def derive(self,
src_1=P('Latitude (1)'),
src_2=P('Latitude (2)'),
src_3=P('Latitude (3)')):
sources = [
source for source in [src_1, src_2, src_3] if source is not None
and np.count_nonzero(source.array) > len(source.array) / 2
]
if len(sources) == 1:
self.offset = sources[0].offset
self.frequency = sources[0].frequency
self.array = sources[0].array
elif len(sources) == 2:
self.array, self.frequency, self.offset = blend_two_parameters(
sources[0], sources[1])
elif len(sources) > 2:
self.offset = 0.0
self.frequency = 1.0
self.array = blend_parameters(sources,
offset=self.offset,
frequency=self.frequency)
def _get_speed_parameter(hdf, aircraft_info):
thresholds = {}
if aircraft_info.get('Engine Propulsion', None) == 'ROTOR':
try:
# Preferred source of rotor speed data
parameter = hdf['Nr']
except:
# Alternative if dual sources available
parameter = blend_parameters((hdf['Nr (1)'], hdf['Nr (2)']))
parameter = P(name='Nr',
array=parameter,
data_type=parameter.dtype)
thresholds['speed_threshold'] = settings.ROTORSPEED_THRESHOLD
thresholds['min_duration'] = settings.ROTORSPEED_THRESHOLD_TIME
# Very short dips in rotor speed before recording stops.
thresholds[
'min_split_duration'] = settings.ROTOR_MINIMUM_SPLIT_DURATION
# Let's try one minute on the ground as worth splitting.
# Set to 30 sec as this gives two splits and two keeps in the test data set
# TODO: add to settings
thresholds['hash_min_samples'] = settings.AIRSPEED_HASH_MIN_SAMPLES
else:
parameter = hdf['Airspeed']
thresholds['speed_threshold'] = settings.AIRSPEED_THRESHOLD
thresholds['min_split_duration'] = settings.MINIMUM_SPLIT_DURATION
thresholds['hash_min_samples'] = settings.AIRSPEED_HASH_MIN_SAMPLES
thresholds['min_duration'] = settings.AIRSPEED_THRESHOLD_TIME
return parameter, thresholds
def derive(self,
src_1=P('Longitude (1)'),
src_2=P('Longitude (2)'),
src_3=P('Longitude (3)')):
sources = [
source for source in [src_1, src_2, src_3] if source is not None \
and np.count_nonzero(source.array) > len(source.array)/2
]
if len(sources) > 1:
for source in sources:
source.array = repair_mask(
straighten_longitude(source.array) + 180.0)
if len(sources) == 1:
self.offset = sources[0].offset
self.frequency = sources[0].frequency
self.array = sources[0].array
elif len(sources) == 2:
blended, self.frequency, self.offset = blend_two_parameters(
sources[0], sources[1])
self.array = blended % 360 - 180.0
elif len(sources) > 2:
self.offset = 0.0
self.frequency = 1.0
blended = blend_parameters(sources,
offset=self.offset,
frequency=self.frequency)
self.array = blended % 360 - 180.0
else:
self.array = np_ma_masked_zeros_like(src_1.array)
def derive(self,
src_1=P('Latitude (1)'),
src_2=P('Latitude (2)'),
src_3=P('Latitude (3)')):
sources = [
deepcopy(source) for source in [src_1, src_2, src_3] if source is not None \
and np.count_nonzero(np.ma.compressed(source.array)) > len(source.array)/2
]
for source in sources:
source.array = repair_mask(source.array)
if len(sources) == 1:
self.offset = sources[0].offset
self.frequency = sources[0].frequency
self.array = sources[0].array
elif len(sources) == 2:
self.array, self.frequency, self.offset = blend_two_parameters(
sources[0], sources[1])
elif len(sources) > 2:
self.offset = 0.0
self.frequency = 1.0
self.array = blend_parameters(sources,
offset=self.offset,
frequency=self.frequency)
else:
self.array = np_ma_masked_zeros_like(src_1.array)
def _get_speed_parameter(hdf, aircraft_info):
thresholds = {}
if aircraft_info.get('Engine Propulsion', None) == 'ROTOR':
try:
# Preferred source of rotor speed data
parameter = hdf['Nr']
except:
# Alternative if dual sources available
parameter = blend_parameters((hdf['Nr (1)'], hdf['Nr (2)']))
parameter = P(name='Nr', array=parameter, data_type=parameter.dtype)
thresholds['speed_threshold'] = settings.ROTORSPEED_THRESHOLD
thresholds['min_duration'] = settings.ROTORSPEED_THRESHOLD_TIME
# Very short dips in rotor speed before recording stops.
thresholds['min_split_duration'] = settings.ROTOR_MINIMUM_SPLIT_DURATION
# Let's try one minute on the ground as worth splitting.
# Set to 30 sec as this gives two splits and two keeps in the test data set
# TODO: add to settings
thresholds['hash_min_samples'] = settings.AIRSPEED_HASH_MIN_SAMPLES
else:
parameter = hdf['Airspeed']
thresholds['speed_threshold'] = settings.AIRSPEED_THRESHOLD
thresholds['min_split_duration'] = settings.MINIMUM_SPLIT_DURATION
thresholds['hash_min_samples'] = settings.AIRSPEED_HASH_MIN_SAMPLES
thresholds['min_duration'] = settings.AIRSPEED_THRESHOLD_TIME
return parameter, thresholds
def derive(self,
src_1=P('Latitude (1)'),
src_2=P('Latitude (2)'),
src_3=P('Latitude (3)')):
sources = [
source for source in [src_1, src_2, src_3] if source is not None \
and np.count_nonzero(source.array) > len(source.array)/2
]
if len(sources) == 1:
self.offset = sources[0].offset
self.frequency = sources[0].frequency
self.array = sources[0].array
elif len(sources) == 2:
self.array, self.frequency, self.offset = blend_two_parameters(
sources[0], sources[1]
)
elif len(sources) > 2:
self.offset = 0.0
self.frequency = 1.0
self.array = blend_parameters(sources, offset=self.offset,
frequency=self.frequency)
def derive(self,
src_1=P('Longitude (1)'),
src_2=P('Longitude (2)'),
src_3=P('Longitude (3)')):
sources = [
source for source in [src_1, src_2, src_3] if source is not None \
and np.count_nonzero(source.array) > len(source.array)/2
]
if len(sources) > 1:
for source in sources:
source.array = repair_mask(
straighten_longitude(source.array) + 180.0
)
if len(sources) == 1:
self.offset = sources[0].offset
self.frequency = sources[0].frequency
self.array = sources[0].array
elif len(sources) == 2:
blended, self.frequency, self.offset = blend_two_parameters(
sources[0], sources[1]
)
self.array = blended % 360 - 180.0
elif len(sources) > 2:
self.offset = 0.0
self.frequency = 1.0
blended = blend_parameters(sources, offset=self.offset,
frequency=self.frequency)
self.array = blended % 360 - 180.0
