),
n_channels=n_channels
)
# xy_mask = Mask3D.unmasked(
# shape_3d=grid_3d.shape_3d,
# pixel_scales=grid_3d.pixel_scales,
# sub_size=grid_3d.sub_size,
# )
xy_mask = Mask3D.manual(
mask_2d=al.Mask.circular(
shape_2d=grid_3d.shape_2d,
pixel_scales=grid_3d.pixel_scales,
sub_size=grid_3d.sub_size,
radius=2.5,
centre=(0.0, 0.0)
),
z_mask=np.full(
shape=grid_3d.shape_3d[0],
fill_value=False
),
)
#exit()
transformers = []
for i in range(uv_wavelengths.shape[0]):
transformer = transformer_class(
uv_wavelengths=uv_wavelengths[i],
grid=aa.structures.grids.MaskedGrid.from_mask(
mask=xy_mask.mask_2d
).in_radians
upper_limit=100.0)
phase_folders = [
string_utils.remove_substring_from_end_of_string(
string=os.path.basename(__file__), substring=".py")
]
phase_1 = phase.Phase(
phase_name="phase_1__version_{}".format(autolens_version),
phase_folders=phase_folders,
profiles=af.CollectionPriorModel(
lens=lens_model,
src_model=src_model,
),
lens_redshift=lens_redshift,
source_redshift=source_redshift,
)
phase_1.optimizer.const_efficiency_mode = True
phase_1.optimizer.n_live_points = 100
phase_1.optimizer.sampling_efficiency = 0.2
phase_1.optimizer.evidence_tolerance = 0.5
xy_mask = Mask3D.unmasked(
shape_3d=grid_3d.shape_3d,
pixel_scales=grid_3d.pixel_scales,
sub_size=grid_3d.sub_size,
)
phase_1.run(dataset=dataset, xy_mask=xy_mask)