def test_slices():
assert slices_config('[0:10, 20:30], [30, 40:50], [13::], [::-1]') == [
(slice(0, 10, None), slice(20, 30, None)),
(slice(None, 30, None), slice(40, 50, None)), (slice(13, None,
None), ),
(slice(None, None, -1), )
]
def _load_reducer_vars(self):
"""
Reads config file to the reducer script.
"""
# [paths] - MANDATORY
# strings
self.input_extension = self.get('paths', 'input_extension')
# booleans
for name in ['save_masterdark', 'save_masterflat']:
self.__setattr__(name, self.getboolean('paths', name))
# [keywords] - MANDATORY (except for units)
# strings
for name in ['exposure_type', 'expousure_time', 'filter', 'observed_date', 'date_format', 'dark_type_id',
'bias_type_id', 'flat_type_id', 'science_type_id']:
self.__setattr__(name, self.get('keywords', name))
# units
# If not defined, Unit will be dimensionless.
# Images units: 'adu', 'electron', 'photon' and 'dimensionless_unscaled' (if unknown)
try:
unit = self.get('keywords', 'image_units')
if unit not in self._permitted_image_units:
raise ConfigError('image_units must be one of these: {0}'.format(self._permitted_image_units))
self.image_units = unit
except NoOptionError:
self.image_units = units.dimensionless_unscaled
# [overscan] - OPTIONAL
if 'overscan' in self.sections():
self.subtract_overscan = True
self.overscan_regions = slices_config(self.get('overscan', 'overscan_regions'))
self.science_regions = slices_config(self.get('overscan', 'science_regions'))
self.overscan_axis = self.getint('overscan', 'overscan_axis')
# Sanity check if number overscan and science regions is the same.
if len(self.science_regions) != len(self.overscan_regions):
raise ConfigError('science_regions and overscan_regions must have the same shape!') # TODO: test
# Convert the science regions to arrays with index numbers.
self.science_trim = np.array([], dtype=int)
for science_slice in self.science_regions:
self.science_trim = np.append(self.science_trim, np.r_[science_slice])
self.science_trim = np.sort(self.science_trim)
if self.science_trim.shape != np.unique(self.science_trim).shape:
raise ConfigError('There are two science regions that intersect each other.') # TODO: test
else:
self.subtract_overscan = False
def test_slices():
assert slices_config('[0:10, 20:30], [30, 40:50], [13::], [::-1]') == [(slice(0, 10, None), slice(20, 30, None)),
(slice(None, 30, None), slice(40, 50, None)),
(slice(13, None, None),),
(slice(None, None, -1),)]
