autolens.SimulatorImaging#

class autolens.SimulatorImaging(exposure_time: float, background_sky_level: float = 0.0, psf: Optional[autoarray.structures.arrays.kernel_2d.Kernel2D] = None, normalize_psf: bool = True, read_noise: Optional[float] = None, add_poisson_noise: bool = True, noise_if_add_noise_false: float = 0.1, noise_seed: int = - 1)[source]#
__init__(exposure_time: float, background_sky_level: float = 0.0, psf: Optional[autoarray.structures.arrays.kernel_2d.Kernel2D] = None, normalize_psf: bool = True, read_noise: Optional[float] = None, add_poisson_noise: bool = True, noise_if_add_noise_false: float = 0.1, noise_seed: int = - 1)[source]#

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

Parameters
  • psf (Kernel2D) – An arrays describing the PSF kernel of the image.

  • exposure_time – The exposure time of the simulated imaging.

  • background_sky_level – The level of the background sky of the simulated imaging.

  • normalize_psf – If True, the PSF kernel is normalized so all values sum to 1.0.

  • read_noise – The level of read-noise added to the simulated imaging by drawing from a Gaussian distribution with sigma equal to the value read_noise.

  • add_poisson_noise – Whether Poisson noise corresponding to photon count statistics on the imaging observation is added.

  • noise_if_add_noise_false – If noise is not added to the simulated dataset a noise_map must still be returned. This value gives the value of noise assigned to every pixel in the noise-map.

  • noise_seed – The random seed used to add random noise, where -1 corresponds to a random seed every run.

Methods

__init__(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.