# autolens.SimulatorInterferometer¶

class autolens.SimulatorInterferometer(uv_wavelengths, exposure_time: float, transformer_class=<class 'autoarray.operators.transformer.TransformerDFT'>, noise_sigma=0.1, noise_if_add_noise_false=0.1, noise_seed=-1)
__init__(uv_wavelengths, exposure_time: float, transformer_class=<class 'autoarray.operators.transformer.TransformerDFT'>, noise_sigma=0.1, noise_if_add_noise_false=0.1, noise_seed=-1)

A class representing a Imaging observation, using the shape of the image, the pixel scale, psf, exposure time, etc.

Parameters: shape_native – The shape of the observation. Note that we do not simulator a full Imaging frame (e.g. 2000 x 2000 pixels for Hubble imaging), but instead just a cut-out around the strong lens. pixel_scales – The size of each pixel in arc seconds. psf (PSF) – An arrays describing the PSF kernel of the image. exposure_time_map – The exposure time of an observation using this data.

Methods

 __init__(uv_wavelengths, exposure_time[, …]) A class representing a Imaging observation, using the shape of the image, the pixel scale, psf, exposure time, etc. via_deflections_and_galaxies_from(…[, name]) via_galaxies_from(galaxies, grid[, name]) Simulate imaging data for this data, as follows: via_image_from(image[, name]) Returns a realistic simulated image by applying effects to a plain simulated image. via_tracer_from(tracer, grid[, name]) Returns a realistic simulated image by applying effects to a plain simulated image.
via_tracer_from(tracer, grid, name=None)

Returns a realistic simulated image by applying effects to a plain simulated image.

Parameters: name – image (np.ndarray) – The image before simulating (e.g. the lens and source galaxies before optics blurring and Imaging read-out). pixel_scales (float) – The scale of each pixel in arc seconds exposure_time_map (np.ndarray) – An arrays representing the effective exposure time of each pixel. psf (PSF) – An arrays describing the PSF the simulated image is blurred with. add_poisson_noise (Bool) – If True poisson noise_maps is simulated and added to the image, based on the total counts in each image pixel noise_seed (int) – A seed for random noise_maps generation
via_galaxies_from(galaxies, grid, name=None)

Simulate imaging data for this data, as follows:

1. Setup the image-plane grid of the Imaging arrays, which defines the coordinates used for the ray-tracing.
2. Use this grid and the lens and source galaxies to setup a tracer, which generates the image of the simulated imaging data.
3. Simulate the imaging data, using a special image which ensures edge-effects don’t degrade simulator of the telescope optics (e.g. the PSF convolution).
4. Plot the image using Matplotlib, if the plot_imaging bool is True.
5. Output the dataset to .fits format if a dataset_path and data_name are specified. Otherwise, return the simulated imaging data instance.