def get_grb_mdp(grb_name, repointing=21600., obs_time=100000, \
aeff_file_path=os.path.join(XIMPOL_IRF,'fits',\
'xipe_baseline.arf'), \
mu_file_path=os.path.join(XIMPOL_IRF,'fits',\
'xipe_baseline.mrf')):
"""Calculate the MDP, given GRB name, the repointing elapsed time [sec]
after the trigger, and the oservationrange of time [sec]
"""
file_path = download_swift_grb_lc_file(grb_name)
if file_path is not None:
index = get_grb_spec_index(file_path)
E_light_curve = parse_light_curve(file_path,num_min_data=10.)
#E_light_curve.plot(logx=True,logy=True)
if E_light_curve is not None:
scale_factor = (2. - index)/(numpy.power(MAX_ENERGY, 2. - index) - \
numpy.power(MIN_ENERGY, 2. - index))
scale_factor *= 6.242e8
light_curve = E_light_curve.scale(scale_factor)
#light_curve.plot(logx=True,logy=True)
t_min = repointing
if t_min < light_curve.xmin():
logger.info('Repointing time < to the minimum time of the burst...')
return None
else:
t_max = t_min + obs_time
if t_max > light_curve.xmax():
t_max = light_curve.xmax()
norm = light_curve.integral(t_min,t_max)
_energy = numpy.linspace(2.,MAX_ENERGY,1000)
_modf = get_eff_mu(_energy,mu_file_path)
_spectrum = get_spectrum(_energy,norm,index,aeff_file_path)
energy_spectrum = xInterpolatedUnivariateSplineLinear(_energy,\
_spectrum)
#plt.xlim(1.,10.)
#energy_spectrum.plot(logx=True,logy=True)
num_evt = energy_spectrum.integral(MIN_ENERGY,MAX_ENERGY)
if not math.isnan(num_evt) and num_evt != 0.:
logger.info('Total estimated number of events: %i'\
%int(num_evt))
mu = numpy.average(_modf,weights=_spectrum)
mdp = mdp99(mu,int(num_evt))
if not math.isnan(mdp):
logger.info('%.2f--%.2f keV: %i counts (%.1e s), mu %.2f, MDP %.2f%%'\
%(MIN_ENERGY,MAX_ENERGY,int(num_evt),\
obs_time,mu,mdp*100))
return mdp
else:
return None
else:
logger.info('Total number of events cannot be estimated...')
return None
else:
return None
else:
return None
def get_integral_flux(grb_name,delta_t=600):
file_path = download_swift_grb_lc_file(grb_name)
if file_path is not None:
index = get_grb_spec_index(file_path)
E_light_curve = parse_light_curve(file_path,num_min_data=10.)
if E_light_curve is not None:
scale_factor = (2. - index)/(numpy.power(MAX_ENERGY, 2. - index) - \
numpy.power(MIN_ENERGY, 2. - index))
scale_factor *= 6.242e8
light_curve = E_light_curve.scale(scale_factor)
t_min = light_curve.xmin()
t_max = t_min + delta_t
flux = light_curve.integral(t_min,t_max)
return flux, light_curve.xmin()
else:
return None, None
else:
return None, None
def process_grb(grb_name, tstart=21600., duration=30000., prompt_duration=600):
"""
"""
file_path = download_swift_grb_lc_file(grb_name)
if file_path is None:
return None
pl_index = get_grb_spec_index(file_path)
ra, dec = get_grb_position(file_path)
light_curve = parse_light_curve(file_path, num_min_data=5.)
if light_curve is None:
return None
t = light_curve.x
grb_start, prompt_tstart = t[0], t[0]
grb_stop = t[-1]
prompt_tstop = t[0] + prompt_duration
prompt_flux = light_curve.integral(prompt_tstart, prompt_tstop)
logger.info('Integral energy flux in %.3f--%.3f s: %.3e erg cm^{-2}' %\
(prompt_tstart, prompt_tstop, prompt_flux))
tstart = max(tstart, t[0])
tstop = min(tstart + duration, t[-1])
logger.info('Effective time interval for the MDP: %.3f--%.3f s' %\
(tstart, tstop))
t = t[(t >= tstart)*(t <= tstop)]
if len(t) < 2:
return None
scale_factor = int_eflux2pl_norm(1., 0.3, 10., pl_index, erg=True)
pl_norm = light_curve.scale(scale_factor)# Fix the label.
def energy_spectrum(E, t):
return pl_norm(t)*numpy.power(E, -pl_index)
count_spectrum = xCountSpectrum(energy_spectrum, aeff, t)
mdp_table = count_spectrum.build_mdp_table(ENERGY_BINNING, modf)
logger.info(mdp_table)
mdp = mdp_table.mdp_values()[0]
eff_mu = [row.mu_effective for row in mdp_table.rows]
counts = [row.num_signal for row in mdp_table.rows]
grb_values = [ra, dec, pl_index, tstart, tstop, prompt_flux, prompt_tstart,\
prompt_tstop, grb_start, grb_stop, eff_mu[0], counts[0], mdp]
return grb_values