ngcasa.imaging.make_image_with_gcf

make_image_with_gcf(mxds, gcf_dataset, img_dataset, grid_parms, norm_parms, vis_sel_parms, img_sel_parms)[source]

Creates a cube or continuum dirty image from the user specified visibility, uvw and imaging weight data. A gridding convolution function (gcf_dataset), primary beam image (img_dataset) and a primary beam weight image (img_dataset) must be supplied.

Parameters

  • vis_dataset (xarray.core.dataset.Dataset) – Input visibility dataset.

  • gcf_dataset (xarray.core.dataset.Dataset) – Input gridding convolution dataset.

  • img_dataset (xarray.core.dataset.Dataset) – Input image dataset.

  • grid_parms (dictionary) –

  • grid_parms['image_size'] (list of int, length = 2) – The image size (no padding).

  • grid_parms['cell_size'] (list of number, length = 2, units = arcseconds) – The image cell size.

  • grid_parms['chan_mode'] ({'continuum'/'cube'}, default = 'continuum') – Create a continuum or cube image.

  • grid_parms['fft_padding'] (number, acceptable range [1,100], default = 1.2) – The factor that determines how much the gridded visibilities are padded before the fft is done.

  • norm_parms (dictionary) –

  • norm_parms['norm_type'] ({'none'/'flat_noise'/'flat_sky'}, default = 'flat_sky') –

    Gridded (and FT’d) images represent the PB-weighted sky image.

    Qualitatively it can be approximated as two instances of the PB applied to the sky image (one naturally present in the data and one introduced during gridding via the convolution functions). normtype=’flat_noise’ : Divide the raw image by sqrt(sel_parms[‘weight_pb’]) so that

    the input to the minor cycle represents the product of the sky and PB. The noise is ‘flat’ across the region covered by each PB.

    normtype=’flat_sky’Divide the raw image by sel_parms[‘weight_pb’] so that the input

    to the minor cycle represents only the sky. The noise is higher in the outer regions of the primary beam where the sensitivity is low.

    normtype=’none’ : No normalization after gridding and FFT.

  • sel_parms (dictionary) –

  • sel_parms['uvw'] (str, default ='UVW') – The name of uvw data variable that will be used to grid the visibilities.

  • sel_parms['data'] (str, default = 'DATA') – The name of the visibility data to be gridded.

  • sel_parms['imaging_weight'] (str, default ='IMAGING_WEIGHT') – The name of the imaging weights to be used.

  • sel_parms['image'] (str, default ='IMAGE') – The created image name.

  • sel_parms['sum_weight'] (str, default ='SUM_WEIGHT') – The created sum of weights name.

  • sel_parms['pb'] (str, default ='PB') – The primary beam image to use for normalization.

  • sel_parms['weight_pb'] (str, default ='WEIGHT_PB') – The primary beam weight image to use for normalization.

Returns

image_dataset – The image_dataset will contain the image created and the sum of weights.

Return type

xarray.core.dataset.Dataset