def test_raster_overlap(self):
m31original = create_test_image(
polarisation_frame=PolarisationFrame('stokesI'))
assert numpy.max(numpy.abs(m31original.data)), "Original is empty"
flat = create_empty_image_like(m31original)
for nraster, overlap in [(1, 0), (1, 16), (4, 8), (4, 16), (8, 8),
(16, 4), (9, 5)]:
m31model = create_test_image(
polarisation_frame=PolarisationFrame('stokesI'))
for patch, flat_patch in zip(
image_raster_iter(m31model,
facets=nraster,
overlap=overlap),
image_raster_iter(flat, facets=nraster, overlap=overlap)):
patch.data *= 2.0
flat_patch.data[...] += 1.0
assert numpy.max(numpy.abs(
m31model.data)), "Raster is empty for %d" % nraster
def test_raster_exception(self):
m31original = self.get_test_image()
assert numpy.max(numpy.abs(m31original.data)), "Original is empty"
for nraster, overlap in [(-1, -1), (-1, 0), (2, 128), (1e6, 127)]:
with self.assertRaises(AssertionError):
m31model = create_test_image(
polarisation_frame=PolarisationFrame('stokesI'))
for patch in image_raster_iter(m31model,
facets=nraster,
overlap=overlap):
patch.data *= 2.0
def test_raster(self):
m31original = self.get_test_image()
assert numpy.max(numpy.abs(m31original.data)), "Original is empty"
for nraster in [1, 2, 4, 8, 9]:
m31model = self.get_test_image()
for patch in image_raster_iter(m31model, facets=nraster):
assert patch.data.shape[3] == (m31model.data.shape[3] // nraster), \
"Number of pixels in each patch: %d not as expected: %d" % (patch.data.shape[3],
(m31model.data.shape[3] // nraster))
assert patch.data.shape[2] == (m31model.data.shape[2] // nraster), \
"Number of pixels in each patch: %d not as expected: %d" % (patch.data.shape[2],
(m31model.data.shape[2] // nraster))
patch.data *= 2.0
diff = m31model.data - 2.0 * m31original.data
assert numpy.max(numpy.abs(
m31model.data)), "Raster is empty for %d" % nraster
assert numpy.max(
numpy.abs(diff)) == 0.0, "Raster set failed for %d" % nraster
def image_scatter_facets(im: Image,
facets=1,
overlap=0,
taper=None) -> List[Image]:
"""Scatter an image into a list of subimages using the image_raster_iterator
If the overlap is greater than zero, we choose to keep all images the same size so the
other ring of facets are ignored. So if facets=4 and overlap > 0 then the scatter returns
(facets-2)**2 = 4 images.
:param im: Image
:param facets: Number of image partitions on each axis (2)
:param overlap: Number of pixels overlap
:param taper: Taper at edges None or 'linear'
:return: list of subimages
See also:
:py:func:`processing_components.image.iterators.image_raster_iter`
"""
return [
flat_facet for flat_facet in image_raster_iter(
im, facets=facets, overlap=overlap, taper=taper)
]
def image_gather_facets(image_list: List[Image],
im: Image,
facets=1,
overlap=0,
taper=None,
return_flat=False):
"""Gather a list of subimages back into an image using the image_raster_iterator
If the overlap is greater than zero, we choose to keep all images the same size so the
other ring of facets are ignored. So if facets=4 and overlap > 0 then the gather expects
(facets-2)**2 = 4 images.
To normalize the overlap we make a set of flats, gather that and divide. The flat may be optionally returned
instead of the result
:param image_list: List of subimages
:param im: Output image
:param facets: Number of image partitions on each axis (2)
:param overlap: Overlap between neighbours in pixels
:param taper: Taper at edges None or 'linear' or 'Tukey'
:param return_flat: Return the flat
:return: list of subimages
See also
:py:func:`rascil.processing_components.image.iterators.image_raster_iter`
"""
out = create_empty_image_like(im)
if overlap > 0:
flat = create_empty_image_like(im)
flat.data[...] = 1.0
flats = [
f for f in image_raster_iter(flat,
facets=facets,
overlap=overlap,
taper=taper,
make_flat=True)
]
sum_flats = create_empty_image_like(im)
if return_flat:
i = 0
for sum_flat_facet in image_raster_iter(sum_flats,
facets=facets,
overlap=overlap,
taper=taper):
sum_flat_facet.data[...] += flats[i].data[...]
i += 1
return sum_flats
else:
i = 0
for out_facet, sum_flat_facet in zip(
image_raster_iter(out,
facets=facets,
overlap=overlap,
taper=taper),
image_raster_iter(sum_flats,
facets=facets,
overlap=overlap,
taper=taper)):
out_facet.data[...] += flats[i].data * image_list[i].data[...]
sum_flat_facet.data[...] += flats[i].data[...]
i += 1
out.data[sum_flats.data > 0.0] /= sum_flats.data[
sum_flats.data > 0.0]
out.data[sum_flats.data <= 0.0] = 0.0
return out
else:
flat = create_empty_image_like(im)
flat.data[...] = 1.0
if return_flat:
return flat
else:
for i, facet in enumerate(
image_raster_iter(out,
facets=facets,
overlap=overlap,
taper=taper)):
facet.data[...] += image_list[i].data[...]
return out
