Metadata-Version: 2.1
Name: succolib
Version: 2020.6.4
Summary: A set of handy, Python-based tools for the INSULAb detectors data analysis
Home-page: https://github.com/mattiasoldani/succolib
Author: Mattia Soldani
Author-email: mattiasoldani93@gmail.com
License: MIT
Download-URL: https://github.com/mattiasoldani/succolib/archive/v2020.6.4.tar.gz
Description: # succolib
        
        This is **succolib**, a library of handy Python functions for High-Energy Physics beamtests data analysis. In particular, it has been developed with a focus on the event-by-event analysis of the data collected with the INSULAb detectors &mdash; see, for example, the experimental configurations described [here](http://cds.cern.ch/record/2672249), [here](http://hdl.handle.net/10277/857) and [here](http://cds.cern.ch/record/1353904).
        
        succolib provides several tools, mainly for
        * **data input** and storage in pandas DataFrames &mdash; supported input formats are formatted text files (e.g. DAT files) and ROOT TTree files;
        * **data conditioning**, i.e. typical transformations applied to and calculations performed on the raw data &mdash; e.g. particle tracking data reconstruction;
        * **statistical analysis**, e.g. common distributions in High-Energy Physics, given in a highly accessible form to facilitate data visualisation and fitting.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Intended Audience :: Science/Research
Requires-Python: >3.0
Description-Content-Type: text/markdown
