[1]:

%pylab inline

Populating the interactive namespace from numpy and matplotlib

[2]:

import os
import pyhf
from ipywidgets import interact, fixed


# Binned HEP Statistical Analysis in Python¶

## HistFactory¶

HistFactory is a popular framework to analyze binned event data and commonly used in High Energy Physics. At its core it is a template for building a statistical model from individual binned distribution (‘Histograms’) and variations on them (‘Systematics’) that represent auxiliary measurements (for example an energy scale of the detector which affects the shape of a distribution)

## pyhf¶

pyhf is a work-in-progress standalone implementation of the HistFactory p.d.f. template and an implementation of the test statistics and asymptotic formulae described in the paper by Cowan, Cranmer, Gross, Vitells: Asymptotic formulae for likelihood-based tests of new physics [arxiv:1007.1727].

Models can be defined using JSON specification, but existing models based on the XML + ROOT file scheme are readable as well.

## The Demo¶

The input data for the statistical analysis was built generated using the containerized workflow engine yadage (see demo from KubeCon 2018 [youtube]). Similarly to Binder this utilizes modern container technology for reproducible science. Below you see the execution graph leading up to the model input data at the bottom.

[3]:

import base64
from IPython.core.display import display, HTML

[3]: