def test_insert_skycomponent_lanczos(self):
sc = create_skycomponent(
direction=self.phasecentre,
flux=numpy.array([[1.0]]),
frequency=self.frequency,
polarisation_frame=PolarisationFrame('stokesI'))
dphasecentre = SkyCoord(ra=+181.0 * u.deg,
dec=-58.0 * u.deg,
frame='icrs',
equinox=2000.0)
sc = create_skycomponent(
direction=dphasecentre,
flux=numpy.array([[1.0]]),
frequency=self.frequency,
polarisation_frame=PolarisationFrame('stokesI'))
self.model.data *= 0.0
insert_skycomponent(self.model, sc, insert_method='Lanczos')
npixel = self.model.shape[3]
rpix = numpy.round(self.model.wcs.wcs.crpix).astype('int')
assert rpix[0] == npixel // 2
assert rpix[1] == npixel // 2
# These test a regression but are not known a priori to be correct
self.assertAlmostEqual(self.model.data[0, 0, 119, 150], 0.887186883218,
7)
self.assertAlmostEqual(self.model.data[0, 0, 119, 151],
-0.145093950704, 7)
def ingest_visibility(self, freq=None, chan_width=None, times=None, reffrequency=None, add_errors=False,
block=True):
if freq is None:
freq = [1e8]
if times is None:
ntimes = 5
times = numpy.linspace(-numpy.pi / 3.0, numpy.pi / 3.0, ntimes)
if chan_width is None:
chan_width = [1e6]
if reffrequency is None:
reffrequency = [1e8]
lowcore = create_named_configuration('LOWBD2-CORE')
frequency = numpy.array([freq])
channel_bandwidth = numpy.array([chan_width])
phasecentre = SkyCoord(ra=+180.0 * u.deg, dec=-60.0 * u.deg, frame='icrs', equinox='J2000')
if block:
vt = create_blockvisibility(lowcore, times, frequency, channel_bandwidth=channel_bandwidth,
weight=1.0, phasecentre=phasecentre,
polarisation_frame=PolarisationFrame("stokesI"))
else:
vt = create_visibility(lowcore, times, frequency, channel_bandwidth=channel_bandwidth,
weight=1.0, phasecentre=phasecentre,
polarisation_frame=PolarisationFrame("stokesI"))
cellsize = 0.001
model = create_image_from_visibility(vt, npixel=self.npixel, cellsize=cellsize, npol=1,
frequency=reffrequency, phasecentre=phasecentre,
polarisation_frame=PolarisationFrame("stokesI"))
flux = numpy.array([[100.0]])
facets = 4
rpix = model.wcs.wcs.crpix - 1.0
spacing_pixels = self.npixel // facets
centers = [-1.5, -0.5, 0.5, 1.5]
comps = list()
for iy in centers:
for ix in centers:
p = int(round(rpix[0] + ix * spacing_pixels * numpy.sign(model.wcs.wcs.cdelt[0]))), \
int(round(rpix[1] + iy * spacing_pixels * numpy.sign(model.wcs.wcs.cdelt[1])))
sc = pixel_to_skycoord(p[0], p[1], model.wcs, origin=1)
comp = create_skycomponent(flux=flux, frequency=frequency, direction=sc,
polarisation_frame=PolarisationFrame("stokesI"))
comps.append(comp)
if block:
predict_skycomponent_blockvisibility(vt, comps)
else:
predict_skycomponent_visibility(vt, comps)
insert_skycomponent(model, comps)
self.model = copy_image(model)
self.empty_model = create_empty_image_like(model)
export_image_to_fits(model, '%s/test_pipeline_bags_model.fits' % self.dir)
if add_errors:
# These will be the same for all calls
numpy.random.seed(180555)
gt = create_gaintable_from_blockvisibility(vt)
gt = simulate_gaintable(gt, phase_error=1.0, amplitude_error=0.0)
vt = apply_gaintable(vt, gt)
return vt
def ingest_visibility(self,
freq=1e8,
chan_width=1e6,
times=None,
reffrequency=None,
add_errors=False):
if times is None:
times = (numpy.pi / 12.0) * numpy.linspace(-3.0, 3.0, 5)
if reffrequency is None:
reffrequency = [1e8]
lowcore = create_named_configuration('LOWBD2-CORE')
frequency = numpy.array([freq])
channel_bandwidth = numpy.array([chan_width])
phasecentre = SkyCoord(ra=+180.0 * u.deg,
dec=-60.0 * u.deg,
frame='icrs',
equinox='J2000')
vt = create_visibility(lowcore,
times,
frequency,
channel_bandwidth=channel_bandwidth,
weight=1.0,
phasecentre=phasecentre,
polarisation_frame=PolarisationFrame("stokesI"))
cellsize = 0.001
model = create_image_from_visibility(
vt,
npixel=self.npixel,
cellsize=cellsize,
npol=1,
