Page MenuHomeHEPForge
Files F10881541

example.py
No OneTemporary
Actions

example.py
View Options

#!/usr/bin/env python3
#
#----------------------------------------------------------------------
# $Id: example.py 1157 2018-08-22 20:11:52Z frdreyer $
#
# Copyright (c) -, Frederic A. Dreyer, Gavin P. Salam, Gregory Soyez
#
#----------------------------------------------------------------------
# This file is part of FastJet contrib.
#
# It is free software; you can redistribute it and/or modify it under
# the terms of the GNU General Public License as published by the
# Free Software Foundation; either version 2 of the License, or (at
# your option) any later version.
#
# It is distributed in the hope that it will be useful, but WITHOUT
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
# or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
# License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this code. If not, see <http://www.gnu.org/licenses/>.
#----------------------------------------------------------------------
#
# Load a sample file and plot it.
#
# Usage:
# python3 plot_lund.py [--file filename] [--bkg file_bkg]
# [--njet njet] [--npxl npixels]
#
import read_lund_json as lund
#from import LundImage
from matplotlib.colors import LogNorm
import numpy as np
import matplotlib.pyplot as plt
import argparse
parser = argparse.ArgumentParser(description='Plot lund images')
parser.add_argument('--file', action = 'store', default = 'jets.json')
parser.add_argument('--njet', type = int, default = 2, help='Maximum number of jets to analyse')
parser.add_argument('--npxl', type = int, default = 25, help="Number of pixels in each dimension of the image")
args = parser.parse_args()
# set up the reader and get array from file
xval = [0.0, 3.0]
yval = [-3.0, 5.0]
# start by creating a reader for the json file produced by example.cc
# (one json entry per line, correspond to one jet per json entry)
reader = lund.Reader(args.file, args.njet)
# Then examine the jets it contains
print ("Contents of the file", args.file)
for jet in reader:
# jet is an array of declusterings.
# The jet's pt can be obtained by looking at the first declustering (jet[0])
# and extracting the subjet-pair pt ("p_pt")
print(" Jet with pt = {:6.1f} GeV with {:3d} primary Lund-plane declusterings".format(jet[0]["p_pt"], len(jet)))
print()
# Reset the reader to the start and use it with a helper
# class to extract an image for each jet
reader.reset()
image_generator = lund.LundImage(reader, args.njet, args.npxl, xval, yval)
images = image_generator.values()
# Get the average of the images
print("Now creating average lund image from the {} jets".format(len(images)))
avg_img = np.average(images,axis=0)
# Plot the result
fig=plt.figure(figsize=(6, 4.5))
plt.title('Averaged Lund image')
plt.xlabel('$\ln(R / \Delta)$')
plt.ylabel('$\ln(k_t / \mathrm{GeV})$')
plt.imshow(avg_img.transpose(), origin='lower', aspect='auto',
extent=xval+yval, cmap=plt.get_cmap('BuPu'))
plt.colorbar()
print("Close the viewer window to exit")
plt.show()

File Metadata

Mime Type
text/x-python
Expires
Sat, May 3, 6:30 AM (1 d, 17 h)
Storage Engine
blob
Storage Format
Raw Data
Storage Handle
4943830
Default Alt Text
example.py (3 KB)

Event Timeline