def get_mbobs(self, iobj, weight_type='weight'):
"""Get a `MultiBandObsList` for a given object.
Parameters
----------
iobj : int
Index of the object.
weight_type: string, optional
Weight type. can be one of
'weight': the actual weight map
'uberseg': uberseg modified weight map
'cweight': weight map zeroed outside the object's seg map
'cseg': weight map zeroed outside of circular aperture that
doesn't touch any other object.
'cseg-canonical': same as 'cseg' but uses the postage stamp
center instead of the object's position.
Default is 'weight'
Returns
-------
mbobs : ngmix.MultiBandObsList
A `MultiBandObsList` holding all of the observations for this
object.
"""
mbobs = MultiBandObsList()
for m in self.mlist:
obslist = m.get_obslist(iobj, weight_type=weight_type)
mbobs.append(obslist)
return mbobs
def create_mb(mb_mod, bg_rms, coord1, coord2, psf_bg_rms, psf_im, noise):
#creats multiband object
mb = MultiBandObsList()
for i in range(len(mb_mod[:])):
o = observation(mb_mod[i], bg_rms, coord1, coord2, psf_bg_rms, psf_im)
o.noise = noise[i]
olist = ObsList()
olist.append(o)
mb.append(olist)
return mb
def _get_mof_obs(self):
im, psf_im, coords, dims, dx1, dy1, noises = self.sim()
bg_rms = self.sim['Image']['Bgrms'] / np.sqrt(len(im))
bg_rms_psf = self.sim['Psf']['Bgrms_psf']
psf_ccen = (np.array(psf_im.shape) - 1.0) / 2.0
psf_jacob = ngmix.UnitJacobian(
row=psf_ccen[0],
col=psf_ccen[1],
)
psf_weight = psf_im * 0 + 1.0 / bg_rms_psf**2
psf_obs = ngmix.Observation(
psf_im,
weight=psf_weight,
jacobian=psf_jacob,
)
psf_gmix = self._fit_psf_admom(psf_obs)
psf_obs.set_gmix(psf_gmix)
mb = MultiBandObsList()
for i in range(len(im)):
if self.show:
import images
tim = im[i] / im[i].max()
tim = np.log10(tim - tim.min() + 1.0)
images.view(tim)
if 'q' == input('hit a key: (q to quit) '):
stop
weight = im[i] * 0 + 1.0 / bg_rms**2
jacobian = ngmix.UnitJacobian(
row=0,
col=0,
)
obs = ngmix.Observation(
im[i],
weight=weight,
jacobian=jacobian,
psf=psf_obs,
)
obs.noise = noises[i]
olist = ObsList()
olist.append(obs)
mb.append(olist)
return mb, coords
def test_multibandobslist_smoke():
rng = np.random.RandomState(seed=11)
meta = {'duh': 5}
mbobs = MultiBandObsList(meta=meta)
for _ in range(5):
obslist = ObsList()
for _ in range(3):
obslist.append(Observation(image=rng.normal(size=(13, 15))))
mbobs.append(obslist)
assert mbobs.meta == meta
rng = np.random.RandomState(seed=11)
for obslist in mbobs:
for obs in obslist:
assert np.all(obs.image == rng.normal(size=(13, 15)))
def test_multibandobslist_s2n():
rng = np.random.RandomState(seed=11)
mbobs = MultiBandObsList()
numer = 0
denom = 0
for _ in range(5):
obslist = ObsList()
for _ in range(3):
img = rng.normal(size=(13, 15))
obslist.append(Observation(image=img))
numer += np.sum(img)
denom += np.sum(1.0 / obslist[-1].weight)
mbobs.append(obslist)
s2n = mbobs.get_s2n()
assert s2n == numer / np.sqrt(denom)
def test_multibandobslist_s2n_zeroweight():
rng = np.random.RandomState(seed=11)
mbobs = MultiBandObsList()
for _ in range(5):
obslist = ObsList()
for _ in range(3):
img = rng.normal(size=(13, 15))
obslist.append(
Observation(
image=img,
weight=np.zeros((13, 15)),
store_pixels=False,
))
mbobs.append(obslist)
assert np.allclose(mbobs.get_s2n(), -9999)
def test_get_mbobs():
rng = np.random.RandomState(seed=11)
obs = Observation(image=rng.normal(size=(11, 13)))
mbobs = get_mb_obs(obs)
rng = np.random.RandomState(seed=11)
assert np.all(mbobs[0][0].image == rng.normal(size=(11, 13)))
assert len(mbobs) == 1
assert len(mbobs[0]) == 1
rng = np.random.RandomState(seed=12)
obslist = ObsList()
for _ in range(3):
obslist.append(Observation(image=rng.normal(size=(11, 13))))
mbobs = get_mb_obs(obslist)
rng = np.random.RandomState(seed=12)
for obs in mbobs[0]:
assert np.all(obs.image == rng.normal(size=(11, 13)))
assert len(mbobs) == 1
assert len(mbobs[0]) == 3
rng = np.random.RandomState(seed=13)
mbobs = MultiBandObsList()
for _ in range(5):
