invert_wg

ska_sdp_func_python.imaging.wg.invert_wg(bvis: ~ska_sdp_datamodels.visibility.vis_model.Visibility, model: ~ska_sdp_datamodels.image.image_model.Image, dopsf: bool = False, normalise: bool = True, **kwargs) -> (<class 'ska_sdp_datamodels.image.image_model.Image'>, <class 'numpy.ndarray'>)

Invert using GPU-based w-stacking gridder module.

Use the Image im as a template. Do PSF in a separate call.

In the imaging and pipeline workflows, this may be invoked using context=’wg’.

Parameters:

• dopsf – Make the PSF instead of the dirty image

• bvis – Visibility to be inverted

• model – Image template (not changed)

• normalise – Normalise by the sum of weights (True)

Returns:

(resulting Image, sum of the weights for each frequency and polarization)