|
| | rf101_basics.C |
| |   Basic functionality: fitting, plotting, toy data generation on one-dimensional PDFs.
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| |
| | rf101_basics.py |
| | This tutorial illustrates the basic features of RooFit.
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| |
| | rf102_dataimport.C |
| | Basic functionality: importing data from ROOT TTrees and THx histograms.
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| |
| | rf103_interprfuncs.C |
| | Basic functionality: interpreted functions and PDFs.
|
| |
| | rf103_interprfuncs.py |
| | Basic functionality: interpreted functions and pdfs
|
| |
| | rf104_classfactory.C |
| | Basic functionality: The class factory for functions and pdfs
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| |
| | rf104_classfactory.py |
| | Basic functionality: the class factory for functions and pdfs
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| |
| | rf105_funcbinding.C |
| | Basic functionality: binding ROOT math functions as RooFit functions and pdfs
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| |
| | rf106_plotdecoration.C |
| | Basic functionality: adding boxes with parameters, statistics to RooPlots, decorating with arrows, text etc...
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| |
| | rf106_plotdecoration.py |
| | Basic functionality: adding boxes with parameters to RooPlots and decorating with arrows, etc...
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| |
| | rf107_plotstyles.C |
| | Basic functionality: various plotting styles of data, functions in a RooPlot
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| |
| | rf107_plotstyles.py |
| | Basic functionality: demonstration of various plotting styles of data, functions in a RooPlot
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| |
| | rf108_plotbinning.C |
| | Basic functionality: plotting unbinned data with alternate and variable binnings
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| |
| | rf108_plotbinning.py |
| | Basic functionality: plotting unbinned data with alternate and variable binnings
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| |
| | rf109_chi2residpull.C |
| | Basic functionality: Calculating chi^2 from histograms and curves in RooPlots, making histogram of residual and pull distributions
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| |
| | rf110_normintegration.C |
| | Basic functionality: normalization and integration of pdfs, construction of cumulative distribution monodimensional functions
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| |
| | rf110_normintegration.py |
| | Basic functionality: examples on normalization and integration of pdfs, construction of cumulative distribution functions from monodimensional pdfs
|
| |
| | rf111_derivatives.C |
| | Basic functionality: numerical 1st,2nd and 3rd order derivatives w.r.t.
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| |
| | rf111_derivatives.py |
| | Basic functionality: numerical 1st, and 3rd order derivatives w.r.t.
|
| |
| | rf201_composite.C |
| | Addition and convolution: composite pdf with signal and background component
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| |
| | rf201_composite.py |
| | Addition and convolution: composite pdf with signal and background component
|
| |
| | rf202_extendedmlfit.C |
| | Setting up an extended maximum likelihood fit.
|
| |
| | rf202_extendedmlfit.py |
| | Addition and convolution: setting up an extended maximum likelihood fit
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| |
| | rf203_ranges.C |
| | Fitting and plotting in sub ranges.
|
| |
| | rf203_ranges.py |
| | Addition and convolution: fitting and plotting in sub ranges
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| |
| | rf204_extrangefit.py |
| |
| | rf204a_extendedLikelihood.C |
| | Extended maximum likelihood fit in multiple ranges.
|
| |
| | rf204b_extendedLikelihood_rangedFit.C |
| | This macro demonstrates how to set up a fit in two ranges such that it does not only fit the shapes in each region, but also takes into account the relative normalization of the two.
|
| |
| | rf205_compplot.C |
| | Addition and convolution: options for plotting components of composite pdfs.
|
| |
| | rf205_compplot.py |
| | Addition and convolution: options for plotting components of composite pdfs.
|
| |
| | rf206_treevistools.C |
| | Addition and convolution: tools for visualization of RooAbsArg expression trees
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| |
| | rf206_treevistools.py |
| | Addition and convolution: tools for visualization of ROOT.RooAbsArg expression trees
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| |
| | rf207_comptools.C |
| | Addition and convolution: tools and utilities for manipulation of composite objects
|
| |
| | rf208_convolution.C |
| | Addition and convolution: one-dimensional numeric convolution
|
| |
| | rf209_anaconv.C |
| | Addition and convolution: decay function pdfs with optional B physics effects (mixing and CP violation)
|
| |
| | rf209_anaconv.py |
| | Addition and convolution: decay function pdfs with optional B physics effects (mixing and CP violation) that can be analytically convolved with e.g.
