def get_spec(self, project_name: str,
model_name: str) -> typing.Optional[SensorDataSpec]:
model = self.get_model_by_key(project_name=project_name,
model_name=model_name)
if not model:
return None
spec = SensorDataSpec(tag_list=model.tag_list)
return spec
def get_spec(self, project_name: str,
model_name: str) -> typing.Optional[SensorDataSpec]:
model = self.get_machine_by_key(project_name=project_name,
model_name=model_name)
if not model:
return None
spec = SensorDataSpec(
tag_list=_gordo_to_latigo_tag_list(model.tag_list))
return spec
def load_series(
self,
train_start_date: datetime,
train_end_date: datetime,
tag_list: typing.List[SensorTag],
dry_run: typing.Optional[bool] = False,
) -> typing.Iterable[pd.Series]:
if dry_run:
raise NotImplementedError(
"Dry run for LatigoDataProvider is not implemented")
if not tag_list:
logger.warning(
"LatigoDataProvider called with empty tag_list, returning none"
)
return
if train_end_date < train_start_date:
raise ValueError(
f"LatigoDataProvider called with to_ts: {train_end_date} before from_ts: {train_start_date}"
)
if not self.sensor_data_provider:
logger.warning("Skipping, no sensor_data_provider")
return
spec: SensorDataSpec = SensorDataSpec(
tag_list=_gordo_to_latigo_tag_list(tag_list))
time_range = TimeRange(from_time=train_start_date,
to_time=train_end_date)
sensor_data, err = self.sensor_data_provider.get_data_for_range(
spec, time_range)
if err:
logger.error(f"Could not load sensor data: {err}")
return
if not sensor_data:
logger.error(f"No sensor data")
return
if not sensor_data.ok():
logger.error(f"Sensor data not OK")
return
if not sensor_data.data:
logger.error(f"No data.data")
return
if not sensor_data.data:
logger.error(f"No gordo data")
return
for d in sensor_data.data:
yield d
return
def load_series(
self,
from_ts: datetime,
to_ts: datetime,
tag_list: typing.List[SensorTag],
dry_run: typing.Optional[bool] = False
) -> typing.Iterable[pd.Series]:
if self.sensor_data_provider:
if isinstance(self.sensor_data_provider, str):
raise Exception(f"IS STR: '{self.sensor_data_provider}'")
spec: SensorDataSpec = SensorDataSpec(
tag_list=_gordo_to_latigo_tag_list(tag_list))
time_range = TimeRange(from_ts, to_ts)
sensor_data, err = self.sensor_data_provider.get_data_for_range(
spec, time_range)
if sensor_data and sensor_data.ok():
logger.info(f"Providing data: ")
logger.info(pprint.pformat(sensor_data.data))
for item in sensor_data.data:
yield item
else:
logger.warning(f"Could not load series: {err}")
not_found)
},
}
# fmt: on
name: str = "latigo_integration_test"
from_time = datetime_from_rfc3339("2019-01-02T00:00:00Z")
to_time = datetime_from_rfc3339("2019-11-02T00:00:00Z")
time_range = TimeRange(from_time=from_time, to_time=to_time)
tag_list = [
LatigoSensorTag(name="tag_name_1", asset="tag_asset_1"),
LatigoSensorTag(name="tag_name_2", asset="tag_asset_2")
]
spec: SensorDataSpec = SensorDataSpec(tag_list=tag_list)
# actual_tag_list = [LatigoSensorTag(name="GRA-STAT-20-1310_G01.ST", asset="1755-gra")]
# actual_tag_list = [LatigoSensorTag(name="GRA-FOI -13-0979.PV", asset="GRA")]
actual_tag_list = [
LatigoSensorTag(name="PT-13005/MeasA/PRIM", asset="1101-sfb")
]
# ioc-preprod.ginkgrog-b17
#'PT-13005/MeasA/PRIM', asset='1101-sfb'), SensorTag(name='TT-13092/Meas1/PRIM', asset='1101-sfb'), Sen..., SensorTag(name='DQ-TT-T-B30L/Meas1/PRIM', asset='1101-sfb'), SensorTag(name='PT-13009/MeasA/PRIM', asset='1101-sfb')
actual_spec: SensorDataSpec = SensorDataSpec(tag_list=actual_tag_list)
# , ("GRA-HIC -13-0035.PV", "1755-gra")]
data: typing.Iterable[typing.Tuple[str, pd.DataFrame, typing.List[str]]] = []
def get_spec(self) -> typing.Optional[SensorDataSpec]:
return SensorDataSpec(tag_list=self.tag_list)