obslist = ObsList()
for _ in range(3):
obslist.append(Observation(image=rng.normal(size=(13, 15))))
mbobs.append(obslist)
new_mbobs = get_mb_obs(mbobs)
rng = np.random.RandomState(seed=13)
for obslist in new_mbobs:
for obs in obslist:
assert np.all(obs.image == rng.normal(size=(13, 15)))
with pytest.raises(ValueError):
get_mb_obs(None)
def test_multibandobslist_set():
rng = np.random.RandomState(seed=11)
meta = {'duh': 5}
mbobs = MultiBandObsList(meta=meta)
for _ in range(5):
obslist = ObsList()
for _ in range(3):
obslist.append(Observation(image=rng.normal(size=(13, 15))))
mbobs.append(obslist)
assert mbobs.meta == meta
new_meta = {'blah': 6}
mbobs.meta = new_meta
assert mbobs.meta == new_meta
new_meta = {'bla': 6}
new_meta.update(mbobs.meta)
mbobs.update_meta_data({'bla': 6})
assert mbobs.meta == new_meta
rng = np.random.RandomState(seed=12)
new_obs = Observation(image=rng.normal(size=(13, 15)))
rng = np.random.RandomState(seed=11)
for obslist in mbobs:
for obs in obslist:
assert np.all(obs.image == rng.normal(size=(13, 15)))
mbobs[1][2] = new_obs
assert np.all(mbobs[1][2].image == new_obs.image)
rng = np.random.RandomState(seed=13)
obslist = ObsList()
for _ in range(4):
obslist.append(Observation(image=rng.normal(size=(13, 15))))
mbobs[2] = obslist
rng = np.random.RandomState(seed=13)
for obs in mbobs[2]:
assert np.all(obs.image == rng.normal(size=(13, 15)))
def multiband_coadd():
local_Hmeds = './fiducial_H158_2285117.fits'
local_Jmeds = './fiducial_J129_2285117.fits'
local_Fmeds = './fiducial_F184_2285117.fits'
truth = fio.FITS(
'/hpc/group/cosmology/phy-lsst/my137/roman_H158/g1002/truth/fiducial_lensing_galaxia_g1002_truth_gal.fits'
)[-1]
m_H158 = meds.MEDS(local_Hmeds)
m_J129 = meds.MEDS(local_Jmeds)
m_F184 = meds.MEDS(local_Fmeds)
indices_H = np.arange(len(m_H158['number'][:]))
indices_J = np.arange(len(m_J129['number'][:]))
indices_F = np.arange(len(m_F184['number'][:]))
roman_H158_psfs = get_psf_SCA('H158')
roman_J129_psfs = get_psf_SCA('J129')
roman_F184_psfs = get_psf_SCA('F184')
oversample = 1
metacal_keys = ['noshear', '1p', '1m', '2p', '2m']
res_noshear = np.zeros(len(m_H158['number'][:]),
dtype=[('ind', int), ('ra', float), ('dec', float),
('flags', int), ('coadd_px', float),
('coadd_py', float), ('coadd_flux', float),
('coadd_snr', float), ('coadd_e1', float),
('coadd_e2', float), ('coadd_hlr', float),
('coadd_psf_e1', float),
('coadd_psf_e2', float),
('coadd_psf_T', float)])
res_1p = np.zeros(len(m_H158['number'][:]),
dtype=[('ind', int), ('ra', float), ('dec', float),
('flags', int), ('coadd_px', float),
('coadd_py', float), ('coadd_flux', float),
('coadd_snr', float), ('coadd_e1', float),
('coadd_e2', float), ('coadd_hlr', float),
('coadd_psf_e1', float), ('coadd_psf_e2', float),
('coadd_psf_T', float)])
res_1m = np.zeros(len(m_H158['number'][:]),
dtype=[('ind', int), ('ra', float), ('dec', float),
('flags', int), ('coadd_px', float),
('coadd_py', float), ('coadd_flux', float),
('coadd_snr', float), ('coadd_e1', float),
('coadd_e2', float), ('coadd_hlr', float),
('coadd_psf_e1', float), ('coadd_psf_e2', float),
('coadd_psf_T', float)])
res_2p = np.zeros(len(m_H158['number'][:]),
dtype=[('ind', int), ('ra', float), ('dec', float),
('flags', int), ('coadd_px', float),
('coadd_py', float), ('coadd_flux', float),
('coadd_snr', float), ('coadd_e1', float),
('coadd_e2', float), ('coadd_hlr', float),
('coadd_psf_e1', float), ('coadd_psf_e2', float),
('coadd_psf_T', float)])
res_2m = np.zeros(len(m_H158['number'][:]),
dtype=[('ind', int), ('ra', float), ('dec', float),
('flags', int), ('coadd_px', float),
('coadd_py', float), ('coadd_flux', float),
('coadd_snr', float), ('coadd_e1', float),
('coadd_e2', float), ('coadd_hlr', float),
('coadd_psf_e1', float), ('coadd_psf_e2', float),
('coadd_psf_T', float)])
res_tot = [res_noshear, res_1p, res_1m, res_2p, res_2m]
for i, ii in enumerate(
indices_H): # looping through all the objects in meds file.