|
| |
| | rf210_angularconv.C |
| | Addition and convolution: convolution in cyclical angular observables theta
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| |
| | rf211_paramconv.C |
| | Addition and convolution: working with a pdf with a convolution operator in terms of a parameter
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| |
| | rf212_plottingInRanges_blinding.C |
| | Plot a PDF in disjunct ranges, and get normalisation right.
|
| |
| | rf301_composition.C |
| | Multidimensional models: multi-dimensional pdfs through composition e.g.
|
| |
| | rf301_composition.py |
| | Multidimensional models: multi-dimensional pdfs through composition, e.g.
|
| |
| | rf302_utilfuncs.C |
| | Multidimensional models: utility functions classes available for use in tailoring of composite (multidimensional) pdfs
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| |
| | rf302_utilfuncs.py |
| | Multidimensional models: utility functions classes available for use in tailoring of composite (multidimensional) pdfs
|
| |
| | rf303_conditional.C |
| | Multidimensional models: use of tailored pdf as conditional pdfs.s
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| |
| | rf304_uncorrprod.C |
| | Multidimensional models: simple uncorrelated multi-dimensional pdfs
|
| |
| | rf304_uncorrprod.py |
| | Multidimensional models: simple uncorrelated multi-dimensional pdfs
|
| |
| | rf305_condcorrprod.C |
| | Multidimensional models: multi-dimensional pdfs with conditional pdfs in product
|
| |
| | rf305_condcorrprod.py |
| | Multidimensional models: multi-dimensional pdfs with conditional pdfs in product
|
| |
| | rf306_condpereventerrors.C |
| | Multidimensional models: conditional pdf with per-event errors
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| |
| | rf306_condpereventerrors.py |
| | Multidimensional models: complete example with use of conditional pdf with per-event errors
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| |
| | rf307_fullpereventerrors.C |
| | Multidimensional models: full pdf with per-event errors
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| |
| | rf307_fullpereventerrors.py |
| | Multidimensional models: usage of full pdf with per-event errors
|
| |
| | rf308_normintegration2d.C |
| | Multidimensional models: normalization and integration of pdfs, construction of cumulative distribution functions from pdfs in two dimensions
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| |
| | rf308_normintegration2d.py |
| | Multidimensional models: normalization and integration of pdfs, construction of cumulative distribution functions from pdfs in two dimensions
|
| |
| | rf309_ndimplot.C |
| | Multidimensional models: making 2/3 dimensional plots of pdfs and datasets
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| |
| | rf309_ndimplot.py |
| | Multidimensional models: making 2/3 dimensional plots of pdfs and datasets
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| |
| | rf310_sliceplot.C |
| | Multidimensional models: projecting pdf and data slices in discrete observables
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| |
| | rf310_sliceplot.py |
| | Multidimensional models: projecting pdf and data slices in discrete observables
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| |
| | rf311_rangeplot.C |
| | Multidimensional models: projecting pdf and data ranges in continuous observables
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| |
| | rf311_rangeplot.py |
| | Multidimensional models: projecting pdf and data ranges in continuous observables
|
| |
| | rf312_multirangefit.C |
| | Multidimensional models: performing fits in multiple (disjoint) ranges in one or more dimensions
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| |
| | rf312_multirangefit.py |
| | Multidimensional models: performing fits in multiple (disjoint) ranges in one or more dimensions
|
| |
| | rf313_paramranges.C |
| | Multidimensional models: working with parametrized ranges to define non-rectangular regions for fitting and integration
|
| |
| | rf313_paramranges.py |
| | Multidimensional models: working with parameterized ranges to define non-rectangular regions for fitting and integration
|
| |
| | rf314_paramfitrange.C |
| | Multidimensional models: working with parametrized ranges in a fit.
