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 test_vis_auto_conversion_I(self):
stokes = numpy.array(random.uniform(-1.0, 1.0, [1000, 3, 1]))
ipf = PolarisationFrame('stokesI')
opf = PolarisationFrame('stokesI')
cir = convert_pol_frame(stokes, ipf, opf, polaxis=2)
st = convert_pol_frame(cir, opf, ipf, polaxis=2)
assert_array_almost_equal(st.real, stokes, 15)
def import_image_from_fits(fitsfile: str, mute_warnings=True) -> Image:
""" Read an Image from fits
:param fitsfile:
:return: Image
"""
fim = Image()
with warnings.catch_warnings():
warnings.simplefilter('ignore')
hdulist = fits.open(arl_path(fitsfile))
fim.data = hdulist[0].data
fim.wcs = WCS(arl_path(fitsfile))
hdulist.close()
if len(fim.data) == 2:
fim.polarisation_frame = PolarisationFrame('stokesI')
else:
try:
fim.polarisation_frame = polarisation_frame_from_wcs(
fim.wcs, fim.data.shape)
except:
fim.polarisation_frame = PolarisationFrame('stokesI')
log.debug(
"import_image_from_fits: created %s image of shape %s, size %.3f (GB)"
% (fim.data.dtype, str(fim.shape), image_sizeof(fim)))
log.debug("import_image_from_fits: Max, min in %s = %.6f, %.6f" %
(fitsfile, fim.data.max(), fim.data.min()))
assert isinstance(fim, Image)
return fim
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 actualSetup(self,
sky_pol_frame='stokesIQUV',
data_pol_frame='linear',
f=[100.0, 50.0, -10.0, 40.0]):
f = numpy.array(f)
self.flux = numpy.array([f, 0.8 * f, 0.6 * f])
# The phase centre is absolute and the component is specified relative (for now).
# This means that the component should end up at the position phasecentre+compredirection
self.phasecentre = SkyCoord(ra=+180.0 * u.deg,
dec=-35.0 * u.deg,
frame='icrs',
equinox='J2000')
self.compabsdirection = SkyCoord(ra=+181.0 * u.deg,
dec=-35.0 * u.deg,
frame='icrs',
equinox='J2000')
self.comp = Skycomponent(
direction=self.compabsdirection,
frequency=self.frequency,
flux=self.flux,
polarisation_frame=PolarisationFrame(sky_pol_frame))
self.vis = create_blockvisibility(
self.lowcore,
self.times,
self.frequency,
phasecentre=self.phasecentre,
channel_bandwidth=self.channel_bandwidth,
weight=1.0,
polarisation_frame=PolarisationFrame(data_pol_frame))
self.vis = predict_skycomponent_blockvisibility(self.vis, self.comp)
def test_image_auto_conversion_I(self):
stokes = numpy.array(random.uniform(-1.0, 1.0, [3, 4, 128, 128]))
ipf = PolarisationFrame('stokesI')
opf = PolarisationFrame('stokesI')
cir = convert_pol_frame(stokes, ipf, opf)
st = convert_pol_frame(cir, opf, ipf)
assert_array_almost_equal(st.real, stokes, 15)
def test_create_vis_iter_with_model(self):
model = create_test_image(canonical=True,
cellsize=0.001,
frequency=self.frequency,
phasecentre=self.phasecentre)
comp = Skycomponent(direction=self.phasecentre,
frequency=self.frequency,
flux=self.flux,
polarisation_frame=PolarisationFrame('stokesI'))
vis_iter = create_blockvisibility_iterator(
self.config,
self.times,
self.frequency,
channel_bandwidth=self.channel_bandwidth,
phasecentre=self.phasecentre,
weight=1.0,
polarisation_frame=PolarisationFrame('stokesI'),
integration_time=30.0,
number_integrations=3,
model=model,
components=comp)
fullvis = None
totalnvis = 0
for i, vis in enumerate(vis_iter):
assert vis.phasecentre == self.phasecentre
assert vis.nvis
if i == 0:
fullvis = vis
totalnvis = vis.nvis
else:
fullvis = append_visibility(fullvis, vis)
totalnvis += vis.nvis
assert fullvis.nvis == totalnvis
def setUp(self):
self.dir = './test_results'
os.makedirs(self.dir, exist_ok=True)
self.niter = 1000
self.lowcore = create_named_configuration('LOWBD2-CORE')
