def get_exp_list(self, psf2=None):
if psf2 is None:
psf2 = self.psfs
obs_list = ObsList()
psf_list = ObsList()
w = []
for i in range(len(self.gals)):
im = self.gals[i].array
im_psf = self.psfs[i].array
im_psf2 = psf2[i].array
weight = 1 / self.skys[i].array
jacob = self.gals[i].wcs.jacobian()
dx = self.offsets[i].x
dy = self.offsets[i].y
gal_jacob = Jacobian(row=self.gals[i].true_center.y + dy,
col=self.gals[i].true_center.x + dx,
dvdrow=jacob.dvdy,
dvdcol=jacob.dvdx,
dudrow=jacob.dudy,
dudcol=jacob.dudx)
psf_jacob2 = gal_jacob
mask = np.where(weight != 0)
w.append(np.mean(weight[mask]))
noise = old_div(np.ones_like(weight), w[-1])
psf_obs = Observation(im_psf,
jacobian=gal_jacob,
meta={
'offset_pixels': None,
'file_id': None
})
psf_obs2 = Observation(im_psf2,
jacobian=psf_jacob2,
meta={
'offset_pixels': None,
'file_id': None
})
obs = Observation(im,
weight=weight,
jacobian=gal_jacob,
psf=psf_obs,
meta={
'offset_pixels': None,
'file_id': None
})
obs.set_noise(noise)
obs_list.append(obs)
psf_list.append(psf_obs2)
return obs_list, psf_list, np.array(w)
def get_exp_list(gals_array, psfs_array, offsets, skys_array, gal_true, gal_jacobs, psf2=None):
#def get_exp_list(gal, psf, sky_stamp, psf2=None):
if psf2 is None:
psf2 = psfs_array
obs_list=ObsList()
psf_list=ObsList()
w = []
for i in range(len(gals_array)):
im = gals_array[i]
im_psf = psfs_array[i]
im_psf2 = psf2[i]
weight = 1/skys_array[i]
jacob = gal_jacobs[i]
dx = offsets[i].x
dy = offsets[i].y
gal_jacob = Jacobian(
row=gal_true[i].y+dy,
col=gal_true[i].x+dx,
dvdrow=jacob.dvdy,
dvdcol=jacob.dvdx,
dudrow=jacob.dudy,
dudcol=jacob.dudx)
psf_jacob2 = gal_jacob
print(gal_jacob)
mask = np.where(weight!=0)
w.append(np.mean(weight[mask]))
noise = old_div(np.ones_like(weight),w[-1])
psf_obs = Observation(im_psf, jacobian=gal_jacob, meta={'offset_pixels':None,'file_id':None})
psf_obs2 = Observation(im_psf2, jacobian=psf_jacob2, meta={'offset_pixels':None,'file_id':None})
obs = Observation(im, weight=weight, jacobian=gal_jacob, psf=psf_obs, meta={'offset_pixels':None,'file_id':None})
obs.set_noise(noise)
obs_list.append(obs)
psf_list.append(psf_obs2)
return obs_list,psf_list,np.array(w)
def get_exp_list_coadd(m, i, m2=None):
def make_jacobian(dudx, dudy, dvdx, dvdy, x, y):
j = galsim.JacobianWCS(dudx, dudy, dvdx, dvdy)
return j.withOrigin(galsim.PositionD(x, y))
oversample = 1
#def psf_offset(i,j,star_):
m3 = [0]
#relative_offset=[0]
for jj, psf_ in enumerate(m2): # m2 has psfs for each observation.
if jj == 0:
continue
gal_stamp_center_row = m['orig_start_row'][i][jj] + m['box_size'][
i] / 2 - 0.5 # m['box_size'] is the galaxy stamp size.
gal_stamp_center_col = m['orig_start_col'][i][jj] + m['box_size'][
i] / 2 - 0.5 # m['orig_start_row/col'] is in SCA coordinates.
