def test_calibrate_function(self):
self.actualSetup('stokesI', 'stokesI', f=[100.0])
# Prepare the corrupted visibility data
gt = create_gaintable_from_blockvisibility(self.vis)
log.info("Created gain table: %s" % (gaintable_summary(gt)))
gt = simulate_gaintable(gt,
phase_error=10.0,
amplitude_error=0.1,
timeslice='auto')
bgt = simulate_gaintable(gt,
phase_error=0.1,
amplitude_error=0.01,
timeslice=1e5)
original = copy_visibility(self.vis)
self.vis = apply_gaintable(self.vis, bgt, timeslice=1e5)
self.vis = apply_gaintable(self.vis, gt, timeslice='auto')
# Now get the control dictionary and calibrate
controls = create_calibration_controls()
controls['T']['first_selfcal'] = 0
controls['B']['first_selfcal'] = 0
calibrated_vis, gaintables = calibrate_function(self.vis,
original,
context='TB',
controls=controls)
residual = numpy.max(gaintables['T'].residual)
assert residual < 3e-2, "Max T residual = %s" % (residual)
residual = numpy.max(gaintables['B'].residual)
assert residual < 6e-5, "Max B residual = %s" % (residual)
def core_solve(self,
spf,
dpf,
phase_error=0.1,
amplitude_error=0.0,
leakage=0.0,
phase_only=True,
niter=200,
crosspol=False,
residual_tol=1e-6,
f=[100.0, 50.0, -10.0, 40.0]):
self.actualSetup(spf, dpf, f=f)
gt = create_gaintable_from_blockvisibility(self.vis)
log.info("Created gain table: %s" % (gaintable_summary(gt)))
gt = simulate_gaintable(gt,
phase_error=phase_error,
amplitude_error=amplitude_error,
leakage=leakage)
original = copy_visibility(self.vis)
vis = apply_gaintable(self.vis, gt)
gtsol = solve_gaintable(self.vis,
original,
phase_only=phase_only,
niter=niter,
crosspol=crosspol,
tol=1e-6)
vis = apply_gaintable(vis, gtsol, inverse=True)
residual = numpy.max(gtsol.residual)
assert residual < residual_tol, "%s %s Max residual = %s" % (spf, dpf,
residual)
log.debug(qa_gaintable(gt))
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 test_create_gaintable_from_visibility(self):
for spf, dpf in [('stokesIQUV', 'linear'), ('stokesIQUV', 'circular')]:
self.actualSetup(spf, dpf)
gt = create_gaintable_from_blockvisibility(self.vis)
log.info("Created gain table: %s" % (gaintable_summary(gt)))
gt = simulate_gaintable(gt, phase_error=0.1)
original = copy_visibility(self.vis)
vis = apply_gaintable(self.vis, gt)
assert numpy.max(numpy.abs(vis.vis - original.vis)) > 0.0
def test_solve_gaintable_scalar(self):
self.actualSetup('stokesI', 'stokesI', f=[100.0])
gt = create_gaintable_from_blockvisibility(self.vis)
log.info("Created gain table: %s" % (gaintable_summary(gt)))
gt = simulate_gaintable(gt, phase_error=10.0, amplitude_error=0.0)
original = copy_visibility(self.vis)
vis = apply_gaintable(self.vis, gt)
gtsol = solve_gaintable(self.vis, original, phase_only=True, niter=200)
residual = numpy.max(gtsol.residual)
assert residual < 3e-8, "Max residual = %s" % (residual)
def corrupt_kernel(vis, gt, **kwargs):
if gt is None:
gt = create_gaintable_from_blockvisibility(vis, **kwargs)
gt = simulate_gaintable(gt, **kwargs)
result = apply_gaintable(vis, gt)
label = "corrupt Kernel"
print(label + str(result))
return result
def test_apply_gaintable_only(self):
for spf, dpf in[('stokesI', 'stokesI'), ('stokesIQUV', 'linear'), ('stokesIQUV', 'circular')]:
