autolens.Interferometer#

class Interferometer[source]#

A class containing an interferometer dataset, including the visibilities data, noise-map and the uv-plane baseline wavelengths.

Parameters
  • visibilities (Visibilities) – The array of the visibilities data, containing by real and complex values.

  • noise_map (VisibilitiesNoiseMap) – An array describing the RMS standard deviation error in each visibility.

  • uv_wavelengths (ndarray) – The uv-plane baseline wavelengths.

  • real_space_mask – A 2D mask in real-space (e.g. not Fourier space like the visibilities) which defines in real space how calculations are performed.

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

__init__(visibilities, noise_map, uv_wavelengths, real_space_mask, settings=<autoarray.dataset.interferometer.settings.SettingsInterferometer object>)[source]#

A class containing an interferometer dataset, including the visibilities data, noise-map and the uv-plane baseline wavelengths.

Parameters
  • visibilities (Visibilities) – The array of the visibilities data, containing by real and complex values.

  • noise_map (VisibilitiesNoiseMap) – An array describing the RMS standard deviation error in each visibility.

  • uv_wavelengths (ndarray) – The uv-plane baseline wavelengths.

  • real_space_mask – A 2D mask in real-space (e.g. not Fourier space like the visibilities) which defines in real space how calculations are performed.

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

Methods

__init__(visibilities, noise_map, ...[, ...])

A class containing an interferometer dataset, including the visibilities data, noise-map and the uv-plane baseline wavelengths.

apply_settings(settings)

from_fits(visibilities_path, noise_map_path, ...)

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

output_to_fits([visibilities_path, ...])

trimmed_after_convolution_from(kernel_shape)

rtype

AbstractDataset

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.

amplitudes

blurring_grid

convolver

dirty_image

dirty_inverse_noise_map

dirty_noise_map

dirty_signal_to_noise_map

inverse_noise_map

rtype

Structure

mask

noise_covariance_matrix_inv

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

phases

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.

uv_distances

visibilities

w_tilde

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

__init__(visibilities, noise_map, uv_wavelengths, real_space_mask, settings=<autoarray.dataset.interferometer.settings.SettingsInterferometer object>)[source]#

A class containing an interferometer dataset, including the visibilities data, noise-map and the uv-plane baseline wavelengths.

Parameters
  • visibilities (Visibilities) – The array of the visibilities data, containing by real and complex values.

  • noise_map (VisibilitiesNoiseMap) – An array describing the RMS standard deviation error in each visibility.

  • uv_wavelengths (ndarray) – The uv-plane baseline wavelengths.

  • real_space_mask – A 2D mask in real-space (e.g. not Fourier space like the visibilities) which defines in real space how calculations are performed.

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

__new__(*args, **kwargs)#