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- add additional projecta reas for the automatic inclinometer import

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- beginning with voegelsberg (ftp download, moving objects)
This commit is contained in:
Arno Kaimbacher 2022-03-23 16:30:17 +01:00
parent e068773eec
commit 7f08225b40
12 changed files with 1145 additions and 298 deletions
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4
automatic_inclinometer/firebird_queries.sql
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@ -68,7 +68,7 @@ CHIAVE NOME NUMERO_SENSORI SITO x y
5 GSA002-017-0510 17 Rosano 43.7685394,11.4232703
6 GSA02A-010-1210 10 Ampflwang - KB1 48.0889892,13.5583703
7 GSA02B-007-1210 17 Ampflwang - KB2 48.088,13.5583
8 GSA02B-007-0911 19 Laakirchen 47.9789118,13.8141457
8 GSA02B-007-0911 19 Laakirchen 47.9789118,13.8141457 erledigt
9 Copy of GSA002-017-0510 17 Rosano 43.7685394,11.4232703
10 GSA02B-007-0613 17 Pechgraben Haus 47.9193704,14.5242307
11 Copy of GSA02B-007-0911 19 Laakirchen 47.9789118,13.8141457
@ -77,7 +77,7 @@ CHIAVE NOME NUMERO_SENSORI SITO x y
14 TAC003-020-1213 20 Pechgraben KB1 47.9193704,14.5242307
15 GSA02A-010-1213 10 Pechgraben KB2 47.9193704,14.5242307
16 TAC003-020-0414 20 Pechgraben KB1 47.9193704,14.5242307
17 TAC003-020-0517 20 Wolfsegg KB1 48.1064354,13.6731638
17 TAC003-020-0517 20 Wolfsegg KB1 48.1064354,13.6731638 erledigt
18 GSA02A-010-0517 10 Wolfsegg KB3 48.1064354,13.6731638
19 TAC005-013-0517 14 Wolfsegg KB2 48.1064354,13.6731638
20 GSA003-020-0517 34 Wolfsegg KB5 48.1064354,13.6731638

314
automatic_inclinometer/import_observations_ampfwang_kb1.py Normal file
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@ -0,0 +1,314 @@
""" import firebird, export to postgresql """
#!/usr/bin/python# -*- coding: utf-8 -*-
import os
import time
from typing import List
from itertools import chain
import uuid
import json
from dotenv import load_dotenv, find_dotenv
from sqlalchemy.orm import session
from sqlalchemy import asc, desc
# from sqlalchemy.dialects import firebird
from sqlalchemy.sql import or_
from db.fb_models import (create_session, FbObservation, Catena)
from db.models import (create_pg_session, Dataset,
Observation, Procedure, Phenomenon, Platform, Format)
def main():
"""
Main function.
"""
#sensor_id = 0
# name of project area in firebird db
feature_of_interest = 'GSA02A-010-1210' # Ampflwang KB1
# sensor name in postgis db
# sensor = 'wolfsegg_kb1_0'
platform = 'ampflwang_kb1_inclinometer'
sensor_env_list = os.getenv('AMPFLWANG_KB1_SENSORS').replace('\n', '')
sensor_list = json.loads(sensor_env_list)
# print(sensor_list)
firebird_session: session = create_session()
# this will print elements along with their index value
for sensor_id, sensor in enumerate(sensor_list):
# db_observation = session.query(Observation) \
# .filter_by(name='John Snow').first()
query_count = firebird_session.query(FbObservation).join(FbObservation.catena) \
.filter(FbObservation.sensore == sensor_id) \
.filter(Catena.name == feature_of_interest) \
.filter(
or_(
FbObservation.temperature != None,
FbObservation.pitch != None # this is used to check NULL values
)) \
.count()