self.nchan = 5
self.times = (numpy.pi / 12.0) * numpy.linspace(-3.0, 3.0, 7)
self.frequency = numpy.linspace(0.9e8, 1.1e8, self.nchan)
self.channel_bandwidth = numpy.array(self.nchan * [self.frequency[1] - self.frequency[0]])
self.phasecentre = SkyCoord(ra=+0.0 * u.deg, dec=-45.0 * u.deg, frame='icrs', equinox='J2000')
self.vis = create_visibility(self.lowcore, self.times, self.frequency, self.channel_bandwidth,
phasecentre=self.phasecentre, weight=1.0,
polarisation_frame=PolarisationFrame('stokesI'))
self.vis.data['vis'] *= 0.0
# Create model
self.test_model = create_low_test_image_from_gleam(npixel=512, cellsize=0.001,
phasecentre=self.vis.phasecentre,
frequency=self.frequency,
channel_bandwidth=self.channel_bandwidth)
beam = create_low_test_beam(self.test_model)
export_image_to_fits(beam, "%s/test_deconvolve_msmfsclean_beam.fits" % self.dir)
self.test_model.data *= beam.data
export_image_to_fits(self.test_model, "%s/test_deconvolve_msmfsclean_model.fits" % self.dir)
self.vis = predict_2d(self.vis, self.test_model)
assert numpy.max(numpy.abs(self.vis.vis)) > 0.0
self.model = create_image_from_visibility(self.vis, npixel=512, cellsize=0.001,
polarisation_frame=PolarisationFrame('stokesI'))
self.dirty, sumwt = invert_2d(self.vis, self.model)
self.psf, sumwt = invert_2d(self.vis, self.model, dopsf=True)
export_image_to_fits(self.dirty, "%s/test_deconvolve_msmfsclean_dirty.fits" % self.dir)
export_image_to_fits(self.psf, "%s/test_deconvolve_msmfsclean_psf.fits" % self.dir)
window = numpy.ones(shape=self.model.shape, dtype=numpy.bool)
window[..., 129:384, 129:384] = True
self.innerquarter = create_image_from_array(window, self.model.wcs)
def setUp(self):
self.dir = './test_results'
os.makedirs(self.dir, exist_ok=True)
self.lowcore = create_named_configuration('LOWBD2-CORE')
self.times = (numpy.pi / (12.0)) * numpy.linspace(-3.0, 3.0, 7)
self.frequency = numpy.array([1e8])
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.vis = create_visibility(self.lowcore, self.times, self.frequency,
channel_bandwidth=self.channel_bandwidth,
phasecentre=self.phasecentre, weight=1.0,
polarisation_frame=PolarisationFrame('stokesI'))
self.vis.data['vis'] *= 0.0
# Create model
self.test_model = create_test_image(cellsize=0.001, phasecentre=self.vis.phasecentre,
frequency=self.frequency)
self.vis = predict_2d(self.vis, self.test_model)
assert numpy.max(numpy.abs(self.vis.vis)) > 0.0
self.model = create_image_from_visibility(self.vis, npixel=512, cellsize=0.001,
polarisation_frame=PolarisationFrame('stokesI'))
self.dirty, sumwt = invert_2d(self.vis, self.model)
self.psf, sumwt = invert_2d(self.vis, self.model, dopsf=True)
window = numpy.zeros(shape=self.model.shape, dtype=numpy.bool)
window[..., 129:384, 129:384] = True
self.innerquarter = create_image_from_array(window, self.model.wcs)
def test_phase_rotation(self):
self.vis = create_visibility(
self.lowcore,
self.times,
self.frequency,
channel_bandwidth=self.channel_bandwidth,
phasecentre=self.phasecentre,
weight=1.0,
polarisation_frame=PolarisationFrame("stokesIQUV"))
self.vismodel = predict_skycomponent_visibility(self.vis, self.comp)
# Predict visibilities with new phase centre independently
ha_diff = -(self.compabsdirection.ra - self.phasecentre.ra).to(
u.rad).value
vispred = create_visibility(
self.lowcore,
self.times + ha_diff,
self.frequency,
channel_bandwidth=self.channel_bandwidth,
phasecentre=self.compabsdirection,
weight=1.0,
polarisation_frame=PolarisationFrame("stokesIQUV"))
vismodel2 = predict_skycomponent_visibility(vispred, self.comp)