self.actualSetup(spf, dpf)
gt = create_gaintable_from_blockvisibility(self.vis, timeslice='auto')
log.info("Created gain table: %s" % (gaintable_summary(gt)))
gt = simulate_gaintable(gt, phase_error=0.1, amplitude_error=0.01, timeslice='auto')
original = copy_visibility(self.vis)
vis = apply_gaintable(self.vis, gt, timeslice='auto')
error = numpy.max(numpy.abs(vis.vis - original.vis))
assert error > 10.0, "Error = %f" % (error)
def test_apply_gaintable_and_inverse_both(self):
for spf, dpf in [('stokesIQUV', 'linear'), ('stokesIQUV', 'circular')]:
self.actualSetup(spf, dpf)
gt = create_gaintable_from_blockvisibility(self.vis)
log.info("Created gain table: %s" % (gaintable_summary(gt)))
gt = simulate_gaintable(gt, phase_error=0.1, amplitude_error=0.1)
original = copy_visibility(self.vis)
vis = apply_gaintable(self.vis, gt)
vis = apply_gaintable(self.vis, gt, inverse=True)
error = numpy.max(numpy.abs(vis.vis - original.vis))
assert error < 1e-12, "Error = %s" % (error)
def test_create_gaintable_from_visibility_interval(self):
for timeslice in [10.0, 'auto', 1e5]:
for spf, dpf in[('stokesIQUV', 'linear')]:
self.actualSetup(spf, dpf)
gt = create_gaintable_from_blockvisibility(self.vis, timeslice=timeslice)
log.info("Created gain table: %s" % (gaintable_summary(gt)))
gt = simulate_gaintable(gt, phase_error=1.0, timeslice=timeslice)
original = copy_visibility(self.vis)
vis = apply_gaintable(self.vis, gt, timeslice=timeslice)
assert numpy.max(numpy.abs(original.vis)) > 0.0
assert numpy.max(numpy.abs(vis.vis)) > 0.0
assert numpy.max(numpy.abs(vis.vis - original.vis)) > 0.0
def test_solve_gaintable_scalar_bandpass(self):
self.actualSetup('stokesI', 'stokesI', f=[100.0], vnchan=128)
gt = create_gaintable_from_blockvisibility(self.vis)
log.info("Created gain table: %s" % (gaintable_summary(gt)))
gt = simulate_gaintable(gt,
phase_error=10.0,
amplitude_error=0.01,
smooth_channels=8)
original = copy_visibility(self.vis)
self.vis = apply_gaintable(self.vis, gt)
gtsol = solve_gaintable(self.vis,
original,
phase_only=False,
niter=200)
residual = numpy.max(gtsol.residual)
assert residual < 3e-8, "Max residual = %s" % (residual)
assert numpy.max(numpy.abs(gtsol.gain - 1.0)) > 0.1
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 corrupt_vis(vis, gt, **kwargs):
if gt is None:
gt = create_gaintable_from_blockvisibility(vis, **kwargs)
gt = simulate_gaintable(gt, **kwargs)
return apply_gaintable(vis, gt)
def test_peel_skycomponent_blockvisibility(self):
df = 1e6
frequency = numpy.array([1e8 - df, 1e8, 1e8 + df])
channel_bandwidth = numpy.array([df, df, df])
# Define the component and give it some spectral behaviour
f = numpy.array([100.0, 20.0, -10.0, 1.0])
flux = numpy.array([f, 0.8 * f, 0.6 * f])
phasecentre = SkyCoord(0 * u.deg, -60.0 * u.deg)
config = create_named_configuration('LOWBD2-CORE')
peeldirection = SkyCoord(+15 * u.deg, -60.0 * u.deg)
times = numpy.linspace(-3.0, 3.0, 7) * numpy.pi / 12.0
# Make the visibility
vis = create_blockvisibility(
config,
times,
frequency,
phasecentre=phasecentre,
weight=1.0,
polarisation_frame=PolarisationFrame('linear'),
channel_bandwidth=channel_bandwidth)
