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- add module 'automatic_inclinometer'

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Arno Kaimbacher 2022-03-18 16:23:44 +01:00
parent c2f2dc1b41
commit b704e55a3e
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automatic_inclinometer/import_observations_wolfsegg_kb1.py Normal file
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""" import firebird, export to postgresql """
#!/usr/bin/python# -*- coding: utf-8 -*-
from typing import List
import uuid
from sqlalchemy.orm import session
from sqlalchemy import desc, asc
from db.fb_models import (create_session, FbObservation, Catena)
from db.models import (create_pg_session, Dataset, Observation, Procedure, Phenomenon, Platform)
def main():
"""
Main function.
"""
# parameter:
# sensor id in firebird db:
# sensor_id = 1
# # name of project area in firebird db
# feature_of_interest = 'TAC003-020-0517' # Wolfsegg KB1
# # sensor name in postgis db
# sensor = 'wolfsegg_kb1_1'
# platform = 'wolfsegg'
sensor_id = 0
# name of project area in firebird db
feature_of_interest = 'TAC003-020-0517' # Wolfsegg KB1
# sensor name in postgis db
sensor = 'wolfsegg_kb1_0'
platform = 'wolfsegg'
firebird_session: session = create_session()
# db_observation = session.query(Observation) \
# .filter_by(name='John Snow').first()
query = firebird_session.query(FbObservation).join(FbObservation.catena) \
.filter(FbObservation.sensore == sensor_id) \
.filter(Catena.name == feature_of_interest)
# feature_of_interest = query.statement.compile(dialect=firebird.dialect())
firebird_observations: List[FbObservation] = query.all()
firebird_session.close()
pg_session: session = create_pg_session()
# pg_datasets: List[Dataset] = pg_query.all()
pg_query = pg_session.query(Dataset) \
.join(Procedure) \
.join(Phenomenon) \
.filter(Procedure.sta_identifier == sensor.lower())
# .join(Platform).all() \
# roll_dataset = [x for x in pg_datasets if x.phenomenon.sta_identifier == "Roll"]
roll_dataset = pg_query.filter(Phenomenon.sta_identifier == "Roll").first()
roll_dataset.is_published = 1
roll_dataset.is_hidden = 0
roll_dataset.dataset_type = "timeseries"
roll_dataset.observation_type = "simple"
roll_dataset.value_type = "quantity"
slope_dataset = pg_query.filter(
Phenomenon.sta_identifier == "Slope").first()
slope_dataset.is_published = 1
slope_dataset.is_hidden = 0
slope_dataset.dataset_type = "timeseries"
slope_dataset.observation_type = "simple"
slope_dataset.value_type = "quantity"
temperature_dataset = pg_query.filter(
Phenomenon.sta_identifier == "InSystemTemperature").first()
temperature_dataset.is_published = 1
temperature_dataset.is_hidden = 0
temperature_dataset.dataset_type = "timeseries"
temperature_dataset.observation_type = "simple"
temperature_dataset.value_type = "quantity"
pg_session.commit()
# max_id = pg_session.query(func.max(Observation.id)).scalar()
for fb_observation in firebird_observations:
# print(fb_observation.catena.name)
if(fb_observation.roll is not None and roll_dataset is not None):
# max_id = max_id + 1
pg_roll_observation = Observation(
# id=max_id,
value_type='quantity',
sampling_time_start=fb_observation.result_time,
sampling_time_end=fb_observation.result_time,
result_time=fb_observation.result_time,
sta_identifier=str(uuid.uuid4()),
value_quantity=fb_observation.roll
)
roll_dataset.observations.append(pg_roll_observation)
if(fb_observation.pitch is not None and slope_dataset is not None):
# max_id = max_id + 1
pg_slope_observation = Observation(
# id=max_id,
value_type='quantity',
sampling_time_start=fb_observation.result_time,
sampling_time_end=fb_observation.result_time,
result_time=fb_observation.result_time,
sta_identifier=str(uuid.uuid4()),
value_quantity=fb_observation.pitch
)
slope_dataset.observations.append(pg_slope_observation)
if(fb_observation.temperature is not None and temperature_dataset is not None):
