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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 | 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 CINT. | |

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 | 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 | |