show_pull_histogram.py
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#! /usr/bin/env python
# ==========================================================================
# This script displays pull histograms that have been generated using the
# cspull script. The pull is defined by
#
# (fitted value - simulated value) / estimated error
#
# and the pull histogram allows to assess possible biases in the fit
# parameters and errors.
#
# Required 3rd party modules:
# - matplotlib
# - numpy
#
# Copyright (C) 2011 Jurgen Knodlseder
#
# This program 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 3 of the License, or
# (at your option) any later version.
#
# This program 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 program. If not, see <http://www.gnu.org/licenses/>.
#
# ==========================================================================
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
import numpy as np
import sys
import csv
# ====================== #
# Read pull distribution #
# ====================== #
def read_pull(filename, parname):
"""
Read pull distribution.
"""
# Initialise list
values = []
# Open reader
reader = csv.reader(open(filename, 'r'), delimiter=',')
# Read rows
first = True
index = -1
for row in reader:
# Get column index if first row
if first:
try:
index = row.index(parname)
except:
print 'ERROR: Parameter "'+parname+'" not found in list:'
for p in row:
print ' "'+p+'"'
raise NameError(parname)
#print index
# Handle data rows
else:
values.append(float(row[index]))
# Flag that first row has been passed
first = False
# Create numpy array
a = np.array(values)
#print a
# Return array
return a
# ======================== #
# Main routine entry point #
# ======================== #
if __name__ == '__main__':
"""
Display pull histogram generated by cspull using matplotlib.
"""
# Print usage information
usage = "Usage: show_pull_histogram filename parname [bins]"
if len(sys.argv) < 3:
print usage
sys.exit()
# Extract parameters
filename = sys.argv[1]
parname = sys.argv[2]
if len(sys.argv) > 3:
nbins = int(sys.argv[3])
else:
nbins = 50
# Read values from CSV file
values = read_pull(filename, parname)
# Create histogram
n, bins, patches = plt.hist(values, nbins, range=[-4.0,4.0],
normed=True, facecolor='green')
# Create expected distribution
y = mlab.normpdf(bins, 0.0, 1.0)
l = plt.plot(bins, y, 'r-', linewidth=2)
# Set parname for plotting
name = parname
# Set plot
plt.xlabel('Pull ('+name+')')
plt.ylabel('Arbitrary units')
plt.title(name)
plt.grid(True)
# Show histogram
plt.show()