# Should yield the same results as rotation
rotatedvis = phaserotate_visibility(
self.vismodel, newphasecentre=self.compabsdirection, tangent=False)
assert_allclose(rotatedvis.vis, vismodel2.vis, rtol=1e-7)
assert_allclose(rotatedvis.uvw, vismodel2.uvw, rtol=1e-7)
def test_scatter_gather(self):
m31original = create_test_image(
polarisation_frame=PolarisationFrame('stokesI'))
assert numpy.max(numpy.abs(m31original.data)), "Original is empty"
for nraster in [2, 4, 8]:
m31model = create_test_image(
polarisation_frame=PolarisationFrame('stokesI'))
image_list = image_scatter(m31model, facets=nraster)
for patch in image_list:
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
m31model = image_gather(image_list, m31model, facets=nraster)
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 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 actualSetUp(self,
time=None,
frequency=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')
else:
self.vis_pol = PolarisationFrame('stokesI')
self.image_pol = PolarisationFrame('stokesI')
if dopol:
f = numpy.array([100.0, 20.0, -10.0, 1.0])
else:
f = numpy.array([100.0])
if dospectral:
numpy.array([f, 0.8 * f, 0.6 * f])
else:
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=512,
cellsize=0.001,
nchan=len(self.frequency),
polarisation_frame=self.image_pol)
def setUp(self):
self.dir = './test_results'
os.makedirs(self.dir, exist_ok=True)
lowcore = create_named_configuration('LOWBD2-CORE')
times = numpy.arange(-3.0, +3.0, 1.0) * numpy.pi / 12.0
vnchan = 8
frequency = numpy.linspace(0.8e8, 1.20e8, vnchan)
channel_bandwidth = numpy.array(vnchan * [frequency[1] - frequency[0]])
# Define the component and give it some polarisation and spectral behaviour
f = numpy.array([100.0, 20.0, -10.0, 1.0])
self.flux = numpy.array(
[f, 0.9 * f, 0.8 * f, 0.7 * f, 0.6 * f, 0.5 * f, 0.4 * f, 0.3 * f])
self.phasecentre = SkyCoord(ra=+15.0 * u.deg,
dec=-35.0 * u.deg,
frame='icrs',
equinox='J2000')
self.compabsdirection = SkyCoord(ra=17.0 * u.deg,
dec=-36.5 * u.deg,
frame='icrs',
equinox='J2000')
self.comp = create_skycomponent(flux=self.flux,
frequency=frequency,
direction=self.compabsdirection)
self.image = create_test_image(
frequency=frequency,
phasecentre=self.phasecentre,
cellsize=0.001,
polarisation_frame=PolarisationFrame('stokesIQUV'))
self.blockvis = create_blockvisibility_iterator(
lowcore,
times=times,
frequency=frequency,
channel_bandwidth=channel_bandwidth,
phasecentre=self.phasecentre,
weight=1,
polarisation_frame=PolarisationFrame('linear'),
integration_time=1.0,
number_integrations=1,
predict=predict_2d,
components=self.comp,
phase_error=0.1,
amplitude_error=0.01,
sleep=1.0)
self.vis = create_blockvisibility(
lowcore,
times=times,
frequency=frequency,
channel_bandwidth=channel_bandwidth,
phasecentre=self.phasecentre,
weight=1,
polarisation_frame=PolarisationFrame('stokesIQUV'),
integration_time=1.0)
self.vis = predict_2d(self.vis, self.image)
def test_circular_to_linear(self):
stokes = numpy.array(random.uniform(-1.0, 1.0, [3, 4, 128, 128]))
ipf = PolarisationFrame('stokesIQUV')
opf = PolarisationFrame('circular')
cir = convert_pol_frame(stokes, ipf, opf)
wrong_pf = PolarisationFrame('linear')
with self.assertRaises(ValueError):
lin = convert_pol_frame(cir, opf, wrong_pf)
def create_test_image(
canonical=True,
cellsize=None,
frequency=None,
channel_bandwidth=None,
phasecentre=None,
polarisation_frame=PolarisationFrame("stokesI")) -> Image:
"""Create a useful test image
This is the test image M31 widely used in ALMA and other simulations. It is actually part of an Halpha region in
M31.