frequency=reffrequency,
phasecentre=phasecentre,
polarisation_frame=PolarisationFrame("stokesI"))
flux = numpy.array([[100.0]])
facets = 4
rpix = model.wcs.wcs.crpix
spacing_pixels = self.npixel // facets
centers = [-1.5, -0.5, 0.5, 1.5]
comps = list()
for iy in centers:
for ix in centers:
p = int(round(rpix[0] + ix * spacing_pixels * numpy.sign(model.wcs.wcs.cdelt[0]))), \
int(round(rpix[1] + iy * spacing_pixels * numpy.sign(model.wcs.wcs.cdelt[1])))
sc = pixel_to_skycoord(p[0], p[1], model.wcs, origin=0)
comp = create_skycomponent(
flux=flux,
frequency=frequency,
direction=sc,
polarisation_frame=PolarisationFrame("stokesI"))
comps.append(comp)
predict_skycomponent_visibility(vt, comps)
insert_skycomponent(model, comps)
self.model = copy_image(model)
export_image_to_fits(model,
'%s/test_bags_model.fits' % (self.results_dir))
return vt
def test_insert_skycomponent_sinc(self):
dphasecentre = SkyCoord(ra=+181.0 * u.deg, dec=-58.0 * u.deg, frame='icrs', equinox='J2000')
sc = create_skycomponent(direction=dphasecentre, flux=numpy.array([[1.0]]), frequency=self.frequency,
polarisation_frame=PolarisationFrame('stokesI'))
self.model.data *= 0.0
insert_skycomponent(self.model, sc, insert_method='Sinc')
npixel = self.model.shape[3]
rpix = numpy.round(self.model.wcs.wcs.crpix).astype('int')
assert rpix[0] == npixel // 2
assert rpix[1] == npixel // 2
# These test a regression but are not known a priori to be correct
self.assertAlmostEqual(self.model.data[0, 0, 151, 122], 0.87684398703184396, 7)
self.assertAlmostEqual(self.model.data[0, 0, 152, 122], 0.2469311811046056, 7)
def test_insert_skycomponent_lanczos_bandwidth(self):
dphasecentre = SkyCoord(ra=+181.0 * u.deg, dec=-58.0 * u.deg, frame='icrs', equinox='J2000')
sc = create_skycomponent(direction=dphasecentre, flux=numpy.array([[1.0]]), frequency=self.frequency,
polarisation_frame=PolarisationFrame('stokesI'))
self.model.data *= 0.0
insert_skycomponent(self.model, sc, insert_method='Lanczos', bandwidth=0.5)
npixel = self.model.shape[3]
rpix = numpy.round(self.model.wcs.wcs.crpix).astype('int')
assert rpix[0] == npixel // 2
assert rpix[1] == npixel // 2
# These test a regression but are not known a priori to be correct
self.assertAlmostEqual(self.model.data[0,0,151, 122], 0.24031092091707615, 7)
self.assertAlmostEqual(self.model.data[0,0,152, 122], 0.18648989466050975, 7)
def test_insert_skycomponent_nearest(self):
dphasecentre = SkyCoord(ra=+181.0 * u.deg,
dec=-58.0 * u.deg,
frame='icrs',
equinox='J2000')
sc = create_skycomponent(
direction=dphasecentre,
flux=numpy.array([[1.0]]),
frequency=self.frequency,
polarisation_frame=PolarisationFrame('stokesI'))
self.model.data *= 0.0
insert_skycomponent(self.model, sc, insert_method='Nearest')
# These test a regression but are not known a priori to be correct
self.assertAlmostEqual(self.model.data[0, 0, 151, 122], 1.0, 7)
self.assertAlmostEqual(self.model.data[0, 0, 152, 122], 0.0, 7)
def reppre_ifft_kernel(ix, data_extract_lsm, dep_image, insert_method,
applybeam):
frequency = dep_image["frequency"]
comps = []
for i in data_extract_lsm.value:
if i[0][2] == ix[2]:
comps = i[1]
wcs = dep_image["wcs"]
shape = dep_image["shape"]
polarisation_frame = dep_image["polarisation_frame"]
model = create_image_from_array(np.zeros(shape),
wcs,
polarisation_frame=polarisation_frame)
model = insert_skycomponent(model, comps, insert_method=insert_method)
if applybeam:
beam = create_low_test_beam(model)
model.data = model.data * beam
result = model
label = "Reprojection Predict + IFFT (14645.6 MB, 2.56 Tflop) "
# print(label + str(result))
return result
def test_insert_skycomponent(self):
sc = create_skycomponent(direction=self.phasecentre, flux=numpy.array([[1.0]]), frequency=self.frequency,
polarisation_frame = PolarisationFrame('stokesI'))
log.debug(self.model.wcs)
log.debug(str(sc))
