def get_round_mbo(self, index, mbo, model):
"""
get round observations, with simulated
galaxy images
"""
new_mbo = MultiBandObsList()
bpars=zeros(6)
n=Namer(model)
pname=n(self.pname)
pars=self.model_fits[pname][index].copy()
if self['use_logpars']:
pars[4:] = exp(pars[4:])
for band in xrange(self.nband):
bpars[0:5] = pars[0:5]
bpars[5] = pars[5+band]
obslist=mbo[band]
new_obslist = self.get_round_band_obslist(bpars,model,obslist)
new_mbo.append( new_obslist )
factor=ngmix.shape.get_round_factor(pars[2], pars[3])
Tround = pars[4]*factor
pars_round=pars.copy()
pars_round[2]=0.0
pars_round[3]=0.0
pars_round[4]=Tround
return new_mbo, pars_round
def _get_multi_band_observations(self, mindex):
"""
Get an ObsList object for the Coadd observations
Get a MultiBandObsList object for the SE observations.
"""
coadd_mb_obs_list = MultiBandObsList()
mb_obs_list = MultiBandObsList()
for band in self.iband:
cobs_list, obs_list = self._get_band_observations(band, mindex)
coadd_mb_obs_list.append(cobs_list)
mb_obs_list.append(obs_list)
meta_row = self._get_meta_row()
meta_row["id"][0] = self.meds_list[0]["id"][mindex]
meta_row["number"][0] = self.meds_list[0]["number"][mindex]
meta_row["nimage_tot"][0, :] = numpy.array(
[self.meds_list[b]["ncutout"][mindex] - 1 for b in xrange(self.conf["nband"])], dtype="i4"
)
meta = {"meta_data": meta_row, "meds_index": mindex, "id": self.meds_list[0]["id"][mindex], "obj_flags": 0}
coadd_mb_obs_list.update_meta_data(meta)
mb_obs_list.update_meta_data(meta)
return coadd_mb_obs_list, mb_obs_list
def get_mb_obs_list(self, index):
"""
raise MissingFit if any bands missing or no cutouts
"""
mbo=MultiBandObsList()
rev=self.rev_number
ncut=self.h_number[index]
print(" number:",index+1,"total cutouts:",ncut)
i=index
if rev[i] != rev[i+1]:
w=rev[ rev[i]:rev[i+1] ]
ed=self.epoch_data[w]
for band in xrange(self.nband):
obslist=self.get_band_obslist(index, band, ed)
mbo.append( obslist )
else:
raise MissingFit("band missing")
return mbo
def _trim_images(self, mbo_input, censky):
"""
cen in sky coords, relative to jacobian
center
"""
mbo = MultiBandObsList()
for obslist in mbo_input:
new_obslist=ObsList()
for obs in obslist:
j=obs.jacobian
scale=j.get_scale()
cenpix=array( j.get_cen() )
new_cen = cenpix + censky/scale
#print("cen0:",cenpix,"newcen:",new_cen)
new_im=_trim_image(obs.image, new_cen)
new_wt=_trim_image(obs.weight, new_cen)
new_j = j.copy()
new_j.set_cen(row=new_cen[0], col=new_cen[1])
newobs = Observation(
new_im,
weight=new_wt,
jacobian=new_j,
psf=obs.psf,
)
new_obslist.append( newobs )
mbo.append( new_obslist )
return mbo
def _get_multi_band_observations(self, mindex):
"""
Get an ObsList object for the Coadd observations
Get a MultiBandObsList object for the SE observations.