:param canonical: Make the image into a 4 dimensional image
:param cellsize:
:param frequency: Frequency (array) in Hz
:param channel_bandwidth: Channel bandwidth (array) in Hz
:param phasecentre: Phase centre of image (SkyCoord)
:param polarisation_frame: Polarisation frame
:return: Image
"""
if frequency is None:
frequency = [1e8]
im = import_image_from_fits(arl_path("data/models/M31.MOD"))
if canonical:
if polarisation_frame is None:
im.polarisation_frame = PolarisationFrame("stokesI")
elif isinstance(polarisation_frame, PolarisationFrame):
im.polarisation_frame = polarisation_frame
else:
raise ValueError("polarisation_frame is not valid")
im = replicate_image(im,
frequency=frequency,
polarisation_frame=im.polarisation_frame)
if cellsize is not None:
im.wcs.wcs.cdelt[0] = -180.0 * cellsize / numpy.pi
im.wcs.wcs.cdelt[1] = +180.0 * cellsize / numpy.pi
if frequency is not None:
im.wcs.wcs.crval[3] = frequency[0]
if channel_bandwidth is not None:
im.wcs.wcs.cdelt[3] = channel_bandwidth[0]
else:
if len(frequency) > 1:
im.wcs.wcs.cdelt[3] = frequency[1] - frequency[0]
else:
im.wcs.wcs.cdelt[3] = 0.001 * frequency[0]
im.wcs.wcs.radesys = 'ICRS'
im.wcs.wcs.equinox = 2000.00
if phasecentre is not None:
im.wcs.wcs.crval[0] = phasecentre.ra.deg
im.wcs.wcs.crval[1] = phasecentre.dec.deg
# WCS is 1 relative
im.wcs.wcs.crpix[0] = im.data.shape[3] // 2 + 1
im.wcs.wcs.crpix[1] = im.data.shape[2] // 2 + 1
return im
def get_polarisation_map(vis: Visibility, im: Image = None):
""" Get the mapping of visibility polarisations to image polarisations
"""
if vis.polarisation_frame == im.polarisation_frame:
if vis.polarisation_frame == PolarisationFrame('stokesI'):
return "stokesI->stokesI", lambda pol: 0
elif vis.polarisation_frame == PolarisationFrame('stokesIQUV'):
return "stokesIQUV->stokesIQUV", lambda pol: pol
return "unknown", lambda pol: pol
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_subtract(self):
vis1 = create_visibility(self.lowcore, self.times, self.frequency,
channel_bandwidth=self.channel_bandwidth,
phasecentre=self.phasecentre, weight=1.0,
polarisation_frame=PolarisationFrame("stokesIQUV"))
vis1.data['vis'][...] = 1.0
vis2 = create_visibility(self.lowcore, self.times, self.frequency,
channel_bandwidth=self.channel_bandwidth,
phasecentre=self.phasecentre, weight=1.0,
polarisation_frame=PolarisationFrame("stokesIQUV"))
vis2.data['vis'][...] = 1.0
zerovis = subtract_visibility(vis1, vis2)
qa = qa_visibility(zerovis, context='test_qa')
self.assertAlmostEqual(qa.data['maxabs'], 0.0, 7)
def convert_polimage_to_stokes(im: Image):
"""Convert a polarisation image to stokes (complex)
"""
assert type(im) == Image
assert im.data.dtype == 'complex'
if im.polarisation_frame == PolarisationFrame('linear'):
cimarr = convert_linear_to_stokes(im.data)
return create_image_from_array(cimarr, im.wcs, PolarisationFrame('stokesIQUV'))
elif im.polarisation_frame == PolarisationFrame('circular'):
cimarr = convert_circular_to_stokes(im.data)
