def setUp(self):
from data_models.parameters import arl_path
self.lowcore = create_named_configuration('LOWBD2', rmax=300.0)
self.dir = arl_path('test_results')
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_blockvisibility(
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
def actualSetup(self):
self.lowcore = create_named_configuration('LOWBD2-CORE')
self.times = (numpy.pi / 43200.0) * numpy.arange(0.0, 300.0, 30.0)
self.times = [0.0]
self.frequency = numpy.linspace(1.0e8, 1.1e8, 1)
self.channel_bandwidth = numpy.array([1e7])
# Define the component and give it some spectral behaviour
f = numpy.array([100.0, 20.0, -10.0, 1.0])
self.flux = numpy.array([f, 0.8 * f, 0.6 * f])
f = numpy.array([100.0])
self.flux = numpy.array([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.comp_actual_direction = SkyCoord(ra=+180.2 * u.deg,
dec=-35.1 * u.deg,
frame='icrs',
equinox='J2000')
self.comp_start_direction = SkyCoord(ra=+180.0 * u.deg,
dec=-35.0 * u.deg,
frame='icrs',
equinox='J2000')
self.comp = Skycomponent(
direction=self.comp_actual_direction,
frequency=self.frequency,
flux=self.flux,
polarisation_frame=PolarisationFrame("stokesI"))
def main():
lowcore = create_named_configuration('LOWBD2', rmax=400.0)
# We create the visibility.
# This just makes the uvw, time, antenna1, antenna2, weight columns in a table
dlg_string = os.environ['DLG_UID']
dlg_string = dlg_string[(dlg_string.rindex('_') + 1):len(dlg_string)]
dlg_uid = dlg_string.split('/')
Freq_Iteration = int(dlg_uid[1]) # derived from ID
#Facet_Iteration=int(dlg_uid[2]) # derived from ID
phasecentre_array = [[+15, -45], [+15.2, -45], [+15, -44], [+14.8, -45],
[+15, -46]]
t_range = 0
t_step = 1.0
# once a second between the time ranges in HA
times = numpy.arange(-t_range, +t_range,
tstep / 3600.0) * (numpy.pi / 12.0)
frequency = numpy.array([1e8 + Freq_Iteration * 1e6])
channel_bandwidth = numpy.array([1e6])
phasecentre = SkyCoord(ra=phasecentre_array[0][0] * u.deg,
dec=phasecentre_array[0][1] * 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'))
dump(1, vt)
def setUp(self):
from data_models.parameters import arl_path
self.dir = arl_path('test_results')
self.lowcore = create_named_configuration('LOWBD2-CORE')
self.times = (numpy.pi / 43200.0) * numpy.arange(0.0, 300.0, 100.0)
self.frequency = numpy.linspace(1.0e8, 1.1e8, 3)
self.channel_bandwidth = numpy.array([1e7, 1e7, 1e7])
# Define the component and give it some spectral behaviour
f = numpy.array([100.0, 20.0, -10.0, 1.0])
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)
def setUp(self):
from data_models.parameters import arl_path
self.dir = arl_path('test_results')
self.vnchan = 7
self.lowcore = create_named_configuration('LOWBD2', rmax=300.0)
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 * [(1.0 - 1.0e-7) *
(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=128,
cellsize=0.001,
nchan=self.vnchan,
frequency=self.startfrequency)
def actualSetUp(self,
time=None,
frequency=None,
dospectral=False,
dopol=False):
self.lowcore = create_named_configuration('LOWBD2', rmax=600)
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=self.npixel,
cellsize=0.001,
nchan=len(self.frequency),
polarisation_frame=self.image_pol)
def setUp(self):
from data_models.parameters import arl_path
self.dir = arl_path('test_results')