if i % 100 == 0:
print('object number ', i)
ind = m_H158['number'][ii]
t = truth[ind]
sca_Hlist = m_H158[ii][
'sca'] # List of SCAs for the same object in multiple observations.
sca_Jlist = m_J129[ii]['sca']
sca_Flist = m_F184[ii]['sca']
m2_H158_coadd = [
roman_H158_psfs[j - 1] for j in sca_Hlist[:m_H158['ncutout'][i]]
]
m2_J129_coadd = [
roman_J129_psfs[j - 1] for j in sca_Jlist[:m_J129['ncutout'][i]]
]
m2_F184_coadd = [
roman_F184_psfs[j - 1] for j in sca_Flist[:m_F184['ncutout'][i]]
]
obs_Hlist, psf_Hlist, included_H, w_H = get_exp_list_coadd(
m_H158, ii, m2=m2_H158_coadd)
coadd_H = psc.Coadder(obs_Hlist, flat_wcs=True).coadd_obs
coadd_H.psf.image[
coadd_H.psf.image < 0] = 0 # set negative pixels to zero.
coadd_H.set_meta({'offset_pixels': None, 'file_id': None})
obs_Jlist, psf_Jlist, included_J, w_J = get_exp_list_coadd(
m_J129, ii, m2=m2_J129_coadd)
coadd_J = psc.Coadder(obs_Jlist, flat_wcs=True).coadd_obs
coadd_J.psf.image[
coadd_J.psf.image < 0] = 0 # set negative pixels to zero.
coadd_J.set_meta({'offset_pixels': None, 'file_id': None})
obs_Flist, psf_Flist, included_F, w_F = get_exp_list_coadd(
m_F184, ii, m2=m2_F184_coadd)
coadd_F = psc.Coadder(obs_Flist, flat_wcs=True).coadd_obs
coadd_F.psf.image[
coadd_F.psf.image < 0] = 0 # set negative pixels to zero.
coadd_F.set_meta({'offset_pixels': None, 'file_id': None})
coadd = [coadd_H, coadd_J, coadd_F]
mb_obs_list = MultiBandObsList()
#coadd = [coadd_H]
for band in range(3):
obs_list = ObsList()
new_coadd_psf_block = block_reduce(coadd[band].psf.image,
block_size=(4, 4),
func=np.sum)
new_coadd_psf_jacob = Jacobian(
row=15.5,
col=15.5,
dvdrow=(coadd[band].psf.jacobian.dvdrow * oversample),
dvdcol=(coadd[band].psf.jacobian.dvdcol * oversample),
dudrow=(coadd[band].psf.jacobian.dudrow * oversample),
dudcol=(coadd[band].psf.jacobian.dudcol * oversample))
coadd_psf_obs = Observation(new_coadd_psf_block,
jacobian=new_coadd_psf_jacob,
meta={
'offset_pixels': None,
'file_id': None
})
coadd[band].psf = coadd_psf_obs
obs_list.append(coadd[band])
mb_obs_list.append(obs_list)
iteration = 0
for key in metacal_keys:
res_tot[iteration]['ind'][i] = ind
res_tot[iteration]['ra'][i] = t['ra']
res_tot[iteration]['dec'][i] = t['dec']
iteration += 1
#print(i, t['size'], mb_obs_list[0][0].image.sum(), mb_obs_list[1][0].image.sum(), mb_obs_list[2][0].image.sum())
res_ = measure_shape_metacal_multiband(
mb_obs_list,
t['size'],
method='bootstrap',
fracdev=t['bflux'],
use_e=[t['int_e1'], t['int_e2']])
iteration = 0
for key in metacal_keys:
if res_ == 0:
res_tot[iteration]['ind'][i] = 0
elif res_[key]['flags'] == 0:
res_tot[iteration]['coadd_px'][i] = res_[key]['pars'][0]
res_tot[iteration]['coadd_py'][i] = res_[key]['pars'][1]
res_tot[iteration]['coadd_snr'][i] = res_[key]['s2n']
res_tot[iteration]['coadd_e1'][i] = res_[key]['pars'][2]
res_tot[iteration]['coadd_e2'][i] = res_[key]['pars'][3]
res_tot[iteration]['coadd_hlr'][i] = res_[key]['pars'][4]
iteration += 1
mask = res_tot[0]['ind'] != 0
print(len(res_tot[0]), len(res_tot[0][mask]))
#print(res_['noshear'].dtype.names)
print('done')
def test_multibandobslist_append_err():
mbobs = MultiBandObsList()
with pytest.raises(AssertionError):
mbobs.append(None)
