autolens.Imaging#

class autolens.Imaging(image: ~autoarray.structures.arrays.uniform_2d.Array2D, noise_map: ~typing.Optional[~autoarray.structures.arrays.uniform_2d.Array2D] = None, psf: ~typing.Optional[~autoarray.structures.arrays.kernel_2d.Kernel2D] = None, noise_covariance_matrix: ~typing.Optional[~numpy.ndarray] = None, settings: ~autoarray.dataset.imaging.settings.SettingsImaging = <autoarray.dataset.imaging.settings.SettingsImaging object>, pad_for_convolver: bool = False)[source]#
__init__(image: ~autoarray.structures.arrays.uniform_2d.Array2D, noise_map: ~typing.Optional[~autoarray.structures.arrays.uniform_2d.Array2D] = None, psf: ~typing.Optional[~autoarray.structures.arrays.kernel_2d.Kernel2D] = None, noise_covariance_matrix: ~typing.Optional[~numpy.ndarray] = None, settings: ~autoarray.dataset.imaging.settings.SettingsImaging = <autoarray.dataset.imaging.settings.SettingsImaging object>, pad_for_convolver: bool = False)[source]#

A class containing an imaging dataset, including the image data, noise-map and a point spread function (PSF).

Parameters
  • image – The array of the image data, for example in units of electrons per second.

  • noise_map – An array describing the RMS standard deviation error in each pixel, for example in units of electrons per second.

  • psf – An array describing the Point Spread Function kernel of the image which accounts for diffraction due to the telescope optics via 2D convolution.

  • settings – Controls settings of how the dataset is set up (e.g. the types of grids used to perform calculations).

Methods

__init__(image[, noise_map, psf, ...])

A class containing an imaging dataset, including the image data, noise-map and a point spread function (PSF).

apply_mask(mask)

Apply a mask to the imaging dataset, whereby the mask is applied to the image data, noise-map and other quantities one-by-one.

apply_settings(settings)

Returns a new instance of the imaging with the input SettingsImaging applied to them.

from_fits(image_path, pixel_scales, ...[, ...])

Factory for loading the imaging data_type from .fits files, as well as computing properties like the noise-map, exposure-time map, etc.

output_to_fits(image_path[, psf_path, ...])

trimmed_after_convolution_from(kernel_shape)

Attributes

absolute_signal_to_noise_map

The estimated absolute_signal-to-noise_maps mappers of the image.

absolute_signal_to_noise_max

The maximum value of absolute signal-to-noise_map in an image pixel in the image's signal-to-noise_maps mappers.

blurring_grid

A property that is only computed once per instance and then replaces itself with an ordinary attribute.

convolver

A property that is only computed once per instance and then replaces itself with an ordinary attribute.

image

inverse_noise_map

mask

noise_covariance_matrix_inv

A property that is only computed once per instance and then replaces itself with an ordinary attribute.

pixel_scales

potential_chi_squared_map

The potential chi-squared-map of the imaging data_type.

potential_chi_squared_max

The maximum value of the potential chi-squared-map.

shape_native

shape_slim

signal_to_noise_map

The estimated signal-to-noise_maps mappers of the image.

signal_to_noise_max

The maximum value of signal-to-noise_maps in an image pixel in the image's signal-to-noise_maps mappers.

w_tilde

A property that is only computed once per instance and then replaces itself with an ordinary attribute.