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'),
zerow=True)
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,
flux_limit=1.0)
beam = create_low_test_beam(self.test_model)
export_image_to_fits(beam,
"%s/test_deconvolve_mmclean_beam.fits" % self.dir)
self.test_model.data *= beam.data
export_image_to_fits(
self.test_model,
"%s/test_deconvolve_mmclean_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_mmclean-dirty.fits" % self.dir)
export_image_to_fits(self.psf,
"%s/test_deconvolve_mmclean-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,
polarisation_frame=PolarisationFrame('stokesI'))
def setUp(self):
self.lowcore = create_named_configuration('LOWBD2', rmax=300.0)
self.times = (numpy.pi / 43200.0) * numpy.arange(0.0, 30 * 3.76, 3.76)
df = 27343.75000
self.frequency = numpy.array([1e8 - df, 1e8, 1e8 + df])
self.channel_bandwidth = numpy.array([27343.75, 27343.75, 27343.75])
self.phasecentre = SkyCoord(ra=+0.0 * u.deg, dec=-35.0 * u.deg, frame='icrs', equinox='J2000')
self.blockvis = create_blockvisibility(self.lowcore, self.times, self.frequency, phasecentre=self.phasecentre,
weight=1.0, polarisation_frame=PolarisationFrame('stokesI'),
channel_bandwidth=self.channel_bandwidth)
def setUp(self):
self.lowcore = create_named_configuration('LOWBD2', rmax=750.0)
self.times = numpy.linspace(-300.0, 300.0, 5) * numpy.pi / 43200.0
self.frequency = numpy.array([1e8])
self.channel_bandwidth = numpy.array([1e8])
self.phasecentre = SkyCoord(ra=+15.0 * u.deg,
dec=-35.0 * u.deg,
frame='icrs',
equinox='J2000')
def actualSetUp(self,
add_errors=False,
freqwin=1,
block=False,
dospectral=True,
dopol=False):
self.npixel = 256
self.low = create_named_configuration('LOWBD2', rmax=750.0)
self.freqwin = freqwin
self.vis_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.vis = ingest_unittest_visibility(self.low,
self.frequency,
self.channelwidth,
self.times,
self.vis_pol,
self.phasecentre,
block=block)
self.model = create_unittest_model(self.vis,
self.image_pol,
npixel=self.npixel)
def createVis(self, config, dec=-35.0, rmax=None):
self.config = create_named_configuration(config, rmax=rmax)
self.phasecentre = SkyCoord(ra=+15 * u.deg,
dec=dec * u.deg,
frame='icrs',
equinox='J2000')
self.vis = create_visibility(
self.config,
self.times,
self.frequency,
channel_bandwidth=self.channel_bandwidth,
phasecentre=self.phasecentre,
weight=1.0,
polarisation_frame=PolarisationFrame('stokesI'))
def setUp(self):
self.lowcore = create_named_configuration('LOWBD2-CORE')
self.times = numpy.linspace(-300.0, 300.0, 11) * numpy.pi / 43200.0
self.frequency = numpy.linspace(1e8, 1.5e9, 7)
self.channel_bandwidth = numpy.array(
7 * [self.frequency[1] - self.frequency[0]])
self.phasecentre = SkyCoord(ra=+15.0 * u.deg,
dec=-35.0 * u.deg,
frame='icrs',
equinox='J2000')
def setUp(self):
from data_models.parameters import arl_path
self.dir = arl_path('test_results')
self.frequency = numpy.linspace(1e8, 1.5e8, 3)
self.channel_bandwidth = numpy.array([2.5e7, 2.5e7, 2.5e7])
self.flux = numpy.array([[100.0], [100.0], [100.0]])
self.phasecentre = SkyCoord(ra=+15.0 * u.deg,
dec=-35.0 * u.deg,
frame='icrs',
equinox='J2000')
self.config = create_named_configuration('LOWBD2-CORE')
self.times = numpy.linspace(-300.0, 300.0, 3) * numpy.pi / 43200.0
