def invert_2d_from_grid(uv_grid_vis,
sumwt,
im: Image,
normalize: bool = True,
**kwargs):
"""
Perform the 2d fourier transform on the gridded uv visibility
:param uv_grid_vis: the gridded uv visibility
:param sumwt: the weight for the uv visibility
:param im: image template (not changed)
:param return: resulting image[nchan, npol, ny, nx], sum of weights[nchan, npol]
"""
### Calculate gcf -> grid correction function ###
# 2D Prolate spheroidal angular function is separable
npixel = get_parameter(kwargs, "npixel", 512)
nx = npixel
ny = npixel
nu = numpy.abs(2.0 * (numpy.arange(nx) - nx // 2) / nx)
gcf1d, _ = grdsf(nu)
gcf = numpy.outer(gcf1d, gcf1d)
gcf[gcf > 0.0] = gcf.max() / gcf[gcf > 0.0]
result = numpy.real(ifft(uv_grid_vis)) * gcf
#Create image array
resultimage = create_image_from_array(result, im.wcs)
if normalize:
resultimage = normalize_sumwt(resultimage, sumwt)
return resultimage, sumwt
def insert_function_pswf(x, a=5):
from arl.fourier_transforms.convolutional_gridding import grdsf
return grdsf(abs(x) / a)[0]