|
| |
| | rf314_paramfitrange.py |
| | Multidimensional models: working with parameterized ranges in a fit.
|
| |
| | rf315_projectpdf.C |
| | Multidimensional models: marginizalization of multi-dimensional pdfs through integration
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| |
| | rf315_projectpdf.py |
| | Multidimensional models: marginizalization of multi-dimensional pdfs through integration
|
| |
| | rf316_llratioplot.C |
| | Multidimensional models: using the likelihood ratio technique to construct a signal enhanced one-dimensional projection of a multi-dimensional pdf
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| |
| | rf316_llratioplot.py |
| | Multidimensional models: using the likelihood ratio techique to construct a signal enhanced one-dimensional projection of a multi-dimensional pdf
|
| |
| | rf401_importttreethx.C |
| | Data and categories: advanced options for importing data from ROOT TTree and THx histograms
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| |
| | rf402_datahandling.C |
| | Data and categories: tools for manipulation of (un)binned datasets
|
| |
| | rf402_datahandling.py |
| | Data and categories: tools for manipulation of (un)binned datasets
|
| |
| | rf403_weightedevts.C |
| | Data and categories: using weights in unbinned datasets
|
| |
| | rf404_categories.C |
| | Data and categories: working with RooCategory objects to describe discrete variables
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| |
| | rf404_categories.py |
| | Data and categories: working with ROOT.RooCategory objects to describe discrete variables
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| |
| | rf405_realtocatfuncs.C |
| | Data and categories: demonstration of real-->discrete mapping functions
|
| |
| | rf405_realtocatfuncs.py |
| | Data and categories: demonstration of real-discrete mapping functions
|
| |
| | rf406_cattocatfuncs.C |
| | Data and categories: demonstration of discrete-->discrete (invertible) functions
|
| |
| | rf406_cattocatfuncs.py |
| | Data and categories: demonstration of discrete-discrete (invertable) functions
|
| |
| | rf407_latextables.C |
| | Data and categories: latex printing of lists and sets of RooArgSets
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| |
| | rf407_latextables.py |
| | Data and categories: latex printing of lists and sets of RooArgSets
|
| |
| | rf501_simultaneouspdf.C |
| | Organisation and simultaneous fits: using simultaneous pdfs to describe simultaneous fits to multiple datasets
|
| |
| | rf501_simultaneouspdf.py |
| | Organization and simultaneous fits: using simultaneous pdfs to describe simultaneous fits to multiple datasets
|
| |
| | rf502_wspacewrite.C |
| | Organisation and simultaneous fits: creating and writing a workspace
|
| |
| | rf502_wspacewrite.py |
| | Organization and simultaneous fits: creating and writing a workspace
|
| |
| | rf503_wspaceread.C |
| | Organisation and simultaneous fits: reading and using a workspace
|
| |
| | rf504_simwstool.C |
| | Organisation and simultaneous fits: using RooSimWSTool to construct a simultaneous pdf that is built of variations of an input pdf
|
| |
| | rf504_simwstool.py |
| | Organization and simultaneous fits: using RooSimWSTool to construct a simultaneous pdf that is built of variations of an input pdf
|
| |
| | rf505_asciicfg.C |
| | Organisation and simultaneous fits: reading and writing ASCII configuration files
|
| |
| | rf505_asciicfg.py |
| | Organization and simultaneous fits: reading and writing ASCII configuration files
|
| |
| | rf506_msgservice.C |
| | Organisation and simultaneous fits: tuning and customizing the RooFit message logging facility
|
| |
| | rf506_msgservice.py |
| | Organization and simultaneous fits: tuning and customizing the ROOT.RooFit message logging facility
|
| |
| | rf507_debugtools.C |
| | Organization and simultaneous fits: RooFit memory tracing debug tool
|
| |
| | rf507_debugtools.py |
| | Organization and simultaneous fits: RooFit memory tracing debug tool
