pylab.rcParams['figure.figsize'] = (12.0, 12.0)
pylab.rcParams['image.cmap'] = 'rainbow'
lowcore = create_configuration('MUSER')
# lowcore = create_named_configuration('MUSER')
# arlexecute.set_client(use_dask=True)
arlexecute.set_client(use_dask=True, threads_per_worker=1, memory_limit=32 * 1024 * 1024 * 1024, n_workers=8,
local_dir=dask_dir)
times = numpy.array([-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0]) * (numpy.pi / 12.0)
frequency = numpy.array([4e8])
channel_bandwidth = numpy.array([25e6])
reffrequency = numpy.max(frequency)
phasecentre = SkyCoord(ra=+5 * u.deg, dec=20 * 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'))
advice = advise_wide_field(vt, wprojection_planes=1)
vt.data['vis'] *= 0.0
npixel=256
model = create_image_from_visibility(vt, npixel=npixel, cellsize=6.8e-5, nchan=1,
polarisation_frame=PolarisationFrame('stokesI'))
centre = model.wcs.wcs.crpix-1
spacing_pixels = npixel // 8
log.info('Spacing in pixels = %s' % spacing_pixels)
spacing = model.wcs.wcs.cdelt * spacing_pixels
locations = [-3.5, -2.5, -1.5, -0.5, 0.5, 1.5, 2.5, 3.5]
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