def run(self, method='sherpa', outdir=None):
"""Run all steps
Parameters
----------
method : str {sherpa}
Fit method to use
outdir : Path, str
directory to write results files to
"""
cwd = Path.cwd()
outdir = cwd if outdir is None else make_path(outdir)
outdir.mkdir(exist_ok=True)
os.chdir(str(outdir))
self.set_default_thresholds()
if method == 'hspec':
self._run_hspec_fit()
elif method == 'sherpa':
self._run_sherpa_fit()
else:
raise ValueError('Undefined fitting method')
modelname = self.result.spectral_model
self.result.to_yaml('fit_result_{}.yaml'.format(modelname))
self.write_npred()
os.chdir(str(cwd))
def read(cls, phafile, rmffile=None):
"""Read PHA fits file
The energy binning is not contained in the PHA standard. Therefore is
is inferred from the corresponding RMF EBOUNDS extension.
Parameters
----------
phafile : str
PHA file with ``SPECTRUM`` extension
rmffile : str
RMF file with ``EBOUNDS`` extennsion, optional
"""
phafile = make_path(phafile)
spectrum = fits.open(str(phafile))['SPECTRUM']
counts = [val[1] for val in spectrum.data]
if rmffile is None:
val = spectrum.header['RESPFILE']
if val == '':
raise ValueError('RMF file not set in PHA header. '
'Please provide RMF file for energy binning')
parts = phafile.parts[:-1]
rmffile = Path.cwd()
for part in parts:
rmffile = rmffile.joinpath(part)
rmffile = rmffile.joinpath(val)
rmffile = make_path(rmffile)
ebounds = fits.open(str(rmffile))['EBOUNDS']
bins = EnergyBounds.from_ebounds(ebounds)
livetime = Quantity(0, 's')
return cls(counts, bins, livetime=livetime)
def run(self, method='sherpa', outdir=None):
"""Run all steps
Parameters
----------
method : str {sherpa}
Fit method to use
outdir : Path, str
directory to write results files to
"""
cwd = Path.cwd()
outdir = cwd if outdir is None else make_path(outdir)
outdir.mkdir(exist_ok=True)
os.chdir(str(outdir))
self.set_default_thresholds()
if method == 'hspec':
self._run_hspec_fit()
elif method == 'sherpa':
self._run_sherpa_fit()
else:
raise ValueError('Undefined fitting method')
modelname = self.result.spectral_model
self.result.to_yaml('fit_result_{}.yaml'.format(modelname))
self.write_npred()
os.chdir(str(cwd))
def stack_groups(self):
"""Stack observations in each group """
stacked_obs = list()
sorted_table = self.obs_table.group_by('GROUP_ID')
for group in sorted_table.groups:
group_id = group['GROUP_ID'][0]
log.info('Stacking observations in group {}'.format(group_id))
log.info('{}'.format([group['OBS_ID']]))
temp = SpectrumObservationList.from_observation_table(group)
stacked = SpectrumObservation.stack_observation_list(temp)
stacked.meta.phafile = 'pha_group{}.fits'.format(group_id)
stacked.meta.ogip_dir = Path.cwd() / 'ogip_data_stacked'
stacked_obs.append(stacked)
self.stacked_observations = SpectrumObservationList(stacked_obs)
def stack_groups(self):
"""Stack observations in each group """
stacked_obs = list()
sorted_table = self.obs_table.group_by('GROUP_ID')
for group in sorted_table.groups:
group_id = group['GROUP_ID'][0]
log.info('Stacking observations in group {}'.format(group_id))
log.info('{}'.format([group['OBS_ID']]))
temp = SpectrumObservationList.from_observation_table(group)
stacked = SpectrumObservation.stack_observation_list(temp)
stacked.meta.phafile = 'pha_group{}.fits'.format(group_id)
stacked.meta.ogip_dir = Path.cwd() / 'ogip_data_stacked'
stacked_obs.append(stacked)
self.stacked_observations = SpectrumObservationList(stacked_obs)