# The actual phase centre of a numpy FFT is at nx //2, nx //2 (0 rel).
self.model.data *= 0.0
insert_skycomponent(self.model, sc)
npixel = self.model.shape[3]
rpix = numpy.round(self.model.wcs.wcs.crpix).astype('int')
assert rpix[0] == npixel // 2
assert rpix[1] == npixel // 2
assert self.model.data[0,0,rpix[1],rpix[0]] == 1.0
self.vis = predict_2d(self.vis, self.model)
assert self.vis.vis.imag.all() == 0.0
def ingest_visibility(self, freq=1e8, chan_width=1e6, times=None, reffrequency=None, add_errors=False):
if times is None:
times = [0.0]
if reffrequency is None:
reffrequency = [1e8]
lowcore = create_named_configuration('LOWBD2-CORE')
frequency = numpy.array([freq])
channel_bandwidth = numpy.array([chan_width])
# phasecentre = SkyCoord(ra=+180.0 * u.deg, dec=-60.0 * u.deg, frame='icrs', equinox='J2000')
# Observe at zenith to ensure that timeslicing works well. We test that elsewhere.
phasecentre = SkyCoord(ra=+180.0 * u.deg, dec=-60.0 * u.deg, frame='icrs', equinox='J2000')
vt = create_blockvisibility(lowcore, times, frequency, channel_bandwidth=channel_bandwidth,
weight=1.0, phasecentre=phasecentre,
polarisation_frame=PolarisationFrame("stokesI"))
cellsize = 0.001
model = create_image_from_visibility(vt, npixel=self.npixel, cellsize=cellsize, npol=1,
frequency=reffrequency,
polarisation_frame=PolarisationFrame("stokesI"))
flux = numpy.array([[100.0]])
facets = 4
rpix = model.wcs.wcs.crpix - 1.0
spacing_pixels = self.npixel // facets
centers = [-1.5, -0.5, 0.5, 1.5]
comps = list()
for iy in centers:
for ix in centers:
p = int(round(rpix[0] + ix * spacing_pixels * numpy.sign(model.wcs.wcs.cdelt[0]))), \
int(round(rpix[1] + iy * spacing_pixels * numpy.sign(model.wcs.wcs.cdelt[1])))
sc = pixel_to_skycoord(p[0], p[1], model.wcs, origin=1)
comps.append(create_skycomponent(flux=flux, frequency=vt.frequency, direction=sc,
polarisation_frame=PolarisationFrame("stokesI")))
predict_skycomponent_blockvisibility(vt, comps)
insert_skycomponent(model, comps)
self.actualmodel = copy_image(model)
export_image_to_fits(model, '%s/test_imaging_model.fits' % (self.results_dir))
if add_errors:
# These will be the same for all calls
numpy.random.seed(180555)
gt = create_gaintable_from_blockvisibility(vt)
gt = simulate_gaintable(gt, phase_error=1.0, amplitude_error=0.0)
vt = apply_gaintable(vt, gt)
return vt
def test_insert_skycomponent(self):
sc = create_skycomponent(
direction=self.phasecentre,
flux=numpy.array([[1.0]]),
frequency=self.frequency,
polarisation_frame=PolarisationFrame('stokesI'))
self.model.data *= 0.0
insert_skycomponent(self.model, sc)
npixel = self.model.shape[3]
# WCS is 1-relative
rpix = numpy.round(self.model.wcs.wcs.crpix).astype('int') - 1
assert rpix[0] == npixel // 2
assert rpix[1] == npixel // 2
# The phase centre is at rpix[0], rpix[1] in 0-relative pixels
assert self.model.data[0, 0, rpix[1], rpix[0]] == 1.0
# If we predict the visibility, then the imaginary part must be zero. This is determined entirely
# by shift_vis_to_image in arl.imaging.base
self.vis = predict_2d(self.vis, self.model)
