def screen_bad_profiles(self):
good_ind = []
for ind, flag in enumerate(self.data['quality_flag']):
if not (utils.isbit(flag, 1) and utils.isbit(flag, 2)):
good_ind.append(ind)
for key in self.data.keys():
self.data[key] = self.data[key][good_ind]
def _find_pixels_hard_to_correct(self) -> np.ndarray:
melting_layer = utils.isbit(self.classification.category_bits, 3)
hard_to_correct = np.cumsum(melting_layer, axis=1) >= 1
hard_to_correct[self.classification.is_rain, :] = True
attenuated = self._find_attenuated_part_of_atmosphere()
hard_to_correct[attenuated & self.atten.mask] = True
return hard_to_correct
def _read_bits(self, bit_type):
""" Converts bitfield into dictionary."""
nc = netCDF4.Dataset(self._categorize_file)
bitfield = nc.variables[f"{bit_type}_bits"][:]
keys = getattr(CategorizeBits, f"{bit_type}_keys")
bits = {key: utils.isbit(bitfield, i) for i, key in enumerate(keys)}
nc.close()
return bits
def _read_bits(self, bit_type: str) -> dict:
"""Converts bitfield into dictionary."""
nc = netCDF4.Dataset(self._categorize_file)
try:
bitfield = nc.variables[f"{bit_type}_bits"][:]
except KeyError as err:
nc.close()
raise KeyError from err
keys = getattr(CategorizeBits, f"{bit_type}_keys")
bits = {key: utils.isbit(bitfield, i) for i, key in enumerate(keys)}
nc.close()
return bits
def test_isbit(number, nth_bit, result):
assert utils.isbit(number, nth_bit) is result
def __init__(self, model: Model, classification: ClassificationResult):
self._dheight = utils.mdiff(model.height)
self._model = model.data_dense
self._liquid_in_pixel = utils.isbit(classification.category_bits, 0)
self.classification = classification
