def test_griddata_invert_wterm(self):
self.actualSetUp(zerow=False)
gcf, cf = create_awterm_convolutionfunction(self.model,
nw=100,
wstep=8.0,
oversampling=8,
support=32,
use_aaf=True)
cf_image = convert_convolutionfunction_to_image(cf)
cf_image.data = numpy.real(cf_image.data)
if self.persist:
export_image_to_fits(cf_image,
"%s/test_gridding_wterm_cf.fits" % self.dir)
griddata = create_griddata_from_image(self.model, self.vis, nw=1)
griddata, sumwt = grid_visibility_to_griddata(self.vis,
griddata=griddata,
cf=cf)
cim = fft_griddata_to_image(griddata, gcf)
cim = normalize_sumwt(cim, sumwt)
im = convert_polimage_to_stokes(cim)
if self.persist:
export_image_to_fits(
im, '%s/test_gridding_dirty_wterm.fits' % self.dir)
self.check_peaks(im, 97.13333924372108)
def test_griddata_invert_aterm_noover(self):
self.actualSetUp(zerow=True)
make_pb = functools.partial(create_pb_generic,
diameter=35.0,
blockage=0.0,
use_local=False)
pb = make_pb(self.model)
if self.persist:
export_image_to_fits(pb,
"%s/test_gridding_aterm_pb.fits" % self.dir)
gcf, cf = create_awterm_convolutionfunction(self.model,
make_pb=make_pb,
nw=1,
oversampling=1,
support=16,
use_aaf=True)
griddata = create_griddata_from_image(self.model, self.vis)
griddata, sumwt = grid_visibility_to_griddata(self.vis,
griddata=griddata,
cf=cf)
cim = fft_griddata_to_image(griddata, gcf)
cim = normalize_sumwt(cim, sumwt)
im = convert_polimage_to_stokes(cim)
if self.persist:
export_image_to_fits(
im, '%s/test_gridding_dirty_aterm_noover.fits' % self.dir)
self.check_peaks(im, 97.10594988491547)
def test_griddata_invert_box(self):
self.actualSetUp(zerow=True)
gcf, cf = create_box_convolutionfunction(self.model)
griddata = create_griddata_from_image(self.model, self.vis)
griddata, sumwt = grid_visibility_to_griddata(self.vis,
griddata=griddata,
cf=cf)
cim = fft_griddata_to_image(griddata, gcf)
cim = normalize_sumwt(cim, sumwt)
im = convert_polimage_to_stokes(cim)
if self.persist:
export_image_to_fits(im,
'%s/test_gridding_dirty_box.fits' % self.dir)
self.check_peaks(im, 97.10594988491547, tol=1e-7)
def test_griddata_visibility_weight_IQ(self):
self.actualSetUp(zerow=True, image_pol=PolarisationFrame("stokesIQUV"))
gcf, cf = create_pswf_convolutionfunction(self.model)
gd = create_griddata_from_image(self.model, self.vis)
gd_list = [
grid_visibility_weight_to_griddata(self.vis, gd, cf)
for i in range(10)
]
gd, sumwt = griddata_merge_weights(gd_list, algorithm='uniform')
self.vis = griddata_visibility_reweight(self.vis, gd, cf)
gd, sumwt = grid_visibility_to_griddata(self.vis, griddata=gd, cf=cf)
cim = fft_griddata_to_image(gd, gcf)
cim = normalize_sumwt(cim, sumwt)
im = convert_polimage_to_stokes(cim)
if self.persist:
export_image_to_fits(
im, '%s/test_gridding_dirty_2d_IQ_uniform.fits' % self.dir)
self.check_peaks(im, 99.40822097133994)
def test_stokes_conversion(self):
assert self.m31image.polarisation_frame == PolarisationFrame("stokesI")
stokes = create_test_image(
cellsize=0.0001,
polarisation_frame=PolarisationFrame("stokesIQUV"))
assert stokes.polarisation_frame == PolarisationFrame("stokesIQUV")
for pol_name in ['circular', 'linear']:
polarisation_frame = PolarisationFrame(pol_name)
polimage = convert_stokes_to_polimage(
stokes, polarisation_frame=polarisation_frame)
assert polimage.polarisation_frame == polarisation_frame
polarisation_frame_from_wcs(polimage.wcs, polimage.shape)
rstokes = convert_polimage_to_stokes(polimage)
assert polimage.data.dtype == 'complex'
assert rstokes.data.dtype == 'complex'
numpy.testing.assert_array_almost_equal(stokes.data,
rstokes.data.real, 12)
def test_griddata_blockvisibility_weight(self):
self.actualSetUp(zerow=True,
block=True,
image_pol=PolarisationFrame("stokesIQUV"))
gcf, cf = create_pswf_convolutionfunction(self.model)
gd = create_griddata_from_image(self.model, self.vis)
gd_list = [
grid_blockvisibility_weight_to_griddata(self.vis, gd, cf)
for i in range(10)
]
assert numpy.max(numpy.abs(gd_list[0][0].data)) > 10.0
gd, sumwt = griddata_merge_weights(gd_list, algorithm='uniform')
self.vis = griddata_blockvisibility_reweight(self.vis, gd, cf)
gd, sumwt = grid_blockvisibility_to_griddata(self.vis,
griddata=gd,
cf=cf)
cim = fft_griddata_to_image(gd, gcf)
cim = normalize_sumwt(cim, sumwt)
im = convert_polimage_to_stokes(cim)
if self.persist:
export_image_to_fits(
im, '%s/test_gridding_dirty_2d_uniform_block.fits' % self.dir)
self.check_peaks(im, 100.13540418821904)
def test_griddata_invert_awterm(self):
self.actualSetUp(zerow=False)
make_pb = functools.partial(create_pb_generic,
diameter=35.0,
blockage=0.0,
use_local=False)
pb = make_pb(self.model)
if self.persist:
export_image_to_fits(pb,
"%s/test_gridding_awterm_pb.fits" % self.dir)
gcf, cf = create_awterm_convolutionfunction(self.model,
make_pb=make_pb,
nw=100,
wstep=8.0,
oversampling=16,
support=32,
use_aaf=True)
cf_image = convert_convolutionfunction_to_image(cf)
cf_image.data = numpy.real(cf_image.data)
if self.persist:
export_image_to_fits(cf_image,
"%s/test_gridding_awterm_cf.fits" % self.dir)
griddata = create_griddata_from_image(self.model,
self.vis,
nw=100,
wstep=8.0)
griddata, sumwt = grid_visibility_to_griddata(self.vis,
griddata=griddata,
cf=cf)
cim = fft_griddata_to_image(griddata, gcf)
cim = normalize_sumwt(cim, sumwt)
im = convert_polimage_to_stokes(cim)
if self.persist:
export_image_to_fits(
im, '%s/test_gridding_dirty_awterm.fits' % self.dir)
self.check_peaks(im, 97.13257546573094)
