'ADDITION AND CONVOLUTION' RooFit tutorial macro #208 One-dimensional numeric convolution (require ROOT to be compiled with –enable-fftw3)
pdf = landau(t) (x) gauss(t)
import ROOT
frame =
t.frame(Title=
"landau (x) gauss convolution")
c =
ROOT.TCanvas(
"rf208_convolution",
"rf208_convolution", 600, 600)
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
[#1] INFO:Eval -- RooRealVar::setRange(t) new range named 'refrange_fft_lxg' created with bounds [-10,30]
[#1] INFO:Caching -- RooAbsCachedPdf::getCache(lxg) creating new cache 0x55e69753db90 with pdf lx_CONV_gauss_CACHE_Obs[t]_NORM_t for nset (t) with code 0
[#1] INFO:Fitting -- RooAbsPdf::fitTo(lxg_over_lxg_Int[t]) fixing normalization set for coefficient determination to observables in data
[#1] INFO:Fitting -- using CPU computation library compiled with -mavx512
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_lxg_over_lxg_Int[t]_lxgData) Summation contains a RooNLLVar, using its error level
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
[#1] INFO:Caching -- RooAbsCachedPdf::getCache(lxg) creating new cache 0x55e697a6f540 with pdf lx_CONV_gauss_CACHE_Obs[t] for nset () with code 1 from preexisting content.
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
[#1] INFO:Caching -- RooAbsCachedPdf::getCache(lxg) creating new cache 0x55e697bd05c0 with pdf lx_CONV_gauss_CACHE_Obs[t]_NORM_t for nset (t) with code 0
- Date
- February 2018
- Authors
- Clemens Lange, Wouter Verkerke (C version)
Definition in file rf208_convolution.py.