def __init__(
self,
settings_masked_interferometer=interferometer.SettingsMaskedInterferometer(),
settings_pixelization=pix.SettingsPixelization(use_border=True),
settings_inversion=inv.SettingsInversion(),
settings_lens=SettingsLens(),
log_likelihood_cap=None,
):
super().__init__(
settings_masked_interferometer=settings_masked_interferometer,
settings_pixelization=settings_pixelization,
settings_inversion=settings_inversion,
log_likelihood_cap=log_likelihood_cap,
)
self.settings_lens = settings_lens
def __init__(
self,
interferometer,
visibilities_mask,
real_space_mask,
settings=inter.SettingsMaskedInterferometer(),
):
"""
The lens dataset is the collection of data (image, noise-map), a mask, grid, convolver \
and other utilities that are used for modeling and fitting an image of a strong lens.
Whilst the image, noise-map, etc. are loaded in 2D, the lens dataset creates reduced 1D arrays of each \
for lens calculations.
Parameters
----------
imaging: im.Imaging
The imaging data all in 2D (the image, noise-map, etc.)
real_space_mask: msk.Mask2D
The 2D mask that is applied to the image.
sub_size : int
The size of the sub-grid used for each lens SubGrid. E.g. a value of 2 grid each image-pixel on a 2x2 \
sub-grid.
positions : [[]]
Lists of image-pixel coordinates (arc-seconds) that mappers close to one another in the source-plane(s), \
used to speed up the non-linear sampling.
pixel_scales_interp : float
If `True`, expensive to compute mass profile deflection angles will be computed on a sparse grid and \
interpolated to the grid, sub and blurring grids.
inversion_pixel_limit : int or None
The maximum number of pixels that can be used by an inversion, with the limit placed primarily to speed \
up run.
"""
super(MaskedInterferometer, self).__init__(
interferometer=interferometer,
visibilities_mask=visibilities_mask,
real_space_mask=real_space_mask,
settings=settings,
)