def test_imager_global_fit_valid(self):
'''Test image production.'''
# Get information on images
scanset = ScanSet('test.hdf5')
scanset.fit_full_images(no_offsets=True)
# It works after calculating images
images = scanset.calculate_images()
nx, ny = images['Feed0_RCP'].shape
excluded = [[nx // 2, ny // 2, nx // 4]]
main_imager('test.hdf5 -g '
'-e {} {} {}'.format(*(excluded[0])).split(' '))
def test_global_fit_image_fails_mixup_channels(self):
'''Test image production.'''
scanset = ScanSet('test.hdf5')
images = scanset.calculate_images()
scanset['Ch0_feed'] = np.random.randint(0, 3, len(scanset['Ch0_feed']))
with pytest.raises(ValueError) as excinfo:
images = scanset.fit_full_images()
assert "Feeds are mixed up" in str(excinfo)
def test_global_fit_image(self):
'''Test image production.'''
scanset = ScanSet('test.hdf5')
# It works with no parameters, before calculating images,
# with no_offsets
scanset.fit_full_images(no_offsets=True)
# It works after calculating images
images = scanset.calculate_images()
nx, ny = images['Feed0_RCP'].shape
excluded = [[nx // 2, ny // 2, nx // 4]]
scanset.fit_full_images(excluded=excluded, chans='Feed0_RCP')
os.path.exists("out_iter_Feed0_RCP_002.txt")
scanset.fit_full_images(excluded=excluded, chans='Feed0_LCP')
os.path.exists("out_iter_Feed0_LCP_000.txt")
if not HAS_MPL:
with pytest.raises(ImportError) as excinfo:
display_intermediate(scanset,
chan="Feed0_RCP",
excluded=excluded,
parfile="out_iter_Feed0_RCP_002.txt")
assert "display_intermediate: matplotlib" in str(excinfo)
else:
display_intermediate(scanset,
chan="Feed0_RCP",
excluded=excluded,
parfile="out_iter_Feed0_RCP_002.txt")
os.path.exists("out_iter_Feed0_LCP_002.png")