autolens.Plane#

class autolens.Plane(galaxies, redshift: Optional[float] = None, profiling_dict: Optional[Dict] = None)[source]#
__init__(galaxies, redshift: Optional[float] = None, profiling_dict: Optional[Dict] = None)[source]#

A plane of galaxies where all galaxies are at the same redshift.

Parameters
  • or None (redshift) – The redshift of the plane.

  • galaxies ([Galaxy]) – The list of galaxies in this plane.

Methods

__init__(galaxies[, redshift, profiling_dict])

A plane of galaxies where all galaxies are at the same redshift.

area_within_tangential_critical_curve_from(grid)

Returns the surface area within the tangential critical curve, the calculation of whihc is described in the function tangential_critical_curve_from()

blurred_image_2d_list_via_convolver_from(…)

Evaluate the light object’s list of 2D images from a input 2D grid of coordinates and convolve each image with a PSF, using a autoarray.operators.convolver.Convolver object.

blurred_image_2d_list_via_psf_from(grid, …)

Evaluate the light object’s list of 2D images from a input 2D grid of coordinates and convolve each image with a PSF.

blurred_image_2d_via_convolver_from(grid, …)

Evaluate the light object’s 2D image from a input 2D grid of coordinates and convolve it with a PSF, using a autoarray.operators.convolver.Convolver object.

blurred_image_2d_via_psf_from(grid, psf, …)

Evaluate the light object’s 2D image from a input 2D grid of coordinates and convolve it with a PSF.

caustics_from(grid[, pixel_scale])

Returns the both the tangential and radial caustics of lensing object as a two entry list of irregular 2D grids.

convergence_2d_from(grid)

Returns the convergence of the list of galaxies of the plane’s sub-grid, by summing the individual convergences of each galaxy’s mass profile.

convergence_2d_via_hessian_from(grid[, buffer])

Returns the convergence of the lensing object, which is computed from the 2D deflection angle map via the Hessian using the expression (see equation 56 https://www.tau.ac.il/~lab3/MICROLENSING/JeruLect.pdf):

convergence_2d_via_jacobian_from(grid[, …])

Returns the convergence of the lensing object, which is computed from the 2D deflection angle map via the Jacobian using the expression (see equation 58 https://www.tau.ac.il/~lab3/MICROLENSING/JeruLect.pdf):

critical_curves_from(grid[, pixel_scale])

Returns the both the tangential and radial critical curves of lensing object as a two entry list of irregular 2D grids.

deflections_yx_2d_from(grid)

dict()

A dictionary representation of the instance comprising a type field which contains the entire class path by which the type can be imported and constructor arguments.

einstein_mass_angular_from(grid[, pixel_scale])

Returns the angular Einstein Mass, which is defined as:

einstein_radius_from(grid[, pixel_scale])

Returns the Einstein radius, which is defined as the radius of the circle which contains the same area as the area within the tangential critical curve.

extract_attribute(cls, attr_name)

Returns an attribute of a class in Plane as a ValueIrregular or Grid2DIrregular object.

extract_attributes_of_galaxies(cls, attr_name)

Returns an attribute of a class in the plane as a list of ValueIrregular or Grid2DIrregular objects, where the list indexes correspond to each galaxy in the plane..

from_dict(cls_dict)

Instantiate an instance of a class from its dictionary representation.

from_json(file_path)

Load the dictable object to a .json file, whereby all attributes are converted from the .json file’s dictionary representation to create the instance of the object

galaxy_blurred_image_2d_dict_via_convolver_from(…)

Evaluate the light object’s dictionary mapping galaixes to their corresponding 2D images and convolve each image with a PSF.

galaxy_image_2d_dict_from(grid)

Returns a dictionary associating every Galaxy object in the Plane with its corresponding 2D image, using the instance of each galaxy as the dictionary keys.

galaxy_visibilities_dict_via_transformer_from(…)

Evaluate the light object’s dictionary mapping galaixes to their corresponding 2D images and transform each image to arrays of visibilities using a autoarray.operators.transformer.Transformer object and therefore a Fourier Transform.

hessian_from(grid[, buffer, deflections_func])

Returns the Hessian of the lensing object, where the Hessian is the second partial derivatives of the the potential (see equation 55 https://www.tau.ac.il/~lab3/MICROLENSING/JeruLect.pdf):

hyper_noise_map_from(noise_map)

hyper_noise_map_list_from(noise_map)

