vis_loop

pyvisgen.simulation.visibility.vis_loop(obs, SI: torch.tensor, num_threads: int = 10, noisy: bool = True, mode: str = 'full', batch_size: int = 'auto', show_progress: bool = False, normalize: bool = True, ft: Literal['default', 'finufft', 'reversed'] = 'default') → Visibilities

Computes the visibilities of an observation.

Parameters:

obsObservation class object

Observation class object generated by the ~pyvisgen.simulation.Observation class.

SItorch.tensor

Tensor containing the sky intensity distribution.

num_threadsint, optional

Number of threads used for intraoperative parallelism on the CPU. See ~torch.set_num_threads. Default: 10

noisybool, optional

If True, generate and add additional noise to the simulated measurements. Default: True

modestr, optional

Select one of ‘full’, ‘grid’, or ‘dense’ to get all valid baselines, a grid of unique baselines, or dense baselines. Default: ‘full’

batch_sizeint, optional

Batch size for iteration over baselines. Default: 100

polarizationstr, optional

Choose between ‘linear’ or ‘circular’ or None to simulate different types of polarizations or disable the simulation of polarization. Default: ‘linear’

random_stateint, optional

Random state used when drawing amp_ratio and during the generation of the random polarization field. Default: 42

show_progressbool, optional

If True, show a progress bar during the iteration over the batches of baselines. Default: False

normalizebool, optional

If True, normalize stokes matrix B by a factor 0.5. Default: True

ftstr, optional

Sets the type of fourier transform used in the RIME. Choose one of 'default', 'finufft' (Flatiron Institute Nonuniform Fast Fourier Transform) or ‘reversed’. Default: 'default'

Returns:

visibilitiesVisibilities

Dataclass object containing visibilities and baselines.