# max_id = max_id + 1
pg_temperature_observation = Observation(
# id=max_id,
value_type='quantity',
sampling_time_start=fb_observation.result_time,
sampling_time_end=fb_observation.result_time,
result_time=fb_observation.result_time,
sta_identifier=str(uuid.uuid4()),
value_quantity=fb_observation.temperature
)
temperature_dataset.observations.append(pg_temperature_observation)
# commit observations:
pg_session.commit()
last_roll_observation = pg_session.query(Observation) \
.filter(Observation.fk_dataset_id == roll_dataset.id) \
.order_by(desc('sampling_time_start')) \
.first()
if last_roll_observation is not None:
roll_dataset.last_time = last_roll_observation.sampling_time_start
roll_dataset.last_value = last_roll_observation.value_quantity
roll_dataset.fk_last_observation_id = last_roll_observation.id
last_slope_observation = pg_session.query(Observation) \
.filter(Observation.fk_dataset_id == slope_dataset.id) \
.order_by(desc('sampling_time_start')) \
.first()
if last_slope_observation is not None:
slope_dataset.last_time = last_slope_observation.sampling_time_start
slope_dataset.last_value = last_slope_observation.value_quantity
slope_dataset.fk_last_observation_id = last_slope_observation.id
last_temperature_observation = pg_session.query(Observation) \
.filter(Observation.fk_dataset_id == temperature_dataset.id) \
.order_by(desc('sampling_time_start')) \
.first()
if last_temperature_observation is not None:
temperature_dataset.last_time = last_temperature_observation.sampling_time_start
temperature_dataset.last_value = last_temperature_observation.value_quantity
temperature_dataset.fk_last_observation_id = last_temperature_observation.id
first_roll_observation = pg_session.query(Observation) \
.filter(Observation.fk_dataset_id == roll_dataset.id) \
.order_by(asc('sampling_time_start')) \
.first()
if first_roll_observation is not None:
roll_dataset.first_time = first_roll_observation.sampling_time_start
roll_dataset.first_value = first_roll_observation.value_quantity
roll_dataset.fk_first_observation_id = first_roll_observation.id
first_slope_observation = pg_session.query(Observation) \
.filter(Observation.fk_dataset_id == slope_dataset.id) \
.order_by(asc('sampling_time_start')) \
.first()
if first_slope_observation is not None:
slope_dataset.first_time = first_slope_observation.sampling_time_start
slope_dataset.first_value = first_slope_observation.value_quantity
slope_dataset.fk_first_observation_id = first_slope_observation.id
first_temperature_observation = pg_session.query(Observation) \
.filter(Observation.fk_dataset_id == temperature_dataset.id) \
.order_by(asc('sampling_time_start')) \
.first()
if first_temperature_observation is not None:
temperature_dataset.first_time = first_temperature_observation.sampling_time_start
temperature_dataset.first_value = first_temperature_observation.value_quantity
temperature_dataset.fk_first_observation_id = first_temperature_observation.id
platform_exists = pg_session.query(Platform.id).filter_by(
name=platform.lower()).scalar() is not None
if not platform_exists:
sensor_platform = Platform()
# max_id = pg_session.query(func.max(Platform.id)).scalar()
# sensor_platform.id = max_id + 1
sensor_platform.sta_identifier = platform.lower()
sensor_platform.identifier = platform.lower()
sensor_platform.name = platform.lower()
slope_dataset.platform = sensor_platform
roll_dataset.platform = sensor_platform
temperature_dataset.platform = sensor_platform
else:
sensor_platform = pg_session.query(Platform.id) \
.filter(Platform.name == platform.lower()) \
.first()
slope_dataset.fk_platform_id = sensor_platform.id
roll_dataset.fk_platform_id = sensor_platform.id
temperature_dataset.fk_platform_id = sensor_platform.id
# commit dataset changes:
pg_session.commit()
pg_session.close()
# -----------------------------------------------------------------------------
if __name__ == "__main__":
main()