nants = self.config.xyz.shape[0]
assert nants > 1
assert len(self.config.names) == nants
assert len(self.config.mount) == nants
def actualSetup(self,
sky_pol_frame='stokesIQUV',
data_pol_frame='linear',
f=None,
vnchan=3):
self.lowcore = create_named_configuration('LOWBD2-CORE')
self.times = (numpy.pi / 43200.0) * numpy.linspace(0.0, 30.0, 3)
self.frequency = numpy.linspace(1.0e8, 1.1e8, vnchan)
self.channel_bandwidth = numpy.array(
vnchan * [self.frequency[1] - self.frequency[0]])
if f is None:
f = [100.0, 50.0, -10.0, 40.0]
if sky_pol_frame == 'stokesI':
f = [100.0]
self.flux = numpy.outer(
numpy.array(
[numpy.power(freq / 1e8, -0.7) for freq in self.frequency]), 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_visibility(self.vis, self.comp)
def setUp(self):
arlexecute.set_client(use_dask=False)
from data_models.parameters import arl_path
self.dir = arl_path('test_results')
self.lowcore = create_named_configuration('LOWBD2-CORE')
self.times = numpy.linspace(-3, +3, 13) * (numpy.pi / 12.0)
self.frequency = numpy.array([1e8])
self.channel_bandwidth = numpy.array([1e7])
# Define the component and give it some polarisation and spectral behaviour
f = numpy.array([100.0])
self.flux = numpy.array([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(
direction=self.compabsdirection,
flux=self.flux,
frequency=self.frequency,
polarisation_frame=PolarisationFrame('stokesI'))
self.image = create_test_image(
frequency=self.frequency,
phasecentre=self.phasecentre,
cellsize=0.001,
polarisation_frame=PolarisationFrame('stokesI'))
self.image.data[self.image.data < 0.0] = 0.0
self.image_graph = arlexecute.execute(create_test_image)(
frequency=self.frequency,
phasecentre=self.phasecentre,
cellsize=0.001,
polarisation_frame=PolarisationFrame('stokesI'))
def setUp(self):
from data_models.parameters import arl_path
self.dir = arl_path('test_results')
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='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'),
zerow=True)
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,
polarisation_frame=PolarisationFrame('stokesI'))
def test_predict_sky_components_coalesce(self):
sc = create_low_test_skycomponents_from_gleam(
flux_limit=10.0,
polarisation_frame=PolarisationFrame("stokesI"),
frequency=self.frequency,
kind='cubic',
phasecentre=SkyCoord("17h20m31s", "-00d58m45s"),
radius=0.1)
self.config = create_named_configuration('LOWBD2-CORE')
self.phasecentre = SkyCoord("17h20m31s", "-00d58m45s")
sampling_time = 3.76
self.times = numpy.arange(0.0, +300 * sampling_time, sampling_time)
self.vis = create_blockvisibility(
self.config,
self.times,
self.frequency,
phasecentre=self.phasecentre,
weight=1.0,
polarisation_frame=PolarisationFrame('stokesI'),
channel_bandwidth=self.channel_bandwidth)
self.vis = predict_skycomponent_visibility(self.vis, sc)
cvt = coalesce_visibility(self.vis, time_coal=1.0)
assert cvt.cindex is not None
def actualSetup(self, sky_pol_frame='stokesIQUV', data_pol_frame='linear'):
self.lowcore = create_named_configuration('LOWBD2', rmax=300.0)
self.times = (numpy.pi / 43200.0) * numpy.arange(0.0, 300.0, 30.0)
vnchan = 3
self.frequency = numpy.linspace(1.0e8, 1.1e8, vnchan)
self.channel_bandwidth = numpy.array(
vnchan * [self.frequency[1] - self.frequency[0]])
