def model_data_from_instance(self, instance):
galaxies = []
src_profiles = []
for profile in instance.profiles:
if isinstance(profile, al.mp.MassProfile):
galaxies.append(
al.Galaxy(
redshift=self.lens_redshift,
mass=profile,
))
else:
src_profiles.append(profile)
galaxies.append(
al.Galaxy(redshift=self.source_redshift,
light=al.lp.LightProfile()))
tracer = al.Tracer.from_galaxies(galaxies=galaxies)
lensed_cube = autolens_tracer_utils.lensed_cube_from_tracer(
tracer=tracer,
grid=self.masked_dataset.grid_3d.grid_2d,
cube=self.src_model_from_profiles(profiles=src_profiles))
# plot_utils.plot_cube(
# cube=lensed_cube,
# ncols=8
# )
# exit()
# NOTE: This is going to be used for the updated method to compute the lensed cube.
# lensed_cube = self.lensed_cube_from_tracer_and_src_profiles(
# src_profiles=src_profiles,
# tracer=tracer
# )
# plot_utils.plot_cube(
# cube=lensed_cube,
# ncols=8
# )
# exit()
model_data = np.zeros(shape=self.masked_dataset.data.shape)
for i in range(model_data.shape[0]):
model_data[i] = self.transformers[i].visibilities_from_image(
image=Image(array_2d=lensed_cube[i]))
return model_data
cube = cube_src_model_cont + cube_src_model_line
# plot_utils.plot_cube(
# cube=cube,
# ncols=8
# )
# exit()
lensed_cube = autolens_tracer_utils.lensed_cube_from_tracer(
tracer=al.Tracer.from_galaxies(
galaxies=[
al.Galaxy(
redshift=lens_redshift,
mass=lens_mass_profile,
),
al.Galaxy(
redshift=source_redshift,
light=al.lp.LightProfile()
)
]
),
grid=grid_3d.grid_2d,
cube=cube
)
# plot_utils.plot_cube(
# cube=lensed_cube,
# ncols=8
# )
# exit()
visibilities = np.zeros(
shape=uv_wavelengths.shape
def model_data_from_instance(self, instance):
len_profiles = []
src_profiles = []
for profile in instance.profiles:
if isinstance(profile, al.mp.MassProfile):
len_profiles.append(profile)
else:
src_profiles.append(profile)
galaxies = []
for profile in len_profiles:
galaxies.append(
al.Galaxy(
redshift=self.lens_redshift,
mass=profile,
))
src_cont_profiles = []
src_line_profiles = []
for profile in src_profiles:
if not profile.is_3d_profile:
src_cont_profiles.append(profile)
else:
src_line_profiles.append(profile)
# tracer_cont = al.Tracer.from_galaxies(
# galaxies=[
# *galaxies,
# *[
# al.Galaxy(
# redshift=self.source_redshift,
# light=profile,
# )
# for profile in src_cont_profiles
# ]
# ]
# )
#
# lensed_image = tracer_cont.profile_image_from_grid(
# grid=self.masked_dataset.grid_3d.grid_2d
# )
# # plt.figure()
# # plt.imshow(lensed_image.in_2d_binned)
# # plt.show()
# # exit()
#
# lensed_cube = autolens_tracer_utils.lensed_cube_from_tracer(
# tracer=al.Tracer.from_galaxies(
# galaxies=[
# *galaxies,
# al.Galaxy(
# redshift=self.source_redshift,
# light=al.lp.LightProfile()
# )
# ]
# ),
# grid=self.masked_dataset.grid_3d.grid_2d,
# cube=self.src_model_from_profiles(
# profiles=src_line_profiles
# )
# )
# # plot_utils.plot_cube(
# # cube=lensed_cube,
# # ncols=8
# # )
# # exit()
#
#
# model_data_cont = self.transformer_continuum.visibilities_from_image(
# image=lensed_image
# )
# #print(model_data_cont.shape)
#
# # TODO: subtract the continuum
#
# return {
# "continuum":model_data_cont
# }
lensed_cube_cont = autolens_tracer_utils.lensed_cube_from_tracer(
tracer=al.Tracer.from_galaxies(galaxies=[
*galaxies,
al.Galaxy(redshift=self.source_redshift,
light=al.lp.LightProfile())
]),
grid=self.masked_dataset.grid_3d.grid_2d,
cube=self.src_model_from_profiles(profiles=src_cont_profiles))
# plot_utils.plot_cube(
# cube=lensed_cube_cont,
# ncols=8
# )
# exit()
model_data_cont = self.transformer_continuum.visibilities_from_image(
image=Image(array_2d=lensed_cube_cont[0]))
return {"continuum": model_data_cont}
#exit()
"""
def test(dataset,
xy_mask,
profiles,
lens_redshift,
source_redshift,
transformer_class=al.TransformerFINUFFT):
def src_model_from_profiles(profiles, masked_dataset):
return sum([
profile.profile_cube_from_grid(
grid=masked_dataset.grid_3d.grid_2d,
shape_3d=masked_dataset.grid_3d.shape_3d,
z_step_kms=masked_dataset.z_step_kms)
for profile in profiles
])
masked_dataset = MaskedDataset(dataset=dataset, xy_mask=xy_mask)
transformers = []
for i in range(masked_dataset.uv_wavelengths.shape[0]):
transformers.append(
transformer_class(
uv_wavelengths=masked_dataset.uv_wavelengths[i],
grid=masked_dataset.grid_3d.grid_2d.in_radians))
len_profiles = []
src_profiles = []
for profile in profiles:
if isinstance(profile, al.mp.MassProfile):
len_profiles.append(profile)
else:
src_profiles.append(profile)
galaxies = []
for profile in len_profiles:
galaxies.append(al.Galaxy(
redshift=lens_redshift,
mass=profile,
))
galaxies.append(
al.Galaxy(redshift=source_redshift, light=al.lp.LightProfile()))
tracer = al.Tracer.from_galaxies(galaxies=galaxies)
cube = src_model_from_profiles(profiles=src_profiles,
masked_dataset=masked_dataset)
lensed_cube = autolens_tracer_utils.lensed_cube_from_tracer(
tracer=tracer, grid=masked_dataset.grid_3d.grid_2d, cube=cube)
model_data = np.zeros(shape=masked_dataset.data.shape)
for i in range(model_data.shape[0]):
model_data[i] = transformers[i].visibilities_from_image(
image=Image(array_2d=lensed_cube[i]))
# dirty_cube = autolens_plot_utils.dirty_cube_from_visibilities(
# visibilities=masked_dataset.data,
# transformers=transformers,
# shape=masked_dataset.grid_shape_3d
# )
#
# dirty_model_cube = autolens_plot_utils.dirty_cube_from_visibilities(
# visibilities=model_data,
# transformers=transformers,
# shape=masked_dataset.grid_shape_3d
# )
#
#
# velocities = np.linspace(
# -n_channels * z_step_kms / 2.0,
# +n_channels * z_step_kms / 2.0,
# n_channels
# )
# dirty_moment_0 = spectral_utils.moment_0(
# cube=dirty_cube,
# velocities=velocities
# )
# dirty_model_moment_0 = spectral_utils.moment_0(
# cube=dirty_model_cube,
# velocities=velocities
# )
# plt.figure()
# plt.imshow(dirty_moment_0 - dirty_model_moment_0, cmap="jet")
# plt.show()
# exit()
fit_plots.residual_map(fit=fit.DatasetFit(
masked_dataset=masked_dataset, model_data=model_data),
transformers=transformers)