This class allows you to produce plots of the variable stored in TrkAna TTrees. The instantion requires a dictionary with a pandas dataframe. You can convert a ROOT TTree into a pandas dataframe using uproot:
import uproot
file = uproot.open("trkana-mc.root")
trkananeg = file["TrkAnaNeg"]["trkana"]
df = trkananeg.pandas.df(flatten=False)
The plotter class is then instantied as:
import plotter
samples = {'mc': df}
weights = {'mc': 1}
my_plotter = plotter.Plotter(samples, weights)
The main method is plot_variable
which can manipulate different variables and query the dataframe. It is also possible to categorize the events according to the PDG code (demcgen_pdg
) or the GenID code (demcgen_gen
).
This example shows how to plot the reconstructed momentum categorized by GenID code:
fig, ax = plt.subplots(1, 1)
my_plotter.plot_variable(ax,
"deent.mom",
title="Reco. momentum [GeV]",
cat_var="demcgen.gen",
x_range=(95,110),
bins=30)
ax.set_yscale('log')
ax.set_ylim(bottom=0.5, top=5e5)
More information can be found in Example.ipynb.