psf_stamp_size = 32
# Make the bounds for the psf stamp.
b = galsim.BoundsI(
xmin=(m['orig_start_col'][i][jj] +
(m['box_size'][i] - 32) / 2. - 1) * oversample + 1,
xmax=(m['orig_start_col'][i][jj] +
(m['box_size'][i] - 32) / 2. + psf_stamp_size - 1) *
oversample,
ymin=(m['orig_start_row'][i][jj] +
(m['box_size'][i] - 32) / 2. - 1) * oversample + 1,
ymax=(m['orig_start_row'][i][jj] +
(m['box_size'][i] - 32) / 2. + psf_stamp_size - 1) *
oversample)
# Make wcs for oversampled psf.
wcs_ = make_jacobian(
m.get_jacobian(i, jj)['dudcol'] / oversample,
m.get_jacobian(i, jj)['dudrow'] / oversample,
m.get_jacobian(i, jj)['dvdcol'] / oversample,
m.get_jacobian(i, jj)['dvdrow'] / oversample,
m['orig_col'][i][jj] * oversample,
m['orig_row'][i][jj] * oversample)
# Taken from galsim/roman_psfs.py line 266. Update each psf to an object-specific psf using the wcs.
scale = galsim.PixelScale(wfirst.pixel_scale / oversample)
psf_ = wcs_.toWorld(scale.toImage(psf_),
image_pos=galsim.PositionD(wfirst.n_pix / 2,
wfirst.n_pix / 2))
# Convolve with the star model and get the psf stamp.
#st_model = galsim.DeltaFunction(flux=1.)
#st_model = st_model.evaluateAtWavelength(wfirst.getBandpasses(AB_zeropoint=True)['H158'].effective_wavelength)
#st_model = st_model.withFlux(1.)
#st_model = galsim.Convolve(st_model, psf_)
psf_ = galsim.Convolve(psf_, galsim.Pixel(wfirst.pixel_scale))
psf_stamp = galsim.Image(b, wcs=wcs_)
# Galaxy is being drawn with some subpixel offsets, so we apply the offsets when drawing the psf too.
offset_x = m['orig_col'][i][jj] - gal_stamp_center_col
offset_y = m['orig_row'][i][jj] - gal_stamp_center_row
offset = galsim.PositionD(offset_x, offset_y)
if (offset_x <= -1.0 or offset_y <= -1.0):
print(offset)
elif (offset_x >= 1.0 or offset_y >= 1.0):
print(offset)
psf_.drawImage(image=psf_stamp, offset=offset, method='no_pixel')
m3.append(psf_stamp.array)
obs_list = ObsList()
psf_list = ObsList()
included = []
w = []
# For each of these objects create an observation
for j in range(m['ncutout'][i]):
if j == 0:
continue
# if j>1:
# continue
im = m.get_cutout(i, j, type='image')
weight = m.get_cutout(i, j, type='weight')
im_psf = m3[j]
im_psf2 = im_psf
if np.sum(im) == 0.:
#print(local_meds, i, j, np.sum(im))
print('no flux in image ', i, j)
continue
jacob = m.get_jacobian(i, j)
# Get a galaxy jacobian.
gal_jacob = Jacobian(
row=(m['orig_row'][i][j] - m['orig_start_row'][i][j]),
col=(m['orig_col'][i][j] - m['orig_start_col'][i][j]),
dvdrow=jacob['dvdrow'],
dvdcol=jacob['dvdcol'],
dudrow=jacob['dudrow'],
dudcol=jacob['dudcol'])
