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""" Unit tests for calibration solution
"""
import logging
import unittest
import astropy.units as u
import numpy
from astropy.coordinates import SkyCoord
from data_models.memory_data_models import SkyModel
from data_models.polarisation import PolarisationFrame
from processing_components.calibration.operations import apply_gaintable, create_gaintable_from_blockvisibility
from processing_components.calibration.calibration import solve_gaintable
from processing_components.image.operations import export_image_to_fits, qa_image
from processing_components.imaging.base import predict_skycomponent_visibility, create_image_from_visibility
from processing_components.imaging.weighting import weight_visibility
from processing_components.skycomponent.operations import apply_beam_to_skycomponent
from processing_components.simulation.testing_support import create_named_configuration, simulate_gaintable, \
create_low_test_skycomponents_from_gleam, create_low_test_beam
from processing_components.visibility.base import copy_visibility, create_blockvisibility
from processing_components.visibility.coalesce import convert_blockvisibility_to_visibility
from workflows.arlexecute.execution_support.arlexecute import arlexecute
from workflows.arlexecute.calibration.modelpartition_arlexecute import solve_modelpartition_arlexecute
from workflows.arlexecute.imaging.imaging_arlexecute import predict_arlexecute, invert_arlexecute
log = logging.getLogger(__name__)
class TestCalibrationSkyModelcal(unittest.TestCase):
def setUp(self):
from data_models.parameters import arl_path
self.dir = arl_path('test_results')
arlexecute.set_client(use_dask=False)
numpy.random.seed(180555)
def tearDown(self):
arlexecute.close()
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_arlexecute(self.model_vis, self.beam, context='2d')
export_image_to_fits(self.dirty_model, "%s/test_modelpartition-model_dirty.fits" % self.dir)
lvis = convert_blockvisibility_to_visibility(self.vis)
lvis, _, _ = weight_visibility(lvis, self.beam)
dirty, sumwt = invert_arlexecute(lvis, self.beam, context='2d')
if doiso:
export_image_to_fits(dirty, "%s/test_modelpartition-initial-iso-residual.fits" % self.dir)
else:
export_image_to_fits(dirty, "%s/test_modelpartition-initial-noiso-residual.fits" % self.dir)
self.skymodels = [SkyModel(components=[cm], fixed=fixed) for cm in self.components]
@unittest.skip("Not converted to arlexecute")
def test_modelpartition_solve_arlexecute(self):
self.actualSetup(doiso=True)
self.skymodel_list = [arlexecute.execute(SkyModel, nout=1)(components=[cm])
for cm in self.components]
modelpartition_list = solve_modelpartition_arlexecute(self.vis, skymodel_list=self.skymodel_list, niter=30,
gain=0.25)
skymodel, residual_vis = arlexecute.compute(modelpartition_list, sync=True)
residual_vis = convert_blockvisibility_to_visibility(residual_vis)
residual_vis, _, _ = weight_visibility(residual_vis, self.beam)
dirty, sumwt = invert_arlexecute(residual_vis, self.beam, context='2d')
export_image_to_fits(dirty, "%s/test_modelpartition-%s-final-iso-residual.fits" % (self.dir, arlexecute.type()))
qa = qa_image(dirty)
assert qa.data['rms'] < 3.2e-3, qa
if __name__ == '__main__':
unittest.main()