Examples showing the Math classes.
Files | |
file | Bessel.C |
Show the different kinds of Bessel functions available in ROOT To execute the macro type in: | |
file | Bessel.py |
Show the different kinds of Bessel functions available in ROOT To execute the macro type in: | |
file | binomial.C |
tutorial illustrating the use of TMath::Binomial can be run with: | |
file | BreitWigner.C |
Tutorial illustrating how to create a plot comparing a Breit Wigner to a Relativistic Breit Wigner | |
file | ChebyshevPol.C |
Example of Chebyshev polynomials using new TFormula pre-defined definitions of chebyshev polynomials | |
file | chi2test.C |
Example to use chi2 test for comparing two histograms One unweighted histogram is compared with a weighted histogram. | |
file | CrystalBall.C |
Example of CrystalBall Function and its distribution (pdf and cdf) | |
file | exampleFunction.py |
Example of using Python functions and input to numerical algorithm using the ROOT Functor class | |
file | exampleFunctor.C |
Tutorial illustrating how creating a TF1 class using functor or class member functions | |
file | exampleMultiRoot.C |
Example of using multiroot finder based on GSL algorithm. | |
file | exampleTKDE.C |
Example of using the TKDE class (kernel density estimator) | |
file | FeldmanCousins.C |
Example macro of using the TFeldmanCousins class in root. | |
file | GammaFun.C |
Example showing the usage of the major special math functions (gamma, beta, erf) in ROOT To execute the macro type in: | |
file | goftest.C |
GoFTest tutorial macro | |
file | hlquantiles.C |
Demo for quantiles (with highlight mode) | |
file | kdTreeBinning.C |
kdTreeBinning tutorial: bin the data in cells of equal content using a kd-tree | |
file | Legendre.C |
Example of first few Legendre Polynomials | |
file | Legendre.py |
Example of first few Legendre Polynomials. | |
file | LegendreAssoc.C |
Example describing the usage of different kinds of Associate Legendre Polynomials To execute the macro type in: | |
file | limit.C |
This program demonstrates the computation of 95 % C.L. | |
file | mathBeta.C |
Test the TMath::BetaDist and TMath::BetaDistI functions | |
file | mathcoreCDF.C |
Example describing how to use the different cumulative distribution functions in ROOT. | |
file | mathcoreGenVector.C |
Example macro testing available methods and operation of the GenVector classes. | |
file | mathcoreSpecFunc.C |
Example macro describing how to use the special mathematical functions taking full advantage of the precision and speed of the C99 compliant environments. | |
file | mathcoreStatFunc.C |
Example macro showing some major probability density functions in ROOT. | |
file | mathcoreStatFunc.py |
Example macro showing some major probability density functions in ROOT. | |
file | mathcoreVectorCollection.C |
Example showing how to write and read a std vector of ROOT::Math LorentzVector in a ROOT tree. | |
file | mathcoreVectorFloatIO.C |
Macro illustrating I/O with Lorentz Vectors of floats The dictionary for LorentzVector of float is not in the libMathCore, therefore is generated when parsed the file with CLING. | |
file | mathcoreVectorIO.C |
Example of I/O of a mathcore Lorentz Vectors in a Tree and comparison with a TLorentzVector. | |
file | mathGammaNormal.C |
Tutorial illustrating the use of TMath::GammaDist and TMath::LogNormal | |
file | mathLaplace.C |
Test the TMath::LaplaceDist and TMath::LaplaceDistI functions | |
file | mathmoreIntegration.C |
Example on the usage of the adaptive 1D integration algorithm of MathMore it calculates the numerically cumulative integral of a distribution (like in this case the BreitWigner) to execute the macro type it (you need to compile with AClic) | |
file | mathmoreIntegrationMultidim.C |
Example on the usage of the multidimensional integration algorithm of MathMore Please refer to the web documentation for further details: https://root.cern/manual/math/#numerical-integration To execute the macro type the following: | |
file | mathStudent.C |
Tutorial illustrating the use of the Student and F distributions | |
file | multidimSampling.C |
Example of sampling a multi-dim distribution using the DistSampler class NOTE: This tutorial must be run with ACLIC | |
file | multivarGaus.C |
Tutorial illustrating the multivariate gaussian random number generation | |
file | normalDist.C |
Tutorial illustrating the new statistical distributions functions (pdf, cdf and quantile) | |
file | normalDist.py |
Tutorial illustrating the new statistical distributions functions (pdf, cdf and quantile) | |
file | permute.C |
Tutorial illustrating the use of TMath::Permute can be run with: | |
file | principal.C |
Principal Components Analysis (PCA) example | |
file | principal.py |
Principal Components Analysis (PCA) example | |
file | quantiles.C |
Demo for quantiles | |
file | quasirandom.C |
Example of generating quasi-random numbers | |
file | Rolke.C |
Example of the usage of the TRolke class The TRolke class computes the profile likelihood confidence limits for 7 different model assumptions on systematic/statistical uncertainties | |
file | testrandom.C |
Performance test of all the ROOT random generator (TRandom, TRandom1, TRandom2 and TRandom3) Tests the generator TRandom3 against some ref values and creates a timing table against TRandom, TRandom1 and TRandom2. | |
file | tStudent.C |
Example macro describing the student t distribution | |
file | tStudent.py |
Example macro describing the student t distribution | |
file | TSVDUnfoldExample.C |
Data unfolding using Singular Value Decomposition | |
file | vavilov.C |
Test of the TMath::Vavilov distribution | |