# The actual phase centre of a numpy FFT is at nx //2, nx //2 (0 rel).
assert self.vis.vis.imag.all() == 0.0
def create_low_test_image_from_gleam(npixel=512,
polarisation_frame=PolarisationFrame(
"stokesI"),
cellsize=0.000015,
frequency=numpy.array([1e8]),
channel_bandwidth=numpy.array([1e6]),
phasecentre=None,
kind='cubic',
applybeam=False,
flux_limit=0.1,
radius=None,
insert_method='Nearest',
nchan=16) -> Image:
"""Create LOW test image from the GLEAM survey
Stokes I is estimated from a cubic spline fit to the measured fluxes. The polarised flux is always zero.
See http://www.mwatelescope.org/science/gleam-survey The catalog is available from Vizier.
VIII/100 GaLactic and Extragalactic All-sky MWA survey (Hurley-Walker+, 2016)
GaLactic and Extragalactic All-sky Murchison Wide Field Array (GLEAM) survey. I: A low-frequency extragalactic
catalogue. Hurley-Walker N., et al., Mon. Not. R. Astron. Soc., 464, 1146-1167 (2017), 2017MNRAS.464.1146H
:param npixel: Number of pixels
:param polarisation_frame: Polarisation frame (default PolarisationFrame("stokesI"))
:param cellsize: cellsize in radians
:param frequency:
:param channel_bandwidth: Channel width (Hz)
:param phasecentre: phasecentre (SkyCoord)
:param kind: Kind of interpolation (see scipy.interpolate.interp1d) Default: linear
:return: Image
"""
if phasecentre is None:
phasecentre = SkyCoord(ra=+15.0 * u.deg,
dec=-35.0 * u.deg,
frame='icrs',
equinox='J2000')
if radius is None:
radius = npixel * cellsize / numpy.sqrt(2.0)
sc = create_low_test_skycomponents_from_gleam(
flux_limit=flux_limit,
polarisation_frame=polarisation_frame,
frequency=frequency,
phasecentre=phasecentre,
kind=kind,
radius=radius,
nchan=nchan)
if polarisation_frame is None:
polarisation_frame = PolarisationFrame("stokesI")
npol = polarisation_frame.npol
nchan = len(frequency)
shape = [nchan, npol, npixel, npixel]
w = WCS(naxis=4)
# The negation in the longitude is needed by definition of RA, DEC
w.wcs.cdelt = [
-cellsize * 180.0 / numpy.pi, cellsize * 180.0 / numpy.pi, 1.0,
channel_bandwidth[0]
]
w.wcs.crpix = [npixel // 2 + 1, npixel // 2 + 1, 1.0, 1.0]
w.wcs.ctype = ["RA---SIN", "DEC--SIN", 'STOKES', 'FREQ']
w.wcs.crval = [phasecentre.ra.deg, phasecentre.dec.deg, 1.0, frequency[0]]
w.naxis = 4
w.wcs.radesys = 'ICRS'
w.wcs.equinox = 2000.0
model = create_image_from_array(numpy.zeros(shape),
w,
polarisation_frame=polarisation_frame)
model = insert_skycomponent(model, sc, insert_method=insert_method)
if applybeam:
beam = create_low_test_beam(model)
model.data[...] *= beam.data[...]