return create_image_from_array(cimarr, im.wcs, PolarisationFrame('stokesIQUV'))
else:
raise ValueError("Cannot convert %s to stokes" % (im.polarisation_frame.type))
def actualSetup(self, sky_pol_frame='stokesIQUV', data_pol_frame='linear'):
self.comp = Skycomponent(
direction=self.compabsdirection,
frequency=self.frequency,
flux=self.flux,
polarisation_frame=PolarisationFrame(sky_pol_frame))
self.vis = create_blockvisibility(
self.lowcore,
self.times,
self.frequency,
phasecentre=self.phasecentre,
channel_bandwidth=self.channel_bandwidth,
weight=1.0,
polarisation_frame=PolarisationFrame(data_pol_frame))
self.vis = predict_skycomponent_blockvisibility(self.vis, self.comp)
def __init__(self,
data=None, frequency=None, channel_bandwidth=None, phasecentre=None, configuration=None,
uvw=None, time=None,
vis=None, weight=None, integration_time=None,
polarisation_frame=PolarisationFrame('stokesI')):
if data is None and vis is not None:
ntimes = vis.shape[0]
assert vis.shape == weight.shape
nants = vis.shape[1]
assert vis.shape[2] == nants
nchan = vis.shape[3]
npol = vis.shape[4]
desc = [('uvw', '>f8', (nants, nants, 3)),
('time', '>f8'),
('integration_time', '>f8'),
('vis', '>c16', (nants, nants, nchan, npol)),
('weight', '>f8', (nants, nants, nchan, npol))]
data = numpy.zeros(shape=[ntimes], dtype=desc)
data['uvw'] = uvw
data['time'] = time
data['integration_time'] = integration_time
data['vis'] = vis
data['weight'] = weight
self.data = data # numpy structured array
self.frequency = frequency
self.channel_bandwidth = channel_bandwidth
self.phasecentre = phasecentre # Phase centre of observation
self.configuration = configuration # Antenna/station configuration
self.polarisation_frame = polarisation_frame
def __init__(self,
direction=None, frequency=None, name=None, flux=None, shape='Point',
polarisation_frame=PolarisationFrame('stokesIQUV'), **kwargs):
""" Define the required structure
:param direction: SkyCoord
:param frequency: numpy.array [nchan]
:param name: user friendly name
:param flux: numpy.array [nchan, npol]
:param shape: str e.g. 'Point' 'Gaussian'
:param params: numpy.array shape dependent parameters
:param polarisation_frame: Polarisation_frame
"""
self.direction = direction
self.frequency = numpy.array(frequency)
self.name = name
self.flux = numpy.array(flux)
self.shape = shape
self.params = kwargs
self.polarisation_frame = polarisation_frame
assert len(self.frequency.shape) == 1
assert len(self.flux.shape) == 2
assert self.frequency.shape[0] == self.flux.shape[0], "Frequency shape %s, flux shape %s" % (
self.frequency.shape, self.flux.shape)
assert polarisation_frame.npol == self.flux.shape[1], "Polarisation is %s,, flux shape %s" % (
polarisation_frame.type, self.flux.shape)
def setUp(self):
self.dir = './test_results'
self.lowcore = create_named_configuration('LOWBD2-CORE')
os.makedirs(self.dir, exist_ok=True)
self.times = (numpy.pi / (12.0)) * numpy.linspace(-3.0, 3.0, 7)