|
| |
| | rf508_listsetmanip.C |
| | Organization and simultaneous fits: RooArgSet and RooArgList tools and tricks
|
| |
| | rf509_wsinteractive.C |
| | Organization and simultaneous fits: easy interactive access to workspace contents - CINT to CLING code migration
|
| |
| | rf509_wsinteractive.py |
| | Organization and simultaneous fits: easy interactive access to workspace contents - CINT to CLING code migration
|
| |
| | rf510_wsnamedsets.C |
| | Organization and simultaneous fits: working with named parameter sets and parameter snapshots in workspaces
|
| |
| | rf511_wsfactory_basic.C |
| | Organization and simultaneous fits: basic use of the 'object factory' associated with a workspace to rapidly build pdfs functions and their parameter components
|
| |
| | rf511_wsfactory_basic.py |
| | Organization and simultaneous fits: basic use of the 'object factory' associated with a workspace to rapidly build pdfs functions and their parameter components
|
| |
| | rf512_wsfactory_oper.C |
| | Organization and simultaneous fits: operator expressions and expression-based basic pdfs in the workspace factory syntax
|
| |
| | rf513_wsfactory_tools.C |
| | Organization and simultaneous fits: RooCustomizer and RooSimWSTool interface in factory workspace tool in a complex standalone B physics example
|
| |
| | rf513_wsfactory_tools.py |
| | Organization and simultaneous fits: illustration use of ROOT.RooCustomizer and ROOT.RooSimWSTool interface in factory workspace tool in a complex standalone B physics example
|
| |
| | rf514_RooCustomizer.C |
| | Using the RooCustomizer to create multiple PDFs that share a lot of properties, but have unique parameters for each category.
|
| |
| | rf601_intminuit.C |
| | Likelihood and minimization: interactive minimization with MINUIT
|
| |
| | rf602_chi2fit.C |
| | Likelihood and minimization: setting up a chi^2 fit to a binned dataset
|
| |
| | rf603_multicpu.C |
| | Likelihood and minimization: setting up a multi-core parallelized unbinned maximum likelihood fit
|
| |
| | rf603_multicpu.py |
| | Likelihood and minimization: setting up a multi-core parallelized unbinned maximum likelihood fit
|
| |
| | rf604_constraints.C |
| | Likelihood and minimization: fitting with constraints
|
| |
| | rf604_constraints.py |
| | Likelihood and minimization: fitting with constraints
|
| |
| | rf605_profilell.C |
| | Likelihood and minimization: working with the profile likelihood estimator
|
| |
| | rf606_nllerrorhandling.C |
| | Likelihood and minimization: understanding and customizing error handling in likelihood evaluations
|
| |
| | rf607_fitresult.C |
| | Likelihood and minimization: demonstration of options of the RooFitResult class
|
| |
| | rf607_fitresult.py |
| | Likelihood and minimization: demonstration of options of the RooFitResult class
|
| |
| | rf608_fitresultaspdf.C |
| | Likelihood and minimization: representing the parabolic approximation of the fit as a multi-variate Gaussian on the parameters of the fitted pdf
|
| |
| | rf608_fitresultaspdf.py |
| | Likelihood and minimization: representing the parabolic approximation of the fit as a multi-variate Gaussian on the parameters of the fitted pdf
|
| |
| | rf609_xychi2fit.C |
| | Likelihood and minimization: setting up a chi^2 fit to an unbinned dataset with X,Y,err(Y) values (and optionally err(X) values)
|
| |
| | rf609_xychi2fit.py |
| | Likelihood and minimization: setting up a chi^2 fit to an unbinned dataset with X,Y,err(Y) values (and optionally err(X) values)
|
| |
| | rf610_visualerror.C |
| | Likelihood and minimization: visualization of errors from a covariance matrix
|
| |
| | rf610_visualerror.py |
| | Likelihood and minimization: visualization of errors from a covariance matrix
|
| |
| | rf611_weightedfits.C |
| | Likelihood and minimization: Parameter uncertainties for weighted unbinned ML fits
|
| |
| | rf612_recoverFromInvalidParameters.C |
| | Likelihood and minimization: Recover from regions where the function is not defined.
