run_distributed_fft

ska_sdp_exec_swiftly.fourier_transform_dask.run_distributed_fft(fundamental_params, to_plot=True, fig_name=None, use_dask=False, client=None, use_hdf5=False, hdf5_prefix=None, hdf5_chunksize=None, generate_random=False, source_number=10, facet_to_subgrid_method=3)[source]

Main execution function that reads in the configuration, generates the source data, and runs the algorithm.

Parameters:

  • fundamental_params – dictionary of fundamental parmeters chosen from swift_configs.py

  • to_plot – run plotting?

  • fig_name – If given, figures are saved with this prefix into PNG files. If to_plot is set to False, fig_name doesn’t have an effect.

  • use_dask – boolean; use Dask?

  • client – Dask client or None

  • use_hdf5 – use Hdf5?

  • hdf5_prefix – hdf5 path prefix

  • hdf5_chunksize – hdf5 chunk size in tuple [size(G), size(FG)]

  • generate_random – Whether to generate generic input data with random sources

  • source_number – Number of random sources to add to input data

  • facet_to_subgrid_method – which method to run the facet to subgrid algorithm

Returns:

subgrid_2, facet_2, approx_subgrid, approx_facet

when use_hdf5=False

subgrid_2_file, facet_2_file, approx_subgrid_2_file,

approx_facet_2_file when use_hdf5=True