show_sensitivity.py
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#! /usr/bin/env python
# ==========================================================================
# Display differential sensitivity plot generated by cssens
#
# Copyright (C) 2015-2016 Juergen Knoedlseder
#
# 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 sys
import math
import gammalib
import cscripts
try:
import matplotlib.pyplot as plt
plt.figure()
plt.close()
except (ImportError, RuntimeError):
print('This script needs the "matplotlib" module')
sys.exit()
# ===================== #
# Read sensitivity data #
# ===================== #
def read_sensitivity(filename):
"""
Read sensitivity information from CSV file
Parameters
----------
filename : str
Name of CSV file
Returns
-------
sensitivity : dict
Dictionary with sensitivity information
"""
# Read filename
csv = gammalib.GCsv(filename,',')
# Create dictionnary
sensitivity = {}
for column in range(csv.ncols()):
name = csv[0,column].rstrip('\r')
values = []
for row in range(csv.nrows()-1):
values.append(float(csv[row+1,column]))
sensitivity[name] = values
# Check where file contains differential or integral sensitivity
mode = 'Integral'
if sensitivity.has_key('emax'):
emax_ref = -1.0
for value in sensitivity['emax']:
if emax_ref < 0.0:
emax_ref = value
elif emax_ref != value:
mode = 'Differential'
break
# Add mode
sensitivity['mode'] = mode
# Add linear energy values
if mode == 'Differential':
if sensitivity.has_key('loge'):
name = 'energy'
values = []
for value in sensitivity['loge']:
values.append(math.pow(10.0, value))
sensitivity[name] = values
else:
if sensitivity.has_key('emin'):
name = 'energy'
values = []
for value in sensitivity['emin']:
values.append(value)
sensitivity[name] = values
# Return
return sensitivity
# ===================== #
# Plot sensitivity data #
# ===================== #
def plot_sensitivity(sensitivity, filename, plotfile):
"""
Plot sensitivity data
Parameters
----------
sensitivity : dict
Dictionary with sensitivity information
filename : str
Name of CSV file
plotfile : str
Plot file name
"""
# Build title
title = sensitivity['mode'] + ' sensitivity ('+filename+')'
# Create figure
plt.figure()
# Set plot attributes
plt.title(title)
plt.loglog()
plt.grid()
# Show differential sensitivity
plt.plot(sensitivity['energy'], sensitivity['sensitivity'], 'ro-')
# Set labels
plt.xlabel('Energy (TeV)')
if sensitivity['mode'] == 'Differential':
plt.ylabel(r'E $\times$ F(E) (erg cm$^{-2}$ s$^{-1}$)')
else:
plt.ylabel(r'E $\times$ F($>$E) (erg cm$^{-2}$ s$^{-1}$)')
# Show figure
if len(plotfile) > 0:
plt.savefig(plotfile)
else:
plt.show()
# Return
return
# ================ #
# Show sensitivity #
# ================ #
def show_sensitivity():
"""
Show sensitivity
"""
# Set usage string
usage = 'show_sensitivity.py [-p plotfile] [file]'
# Set default options
options = [{'option': '-p', 'value': ''}]
# Get arguments and options from command line arguments
args, options = cscripts.ioutils.get_args_options(options, usage)
# Extract script parameters from options
plotfile = options[0]['value']
if len(args) > 0:
filename = args[0]
else:
filename = 'sensitivity.dat'
# Read sensitivity data
sensitivity = read_sensitivity(filename)
# Plot sensitivity data
plot_sensitivity(sensitivity, filename, plotfile)
# Return
return
# ======================== #
# Main routine entry point #
# ======================== #
if __name__ == '__main__':
# Show sensitivity
show_sensitivity()