psf_center = (32 / 2.) + 0.5
# Get a oversampled psf jacobian.
if oversample == 1:
psf_jacob2 = Jacobian(
row=15.5 +
(m['orig_row'][i][j] - m['orig_start_row'][i][j] + 1 -
(m['box_size'][i] / 2. + 0.5)) * oversample,
col=15.5 +
(m['orig_col'][i][j] - m['orig_start_col'][i][j] + 1 -
(m['box_size'][i] / 2. + 0.5)) * oversample,
dvdrow=jacob['dvdrow'] / oversample,
dvdcol=jacob['dvdcol'] / oversample,
dudrow=jacob['dudrow'] / oversample,
dudcol=jacob['dudcol'] / oversample)
elif oversample == 4:
psf_jacob2 = Jacobian(
row=63.5 +
(m['orig_row'][i][j] - m['orig_start_row'][i][j] + 1 -
(m['box_size'][i] / 2. + 0.5)) * oversample,
col=63.5 +
(m['orig_col'][i][j] - m['orig_start_col'][i][j] + 1 -
(m['box_size'][i] / 2. + 0.5)) * oversample,
dvdrow=jacob['dvdrow'] / oversample,
dvdcol=jacob['dvdcol'] / oversample,
dudrow=jacob['dudrow'] / oversample,
dudcol=jacob['dudcol'] / oversample)
# Create an obs for each cutout
mask = np.where(weight != 0)
if 1. * len(weight[mask]) / np.product(np.shape(weight)) < 0.8:
continue
w.append(np.mean(weight[mask]))
noise = np.ones_like(weight) / w[-1]
psf_obs = Observation(im_psf,
jacobian=gal_jacob,
meta={
'offset_pixels': None,
'file_id': None
})
psf_obs2 = Observation(im_psf2,
jacobian=psf_jacob2,
meta={
'offset_pixels': None,
'file_id': None
})
#obs = Observation(im, weight=weight, jacobian=gal_jacob, psf=psf_obs, meta={'offset_pixels':None,'file_id':None})
# oversampled PSF
obs = Observation(im,
weight=weight,
jacobian=gal_jacob,
psf=psf_obs2,
meta={
'offset_pixels': None,
'file_id': None
})
obs.set_noise(noise)
obs_list.append(obs)
psf_list.append(psf_obs2)
included.append(j)
return obs_list, psf_list, np.array(included) - 1, np.array(w)
def get_exp_list(gal, psf, offsets, sky_stamp, psf2=None):
#def get_exp_list(gal, psf, sky_stamp, psf2=None):
if psf2 is None:
psf2 = psf
obs_list = ObsList()
psf_list = ObsList()
w = []
for i in range(len(gal)):
im = gal[i].array
im_psf = psf[i].array
im_psf2 = psf2[i].array
weight = 1 / sky_stamp[i].array
jacob = gal[i].wcs.jacobian()
dx = offsets[i].x
dy = offsets[i].y
gal_jacob = Jacobian(row=gal[i].true_center.y + dy,
col=gal[i].true_center.x + dx,
dvdrow=jacob.dvdy,
dvdcol=jacob.dvdx,
dudrow=jacob.dudy,
dudcol=jacob.dudx)
#gal_jacob = Jacobian(
# row=gal[i].true_center.x+dx,
# col=gal[i].true_center.y+dy,
# dvdrow=jacob.dudx,
# dvdcol=jacob.dudy,
# dudrow=jacob.dvdx,
# dudcol=jacob.dvdy)
psf_jacob2 = gal_jacob
mask = np.where(weight != 0)
w.append(np.mean(weight[mask]))
noise = old_div(np.ones_like(weight), w[-1])
psf_obs = Observation(im_psf,
jacobian=gal_jacob,
meta={
'offset_pixels': None,
'file_id': None
})
psf_obs2 = Observation(im_psf2,
jacobian=psf_jacob2,
meta={
'offset_pixels': None,
'file_id': None
})
obs = Observation(im,
weight=weight,
jacobian=gal_jacob,
psf=psf_obs,
meta={
'offset_pixels': None,
'file_id': None
})
obs.set_noise(noise)
obs_list.append(obs)
psf_list.append(psf_obs2)
#print(obs_list)
return obs_list, psf_list, np.array(w)
