const *constrainedParameters, RooArgSet const *externalConstraints, RooArgSet const *globalObservables, const char *globalObservablesTag, bool takeGlobalObservablesFromData)
Create the parameter constraint sum to add to the negative log-likelihood.
ROOT::RRangeCast< T, false, Range_t > static_range_cast(Range_t &&coll)
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
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 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 offset
class to compute the Cholesky decomposition of a matrix
Common abstract base class for objects that represent a value and a "shape" in RooFit.
void setStringAttribute(const Text_t *key, const Text_t *value)
Associate string 'value' to this object under key 'key'.
RooFit::OwningPtr< RooArgSet > getObservables(const RooArgSet &set, bool valueOnly=true) const
Given a set of possible observables, return the observables that this PDF depends on.
void removeStringAttribute(const Text_t *key)
Delete a string attribute with a given key.
RooFit::OwningPtr< RooArgSet > getVariables(bool stripDisconnected=true) const
Return RooArgSet with all variables (tree leaf nodes of expression tree)
void setAttribute(const Text_t *name, bool value=true)
Set (default) or clear a named boolean attribute of this object.
Abstract base class for objects that represent a discrete value that can be set from the outside,...
virtual bool remove(const RooAbsArg &var, bool silent=false, bool matchByNameOnly=false)
Remove the specified argument from our list.
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...
Abstract base class for binned and unbinned datasets.
Abstract interface for all probability density functions.
std::unique_ptr< RooAbsArg > compileForNormSet(RooArgSet const &normSet, RooFit::Detail::CompileContext &ctx) const override
void setNormRange(const char *rangeName)
const char * normRange() const
virtual ExtendMode extendMode() const
Returns ability of PDF to provide extended likelihood terms.
Abstract base class for objects that represent a real value and implements functionality common to al...
virtual void fixAddCoefNormalization(const RooArgSet &addNormSet=RooArgSet(), bool force=true)
Fix the interpretation of the coefficient of any RooAddPdf component in the expression tree headed by...
static void setEvalErrorLoggingMode(ErrorLoggingMode m)
Set evaluation error logging mode.
RooArgList is a container object that can hold multiple RooAbsArg objects.
RooArgSet is a container object that can hold multiple RooAbsArg objects.
RooArgSet * selectByAttrib(const char *name, bool value) const
Use RooAbsCollection::selectByAttrib(), but return as RooArgSet.
static std::unique_ptr< RooAbsPdf > create(RooAbsPdf &pdf, RooAbsData const &data, double precision)
Creates a wrapping RooBinSamplingPdf if appropriate.
Object to represent discrete states.
Named container for two doubles, two integers two object points and three string pointers that can be...
Int_t getInt(Int_t idx) const
Configurable parser for RooCmdArg named arguments.
void defineMutex(const char *head, Args_t &&... tail)
Define arguments where any pair is mutually exclusive.
bool process(const RooCmdArg &arg)
Process given RooCmdArg.
bool hasProcessed(const char *cmdName) const
Return true if RooCmdArg with name 'cmdName' has been processed.
double getDouble(const char *name, double defaultValue=0.0) const
Return double property registered with name 'name'.
bool defineDouble(const char *name, const char *argName, int doubleNum, double defValue=0.0)
Define double property name 'name' mapped to double in slot 'doubleNum' in RooCmdArg with name argNam...
RooArgSet * getSet(const char *name, RooArgSet *set=nullptr) const
Return RooArgSet property registered with name 'name'.
bool defineSet(const char *name, const char *argName, int setNum, const RooArgSet *set=nullptr)
Define TObject property name 'name' mapped to object in slot 'setNum' in RooCmdArg with name argName ...
bool ok(bool verbose) const
Return true of parsing was successful.
bool defineObject(const char *name, const char *argName, int setNum, const TObject *obj=nullptr, bool isArray=false)
Define TObject property name 'name' mapped to object in slot 'setNum' in RooCmdArg with name argName ...
const char * getString(const char *name, const char *defaultValue="", bool convEmptyToNull=false) const
Return string property registered with name 'name'.
bool defineString(const char *name, const char *argName, int stringNum, const char *defValue="", bool appendMode=false)
Define double property name 'name' mapped to double in slot 'stringNum' in RooCmdArg with name argNam...
bool defineInt(const char *name, const char *argName, int intNum, int defValue=0)
Define integer property name 'name' mapped to integer in slot 'intNum' in RooCmdArg with name argName...
void allowUndefined(bool flag=true)
If flag is true the processing of unrecognized RooCmdArgs is not considered an error.
int getInt(const char *name, int defaultValue=0) const
Return integer property registered with name 'name'.
RooLinkedList filterCmdList(RooLinkedList &cmdInList, const char *cmdNameList, bool removeFromInList=true) const
Utility function to filter commands listed in cmdNameList from cmdInList.
TObject * getObject(const char *name, TObject *obj=nullptr) const
Return TObject property registered with name 'name'.
Container class to hold N-dimensional binned data.
Container class to hold unbinned data.
static Value & defaultValue()
Collection class for internal use, storing a collection of RooAbsArg pointers in a doubly linked list...
Wrapper class around ROOT::Math::Minimizer that provides a seamless interface between the minimizer f...
RooFit::OwningPtr< RooFitResult > save(const char *name=nullptr, const char *title=nullptr)
Save and return a RooFitResult snapshot of current minimizer status.
int hesse()
Execute HESSE.
void applyCovarianceMatrix(TMatrixDSym const &V)
Apply results of given external covariance matrix.
Variable that can be changed from the outside.
void setRange(const char *name, double min, double max)
Set a fit or plotting range.
Facilitates simultaneous fitting of multiple PDFs to subsets of a given dataset.
const char * GetName() const override
Returns name of object.
virtual Bool_t InheritsFrom(const char *classname) const
Returns kTRUE if object inherits from class "classname".
RooCmdArg WeightVar(const char *name="weight", bool reinterpretAsWeight=false)
RooCmdArg Hesse(bool flag=true)
RooCmdArg ModularL(bool flag=false)
RooCmdArg PrintLevel(Int_t code)
std::vector< std::string > Split(std::string_view str, std::string_view delims, bool skipEmpty=false)
Splits a string at each character in delims.
double nll(double pdf, double weight, int binnedL, int doBinOffset)
std::unique_ptr< T > compileForNormSet(T const &arg, RooArgSet const &normSet)
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
OffsetMode
For setting the offset mode with the Offset() command argument to RooAbsPdf::fitTo()
std::unique_ptr< T > cloneTreeWithSameParameters(T const &arg, RooArgSet const *observables=nullptr)
Clone RooAbsArg object and reattach to original parameters.
BinnedLOutput getBinnedL(RooAbsPdf const &pdf)
std::string rangeName
Stores the configuration parameters for RooAbsTestStatistic.
std::string addCoefRangeName
bool takeGlobalObservablesFromData
double integrateOverBinsPrecision
RooFit::MPSplit interleave
Config argument to RooMinimizer constructor.