timeslice.py 文件源码

def invert_timeslice_single(vis: Visibility, im: Image, dopsf, normalize=True, **kwargs) -> (Image, numpy.ndarray):
    """Process single time slice

    Extracted for re-use in parallel version
    :param vis: Visibility to be inverted
    :param im: image template (not changed)
    :param dopsf: Make the psf instead of the dirty image
    :param normalize: Normalize by the sum of weights (True)
    """
    inchan, inpol, ny, nx = im.shape

    if not isinstance(vis, Visibility):
        avis = coalesce_visibility(vis, **kwargs)
    else:
        avis = vis

    log.debug("invert_timeslice_single: inverting using single time slice")

    avis, p, q = fit_uvwplane(avis, remove=False)

    workimage, sumwt = invert_2d_base(avis, im, dopsf, normalize=normalize, **kwargs)

    finalimage = create_empty_image_like(im)

    # Use griddata to do the conversion. This could be improved. Only cubic is possible in griddata.
    # The interpolation is ok for invert since the image is smooth.

    # Calculate nominal and distorted coordinates. The image is in distorted coordinates so we
    # need to convert back to nominal
    lnominal, mnominal, ldistorted, mdistorted = lm_distortion(workimage, -p, -q)

    for chan in range(inchan):
        for pol in range(inpol):
            finalimage.data[chan, pol, ...] = \
                griddata((mdistorted.flatten(), ldistorted.flatten()),
                         values=workimage.data[chan, pol, ...].flatten(),
                         method='cubic',
                         xi=(mnominal.flatten(), lnominal.flatten()),
                         fill_value=0.0,
                         rescale=True).reshape(finalimage.data[chan, pol, ...].shape)

    return finalimage, sumwt