# Define the component and give it some spectral behaviour
f = numpy.array([100.0, 20.0, -10.0, 1.0])
self.flux = numpy.array([f, 0.8 * f, 0.6 * f])
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')
if sky_pol_frame == 'stokesI':
self.flux = self.flux[:, 0][:, numpy.newaxis]
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_visibility(self.vis, self.comp)
def setUp(self):
from data_models.parameters import arl_path
self.lowcore = create_named_configuration('LOWBD2-CORE')
self.dir = arl_path('test_results')
self.times = (numpy.pi / (12.0)) * numpy.linspace(-3.0, 3.0, 7)
self.nchan = 8
self.frequency = numpy.linspace(0.8e8, 1.2e8, self.nchan)
self.channel_bandwidth = numpy.array(
self.nchan * [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,
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_image_mm_model.fits' % (self.dir))
self.bigmodel = create_image_from_visibility(self.vis,
cellsize=0.0015,
npixel=512,
frequency=self.frequency)
def actualSetUp(self,
add_errors=False,
freqwin=5,
block=False,
dospectral=True,
dopol=False,
amp_errors=None,
phase_errors=None,
zerow=True):
if amp_errors is None:
amp_errors = {'T': 0.0, 'G': 0.01, 'B': 0.01}
if phase_errors is None:
phase_errors = {'T': 1.0, 'G': 0.1, 'B': 0.01}
self.npixel = 512
self.low = create_named_configuration('LOWBD2', rmax=750.0)
self.freqwin = freqwin
self.vis_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.vis_list = [
arlexecute.execute(ingest_unittest_visibility)(
self.low, [self.frequency[i]], [self.channelwidth[i]],
self.times,
self.vis_pol,
self.phasecentre,
block=block,
zerow=zerow) for i, _ in enumerate(self.frequency)
]
self.model_imagelist = [
arlexecute.execute(create_unittest_model,
nout=freqwin)(self.vis_list[0],
self.image_pol,
npixel=self.npixel)
for i, _ in enumerate(self.frequency)
]
self.components_list = [
arlexecute.execute(create_unittest_components)(
self.model_imagelist[i], flux[i, :][numpy.newaxis, :])
for i, _ in enumerate(self.frequency)
]
# Apply the LOW primary beam and insert into model
self.model_imagelist = [
arlexecute.execute(insert_skycomponent,
nout=1)(self.model_imagelist[freqwin],
self.components_list[freqwin])
for freqwin, _ in enumerate(self.frequency)
]
self.vis_list = [
arlexecute.execute(predict_skycomponent_visibility)(
self.vis_list[freqwin], self.components_list[freqwin])
for freqwin, _ in enumerate(self.frequency)
]
# Calculate the model convolved with a Gaussian.
self.model_imagelist = arlexecute.compute(self.model_imagelist,
sync=True)
model = self.model_imagelist[0]
self.cmodel = smooth_image(model)
export_image_to_fits(model,
'%s/test_imaging_delayed_model.fits' % self.dir)
export_image_to_fits(self.cmodel,
'%s/test_imaging_delayed_cmodel.fits' % self.dir)
if add_errors and block:
self.vis_list = [
arlexecute.execute(insert_unittest_errors)(
self.vis_list[i],
amp_errors=amp_errors,
phase_errors=phase_errors)
for i, _ in enumerate(self.frequency)
]
self.vis_list = arlexecute.compute(self.vis_list, sync=True)
self.vis_list = arlexecute.scatter(self.vis_list)
self.model_imagelist = arlexecute.scatter(self.model_imagelist)
log.addHandler(logging.StreamHandler(sys.stdout))
# We create a graph to make the visibility. The parameter rmax determines the distance of the furthest antenna/stations used. All over parameters are determined from this number.
