def load_apim_audio(packet: RedvoxPacketM) -> Optional[PyarrowSummary]:
"""
load audio data from a single redvox packet
:param packet: packet with data to load
:return: audio sensor type, name, data and sample rate
"""
if srupa.__has_sensor(packet, srupa.__AUDIO_FIELD_NAME):
audio_sensor: RedvoxPacketM.Sensors.Audio = packet.sensors.audio
return PyarrowSummary(
audio_sensor.sensor_description, srupa.SensorType.AUDIO, np.nan, audio_sensor.sample_rate, "",
int(audio_sensor.samples.value_statistics.count), 1./audio_sensor.sample_rate, 0.,
pa.Table.from_pydict({"microphone": np.array(audio_sensor.samples.values)})
)
return None
def load_apim_compressed_audio(packet: RedvoxPacketM) -> Optional[PyarrowSummary]:
"""
load compressed audio data from a single redvox packet
:param packet: packet with data to load
:return: compressed audio sensor data if it exists, None otherwise
"""
if srupa.__has_sensor(packet, srupa.__COMPRESSED_AUDIO_FIELD_NAME):
comp_audio: RedvoxPacketM.Sensors.CompressedAudio = (
packet.sensors.compressed_audio
)
return PyarrowSummary(
comp_audio.sensor_description, srupa.SensorType.COMPRESSED_AUDIO, np.nan,
comp_audio.sample_rate, "", np.nan, 1./comp_audio.sample_rate, 0.,
srupa.apim_compressed_audio_to_pyarrow(comp_audio)
)
return None
def load_apim_image(packet: RedvoxPacketM) -> Optional[PyarrowSummary]:
"""
load image data from a single redvox packet
:param packet: packet with data to load
:return: image sensor data if it exists, None otherwise
"""
if srupa.__has_sensor(packet, srupa.__IMAGE_FIELD_NAME):
image_sensor: RedvoxPacketM.Sensors.Image = packet.sensors.image
timestamps = image_sensor.timestamps.timestamps
if len(timestamps) > 1:
sample_rate = 1.
else:
sample_rate = 1 / srupa.__packet_duration_s(packet)
return PyarrowSummary(
image_sensor.sensor_description, srupa.SensorType.IMAGE, np.nan, sample_rate, "",
len(timestamps), 1./sample_rate, 0., srupa.apim_image_to_pyarrow(image_sensor)
)
return None
def load_apim_location(packet: RedvoxPacketM) -> Optional[PyarrowSummary]:
"""
load location data from a single packet
:param packet: packet with data to load
:return: location sensor data if it exists, None otherwise
"""
if srupa.__has_sensor(packet, srupa.__LOCATION_FIELD_NAME):
loc: RedvoxPacketM.Sensors.Location = packet.sensors.location
timestamps = loc.timestamps.timestamps
if len(timestamps) > 0:
if len(timestamps) > 1:
m_intv = dtu.microseconds_to_seconds(float(np.mean(np.diff(timestamps))))
intv_std = dtu.microseconds_to_seconds(float(np.std(np.diff(timestamps))))
else:
m_intv = srupa.__packet_duration_s(packet)
intv_std = 0.
return PyarrowSummary(
loc.sensor_description, srupa.SensorType.LOCATION, np.nan, np.nan, "",
len(timestamps), m_intv, intv_std, srupa.apim_location_to_pyarrow(loc)
)
return None
def load_xyz(
packet: RedvoxPacketM,
sensor_type: srupa.SensorType,
) -> Optional[PyarrowSummary]:
field_name: str = srupa.__SENSOR_TYPE_TO_FIELD_NAME[sensor_type]
sensor_fn: Optional[
Callable[[RedvoxPacketM], srupa.Sensor]
] = srupa.__SENSOR_TYPE_TO_SENSOR_FN[sensor_type]
if srupa.__has_sensor(packet, field_name) and sensor_fn is not None:
sensor = sensor_fn(packet)
t = sensor.timestamps.timestamps
if len(t) > 1:
m_intv = dtu.microseconds_to_seconds(float(np.mean(np.diff(t))))
intv_std = dtu.microseconds_to_seconds(float(np.std(np.diff(t))))
else:
m_intv = srupa.__packet_duration_s(packet)
intv_std = 0.
if len(t) > 0:
return PyarrowSummary(
sensor.sensor_description, sensor_type, np.nan, np.nan, "",
len(t), m_intv, intv_std, srupa.read_apim_xyz_sensor(sensor, field_name)
)
return None
def load_apim_best_location(packet: RedvoxPacketM) -> Optional[PyarrowSummary]:
"""
load best location data from a single redvox packet
:param packet: packet with data to load
:return: best location sensor data if it exists, None otherwise
"""
if srupa.__has_sensor(packet, srupa.__LOCATION_FIELD_NAME):
loc: RedvoxPacketM.Sensors.Location = packet.sensors.location
if loc.HasField("last_best_location") or loc.HasField("overall_best_location"):
best_loc: RedvoxPacketM.Sensors.Location.BestLocation
if loc.HasField("last_best_location"):
best_loc = loc.last_best_location
else:
best_loc = loc.overall_best_location
packet_len_s = srupa.__packet_duration_s(packet)
return PyarrowSummary(
loc.sensor_description, srupa.SensorType.BEST_LOCATION, np.nan,
1./packet_len_s, "", 1, packet_len_s, 0.,
srupa.apim_best_location_to_pyarrow(best_loc,
packet.timing_information.packet_start_mach_timestamp),
)
return None