# if query_count == 0:
# print(f"sensor {sensor} "
# f"doesn't have any observations with measured values in firebird database!")
# # hop to next for iteration, next sensor in list
# continue
# test = query_count.statement.compile(dialect=firebird.dialect())
firebird_observations: List[FbObservation] = []
if query_count > 0:
query = firebird_session.query(FbObservation).join(FbObservation.catena) \
.filter(FbObservation.sensore == sensor_id) \
.filter(Catena.name == feature_of_interest)
# print (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: Dataset = pg_query.filter(
Phenomenon.sta_identifier == "Roll").first()
slope_dataset: Dataset = pg_query.filter(
Phenomenon.sta_identifier == "Slope").first()
temperature_dataset: Dataset = pg_query.filter(
Phenomenon.sta_identifier == "InSystemTemperature").first()
platform_exists = pg_session.query(Platform.id).filter_by(
name=platform.lower()).scalar() is not None
if not platform_exists:
sensor_platform = Platform()
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()
format_exists: bool = pg_session.query(Format.id).filter_by(
definition="http://www.opengis.net/def/observationType/OGC-OM/2.0/OM_Measurement"
).scalar() is not None
if format_exists:
sensor_format = pg_session.query(Format.id) \
.filter(Format.definition ==
"http://www.opengis.net/def/observationType/OGC-OM/2.0/OM_Measurement") \
.first()
slope_dataset.fk_format_id = sensor_format.id
roll_dataset.fk_format_id = sensor_format.id
temperature_dataset.fk_format_id = sensor_format.id
pg_session.commit()
if query_count == 0:
print(f"sensor {sensor} "
f"doesn't have any observations with measured values in firebird database!")
# hop to next for iteration, next sensor in list, don't insert any observations
continue
create_db_observations(firebird_observations, roll_dataset,
slope_dataset, temperature_dataset, pg_session)
# commit new observations:
pg_session.commit()
if len(roll_dataset.observations) > 0:
# if not published yet, publish the roll dataset
if not roll_dataset.is_published:
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"
if len(slope_dataset.observations) > 0:
# if not published yet, publish the roll dataset
if not slope_dataset.is_published:
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"
if len(temperature_dataset.observations) > 0:
# if not published yet, publish the temperature dataset
if not temperature_dataset.is_published:
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()
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
pg_session.commit()
# for loop sensors end
pg_session.close()
# firebird_session.close()
def create_db_observations(firebird_observations: List[FbObservation],
roll_dataset: Dataset,
slope_dataset: Dataset,
temperature_dataset: Dataset,
pg_session: session):
''' insert new observations ito db '''
roll_result = (
pg_session.query(Observation.result_time)
.filter(Observation.fk_dataset_id == roll_dataset.id)
.all()
)
roll_result_time_db_list1: List[str] = list(chain(*roll_result))
roll_result_time_db_list: List[float] = [time.mktime(
date_obj.timetuple()) for date_obj in roll_result_time_db_list1]
slope_result = (
pg_session.query(Observation.result_time)
.filter(Observation.fk_dataset_id == slope_dataset.id)
.all()
)
slope_result_time_db_list1: List[str] = list(chain(*slope_result))
slope_result_time_db_list: List[float] = [time.mktime(
date_obj.timetuple()) for date_obj in slope_result_time_db_list1]
temperature_result = (
pg_session.query(Observation.result_time)
.filter(Observation.fk_dataset_id == temperature_dataset.id)
.all()
)
temperature_result_time_db_list1: List[str] = list(
chain(*temperature_result))
temperature_result_time_db_list: List[float] = [time.mktime(
date_obj.timetuple()) for date_obj in temperature_result_time_db_list1]
for fb_observation in firebird_observations:
# print(fb_observation.catena.name)
if(fb_observation.roll is not None and roll_dataset is not None):
value = fb_observation.roll
add_observation(roll_dataset, fb_observation,
value, roll_result_time_db_list)
if(fb_observation.pitch is not None and slope_dataset is not None):
# max_id = max_id + 1
value = fb_observation.pitch
add_observation(slope_dataset, fb_observation,
value, slope_result_time_db_list)
if(fb_observation.temperature is not None and temperature_dataset is not None):
# max_id = max_id + 1
value = fb_observation.temperature
add_observation(temperature_dataset, fb_observation,
value, temperature_result_time_db_list)
def add_observation(
dataset: Dataset,
fb_observation: FbObservation,
value: str,
value_identifier_db_list: List[float]):
''' check if observation still extists in db,
otherwise add it to fb'''
# ob_id: str = str(observation_json.get('id'))
# existing_observation: bool = (
# db_session.query(Observation)
# .filter(Observation.result_time == fb_observation.result_time,
# Observation.fk_dataset_id == dataset.id)
# .one_or_none()
# )
existing_observation: bool = time.mktime(
fb_observation.result_time.timetuple()) in value_identifier_db_list
# Can we insert this observation?
if existing_observation is False:
# insert bew observation
new_observation: Observation = Observation()
new_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_identifier=str(time.mktime(
fb_observation.result_time.timetuple())),
value_quantity=value
)
dataset.observations.append(new_observation)
print(f"new observation with result time {new_observation.result_time} "
f"for inclinometer {dataset.procedure.name} succesfully imported!")
else:
print(f"observation with result time {fb_observation.result_time} "
f"for inclinometer {dataset.procedure.name} already exists!")