vis.data['vis'][...] = 0.0
# First add in the source to be peeled.
peel = Skycomponent(direction=peeldirection,
frequency=frequency,
flux=flux,
polarisation_frame=PolarisationFrame("stokesIQUV"))
vis = predict_skycomponent_visibility(vis, peel)
# Make a gaintable and apply it to the visibility of the peeling source
gt = create_gaintable_from_blockvisibility(vis, timeslice='auto')
gt = simulate_gaintable(gt,
phase_error=0.01,
amplitude_error=0.01,
timeslice='auto')
gt.data['gain'] *= 0.3
vis = apply_gaintable(vis, gt, timeslice='auto')
# Now create a plausible field using the GLEAM sources
model = create_image_from_visibility(
vis,
cellsize=0.001,
frequency=frequency,
polarisation_frame=PolarisationFrame('stokesIQUV'))
bm = create_low_test_beam(model=model)
sc = create_low_test_skycomponents_from_gleam(
flux_limit=1.0,
polarisation_frame=PolarisationFrame("stokesIQUV"),
frequency=frequency,
kind='cubic',
phasecentre=phasecentre,
radius=0.1)
sc = apply_beam_to_skycomponent(sc, bm)
# Add in the visibility due to these sources
vis = predict_skycomponent_visibility(vis, sc)
assert numpy.max(numpy.abs(vis.vis)) > 0.0
# Now we can peel
vis, peel_gts = peel_skycomponent_blockvisibility(vis, peel)
assert len(peel_gts) == 1
residual = numpy.max(peel_gts[0].residual)
assert residual < 0.7, "Peak residual %.6f too large" % (residual)
im, sumwt = invert_timeslice(vis, model, timeslice='auto')
qa = qa_image(im)
assert numpy.abs(qa.data['max'] - 14.2) < 1.0, str(qa)
predicted_vis = predict_function(block_vis, gleam_model, vis_slices=51, context='wstack')
#print("np.sum(predicted_vis.data): ", numpy.sum(predicted_vis.data['vis']))
block_vis=convert_visibility_to_blockvisibility(predicted_vis)
#print("np.sum(block_vis.data): ", numpy.sum(block_vis.data['vis']))
#print("nchan npol nants ", block_vis.nchan, block_vis.npol, block_vis.nants)
#print("uvw", block_vis.uvw, numpy.sum(block_vis.uvw))
#print("vis", block_vis.vis, numpy.sum(block_vis.vis))
#print("weight", block_vis.weight, numpy.sum(block_vis.weight))
#print("time", block_vis.time, numpy.sum(block_vis.time))
#print("integration_time", block_vis.integration_time, numpy.sum(block_vis.integration_time))
#print("nvis, size", block_vis.nvis, block_vis.size())
gt = create_gaintable_from_blockvisibility(block_vis)
#print("np.sum(gt.data): ", numpy.sum(gt.data['gain']))
gt = simulate_gaintable(gt, phase_error=1.0)
#print("np.sum(gt.data): ", numpy.sum(gt.data['gain']))
blockvis = apply_gaintable(block_vis, gt)
#print("np.sum(blockvis.data): ", numpy.sum(blockvis.data['vis']))
model = create_image_from_visibility(block_vis, npixel=npixel, frequency=[numpy.average(frequency)], nchan=1,
channel_bandwidth=[numpy.sum(channel_bandwidth)], cellsize=cellsize, phasecentre=phasecentre)
#print("model sum, min, max, shape: ", numpy.sum(model.data), numpy.amin(model.data), numpy.amax(model.data), model.shape)
print(qa_image(model, context='Blockvis model image'))
export_image_to_fits(model, '%s/imaging-blockvis_model.fits'
% (results_dir))
dirty, sumwt = invert_function(predicted_vis, model, vis_slices=vis_slices, dopsf=False, context='wstack')
def actualSetup(self, sky_pol_frame='stokesI', data_pol_frame='stokesI', f=None, vnchan=1, doiso=True,
ntimes=1, flux_limit=18.0):
nfreqwin = vnchan
ntimes = ntimes
rmax = 300.0
npixel = 1024
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=+0.0 * u.deg, dec=-45.0 * 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"))
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 / 100.0)
print("Number of components %d" % len(self.components))
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
print('Component %d, flux = %s' % (i, str(sc.flux[0, 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_sagecal-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')
print(qa_image(dirty))
export_image_to_fits(dirty, "%s/test_sagecal-initial_dirty.fits" % self.dir)