These scripts convert ROOT trees into numpy arrays and creates histograms for use with the KU Ewkino Analysis.

histograms and arrays are saved in a dictionary structure based on the sample and file name, functions return these dictionaries.

The dictionaries can be used interactively or in their own script

Different copies of scripts are used to make different histograms

file_table_functions.py: Contains functions for converting TTrees into numpy arrays, making output tables, reading in histograms from root files for plotting

make_table*.py: used for making tables of events for different cut selections, allows for making multiple different cut regions, and saving the events for each one in a dictionary

make_susy_hist*
get_those*: making histograms using the numpy arrays, makes use of list comprehension to deal with jagged arrays, and fancy indexing for applying selection