# -----------------------------------------------------------------------------
if __name__ == "__main__":
load_dotenv(find_dotenv())
main()

131
automatic_inclinometer/import_observations_laakirchen.py
View File

@ -53,22 +53,24 @@ def main():
.filter(
or_(
FbObservation.temperature != None,
FbObservation.pitch != None #this is used to check NULL values
FbObservation.pitch != None # this is used to check NULL values
)) \
.count()
if query_count == 0:
print(f"sensor {sensor} "
f"doesn't have any observations with measured values in firebird database!")
# hop to next for iteration, next sensor in list
continue
# feature_of_interest = query.statement.compile(dialect=firebird.dialect())
# if query_count == 0:
# print(f"sensor {sensor} "
# f"doesn't have any observations with measured values in firebird database!")
# # hop to next for iteration, next sensor in list
# continue
# test = query_count.statement.compile(dialect=firebird.dialect())
query = firebird_session.query(FbObservation).join(FbObservation.catena) \
.filter(FbObservation.sensore == sensor_id) \
.filter(Catena.name == feature_of_interest)
# print (query.statement.compile(dialect=firebird.dialect()))
firebird_observations: List[FbObservation] = query.all()
# firebird_session.close()
firebird_observations: List[FbObservation] = []
if query_count > 0:
query = firebird_session.query(FbObservation).join(FbObservation.catena) \
.filter(FbObservation.sensore == sensor_id) \
.filter(Catena.name == feature_of_interest)
# print (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()
@ -108,7 +110,6 @@ def main():
# commit dataset changes:
pg_session.commit()
format_exists: bool = pg_session.query(Format.id).filter_by(
definition="http://www.opengis.net/def/observationType/OGC-OM/2.0/OM_Measurement"
).scalar() is not None
@ -122,7 +123,14 @@ def main():
temperature_dataset.fk_format_id = sensor_format.id
pg_session.commit()
create_db_observations(firebird_observations, roll_dataset, slope_dataset, temperature_dataset, pg_session)
if query_count == 0:
print(f"sensor {sensor} "
f"doesn't have any observations with measured values in firebird database!")
# hop to next for iteration, next sensor in list, don't insert any observations
continue
create_db_observations(firebird_observations, roll_dataset,
slope_dataset, temperature_dataset, pg_session)
# commit new observations:
pg_session.commit()
@ -155,7 +163,6 @@ def main():
temperature_dataset.value_type = "quantity"
pg_session.commit()
last_roll_observation = pg_session.query(Observation) \
.filter(Observation.fk_dataset_id == roll_dataset.id) \
.order_by(desc('sampling_time_start')) \
@ -213,80 +220,95 @@ def main():
# for loop sensors end
pg_session.close()
firebird_session.close()
# firebird_session.close()
def create_db_observations(firebird_observations: List[FbObservation],
roll_dataset: Dataset,
slope_dataset: Dataset,
temperature_dataset: Dataset,
pg_session: session):
roll_dataset: Dataset,
slope_dataset: Dataset,
temperature_dataset: Dataset,
pg_session: session):
''' insert new observations ito db '''
roll_result = (
pg_session.query(Observation.result_time)
.filter(Observation.fk_dataset_id == roll_dataset.id)
.all()
)
pg_session.query(Observation.result_time)
.filter(Observation.fk_dataset_id == roll_dataset.id)
.all()
)
roll_result_time_db_list1: List[str] = list(chain(*roll_result))
roll_result_time_db_list : List[float]= [time.mktime(date_obj.timetuple()) for date_obj in roll_result_time_db_list1]
roll_result_time_db_list: List[float] = [time.mktime(
date_obj.timetuple()) for date_obj in roll_result_time_db_list1]
slope_result = (
pg_session.query(Observation.result_time)
.filter(Observation.fk_dataset_id == slope_dataset.id)
.all()
)
pg_session.query(Observation.result_time)
.filter(Observation.fk_dataset_id == slope_dataset.id)
.all()
)
slope_result_time_db_list1: List[str] = list(chain(*slope_result))
slope_result_time_db_list : List[float]= [time.mktime(date_obj.timetuple()) for date_obj in slope_result_time_db_list1]
slope_result_time_db_list: List[float] = [time.mktime(