self.frequency = numpy.array([1e8])
self.channel_bandwidth = numpy.array([1e6])
self.phasecentre = SkyCoord(ra=+180.0 * u.deg,
dec=-60.0 * u.deg,
frame='icrs',
equinox='J2000')
self.vis = create_visibility(
self.lowcore,
self.times,
self.frequency,
channel_bandwidth=self.channel_bandwidth,
phasecentre=self.phasecentre,
weight=1.0,
polarisation_frame=PolarisationFrame('stokesI'))
self.vis.data['vis'] *= 0.0
# Create model
self.model = create_test_image(cellsize=0.0015,
phasecentre=self.vis.phasecentre,
frequency=self.frequency)
self.model.data[self.model.data > 1.0] = 1.0
self.vis = predict_2d(self.vis, self.model)
assert numpy.max(numpy.abs(self.vis.vis)) > 0.0
export_image_to_fits(
self.model, '%s/test_solve_skycomponent_model.fits' % (self.dir))
self.bigmodel = create_image_from_visibility(self.vis,
cellsize=0.0015,
npixel=512)
def create_image_from_array(
data: numpy.array,
wcs: WCS = None,
polarisation_frame=PolarisationFrame('stokesI')) -> Image:
""" Create an image from an array and optional wcs
:param data: Numpy.array
:param wcs: World coordinate system
:param polarisation_frame: Polarisation Frame
:return: Image
"""
fim = Image()
fim.polarisation_frame = polarisation_frame
fim.data = data
if wcs is None:
fim.wcs = None
else:
fim.wcs = wcs.deepcopy()
if image_sizeof(fim) >= 1.0:
log.debug(
"create_image_from_array: created %s image of shape %s, size %.3f (GB)"
% (fim.data.dtype, str(fim.shape), image_sizeof(fim)))
assert isinstance(fim, Image), "Type is %s" % type(fim)
return fim
def test_phase_rotation_identity(self):
self.vis = create_visibility(
self.lowcore,
self.times,
self.frequency,
channel_bandwidth=self.channel_bandwidth,
phasecentre=self.phasecentre,
weight=1.0,
polarisation_frame=PolarisationFrame("stokesIQUV"))
self.vismodel = predict_skycomponent_visibility(self.vis, self.comp)
newphasecenters = [
SkyCoord(182, -35, unit=u.deg),
SkyCoord(182, -30, unit=u.deg),
SkyCoord(177, -30, unit=u.deg),
SkyCoord(176, -35, unit=u.deg),
SkyCoord(216, -35, unit=u.deg),
SkyCoord(180, -70, unit=u.deg)
]
for newphasecentre in newphasecenters:
# Phase rotating back should not make a difference
original_vis = self.vismodel.vis
original_uvw = self.vismodel.uvw
rotatedvis = phaserotate_visibility(phaserotate_visibility(
self.vismodel, newphasecentre, tangent=False),
self.phasecentre,
tangent=False)
assert_allclose(rotatedvis.uvw, original_uvw, rtol=1e-7)
assert_allclose(rotatedvis.vis, original_vis, rtol=1e-7)
def create_image_para_2(ny,
nx,
chan,
pol,
facet,
phasecentre,
cellsize=0.001,
polarisation_frame=PolarisationFrame('linear'),
FACET=2):
wcs4 = WCS(naxis=4)
wcs4.wcs.crpix = [ny * FACET // 2, nx * FACET // 2 + 1.0, 1.0, 1.0]
wcs4.wcs.cdelt = [
-180.0 * cellsize / np.pi, +180.0 * cellsize / np.pi, 1.0, 1.0
]
wcs4.wcs.crval = [phasecentre.ra.deg, phasecentre.dec.deg, 1.0, 1.0]
wcs4.wcs.ctype = ["RA---SIN", "DEC--SIN", 'STOKES', 'FREQ']
wcs4.wcs.radesys = 'ICRS'
wcs4.wcs.equinox = 2000.00
