Metadata-Version: 2.1
Name: PyrootCK
Version: 1.0.1
Summary: Improving PyROOT for better productivity.
Home-page: https://gitlab.com/ckhurewa/PyrootCK
Author: Chitsanu Khurewathanakul
Author-email: chitsanu.khurewathanakul@gmail.com
License: GNU GPLv3
Description: PyrootCK
        ========
        
        [![package version](https://img.shields.io/pypi/v/PyrootCK.svg)](https://pypi.org/project/PyrootCK)
        [![pipeline status](https://gitlab.com/ckhurewa/PyrootCK/badges/master/pipeline.svg)](https://gitlab.com/ckhurewa/PyrootCK/commits/master)
        [![coverage report](https://gitlab.com/ckhurewa/PyrootCK/badges/master/coverage.svg)](https://ckhurewa.gitlab.io/PyrootCK)
        [![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)
        [![Documentation Status](https://readthedocs.org/projects/PyrootCK/badge/?version=latest)](http://PyrootCK.readthedocs.io/en/latest/?badge=latest)
        [![python version](https://img.shields.io/pypi/pyversions/PyrootCK.svg)](https://img.shields.io/pypi/pyversions/PyrootCK.svg)
        
        Improving ``PyROOT`` for better productivity.
        
        Collection of utilities are organized into subpackages::
        
        - `mathutils`:
          - `asymvar`: class for variable with asymmetric-error, inspired from `uncertainties.ufloat`.
          - `Eff`, `EffU`, `EffU_unguard`: functions to compute efficiencies with Clopper-Pearson uncertainty.
          - `weighted_average`, `weighted_harmonic_average`: when a simple average is not enough.
          - `combine_fully_correlated`, `combine_uncorrelated`, `combine_BLUE`: for combining multiple observables with uncertainty into one, given choices of correlation. For BLUE (Best Linear Unbiased Estimator), see Valassi, 2013.
        
        - `iouils`
          - `import_tree` to quickly load `TTree` from (multiple) `TFile` overloaded for different source types (local, ganga, eos, xrootd, ...).
        
        - `tmvautils`
          - `TMVA_Adapter` to help setup `TMVA.Reader` variables, and return `TTree` of mva-response weights.
        
        As well as miscellaneous monkey-patching on `ROOT` and `uncertainties`
        for more methods::
        
        - `ROOT`: 
          - Misc conversion to/from `ROOT` (`TH`,`TGraph`,`RooWorkspace`,`RooFitResult`,...) and `pandas` (`Series`, `DataFrame`).
          - `TFile.slice_tree` to extract `TTree` into smaller one.
          - `TTree.drop` to make index-unique TTree.
          - `TH1.vlookup`, `TH2.vlookup`: like in Microsoft Excel, to retrive value in a bin given point(s) on the axis.
          - `TMultiGraph.brazillian`: for the upper limits plot.
        
        - `uncertainties`:
          - class `var`, based on ufloat but ready-made for statistical (Poisson) error.
          - Additional methods on `ufloat`: `rerr`, `upperlim`, `low`, `high`, `interval`, `rounding_PDG`
          - More methods involving error tag: `tags`, `get_error`, `get_rerr`
        
        See the docstring from module index for more details.
        
        
        Installation
        ------------
        
        It's available on pip: `pip install pyrootck`
        
        Dependency: `uncertainties`, `pandas`, `root_numpy`, `pyroot_zen`, `PythonCK`
        
        
        Disclaimer
        ----------
        
        This packacge was written and used during my PhD in 2013-2017 at EPFL (Lausanne) 
        and LHCb collaboration (CERN), for the work in *Z->tau tau* cross-section measurement 
        and *H->mu tau* searches at LHCb (8TeV).
        
        I hope it can be of a good use for future analysis...
        
        
Platform: unix
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Utilities
Requires-Python: ~=2.7
Description-Content-Type: text/markdown
