from ximpol.evt.binning import xBinnedLightCurve
from ximpol.evt.binning import xBinnedPhasogram
VIEW_DICT = {
'PHA1' : xBinnedCountSpectrum,
'LC' : xBinnedLightCurve,
'PHASG': xBinnedPhasogram,
'CMAP' : xBinnedMap,
'MCUBE': xBinnedModulationCube
}
def xpviewbin(file_path):
"""Quick FITS image viewer.
"""
try:
binalg = fits.open(file_path)[0].header['BINALG']
except Exception as e:
abort('Could not determine file type (%s)' % e)
VIEW_DICT[binalg](file_path).plot(show=True)
if __name__ == '__main__':
import argparse
parser = argparse.ArgumentParser(description=__description__)
parser.add_argument('file_path', type=str,
help='the input FITS image file')
args = parser.parse_args()
startmsg()
xpviewbin(args.file_path)
time_integrated_spectrum = count_spectrum.build_time_integral()
else:
tsamples = source.sampling_time(kwargs['tstart'], kwargs['tstop'])
logger.info('Sampling times: %s' % tsamples)
count_spectrum = xCountSpectrum(source.energy_spectrum, aeff, tsamples)
time_integrated_spectrum = count_spectrum.build_time_integral()
# Thuis should be a callable method in the binning module.
ebinning = _make_binning(kwargs['ebinalg'], kwargs['emin'], kwargs['emax'],
kwargs['ebins'], kwargs['ebinning'])
# And this might be implemented in the irf.mrf module.
_x = time_integrated_spectrum.x
_y = time_integrated_spectrum.y * modf(_x)
mu_spectrum = xInterpolatedUnivariateSplineLinear(_x, _y)
for _emin, _emax in zip(ebinning[:-1], ebinning[1:]) +\
[(ebinning[0], ebinning[-1])]:
num_counts = count_spectrum.num_expected_counts(emin=_emin, emax=_emax)
mu_average = mu_spectrum.integral(_emin, _emax) / num_counts
mdp = 4.29 / mu_average / numpy.sqrt(num_counts)
logger.info('%.2f--%.2f keV: %d counts in %d s, mu %.3f, MDP %.2f%%' %\
(_emin, _emax, num_counts, observation_time, mu_average,
100*mdp))
if __name__ == '__main__':
args = PARSER.parse_args()
startmsg()
xpmdp(**args.__dict__)