py21cmsense.observatory.Observatory.grid_baselines¶

Observatory.grid_baselines(coherent: bool, baselines: ~astropy.units.quantity.Quantity | None = None, weights: ~numpy.ndarray | None = None, integration_time: ~astropy.units.quantity.Quantity = <Quantity 60. s>, baseline_filters: ~typing.Callable | tuple[~typing.Callable] = (), observation_duration: ~astropy.units.quantity.Quantity | None = None, ndecimals: int = 1) → ndarray[source]¶

Grid baselines onto a pre-determined uvgrid, accounting for earth rotation.

Parameters:

baselines (array_like, optional) – The baseline co-ordinates to project, assumed to be in metres. If not provided, calculates effective baselines by finding redundancies on all baselines in the observatory. Shape of the array can be (N,N,3) or (N, 3). The co-ordinates are expected to be in ENU. If baselines is provided, weights must also be provided.
weights (array_like, optional) – An array of the same length as baselines, giving the number of independent baselines at each co-ordinate. If not provided, calculates effective baselines by finding redundancies on all baselines in the observatory. If baselines is provided, weights must also be provided.
integration_time (float or Quantity, optional) – The amount of time integrated into a snapshot visibility, assumed to be in seconds.
baseline_filters – A function that takes a single value: a length-3 array of baseline co-ordinates, and returns a bool indicating whether to include the baseline. Built-in filters are provided in the baseline_filters module.
observation_duration (float or Quantity, optional) – Amount of time in a single (coherent) LST bin, assumed to be in minutes.
ndecimals (int, optional) – Number of decimals to which baselines must match to be considered redundant.

Returns:

array – Shape [n_baseline_groups, Nuv, Nuv]. The coherent sum of baselines within grid cells given by ugrid. One can treat different baseline groups independently, or sum over them.