def image_gather_channels(image_list: List[Image],
im: Image = None,
subimages=0) -> Image:
"""Gather a list of subimages back into an image using the channel_iterator
If the template image is not given then it will be formed assuming that the list has
been generated by image_scatter_channels with subimages = number of channels
:param image_list: List of subimages
:param im: Output image
:param subimages: Number of image partitions on each axis (2)
:return: list of subimages
"""
if im is None:
nchan = len(image_list)
_, npol, ny, nx = image_list[0].shape
im_shape = nchan, npol, ny, ny
im = create_image_from_array(
numpy.zeros(im_shape, dtype=image_list[0].data.dtype),
image_list[0].wcs, image_list[0].polarisation_frame)
assert image_is_canonical(im)
if subimages == 0:
subimages = len(image_list)
for i, slab in enumerate(image_channel_iter(im, subimages=subimages)):
slab.data[...] = image_list[i].data[...]
return im
def test_channelise(self):
m31cube = create_test_image(
polarisation_frame=PolarisationFrame('stokesI'),
frequency=numpy.linspace(1e8, 1.1e8, 128))
for subimages in [128, 16, 8, 2, 1]:
for slab in image_channel_iter(m31cube, subimages=subimages):
assert slab.data.shape[0] == 128 // subimages
def image_scatter_channels(im: Image, subimages=None) -> List[Image]:
"""Scatter an image into a list of subimages using the channels
:param im: Image
:param subimages: Number of channels
:return: list of subimages
See also
:py:func:`rascil.processing_components.image.iterators.image_channel_iter`
"""
assert image_is_canonical(im)
image_list = list()
if subimages is None:
subimages = im.shape[0]
for slab in image_channel_iter(im, subimages=subimages):
image_list.append(slab)
assert len(image_list) == subimages, "Too many subimages scattered"
return image_list