data = np.zeros([ny, nx])
keys = {
"beam": 0,
"major_loop": 0,
"channel": chan,
"time": 0,
"facet": facet,
"polarisation": pol
}
y = facet // FACET
x = facet % FACET
wcs4.wcs.crpix[0] -= x * nx
wcs4.wcs.crpix[1] -= y * ny
image_para = image_for_para(data, wcs4_to_wcs2(wcs4), keys)
return image_para
def setUp(self):
self.dir = './test_results'
os.makedirs(self.dir, exist_ok=True)
self.vnchan = 5
self.lowcore = create_named_configuration('LOWBD2-CORE')
self.times = (numpy.pi / 12.0) * numpy.linspace(-3.0, 3.0, 7)
self.frequency = numpy.linspace(8e7, 1.2e8, self.vnchan)
self.startfrequency = numpy.array([8e7])
self.channel_bandwidth = numpy.array(
self.vnchan * [self.frequency[1] - self.frequency[0]])
self.phasecentre = SkyCoord(ra=+180.0 * u.deg,
dec=-60.0 * u.deg,
frame='icrs',
equinox='J2000')
self.vis = create_visibility(
self.lowcore,
times=self.times,
frequency=self.frequency,
phasecentre=self.phasecentre,
weight=1.0,
polarisation_frame=PolarisationFrame('stokesI'),
channel_bandwidth=self.channel_bandwidth)
self.model = create_image_from_visibility(
self.vis,
npixel=512,
cellsize=0.001,
nchan=self.vnchan,
frequency=self.startfrequency)
def create_image(ny,
nx,
frequency,
phasecentre,
cellsize=0.001,
polarisation_frame=PolarisationFrame('linear')):
'''
创建和上个函数等效的非并行的image
:param ny:
:param nx:
:param frequency:
:param phasecentre:
:param cellsize:
:param polarisation_frame:
:return:
'''
wcs4 = WCS(naxis=4)
wcs4.wcs.crpix = [ny // 2, nx // 2 + 1.0, 1.0, 1.0]
wcs4.wcs.cdelt = [
-180.0 * cellsize / np.pi, +180.0 * cellsize / np.pi, 1.0,
frequency[1] - frequency[0]
]
wcs4.wcs.crval = [
phasecentre.ra.deg, phasecentre.dec.deg, 1.0, frequency[0]
]
wcs4.wcs.ctype = ["RA---SIN", "DEC--SIN", 'STOKES', 'FREQ']
wcs4.wcs.radesys = 'ICRS'
wcs4.wcs.equinox = 2000.00
nchan = frequency.shape[0]
npol = polarisation_frame.npol
image = Image()
image.wcs = wcs4
image.data = np.zeros([nchan, npol, ny, nx])
image.polarisation_frame = polarisation_frame
return image
def test_create_low_test_beam(self):
im = create_test_image(
canonical=True,
cellsize=0.002,
frequency=numpy.array([1e8 - 5e7, 1e8, 1e8 + 5e7]),
channel_bandwidth=numpy.array([5e7, 5e7, 5e7]),
polarisation_frame=PolarisationFrame("stokesIQUV"),
phasecentre=self.phasecentre)
bm = create_low_test_beam(model=im)
export_image_to_fits(bm, '%s/test_low_beam.fits' % (self.dir))
assert bm.data.shape[0] == 3
assert bm.data.shape[1] == 4
assert bm.data.shape[2] == im.data.shape[2]
assert bm.data.shape[3] == im.data.shape[3]
# Check to see if the beam scales as expected
for i in [30, 40]:
assert numpy.max(
numpy.abs(bm.data[0, 0, 128, 128 - 2 * i] -
bm.data[1, 0, 128, 128 - i])) < 0.02
assert numpy.max(
numpy.abs(bm.data[0, 0, 128, 128 - 3 * i] -
bm.data[2, 0, 128, 128 - i])) < 0.02
assert numpy.max(
numpy.abs(bm.data[0, 0, 128 - 2 * i, 128] -
bm.data[1, 0, 128 - i, 128])) < 0.02
assert numpy.max(
numpy.abs(bm.data[0, 0, 128 - 3 * i, 128] -
bm.data[2, 0, 128 - i, 128])) < 0.02