nfreqwin = 5
ntimes = 11
rmax = 300.0
frequency = numpy.linspace(0.8e8, 1.2e8, nfreqwin)
channel_bandwidth = numpy.array(nfreqwin * [frequency[1] - frequency[0]])
times = numpy.linspace(-numpy.pi / 3.0, numpy.pi / 3.0, ntimes)
phasecentre = SkyCoord(ra=+30.0 * u.deg,
dec=-60.0 * u.deg,
frame='icrs',
equinox='J2000')
lowcore = create_named_configuration('LOWBD2-CORE', rmax=rmax)
block_vis = create_blockvisibility(
lowcore,
times,
frequency=frequency,
channel_bandwidth=channel_bandwidth,
weight=1.0,
phasecentre=phasecentre,
polarisation_frame=PolarisationFrame("stokesI"))
wprojection_planes = 1
advice = advise_wide_field(block_vis,
guard_band_image=4.0,
delA=0.02,
wprojection_planes=wprojection_planes)
def ingest_visibility(self,
freq=None,
chan_width=None,
times=None,
add_errors=False,
block=True,
bandpass=False):
if freq is None:
freq = [1e8]
if chan_width is None:
chan_width = [1e6]
if times is None:
times = (numpy.pi / 12.0) * numpy.linspace(-3.0, 3.0, 5)
lowcore = create_named_configuration('LOWBD2', rmax=750.0)
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=frequency,
phasecentre=phasecentre,
polarisation_frame=PolarisationFrame("stokesI"))
nchan = len(self.frequency)
flux = numpy.array(nchan * [[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(
direction=sc,
flux=flux,
frequency=frequency,
polarisation_frame=PolarisationFrame("stokesI"))
comps.append(comp)
if block:
predict_skycomponent_visibility(vt, comps)
else:
predict_skycomponent_visibility(vt, comps)
insert_skycomponent(model, comps)
self.comps = comps
self.model = copy_image(model)
self.empty_model = create_empty_image_like(model)
export_image_to_fits(
model, '%s/test_pipeline_functions_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)
if bandpass:
bgt = create_gaintable_from_blockvisibility(vt, timeslice=1e5)
bgt = simulate_gaintable(bgt,
phase_error=0.01,
amplitude_error=0.01,
smooth_channels=4)
vt = apply_gaintable(vt, bgt)
return vt
def actualSetUp(self,
add_errors=False,
freqwin=1,
block=False,
dospectral=True,
dopol=False,
zerow=False):
arlexecute.set_client(use_dask=True)
self.npixel = 256
self.low = create_named_configuration('LOWBD2', rmax=750.0)
self.freqwin = freqwin
self.vis_list = list()
self.ntimes = 5
self.times = numpy.linspace(-3.0, +3.0, self.ntimes) * numpy.pi / 12.0
if freqwin > 1:
self.frequency = numpy.linspace(0.8e8, 1.2e8, self.freqwin)
self.channelwidth = numpy.array(
freqwin * [self.frequency[1] - self.frequency[0]])
else:
self.frequency = numpy.array([0.8e8])
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.vis_list = [
arlexecute.execute(ingest_unittest_visibility)(
self.low, [self.frequency[freqwin]],
[self.channelwidth[freqwin]],
self.times,
self.vis_pol,
self.phasecentre,
block=block,
zerow=zerow) for freqwin, _ in enumerate(self.frequency)
]
self.model_graph = [
arlexecute.execute(create_unittest_model,
nout=freqwin)(self.vis_list[freqwin],
self.image_pol,
npixel=self.npixel)
for freqwin, _ in enumerate(self.frequency)
]
self.components_graph = [
arlexecute.execute(create_unittest_components)(
self.model_graph[freqwin], flux[freqwin, :][numpy.newaxis, :])
for freqwin, _ in enumerate(self.frequency)
]
self.model_graph = [
arlexecute.execute(insert_skycomponent,
nout=1)(self.model_graph[freqwin],
self.components_graph[freqwin])
for freqwin, _ in enumerate(self.frequency)
]
self.vis_list = [
arlexecute.execute(predict_skycomponent_visibility)(
self.vis_list[freqwin], self.components_graph[freqwin])
for freqwin, _ in enumerate(self.frequency)
]
