fnal-column-analysis-tools 0.4.4

Tools for doing Collider HEP style analysis with columnar operations at Fermilab

This package is currently organized into three subpackages:

1. lookup_tools - This package manages importing corrections and scale factors, and provides a unified interface for evaluating those corrections on physics objects.

   • lookup_tools.extractor: handles importing the lookups from root files

   • lookup_tools.evaluator: handles organizing, providing an interface for, and evaluating the lookups

2. analysis_objects - This package contains definitions of physics objects casted in the language of JaggedArrays

   • JaggedCandidateArray - This object represents a list of candidates (things with four momenta and other attribute). Upon creation one can add extra columns of data that were not imported at construction, and all columns are accessible as though they were attributes of the class. This gives analysts a simple-to-read but rich, descriptive, and highly configurable object to represent muons, electrons, etc.

   • JaggedTLorentzVectorArray - This is a jagged representation of a TLorentzVectorArray.

3. striped - This package defines transformations from the raw striped database into JaggedArrays and JaggedCandidateArrays

   • ColumnGroup - This object takes the name of a column that has attributes in striped and creates a dictionary of all given attributes.

   • PhysicalColumnGroup - Just like ColumnGroup except it requires a “p4” attribute to be defined, and is specialized to aide in creating JaggedCandidateArrays

   • jaggedFromColumnGroup - This is a function that takes a column group and returns a JaggedArray if it is a normal column group, or a JaggedCandidateArray if given a PhysicalColumnGroup

Installation

Install fnal-column-analysis-tools like any other Python package:

pip install fnal-column-analysis-tools

or similar (use sudo, --user, virtualenv, or pip-in-conda if you wish).

Strict dependencies:

• Python (2.7+, 3.6+)

The following are installed automatically when you install uproot with pip:

• numpy (1.15+)

• awkward-array to manipulate data from non-flat TTrees, such as jagged arrays (part of Scikit-HEP)

• uproot-methods to allow expressions of things as lorentz vectors

• numba just-in-time compilation of python functions

• scipy for statistical functions

• matplitlib as a plotting backend

• uproot for interacting with ROOT files