make_image(vis_mxds, img_xds, grid_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. Only the prolate spheroidal convolutional gridding function is supported. See make_image_with_gcf function for creating an image with A-projection.

  • vis_mxds (xarray.core.dataset.Dataset) – Input multi-xarray Dataset with global data.

  • img_xds (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.

  • vis_sel_parms (dictionary) –

  • vis_sel_parms['xds'] (str) – The xds within the mxds to use to calculate the imaging weights for.

  • vis_sel_parms['data_group_in_id'] (int, default = first id in xds.data_groups) – The data group in the xds to use.

  • img_sel_parms (dictionary) –

  • img_sel_parms['data_group_in_id'] (int, default = first id in xds.data_groups) – The data group in the image xds to use.

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

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


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

Return type