# Calculate the model convolved with a Gaussian.
self.model = arlexecute.compute(self.model_graph[0], sync=True)
self.cmodel = smooth_image(self.model)
export_image_to_fits(self.model,
'%s/test_imaging_model.fits' % self.dir)
export_image_to_fits(self.cmodel,
'%s/test_imaging_cmodel.fits' % self.dir)
if add_errors and block:
self.vis_list = [
arlexecute.execute(insert_unittest_errors)(self.vis_list[i])
for i, _ in enumerate(self.frequency)
]
self.vis = arlexecute.compute(self.vis_list[0], sync=True)
self.components = arlexecute.compute(self.components_graph[0],
sync=True)
def test_clip_configuration(self):
for rmax in [
100.0, 3000.0, 1000.0, 3000.0, 10000.0, 30000.0, 100000.0
]:
self.config = create_named_configuration('LOWBD2', rmax=rmax)
assert self.config.size() > 0.0
def actualSetup(self,
vnchan=1,
doiso=True,
ntimes=5,
flux_limit=2.0,
zerow=True,
fixed=False):
nfreqwin = vnchan
rmax = 300.0
npixel = 512
cellsize = 0.001
frequency = numpy.linspace(0.8e8, 1.2e8, nfreqwin)
if nfreqwin > 1:
channel_bandwidth = numpy.array(nfreqwin *
[frequency[1] - frequency[0]])
else:
channel_bandwidth = [0.4e8]
times = numpy.linspace(-numpy.pi / 3.0, numpy.pi / 3.0, ntimes)
phasecentre = SkyCoord(ra=-60.0 * u.deg,
dec=-60.0 * u.deg,
frame='icrs',
equinox='J2000')
lowcore = create_named_configuration('LOWBD2', rmax=rmax)
block_vis = create_blockvisibility(
lowcore,
times,
frequency=frequency,
channel_bandwidth=channel_bandwidth,
weight=1.0,
phasecentre=phasecentre,
polarisation_frame=PolarisationFrame("stokesI"),
zerow=zerow)
block_vis.data['uvw'][..., 2] = 0.0
self.beam = create_image_from_visibility(
block_vis,
npixel=npixel,
frequency=[numpy.average(frequency)],
nchan=nfreqwin,
channel_bandwidth=[numpy.sum(channel_bandwidth)],
cellsize=cellsize,
phasecentre=phasecentre)
self.components = create_low_test_skycomponents_from_gleam(
flux_limit=flux_limit,
phasecentre=phasecentre,
frequency=frequency,
polarisation_frame=PolarisationFrame('stokesI'),
radius=npixel * cellsize)
self.beam = create_low_test_beam(self.beam)
self.components = apply_beam_to_skycomponent(self.components,
self.beam,
flux_limit=flux_limit)
self.vis = copy_visibility(block_vis, zero=True)
gt = create_gaintable_from_blockvisibility(block_vis, timeslice='auto')
for i, sc in enumerate(self.components):
if sc.flux[0, 0] > 10:
sc.flux[...] /= 10.0
component_vis = copy_visibility(block_vis, zero=True)
gt = simulate_gaintable(gt,
amplitude_error=0.0,
phase_error=0.1,
seed=None)
component_vis = predict_skycomponent_visibility(component_vis, sc)
component_vis = apply_gaintable(component_vis, gt)
self.vis.data['vis'][...] += component_vis.data['vis'][...]
# Do an isoplanatic selfcal
self.model_vis = copy_visibility(self.vis, zero=True)
self.model_vis = predict_skycomponent_visibility(
self.model_vis, self.components)
if doiso:
gt = solve_gaintable(self.vis,
self.model_vis,
phase_only=True,
timeslice='auto')
self.vis = apply_gaintable(self.vis, gt, inverse=True)
self.model_vis = convert_blockvisibility_to_visibility(self.model_vis)
self.model_vis, _, _ = weight_visibility(self.model_vis, self.beam)
self.dirty_model, sumwt = invert_function(self.model_vis,
self.beam,
context='2d')
export_image_to_fits(self.dirty_model,
"%s/test_skymodel-model_dirty.fits" % self.dir)
lvis = convert_blockvisibility_to_visibility(self.vis)
lvis, _, _ = weight_visibility(lvis, self.beam)
dirty, sumwt = invert_function(lvis, self.beam, context='2d')
if doiso:
export_image_to_fits(
dirty, "%s/test_skymodel-initial-iso-residual.fits" % self.dir)
else:
export_image_to_fits(
dirty,
"%s/test_skymodel-initial-noiso-residual.fits" % self.dir)
self.skymodels = [
SkyModel(components=[cm], fixed=fixed) for cm in self.components
]
def test_unknown_configuration(self):
with self.assertRaises(ValueError):
self.config = create_named_configuration("SKA1-OWL")
