predict_list_rsexecute_workflow

predict_list_rsexecute_workflow(vis_list, model_imagelist, context, **kwargs)[source]

Predict, iterating over both the scattered vis_list and image

The visibility and image are scattered, the visibility is predicted on each part, and then the parts are assembled.

Parameters:

vis_list – list of vis (or graph)
model_imagelist – list of models (or graph)
context – Type of processing e.g. 2d, ng
kwargs – Parameters for functions in components

Returns:

List of vis_lists

For example:

dprepb_model = [rsexecute.execute(create_low_test_image_from_gleam)
    (npixel=npixel, frequency=[frequency[f]], channel_bandwidth=[channel_bandwidth[f]],
    cellsize=cellsize, phasecentre=phasecentre, polarisation_frame=PolarisationFrame("stokesI"),
    flux_limit=3.0, applybeam=True)
    for f, freq in enumerate(frequency)]

dprepb_model_list = rsexecute.persist(dprepb_model_list)
predicted_vis_list = predict_list_rsexecute_workflow(vis_list, model_imagelist=dprepb_model_list,
    context='wstack', vis_slices=51)
predicted_vis_list = rsexecute.compute(predicted_vis_list , sync=True)