def _get_band_observations(self, band, mindex):
"""
Get an ObsList for the coadd observations in each band
If psf fitting fails, the ObsList will be zero length
note we have already checked that we have a coadd and a single epoch
without flags
"""
meds = self.meds_list[band]
ncutout = meds['ncutout'][mindex]
image_flags = self._get_image_flags(band, mindex)
coadd_obs_list = ObsList()
obs_list = ObsList()
fake = numpy.zeros((0, 0))
for icut in xrange(ncutout):
flags = 0
if not self._should_use_obs(band, mindex, icut):
obs = Observation(fake)
flags = IMAGE_FLAGS
else:
iflags = image_flags[icut]
if iflags != 0:
flags = IMAGE_FLAGS
obs = Observation(fake)
else:
obs = self._get_band_observation(band, mindex, icut)
if obs is None:
flags = IMAGE_FLAGS
obs = Observation(fake)
# fill the meta data
self._fill_obs_meta_data(obs, band, mindex, icut)
# set flags
meta = {'flags': flags}
obs.update_meta_data(meta)
if icut == 0:
coadd_obs_list.append(obs)
else:
obs_list.append(obs)
if self.conf['reject_outliers'] and len(obs_list) > 0:
self._reject_outliers(obs_list)
obs_list.update_meta_data({'band_num': band})
coadd_obs_list.update_meta_data({'band_num': band})
return coadd_obs_list, obs_list
def _get_band_observations(self, band, mindex):
"""
Get an ObsList for the coadd observations in each band
If psf fitting fails, the ObsList will be zero length
note we have already checked that we have a coadd and a single epoch
without flags
"""
meds=self.meds_list[band]
ncutout=meds['ncutout'][mindex]
image_flags=self._get_image_flags(band, mindex)
coadd_obs_list = ObsList()
obs_list = ObsList()
fake=numpy.zeros((0,0))
for icut in xrange(ncutout):
flags=0
if not self._should_use_obs(band, mindex, icut):
obs = Observation(fake)
flags = IMAGE_FLAGS
else:
iflags = image_flags[icut]
if iflags != 0:
flags = IMAGE_FLAGS
obs = Observation(fake)
else:
obs = self._get_band_observation(band, mindex, icut)
if obs is None:
flags = IMAGE_FLAGS
obs = Observation(fake)
# fill the meta data
self._fill_obs_meta_data(obs,band,mindex,icut)
# set flags
meta = {'flags':flags}
obs.update_meta_data(meta)
if icut==0:
coadd_obs_list.append(obs)
else:
obs_list.append(obs)
if self.conf['reject_outliers'] and len(obs_list) > 0:
self._reject_outliers(obs_list)
obs_list.update_meta_data({'band_num':band})
coadd_obs_list.update_meta_data({'band_num':band})
return coadd_obs_list, obs_list
def _get_band_observations(self, band, mindex):
"""
Get an ObsList for the coadd observations in each band
If psf fitting fails, the ObsList will be zero length
note we have already checked that we have a coadd and a single epoch
without flags
"""
meds = self.meds_list[band]
ncutout = meds["ncutout"][mindex]
image_flags = self._get_image_flags(band, mindex)
coadd_obs_list = ObsList()
obs_list = ObsList()
for icut in xrange(ncutout):
iflags = image_flags[icut]
if iflags != 0:
flags = IMAGE_FLAGS
obs = Observation(numpy.zeros((0, 0)))
else:
obs = self._get_band_observation(band, mindex, icut)
flags = 0
# fill the meta data
self._fill_obs_meta_data(obs, band, mindex, icut)
# set flags
meta = {"flags": flags}
obs.update_meta_data(meta)
if icut == 0:
coadd_obs_list.append(obs)
else:
obs_list.append(obs)
"""
if ncutout == 0:
for o in [coadd_obs_list,obs_list]:
flags = IMAGE_FLAGS
obs = Observation(numpy.zeros((0,0)))
meta = {'flags':flags}
obs.update_meta_data(meta)
o.append(obs)
"""
if self.conf["reject_outliers"] and len(obs_list) > 0:
self._reject_outliers(obs_list)
return coadd_obs_list, obs_list
def _get_psf_observation(self, band, mindex, icut, image_jacobian):
"""
Get an Observation representing the PSF and the "sigma"
from the psf model
"""
im, cen, sigma_pix, fname = self._get_psf_image(band, mindex, icut)
psf_jacobian = image_jacobian.copy()
psf_jacobian.set_cen(cen[0], cen[1])
psf_obs = Observation(im, jacobian=psf_jacobian)
psf_obs.filename = fname
# convert to sky coords
sigma_sky = sigma_pix * psf_jacobian.get_scale()
psf_obs.update_meta_data({"sigma_sky": sigma_sky})
psf_obs.update_meta_data({"Tguess": sigma_sky * sigma_sky})
psf_obs.update_meta_data({"psf_norm": im.sum()})
return psf_obs
def _get_psf_observation(self, band, mindex, icut, image_jacobian):
"""
Get an Observation representing the PSF and the "sigma"
from the psf model
"""
im, cen, sigma_pix, fname = self._get_psf_image(band, mindex, icut)
psf_jacobian = image_jacobian.copy()
psf_jacobian.set_cen(row=cen[0], col=cen[1])
psf_obs = Observation(im, jacobian=psf_jacobian)
psf_obs.filename = fname
# convert to sky coords
sigma_sky = sigma_pix * psf_jacobian.get_scale()
psf_obs.update_meta_data({'sigma_sky': sigma_sky})
psf_obs.update_meta_data({'Tguess': sigma_sky * sigma_sky})
psf_obs.update_meta_data({'psf_norm': im.sum()})
return psf_obs