|
| |
| | rf701_efficiencyfit.C |
| | Special pdf's: unbinned maximum likelihood fit of an efficiency eff(x) function
|
| |
| | rf701_efficiencyfit.py |
| | Special pdf's: unbinned maximum likelihood fit of an efficiency eff(x) function to a dataset D(x,cut), cut is a category encoding a selection, which the efficiency as function of x should be described by eff(x)
|
| |
| | rf702_efficiencyfit_2D.C |
| | Special pdf's: unbinned maximum likelihood fit of an efficiency eff(x) function to a dataset D(x,cut), cut is a category encoding a selection whose efficiency as function of x should be described by eff(x)
|
| |
| | rf702_efficiencyfit_2D.py |
| | Special pdf's: unbinned maximum likelihood fit of an efficiency eff(x) function to a dataset D(x,cut), cut is a category encoding a selection whose efficiency as function of x should be described by eff(x)
|
| |
| | rf703_effpdfprod.C |
| | Special pdf's: using a product of an (acceptance) efficiency and a pdf as pdf
|
| |
| | rf703_effpdfprod.py |
| | Special pdf's: using a product of an (acceptance) efficiency and a pdf as pdf
|
| |
| | rf704_amplitudefit.C |
| | Special pdf's: using a pdf defined by a sum of real-valued amplitude components
|
| |
| | rf704_amplitudefit.py |
| | Special pdf's: using a pdf defined by a sum of real-valued amplitude components
|
| |
| | rf705_linearmorph.C |
| | Special pdf's: linear interpolation between pdf shapes using the 'Alex Read' algorithm
|
| |
| | rf706_histpdf.C |
| | Special pdf's: histogram-based pdfs and functions
|
| |
| | rf706_histpdf.py |
| | Special pdf's: histogram based pdfs and functions
|
| |
| | rf707_kernelestimation.C |
| | Special pdf's: using non-parametric (multi-dimensional) kernel estimation pdfs
|
| |
| | rf707_kernelestimation.py |
| | Special pdf's: using non-parametric (multi-dimensional) kernel estimation pdfs
|
| |
| | rf708_bphysics.C |
| | Special pdf's: special decay pdf for B physics with mixing and/or CP violation
|
| |
| | rf708_bphysics.py |
| | Special pdf's: special decay pdf for B physics with mixing and/or CP violation
|
| |
| | rf709_BarlowBeeston.C |
| | Implementing the Barlow-Beeston method for taking into account the statistical uncertainty of a Monte-Carlo fit template.
|
| |
| | rf801_mcstudy.C |
| | Validation and MC studies: toy Monte Carlo study that perform cycles of event generation and fitting
|
| |
| | rf801_mcstudy.py |
| | Validation and MC studies: toy Monte Carlo study that perform cycles of event generation and fitting
|
| |
| | rf802_mcstudy_addons.C |
| | Validation and MC studies: RooMCStudy - using separate fit and generator models, using the chi^2 calculator model Running a biased fit model against an optimal fit.
|
| |
| | rf803_mcstudy_addons2.C |
| | Validation and MC studies: RooMCStudy - Using the randomizer and profile likelihood add-on models
|
| |
| | rf804_mcstudy_constr.C |
| | Validation and MC studies: using RooMCStudy on models with constrains
|
| |
| | rf901_numintconfig.C |
| | Numeric algorithm tuning: configuration and customization of how numeric (partial) integrals are executed
|
| |
| | rf901_numintconfig.py |
| | Numeric algorithm tuning: configuration and customization of how numeric (partial) integrals are executed
|
| |
| | rf902_numgenconfig.C |
| | Numeric algorithm tuning: configuration and customization of how MC sampling algorithms on specific pdfs are executed
|
| |
| | rf902_numgenconfig.py |
| | Numeric algorithm tuning: configuration and customization of how MC sampling algorithms on specific pdfs are executed
|
| |
| | rf903_numintcache.C |
| | Numeric algorithm tuning: caching of slow numeric integrals and parameterization of slow numeric integrals
|
| |
| | rf903_numintcache.py |
| | Numeric algorithm tuning: caching of slow numeric integrals and parameterizations of slow numeric integrals
|
| |