log.info(qa_image(model, context='create_low_test_image_from_gleam'))
return model
def actualSetUp(self, time=None, dospectral=False, dopol=False):
self.lowcore = create_named_configuration('LOWBD2-CORE')
self.times = (numpy.pi / 12.0) * numpy.linspace(-3.0, 3.0, 5)
if time is not None:
self.times = time
log.info("Times are %s" % self.times)
if dospectral:
self.nchan = 3
self.frequency = numpy.array([0.9e8, 1e8, 1.1e8])
self.channel_bandwidth = numpy.array([1e7, 1e7, 1e7])
else:
self.frequency = numpy.array([1e8])
self.channel_bandwidth = numpy.array([1e7])
if dopol:
self.vis_pol = PolarisationFrame('linear')
self.image_pol = PolarisationFrame('stokesIQUV')
f = numpy.array([100.0, 20.0, -10.0, 1.0])
else:
self.vis_pol = PolarisationFrame('stokesI')
self.image_pol = PolarisationFrame('stokesI')
f = numpy.array([100.0])
if dospectral:
flux = numpy.array([f, 0.8 * f, 0.6 * f])
else:
flux = numpy.array([f])
self.phasecentre = SkyCoord(ra=+180.0 * u.deg,
dec=-60.0 * u.deg,
frame='icrs',
equinox='J2000')
self.componentvis = create_visibility(
self.lowcore,
self.times,
self.frequency,
channel_bandwidth=self.channel_bandwidth,
phasecentre=self.phasecentre,
weight=1.0,
polarisation_frame=self.vis_pol)
self.uvw = self.componentvis.data['uvw']
self.componentvis.data['vis'][...] = 0.0
# Create model
self.model = create_image_from_visibility(
self.componentvis,
npixel=self.params['npixel'],
cellsize=0.0005,
nchan=len(self.frequency),
polarisation_frame=self.image_pol)
# Fill the visibility with exactly computed point sources.
spacing_pixels = 512 // 8
log.info('Spacing in pixels = %s' % spacing_pixels)
centers = [(x, x) for x in numpy.linspace(-1.4, +1.4, 9)]
for x in numpy.linspace(-1.4, +1.4, 9):
centers.append((-x, x))
centers.append((0.5, 1.1))
centers.append((1e-7, 1e-7))
# Make the list of components
rpix = self.model.wcs.wcs.crpix
self.components = []
for center in centers:
ix, iy = center
# The phase center in 0-relative coordinates is n // 2 so we centre the grid of
# components on ny // 2, nx // 2. The wcs must be defined consistently.
p = int(round(rpix[0] + ix * spacing_pixels * numpy.sign(self.model.wcs.wcs.cdelt[0]))), \
int(round(rpix[1] + iy * spacing_pixels * numpy.sign(self.model.wcs.wcs.cdelt[1])))
sc = pixel_to_skycoord(p[0], p[1], self.model.wcs, origin=1)
log.info("Component at (%f, %f) [0-rel] %s" %
(p[0], p[1], str(sc)))
if ix != 0 and iy != 0:
# Channel images
comp = create_skycomponent(flux=flux,
frequency=self.frequency,
direction=sc,
polarisation_frame=self.image_pol)
self.components.append(comp)
# Predict the visibility from the components exactly
self.componentvis.data['vis'] *= 0.0
self.beam = create_low_test_beam(self.model)
self.components = apply_beam_to_skycomponent(self.components,
self.beam)
self.componentvis = predict_skycomponent_visibility(
self.componentvis, self.components)
self.model = insert_skycomponent(self.model, self.components)
# Calculate the model convolved with a Gaussian.
self.cmodel = smooth_image(self.model)
export_image_to_fits(self.model,
'%s/test_imaging_functions_model.fits' % self.dir)
export_image_to_fits(
self.cmodel, '%s/test_imaging_functions_cmodel.fits' % self.dir)
def actualSetUp(self, time=None, frequency=None):
self.lowcore = create_named_configuration('LOWBD2-CORE')
self.times = (numpy.pi / (12.0)) * numpy.linspace(-3.0, 3.0, 7)
if time is not None:
self.times = time
log.info("Times are %s" % (self.times))
if frequency is None:
self.frequency = numpy.array([1e8])
self.channel_bandwidth = numpy.array([1e7])
else:
self.frequency = frequency
if len(self.frequency) < 1:
self.channel_bandwidth = numpy.full_like(
self.frequency, self.frequency[1] - self.frequency[0])
else:
self.channel_bandwidth = numpy.array([1e6])
self.phasecentre = SkyCoord(ra=+180.0 * u.deg,
dec=-60.0 * u.deg,
frame='icrs',
equinox=2000.0)
self.componentvis = create_visibility(
self.lowcore,
self.times,
self.frequency,
channel_bandwidth=self.channel_bandwidth,
phasecentre=self.phasecentre,
weight=1.0,
polarisation_frame=PolarisationFrame('stokesI'))
self.uvw = self.componentvis.data['uvw']
self.componentvis.data['vis'] *= 0.0
# Create model
self.model = create_image_from_visibility(
self.componentvis,
npixel=256,
cellsize=0.001,
nchan=1,
polarisation_frame=PolarisationFrame('stokesI'))