"""
coadd_mb_obs_list=MultiBandObsList()
mb_obs_list=MultiBandObsList()
for band in self.iband:
cobs_list, obs_list = self._get_band_observations(band, mindex)
coadd_mb_obs_list.append(cobs_list)
mb_obs_list.append(obs_list)
meta_row = self._get_meta_row()
meta_row['id'][0] = self.meds_list[0]['id'][mindex]
meta_row['number'][0] = self.meds_list[0]['number'][mindex]
# to account for max_cutouts limit, we count the actual number
#meta_row['nimage_tot'][0,:] = numpy.array([self.meds_list[b]['ncutout'][mindex]-1 for b in xrange(self.conf['nband'])],dtype='i4')
meta_row['nimage_tot'][0,:] = numpy.array([len(mb_obs_list[b]) for b in xrange(self.conf['nband'])],dtype='i4')
meta = {'meta_data':meta_row,'meds_index':mindex,'id':self.meds_list[0]['id'][mindex],'obj_flags':0}
coadd_mb_obs_list.update_meta_data(meta)
mb_obs_list.update_meta_data(meta)
return coadd_mb_obs_list, mb_obs_list
def mbobs():
mbobs = MultiBandObsList()
for i in range(3):
ol = ObsList()
for j in range(4):
o = Observation(image=np.ones((32, 32)) * (j + 1),
weight=np.ones((32, 32)) * (j + 1),
jacobian=ngmix.DiagonalJacobian(scale=0.25,
row=0,
col=0))
ol.append(o)
mbobs.append(ol)
return mbobs
def _get_good_mb_obs_list(self, mb_obs_list):
new_mb_obs_list = MultiBandObsList()
for obs_list in mb_obs_list:
new_obs_list = ObsList()
for obs in obs_list:
if obs.meta['flags'] == 0:
new_obs_list.append(obs)
new_mb_obs_list.append(new_obs_list)
new_mb_obs_list.update_meta_data(mb_obs_list.meta)
new_mb_obs_list.update_meta_data({'old_mb_obs_list': mb_obs_list})
return new_mb_obs_list
def _check_flags(self, mbobs):
flags = self['metacal'].get('bmask_flags', None)
passed_flags = True
_mbobs = None
if flags is not None:
_mbobs = MultiBandObsList()
_mbobs.update_meta_data(mbobs.meta)
for obslist in mbobs:
_obslist = ObsList()
_obslist.update_meta_data(obslist.meta)
for obs in obslist:
msk = (obs.bmask & flags) != 0
if np.any(msk):
logger.info(" EDGE HIT")
else:
_obslist.append(obs)
passed_flags = True
_mbobs.append(_obslist)
# all bands have to have at least one obs
for ol in _mbobs:
if len(ol) == 0:
passed_flags = False
return passed_flags, _mbobs
def _make_mbobs(im, cen):
dx = cen[0] - int(cen[0] + 0.5)
dy = cen[1] - int(cen[1] + 0.5)
xlow = int(int(cen[0] + 0.5) - nstamp_cen)
ylow = int(int(cen[1] + 0.5) - nstamp_cen)
_im = im[ylow:ylow + nstamp, xlow:xlow + nstamp]
jac = DiagonalJacobian(
scale=wcs.scale,
x=nstamp_cen + dx,
y=nstamp_cen + dy,
)
obs = Observation(image=_im,
jacobian=jac,
psf=psf_obs,
weight=np.ones_like(_im),
noise=rng.normal(size=_im.shape) * noise)
mbobs = MultiBandObsList()
obsl = ObsList()
obsl.append(obs)
mbobs.append(obsl)
return mbobs
def _strip_coadd(mbobs):
_mbobs = MultiBandObsList()
_mbobs.update_meta_data(mbobs.meta)
for ol in mbobs:
_ol = ObsList()
_ol.update_meta_data(ol.meta)
for i in range(1, len(ol)):
_ol.append(ol[i])
_mbobs.append(_ol)
return _mbobs
def _strip_zero_flux(mbobs):
_mbobs = MultiBandObsList()
_mbobs.update_meta_data(mbobs.meta)
