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=None,
vnchan=3):
if f is None:
f = [100.0, 50.0, -10.0, 40.0]
self.actualSetup(spf, dpf, f=f, vnchan=vnchan)
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))
assert numpy.max(numpy.abs(gtsol.gain - 1.0)) > 0.1
def test_create_gaintable_from_other(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)))
new_gt = GainTable(data=gt.data)
assert new_gt.data.shape == gt.data.shape
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)
original = copy_visibility(self.vis)
vis = apply_gaintable(self.vis, gt)
error = numpy.max(numpy.abs(vis.vis - original.vis))
assert error > 10.0, "Error = %f" % (error)
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 test_solve_gaintable_scalar_timeslice(self):
self.actualSetup('stokesI', 'stokesI', f=[100.0], ntimes=10)
gt = create_gaintable_from_blockvisibility(self.vis, timeslice=120.0)
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)
self.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)
assert numpy.max(numpy.abs(gtsol.gain - 1.0)) > 0.1
def test_solve_gaintable_scalar_normalise(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=0.0, amplitude_error=0.1)
gt.data['gain'] *= 2.0
original = copy_visibility(self.vis)
self.vis = apply_gaintable(self.vis, gt)
gtsol = solve_gaintable(self.vis, original, phase_only=False, niter=200, normalise_gains=True)
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 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)
original = copy_visibility(self.vis)
vis = apply_gaintable(self.vis, gt)
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_plot_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=0.1, amplitude_error=0.1)
plt.clf()
fig, ax = plt.subplots(1, 1)
gaintable_plot(gt, ax, value='amp')
plt.show(block=False)
fig, ax = plt.subplots(1, 1)
gaintable_plot(gt, ax, value='phase')
plt.show(block=False)
fig, ax = plt.subplots(1, 1)
gaintable_plot(gt, ax, value='residual')
plt.show(block=False)
def test_calibrate_T_function(self):
self.actualSetup('stokesI', 'stokesI', f=[100.0])
# Prepare the corrupted visibility data_models
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)
self.vis = apply_gaintable(self.vis, gt, vis_slices=None)
# Now get the control dictionary and calibrate
controls = create_calibration_controls()
controls['T']['first_selfcal'] = 0
calibrated_vis, gaintables = calibrate_function(
self.vis, original, calibration_context='T', controls=controls)
residual = numpy.max(gaintables['T'].residual)
assert residual < 1e-8, "Max T residual = %s" % (residual)
