def test_calculate_image_frequency_moments_1(self):
frequency = numpy.linspace(0.9e8, 1.1e8, 9)
cube = create_low_test_image_from_gleam(npixel=512,
cellsize=0.0001,
frequency=frequency,
flux_limit=1.0)
log.debug(
export_image_to_fits(cube,
fitsfile='%s/test_moments_1_cube.fits' %
(self.dir)))
original_cube = copy_image(cube)
moment_cube = calculate_image_frequency_moments(cube, nmoment=1)
log.debug(
export_image_to_fits(
moment_cube,
fitsfile='%s/test_moments_1_moment_cube.fits' % (self.dir)))
reconstructed_cube = calculate_image_from_frequency_moments(
cube, moment_cube)
log.debug(
export_image_to_fits(
reconstructed_cube,
fitsfile='%s/test_moments_1_reconstructed_cube.fits' %
(self.dir)))
error = numpy.std(reconstructed_cube.data - original_cube.data)
assert error < 0.2
def test_create_low_test_image_from_gleam(self):
im = create_low_test_image_from_gleam(
npixel=256,
cellsize=0.001,
channel_bandwidth=self.channel_bandwidth,
frequency=self.frequency,
phasecentre=self.phasecentre,
kind='cubic',
flux_limit=0.3)
assert im.data.shape[0] == 5
assert im.data.shape[1] == 1
assert im.data.shape[2] == 256
assert im.data.shape[3] == 256
if self.persist:
export_image_to_fits(
im, '%s/test_test_support_low_gleam.fits' % (self.dir))
def setUp(self):
from rascil.data_models.parameters import rascil_path
self.dir = rascil_path('test_results')
self.persist = os.getenv("RASCIL_PERSIST", False)
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)
if self.persist: export_image_to_fits(beam, "%s/test_deconvolve_mmclean_beam.fits" % self.dir)
self.test_model.data *= beam.data
if self.persist: 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)
if self.persist: export_image_to_fits(self.dirty, "%s/test_deconvolve_mmclean-dirty.fits" % self.dir)
if self.persist: 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 test_get_frequency_map_gleam(self):
self.model = create_low_test_image_from_gleam(npixel=128, cellsize=0.001, frequency=self.frequency,
channel_bandwidth=self.channel_bandwidth, flux_limit=10.0)
spectral_mode, vfrequency_map = get_frequency_map(self.vis, self.model)
assert numpy.max(vfrequency_map) == self.model.nchan - 1
assert spectral_mode == 'channel'
