show_variability_evolution.py
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#! /usr/bin/env python
# ==========================================================================
# Shows source variability evolution created with ctfindvar
#
# Copyright (C) 2018-2020 Simon Bonnefoy
#
# 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
try:
import matplotlib.pyplot as plt
plt.figure()
plt.close()
except (ImportError, RuntimeError):
print('This script needs the "matplotlib" module')
sys.exit()
import gammalib
import cscripts
# ========================== #
# Plot variability evolution #
# ========================== #
def plot_variability_evolution(filename, plotfile, srcname):
"""
Plot variability evolution
Parameters
----------
filename : str
Name of spectrum FITS file
plotfile : str
Plot file name
srcname : str
Source name
"""
# Read variability file
fits = gammalib.GFits(filename)
table = fits.table(1)
c_gti_start = table['TSTART']
c_gti_stop = table['TSTOP']
c_sig = table[srcname]
# Convert the c_sig object to list
table_c_sig = []
table_c_gti = []
for k in c_sig:
table_c_sig.append(k)
for j, k in zip(c_gti_start, c_gti_stop):
table_c_gti.append(0.5*(j+k))
# Initializing the plots
axarr = []
f = plt.figure(figsize=(12,7))
ax1 = f.add_subplot(121)
ax2 = f.add_subplot(122)
axarr.append(ax1)
axarr.append(ax2)
# Create first plot
axarr[0].plot(table_c_gti, table_c_sig)
axarr[0].set_title('Significance evolution')
axarr[0].set_xlabel('MJD')
axarr[0].set_ylabel('Significance')
# Create second plot
axarr[1].hist(table_c_sig, 20, range=[min(table_c_sig), max(table_c_sig)],
histtype='stepfilled', facecolor='g', alpha=0.75)
axarr[1].set_title('Significance distribution')
axarr[1].set_xlabel('Significance')
axarr[1].set_ylabel('Counts')
# Optionally save result in file
if len(plotfile) > 0:
plt.savefig(plotfile)
else:
plt.show()
# Return
return
# ========================== #
# Show variability evolution #
# ========================== #
def show_variability_evolution():
"""
Show variability
"""
# Set usage string
usage = 'show_variability_evolution.py [-p plotfile] [-s source_name] [file]'
# Set default options
options = [{'option': '-p', 'value': ''},
{'option': '-s', 'value': 'MAXSIGPIXEL'}]
# 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']
srcname = options[1]['value']
# Show variability evolution
plot_variability_evolution(args[0], plotfile, srcname)
# Return
return
# ======================== #
# Main routine entry point #
# ======================== #
if __name__ == '__main__':
# Show variability evolution
show_variability_evolution()