show_lightcurve.py
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#! /usr/bin/env python
# ==========================================================================
# Display lightcurve generated by cslightcrv
#
# Copyright (C) 2017-2020 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
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 lightcurve #
# =============== #
def plot_lightcurve(filename, plotfile):
"""
Plot lightcurve
Parameters
----------
filename : str
Name of lightcurve FITS file
plotfile : str
Plot file name
"""
# Read spectrum file
fits = gammalib.GFits(filename)
table = fits.table(1)
# Extract standard columns
c_mjd = table['MJD']
c_emjd = table['e_MJD']
c_ts = table['TS']
# Extract columns dependent on flux type
if table.contains('EnergyFlux'):
c_flux = table['EnergyFlux']
c_eflux = table['e_EnergyFlux']
c_upper = table['EFluxUpperLimit']
ylabel = r'E $\times$ dN/dE (erg cm$^{-2}$ s$^{-1}$)'
elif table.contains('PhotonFlux'):
c_flux = table['PhotonFlux']
c_eflux = table['e_PhotonFlux']
c_upper = table['FluxUpperLimit']
ylabel = r'N(E) (ph cm$^{-2}$ s$^{-1}$)'
else:
c_flux = table['Prefactor']
c_eflux = table['e_Prefactor']
c_upper = table['DiffUpperLimit']
ylabel = r'dN/dE (cm$^{-2}$ s$^{-1}$ MeV$^{-1}$)'
# Initialise arrays to be filled
mjd = []
e_mjd = []
flux = []
e_flux = []
ul_mjd = []
ul_e_mjd = []
ul_flux = []
ul_e_flux = []
# Loop over rows of the file
nrows = table.nrows()
for row in range(nrows):
# Get Test Statistic, flux and flux error
ts = c_ts.real(row)
flx = c_flux.real(row)
e_flx = c_eflux.real(row)
# If Test Statistic is larger than 9 and twice the flux error is
# smaller than the flux, then append flux point ...
if ts > 9.0 and 2.0*e_flx < flx:
mjd.append(c_mjd.real(row))
e_mjd.append(c_emjd.real(row))
flux.append(c_flux.real(row))
e_flux.append(c_eflux.real(row))
# ... otherwise append upper limit
else:
ul_mjd.append(c_mjd.real(row))
ul_e_mjd.append(c_emjd.real(row))
ul_flux.append(c_upper.real(row))
ul_e_flux.append(0.5*c_upper.real(row))
# Plot the spectrum
plt.figure()
plt.semilogy()
plt.grid()
plt.errorbar(mjd, flux, yerr=e_flux, xerr=[e_mjd, e_mjd],
fmt='ro')
plt.errorbar(ul_mjd, ul_flux, xerr=[ul_e_mjd, ul_e_mjd],
yerr=ul_e_flux, uplims=True, fmt='ro')
plt.xlabel('MJD (days)')
plt.ylabel(ylabel)
# Show figure
if len(plotfile) > 0:
plt.savefig(plotfile)
else:
plt.show()
# Return
return
# =============== #
# Show lightcurve #
# =============== #
def show_lightcurve():
"""
Show lightcurve
"""
# Set usage string
usage = 'show_lightcurve.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']
# Plot lightcurve
plot_lightcurve(args[0], plotfile)
# Return
return
# ======================== #
# Main routine entry point #
# ======================== #
if __name__ == '__main__':
# Show lightcurve
show_lightcurve()