def setUp(self):
uncorr_map = accessors.open(uncorr_path)
corr_map = accessors.open(corr_path)
map_with_sources = accessors.open(deconv_path)
self.uncorr_image = image.ImageData(uncorr_map.data, uncorr_map.beam, uncorr_map.wcs)
self.corr_image = image.ImageData(corr_map.data, uncorr_map.beam, uncorr_map.wcs)
self.image_with_sources = image.ImageData(map_with_sources.data, map_with_sources.beam, map_with_sources.wcs)
def setUp(self):
uncorr_map = accessors.open(uncorr_path)
corr_map = accessors.open(corr_path)
map_with_sources = accessors.open(deconv_path)
self.uncorr_image = image.ImageData(uncorr_map.data, uncorr_map.beam,
uncorr_map.wcs)
self.corr_image = image.ImageData(corr_map.data, uncorr_map.beam,
uncorr_map.wcs)
self.image_with_sources = image.ImageData(map_with_sources.data,
map_with_sources.beam,
map_with_sources.wcs)
def setUp(self):
uncorr_map = accessors.open(os.path.join(DATAPATH,
'UNCORRELATED_NOISE.FITS'))
corr_map = accessors.open(os.path.join(DATAPATH,
'CORRELATED_NOISE.FITS'))
map_with_sources = accessors.open(os.path.join(DATAPATH,
'TEST_DECONV.FITS'))
self.uncorr_image = image.ImageData(uncorr_map.data, uncorr_map.beam,
uncorr_map.wcs)
self.corr_image = image.ImageData(corr_map.data, uncorr_map.beam,
uncorr_map.wcs)
self.image_with_sources = image.ImageData(map_with_sources.data,
map_with_sources.beam,
map_with_sources.wcs)
def testMaskedBackgroundBlind(self):
self.image = accessors.sourcefinder_image_from_accessor(
accessors.open(os.path.join(DATAPATH, "L41391_0.img.restored.corr.fits")),
radius=1.0,
)
result = self.image.extract()
self.assertFalse(result)
def testMaskedBackgroundForcedFit(self):
"""
Background at forced fit is masked
"""
self.image = accessors.sourcefinder_image_from_accessor(
accessors.open(fits_file), radius=1.0)
result = self.image.fit_to_point(256, 256, 10, 0, None)
self.assertFalse(result)
def testMaskedBackgroundForcedFit(self):
"""
Background at forced fit is masked
"""
self.image = accessors.sourcefinder_image_from_accessor(
accessors.open(fits_file), radius=1.0)
result = self.image.fit_to_point(256, 256, 10, 0, None)
self.assertFalse(result)
def testMaskedBackgroundForcedFit(self):
"""
Background at forced fit is masked
"""
self.image = accessors.sourcefinder_image_from_accessor(
accessors.open(os.path.join(DATAPATH, "L41391_0.img.restored.corr.fits")),
radius=1.0,
)
result = self.image.fit_to_point(256, 256, 10, 0, None)
self.assertFalse(result)
def test_theoreticalnoise(self):
good_image = accessors.open(good_file)
bad_image = accessors.open(bad_file)
frequency = good_image.freq_eff
# this stuff should be in the header of a LOFAR image some day
integration_time = 18654.3 # s, should be self.good_image.tau_time some day
bandwidth = 200 * 10**3 # Hz, shoud probably be self.good_image.freq_bw some day
ncore = 23 # ~
nremote = 8 # ~
nintl = 0
configuration = "LBA_INNER"
noise = tkp.lofar.noise.noise_level(frequency, bandwidth, integration_time, configuration, ncore, nremote, nintl)
rms_good = statistics.rms_with_clipped_subregion(good_image.data)
rms_bad = statistics.rms_with_clipped_subregion(bad_image.data)
self.assertFalse(rms_invalid(rms_good, noise))
self.assertTrue(rms_invalid(rms_bad, noise))
def setUp(self):
"""
NB the required image has been committed to the tkp/data subversion repository.
(See tkp/data/unittests/tkp_lib for a full copy of all the unittest data).
Source positions / background positions were simply picked out by eye in DS9
"""
self.image = accessors.sourcefinder_image_from_accessor(
accessors.open(os.path.join(DATAPATH, 'NCP_sample_image_1.fits'))
)
self.assertListEqual(list(self.image.data.shape),[1024,1024])
self.boxsize = BOX_IN_BEAMPIX*max(self.image.beam[0], self.image.beam[1])
self.bright_src_posn = (215.83993,86.307504) #RA, DEC
self.background_posn = (186.33731,82.70002) #RA, DEC
##NB These are simply plucked from a previous run,
# so they merely ensure *consistent*, rather than *correct*, results.
self.known_fit_results = [215.84 , 86.31 , 9.88] #RA, DEC, PEAK
def setUp(self):
"""
NB the required image has been committed to the tkp/data subversion repository.
(See tkp/data/unittests/tkp_lib for a full copy of all the unittest data).
Source positions / background positions were simply picked out by eye in DS9
"""
self.image = accessors.sourcefinder_image_from_accessor(
accessors.open(os.path.join(DATAPATH, 'sourcefinder/NCP_sample_image_1.fits'))
)
self.assertListEqual(list(self.image.data.shape),[1024,1024])
self.boxsize = BOX_IN_BEAMPIX*max(self.image.beam[0], self.image.beam[1])
self.bright_src_posn = (35.76726,86.305771) #RA, DEC
self.background_posn = (6.33731,82.70002) #RA, DEC
# #NB Peak of forced gaussian fit is simply plucked from a previous run;
# so merely ensures *consistent*, rather than *correct*, results.
self.known_fit_results = (self.bright_src_posn[0], # RA,
self.bright_src_posn[1], # Dec
13.457697411730384) # Peak
def setUp(self):
"""
NB the required image has been committed to the tkp/data subversion repository.
(See tkp/data/unittests/tkp_lib for a full copy of all the unittest data).
Source positions / background positions were simply picked out by eye in DS9
"""
self.image = accessors.sourcefinder_image_from_accessor(
accessors.open(
os.path.join(DATAPATH,
'sourcefinder/NCP_sample_image_1.fits')))
self.assertListEqual(list(self.image.data.shape), [1024, 1024])
self.boxsize = BOX_IN_BEAMPIX * max(self.image.beam[0],
self.image.beam[1])
self.bright_src_posn = (35.76726, 86.305771) #RA, DEC
self.background_posn = (6.33731, 82.70002) #RA, DEC
# #NB Peak of forced gaussian fit is simply plucked from a previous run;
# so merely ensures *consistent*, rather than *correct*, results.
self.known_fit_results = (
self.bright_src_posn[0], # RA,
self.bright_src_posn[1], # Dec
13.457697411730384) # Peak
def test_casaimage(self):
image = accessors.open(casatable)
self.assertEqual(type(image), accessors.CasaImage)
def test_rms_fits(self):
accessors.open(good_file)
def testMaskedBackgroundBlind(self):
self.image = accessors.sourcefinder_image_from_accessor(
accessors.open(fits_file), radius=1.0)
result = self.image.extract(det=10.0, anl=3.0)
self.assertFalse(result)
def testMaskedBackgroundBlind(self):
self.image = accessors.sourcefinder_image_from_accessor(
accessors.open(fits_file), radius=1.0)
result = self.image.extract(det=10.0, anl=3.0)
self.assertFalse(result)
def test_header(self):
image = accessors.open(fits_file)
(semimaj, semimin, theta) = image.beam
self.assertFalse(beam_invalid(semimaj, semimin))