# Fill the visibility with exactly computed point sources. These are chosen to lie
# on grid points.
spacing_pixels = 32
log.info('Spacing in pixels = %s' % spacing_pixels)
centers = [-2.5, -0.5, 0.5, 2.5]
# Make the list of components
rpix = self.model.wcs.wcs.crpix - 1
self.components = []
for iy in centers:
for ix in centers:
if ix >= iy:
# The phase center in 0-relative coordinates is n // 2 so we centre the grid of
# components on ny // 2, nx // 2. The wcs must be defined consistently.
p = int(round(rpix[0] + ix * spacing_pixels * numpy.sign(self.model.wcs.wcs.cdelt[0]))), \
int(round(rpix[1] + iy * spacing_pixels * numpy.sign(self.model.wcs.wcs.cdelt[1])))
sc = pixel_to_skycoord(p[0],
p[1],
self.model.wcs,
origin=0)
log.info("Component at (%f, %f) [0-rel] %s" %
(p[0], p[1], str(sc)))
f = (100.0 + 1.0 * ix + iy * 10.0)
# Channel images
flux = numpy.array([[f]])
comp = create_skycomponent(
flux=flux,
frequency=[numpy.average(self.frequency)],
direction=sc,
polarisation_frame=PolarisationFrame('stokesI'))
self.components.append(comp)
# Predict the visibility from the components exactly. We always do this for each spectral channel
self.componentvis.data['vis'] *= 0.0
predict_skycomponent_visibility(self.componentvis, self.components)
insert_skycomponent(self.model, self.components)
# Calculate the model convolved with a Gaussian.
norm = 2.0 * numpy.pi
self.cmodel = copy_image(self.model)
self.cmodel.data[0, 0, :, :] = norm * convolve(
self.model.data[0, 0, :, :],
Gaussian2DKernel(1.0),
normalize_kernel=False)
export_image_to_fits(self.model, '%s/test_model.fits' % self.dir)
export_image_to_fits(self.cmodel, '%s/test_cmodel.fits' % self.dir)
def actualSetUp(self,
add_errors=False,
freqwin=1,
block=False,
dospectral=True,
dopol=False):
self.low = create_named_configuration('LOWBD2', rmax=750.0)
self.freqwin = freqwin
self.vis_graph_list = list()
self.ntimes = 5
self.times = numpy.linspace(-3.0, +3.0, self.ntimes) * numpy.pi / 12.0
self.frequency = numpy.linspace(0.8e8, 1.2e8, self.freqwin)
if freqwin > 1:
self.channelwidth = numpy.array(
freqwin * [self.frequency[1] - self.frequency[0]])
else:
self.channelwidth = numpy.array([1e6])
if dopol:
self.vis_pol = PolarisationFrame('linear')
self.image_pol = PolarisationFrame('stokesIQUV')
f = numpy.array([100.0, 20.0, -10.0, 1.0])
else:
self.vis_pol = PolarisationFrame('stokesI')
self.image_pol = PolarisationFrame('stokesI')
f = numpy.array([100.0])
if dospectral:
flux = numpy.array(
[f * numpy.power(freq / 1e8, -0.7) for freq in self.frequency])
else:
flux = numpy.array([f])
self.phasecentre = SkyCoord(ra=+180.0 * u.deg,
dec=-60.0 * u.deg,
frame='icrs',
equinox='J2000')
self.componentvis = ingest_unittest_visibility(self.low,
self.frequency,
self.channelwidth,
self.times,
self.vis_pol,
self.phasecentre,
block=block)
self.model = create_unittest_model(self.componentvis,
self.image_pol,
npixel=self.params['npixel'])
self.components = create_unittest_components(self.model, flux)
self.model = insert_skycomponent(self.model, self.components)
self.componentvis.data['vis'][...] = 0.0
self.componentvis = predict_skycomponent_visibility(
self.componentvis, self.components)
self.cmodel = smooth_image(self.model)
export_image_to_fits(self.model,
'%s/test_imaging_functions_model.fits' % self.dir)
export_image_to_fits(
self.cmodel, '%s/test_imaging_functions_cmodel.fits' % self.dir)
if add_errors:
self.componentvis = insert_unittest_errors(self.componentvis)
