Open histograms from a ROOT file

The aim of this notebook is to show how to open a 2D ROOT histogram from a Geant4 simulation saved in a ROOT file.

Let's start by importing the required modules

import uproot
import numpy as np

import matplotlib.pyplot as plt

Let's inspect the file

We can see that there are two Ntuples (two matrices) outData and crossPos. Just for informations, there are two different ntuples because they have a different number of rows.

Furthermore there are two Histograms: crossingPos and crossingWeigh, being respectively the raw histogram of particles crossing at a given distance and the weighted one based on their total energy.

with uproot.open("../CERN2022-build/out_data/tbeamdata0000.root") as f:
    for k in f:
        print(k)
        try:
            for kk in f[k]:
                print(kk)
        except:
            pass

outData;1
<TBranch 'NEvent' at 0x7f0f52e52fd0>
<TBranch 'Tracker_NHit_X_0' at 0x7f0f52e53340>
<TBranch 'Tracker_NHit_Y_0' at 0x7f0f52e53f10>
<TBranch 'Tracker_NHit_X_1' at 0x7f0f52e54f40>
<TBranch 'Tracker_NHit_Y_1' at 0x7f0f52e54dc0>
<TBranch 'Tracker_X_0' at 0x7f0f52e90f10>
<TBranch 'Tracker_Y_0' at 0x7f0f52e90070>
<TBranch 'Tracker_X_1' at 0x7f0f52e97b20>
<TBranch 'Tracker_Y_1' at 0x7f0f52e99310>
<TBranch 'GammaCal_EDep_CC' at 0x7f0f52e99be0>
<TBranch 'GammaCal_EDep_TL' at 0x7f0f52ead4f0>
<TBranch 'GammaCal_EDep_TR' at 0x7f0f52eaddc0>
<TBranch 'GammaCal_EDep_BL' at 0x7f0f52e9e940>
<TBranch 'GammaCal_EDep_BR' at 0x7f0f52e9e070>
<TBranch 'GammaCal_EDep_CL' at 0x7f0f52e628b0>
<TBranch 'GammaCal_EDep_CR' at 0x7f0f52e67e50>
<TBranch 'CrystalA_EDep' at 0x7f0f52e67580>
<TBranch 'CrystaB_EDep' at 0x7f0f52e3e3a0>
<TBranch 'CrystalC_EDep' at 0x7f0f52e3ec70>
crossPos;1
<TBranch 'EvID' at 0x7f0f52e43be0>
<TBranch 'Xcrossing' at 0x7f0f52e49580>
<TBranch 'Ycrossing' at 0x7f0f52e49e50>
<TBranch 'PDGEncoding' at 0x7f0f52e5f760>
<TBranch 'ParticleID' at 0x7f0f52e5ffa0>
<TBranch 'totEnergy' at 0x7f0f52e73940>
crossingPos;1
crossingWeigh;1

This is my colormap for logz histograms, for coloring the zeros as ones.

import matplotlib as mpl
import copy 

my_cmap = copy.copy(mpl.cm.jet) # copy the default cmap
my_cmap.set_bad(my_cmap(0))

Exploring the histogram object

Let's have a look in more detail to one histogram, and extract relevant informations

with uproot.open("../CERN2022-build/out_data/tbeamdata0000.root")["crossingWeigh"] as f:
    a = f.all_members
    print(a.keys()) # Print what's inside
        
    # Directly access the bins and height matrix
    b = f.to_numpy()
    for i in range(len(b)):
        print(b[i].shape)
    

# Extract bins and height matrix
hh = b[0]
binsx = b[1]
binsy = b[2]
bincx = binsx[:-1] + (binsx[1] - binsx[0])/2
bincy = binsy[:-1] + (binsy[1] - binsy[0])/2

dict_keys(['@fUniqueID', '@fBits', 'fName', 'fTitle', 'fLineColor', 'fLineStyle', 'fLineWidth', 'fFillColor', 'fFillStyle', 'fMarkerColor', 'fMarkerStyle', 'fMarkerSize', 'fNcells', 'fXaxis', 'fYaxis', 'fZaxis', 'fBarOffset', 'fBarWidth', 'fEntries', 'fTsumw', 'fTsumw2', 'fTsumwx', 'fTsumwx2', 'fMaximum', 'fMinimum', 'fNormFactor', 'fContour', 'fSumw2', 'fOption', 'fFunctions', 'fScalefactor', 'fTsumwy', 'fTsumwy2', 'fTsumwxy', 'fN'])
(300, 300)
(301,)
(301,)

Plot of the histogram

A simple example of how to plot the istogram

# %matplotlib widget
%matplotlib inline
fig, ax = plt.subplots()

prof = ax.imshow(hh.T, cmap = my_cmap, origin = "lower",
                   extent = (binsx.min(), binsx.max(), binsy.min(), binsy.max()))

ax.set_xlabel("X [cm]", fontsize = 14)
ax.set_ylabel("Y [cm]", fontsize = 14)

fig.colorbar(prof, ax = ax)
plt.show()