for ol in mbobs:
_ol = ObsList()
_ol.update_meta_data(ol.meta)
for i in range(len(ol)):
if np.sum(ol[i].image) > 0:
_ol.append(ol[i])
_mbobs.append(_ol)
return _mbobs
def get_model_obs(
*, rng, model,
noise=0.0,
psf_model='turb',
psf_noise=1.0e-6,
set_psf_gmix=False,
set_templates=False,
set_psf_templates=False,
nepoch=None, nband=None,
star=False,
):
if nband is not None:
do_mbobs = True
if nepoch is None:
nepoch = 1
else:
do_mbobs = False
nband = 1
if nepoch is not None:
do_obslist = True
else:
do_obslist = False
nepoch = 1
if star:
T = 0.0
else:
T = 0.27
g1 = 0.1
g2 = 0.05
flux = 100.0
off = 0.5
# not offset from the jacobian center
pars = [0.0, 0.0, g1, g2, T] + [flux]*nband
gm = GMixModel(pars[0:6], model)
mbobs = MultiBandObsList()
for iband in range(nband):
obslist = ObsList()
for i in range(nepoch):
off1_pix, off2_pix = rng.uniform(low=-off, high=off, size=2)
dims = [32, 32]
jcen = (np.array(dims) - 1.0) / 2.0
jacob = DiagonalJacobian(
scale=PIXEL_SCALE,
row=jcen[0] + off1_pix,
col=jcen[1] + off2_pix,
)
psf_ret = get_psf_obs(rng=rng, model=psf_model, noise=psf_noise)
if set_psf_gmix:
psf_ret['obs'].set_gmix(psf_ret['gmix'])
if set_psf_templates:
psf_ret['obs'].template = psf_ret['gmix'].make_image(
dims,
jacobian=jacob,
)
gmconv = gm.convolve(psf_ret['gmix'])
im0 = gmconv.make_image(dims, jacobian=jacob)
im = im0 + rng.normal(size=im0.shape, scale=noise)
if noise == 0.0:
weight = im*0 + 1.0/1.0e-12
else:
weight = im*0 + 1.0/noise**2
obs = Observation(
im,
weight=weight,
jacobian=jacob,
psf=psf_ret['obs'],
)
if set_templates:
obs.template = im0
obslist.append(obs)
mbobs.append(obslist)
ret = {
'gmix': gm,
'pars': pars,
'psf_data': psf_ret,
}
if do_mbobs:
ret['obs'] = mbobs
else:
obslist = mbobs[0]
if not do_obslist:
obs = obslist[0]
ret['obs'] = obs
else:
ret['obs'] = obslist
return ret
def _get_multi_band_observations(self, mindex):
"""
Get an ObsList object for the Coadd observations
Get a MultiBandObsList object for the SE observations.
"""
coadd_mb_obs_list = MultiBandObsList()
mb_obs_list = MultiBandObsList()
for band in self.iband:
cobs_list, obs_list = self._get_band_observations(band, mindex)
coadd_mb_obs_list.append(cobs_list)
mb_obs_list.append(obs_list)
meta_row = self._get_meta_row()
meta_row['id'][0] = self.meds_list[0]['id'][mindex]
meta_row['number'][0] = self.meds_list[0]['number'][mindex]
meta_row['ra'][0] = self.meds_list[0]['ra'][mindex]
meta_row['dec'][0] = self.meds_list[0]['dec'][mindex]
# to account for max_cutouts limit, we count the actual number
#meta_row['nimage_tot'][0,:] = numpy.array([self.meds_list[b]['ncutout'][mindex]-1 for b in xrange(self.conf['nband'])],dtype='i4')
meta_row['nimage_tot'][0, :] = numpy.array(
[len(mb_obs_list[b]) for b in xrange(self.conf['nband'])],
dtype='i4')
meta = {
'meta_data': meta_row,
'meds_index': mindex,
'id': self.meds_list[0]['id'][mindex],
'obj_flags': 0
}
coadd_mb_obs_list.update_meta_data(meta)
mb_obs_list.update_meta_data(meta)
return coadd_mb_obs_list, mb_obs_list
