ROOT is a modular scientific software toolkit. It provides all the functionalities needed to deal with big data processing, statistical analysis, visualisation and storage. It is mainly written in C++ but integrated with other languages such as Python and R.
Almost everything in ROOT should be supported in this Conda package; ROOT was built with lots of options turned on. Here are a few things to try:
root: you can start up a session and see the splash screen; Control-D to exit.
import ROOTwill load PyROOT.
root --notebookwill start a notebook server with a ROOT kernel choice.
rootbrowsewill open a TBrowser session so you can look through files.
root -l -q $ROOTSYS/tutorials/dataframe/df013_InspectAnalysis.Cwill run a DataFrame example with an animated plot.
root -b -q -l -n -e "std::cout << TROOT::GetTutorialDir() << std::endl;"will print the tutorial dir.
root -b -l -q -e 'std::cout << (float) TPython::Eval("1+1") << endl;'will run Python from C++ ROOT.
See the post here for more information about using this Conda package.
The ROOT package will prepare the required compilers. Everything in Conda is symlinked into
$CONDA_PREFIX if you build things by hand; tools like CMake should find it automatically. The
scripts should not be used and are not provided. Graphics,
rootbrowse, etc. all should work. OpenGL is enabled.
There is also a
root_base package, with minimal dependecies, that libraries should depend on this to avoid
having a runtime dependency on the
root-binaries are also available. In most cases users should use the
root package directly, since it adds both of these, along with compilers, Jupyter, and a few other things to facilitate using ROOT or PyROOT.
ROOT was built with and will report