For a contribution map and noise-map, use the model hyper_galaxy galaxies to compute a hyper noise-map.

image_2d_from(grid)

Returns the profile-image plane image of the list of galaxies of the plane’s sub-grid, by summing the individual images of each galaxy’s light profile.

image_2d_list_from(grid)

inversion_imaging_from(grid, image, …[, …])

inversion_interferometer_from(grid, …[, …])

jacobian_from(grid)

Returns the Jacobian of the lensing object, which is computed by taking the gradient of the 2D deflection angle map in four direction (positive y, negative y, positive x, negative x).

linear_obj_list_from(grid[, …])

magnification_2d_from(grid)

Returns the 2D magnification map of lensing object, which is computed as the inverse of the determinant of the jacobian.

magnification_2d_via_hessian_from(grid[, …])

Returns the 2D magnification map of lensing object, which is computed from the 2D deflection angle map via the Hessian using the expressions (see equation 60 https://www.tau.ac.il/~lab3/MICROLENSING/JeruLect.pdf):

mapper_from(source_grid_slim, …[, …])

output_to_json(file_path)

Output the dictable object to a .json file, whereby all attributes are converted to a dictionary representation first.

padded_image_2d_from(grid, psf_shape_2d)

Evaluate the light object’s 2D image from a input 2D grid of padded coordinates, where this padding is sufficient to encapsulate all surrounding pixels that will blur light into the original image given the 2D shape of the PSF’s kernel..

plane_image_2d_from(grid)

potential_2d_from(grid)

Returns the potential of the list of galaxies of the plane’s sub-grid, by summing the individual potentials of each galaxy’s mass profile.

radial_caustic_from(grid[, pixel_scale])

Returns the radial caustic of lensing object, which is computed as follows:

radial_critical_curve_from(grid[, pixel_scale])

Returns the radial critical curve of lensing object, which is computed as follows:

radial_eigen_value_from(grid[, jacobian])

Returns the radial eigen values of lensing jacobian, which are given by the expression:

set_snr_of_snr_light_profiles(grid, …[, …])

shear_yx_2d_via_hessian_from(grid[, buffer])

Returns the 2D (y,x) shear vectors of the lensing object, which are computed from the 2D deflection angle map via the Hessian using the expressions (see equation 57 https://www.tau.ac.il/~lab3/MICROLENSING/JeruLect.pdf):

shear_yx_2d_via_jacobian_from(grid[, jacobian])

Returns the 2D (y,x) shear vectors of the lensing object, which are computed from the 2D deflection angle map via the Jacobian using the expression (see equation 58 https://www.tau.ac.il/~lab3/MICROLENSING/JeruLect.pdf):

sparse_image_plane_grid_list_from(grid[, …])

tangential_caustic_from(grid[, pixel_scale])

Returns the tangential caustic of lensing object, which is computed as follows:

tangential_critical_curve_from(grid[, …])

Returns the tangential critical curve of lensing object, which is computed as follows:

tangential_eigen_value_from(grid[, jacobian])

Returns the tangential eigen values of lensing jacobian, which are given by the expression:

traced_grid_from(grid)

Trace this plane’s grid_stacks to the next plane, using its deflection angles.

unmasked_blurred_image_2d_list_via_psf_from(…)

Evaluate the light object’s list of 2D images from a input 2D grid of coordinates and convolve it with a PSF, using a grid which is not masked.

unmasked_blurred_image_2d_via_psf_from(grid, psf)

Evaluate the light object’s 2D image from a input 2D grid of coordinates and convolve it with a PSF, using a grid which is not masked.

visibilities_list_via_transformer_from(grid, …)

Evaluate the light object’s list of 2D image from a input 2D grid of coordinates and transform each image to arrays of visibilities using a autoarray.operators.transformer.Transformer object and therefore a Fourier Transform.

visibilities_via_transformer_from(grid, …)

Evaluate the light object’s 2D image from a input 2D grid of coordinates and transform this to an array of visibilities using a autoarray.operators.transformer.Transformer object and therefore a Fourier Transform.

Attributes

contribution_map

contribution_map_list

galaxies_with_mass_profile

galaxies_with_pixelization

galaxies_with_regularization

galaxy_redshifts

has_hyper_galaxy

has_light_profile

has_mass_profile

has_pixelization

has_regularization

hyper_galaxies_with_pixelization_image_list

mass_profile_list

mass_profile_list_of_galaxies

pixelization_list

regularization_list