date_obj.timetuple()) for date_obj in slope_result_time_db_list1]
temperature_result = (
pg_session.query(Observation.result_time)
.filter(Observation.fk_dataset_id == temperature_dataset.id)
.all()
)
temperature_result_time_db_list1: List[str] = list(chain(*temperature_result))
temperature_result_time_db_list : List[float]= [time.mktime(date_obj.timetuple()) for date_obj in temperature_result_time_db_list1]
pg_session.query(Observation.result_time)
.filter(Observation.fk_dataset_id == temperature_dataset.id)
.all()
)
temperature_result_time_db_list1: List[str] = list(
chain(*temperature_result))
temperature_result_time_db_list: List[float] = [time.mktime(
date_obj.timetuple()) for date_obj in temperature_result_time_db_list1]
for fb_observation in firebird_observations:
# print(fb_observation.catena.name)
if(fb_observation.roll is not None and roll_dataset is not None):
value = fb_observation.roll
add_observation(roll_dataset, fb_observation, value, roll_result_time_db_list)
add_observation(roll_dataset, fb_observation,
value, roll_result_time_db_list)
if(fb_observation.pitch is not None and slope_dataset is not None):
# max_id = max_id + 1
value = fb_observation.pitch
add_observation(slope_dataset, fb_observation, value, slope_result_time_db_list)
add_observation(slope_dataset, fb_observation,
value, slope_result_time_db_list)
if(fb_observation.temperature is not None and temperature_dataset is not None):
# max_id = max_id + 1
value = fb_observation.temperature
add_observation(temperature_dataset, fb_observation, value, temperature_result_time_db_list)
add_observation(temperature_dataset, fb_observation,
value, temperature_result_time_db_list)
def add_observation(dataset: Dataset, fb_observation: FbObservation, value: str, value_identifier_db_list: List[float]):
def add_observation(
dataset: Dataset,
fb_observation: FbObservation,
value: str,
value_identifier_db_list: List[float]):
''' check if observation still extists in db,
otherwise add it to fb'''
# ob_id: str = str(observation_json.get('id'))
# existing_observation: bool = (
# db_session.query(Observation)
# .filter(Observation.result_time == fb_observation.result_time, Observation.fk_dataset_id == dataset.id)
# .filter(Observation.result_time == fb_observation.result_time,
# Observation.fk_dataset_id == dataset.id)
# .one_or_none()
# )
existing_observation: bool =time.mktime(fb_observation.result_time.timetuple()) in value_identifier_db_list
# Can we insert this observation?
existing_observation: bool = time.mktime(
fb_observation.result_time.timetuple()) in value_identifier_db_list
# Can we insert this observation?
if existing_observation is False:
# insert bew observation
new_observation: Observation = Observation()
new_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_identifier = str(time.mktime(fb_observation.result_time.timetuple())),
value_quantity=value
)
# 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_identifier=str(time.mktime(
fb_observation.result_time.timetuple())),
value_quantity=value
)
dataset.observations.append(new_observation)
print(f"new observation with result time {new_observation.result_time} "
f"for inclinometer {dataset.procedure.name} succesfully imported!")
@ -294,6 +316,7 @@ def add_observation(dataset: Dataset, fb_observation: FbObservation, value: str,
print(f"observation with result time {fb_observation.result_time} "
f"for inclinometer {dataset.procedure.name} already exists!")
# -----------------------------------------------------------------------------
if __name__ == "__main__":
load_dotenv(find_dotenv())

433
automatic_inclinometer/import_observations_wolfsegg_kb1.py
View File

@ -1,197 +1,314 @@
""" import firebird, export to postgresql """
#!/usr/bin/python# -*- coding: utf-8 -*-
import os
import time
from typing import List
from itertools import chain
import uuid
import json
from dotenv import load_dotenv, find_dotenv
from sqlalchemy.orm import session
from sqlalchemy import desc, asc
from sqlalchemy import asc, desc
# from sqlalchemy.dialects import firebird
from sqlalchemy.sql import or_
from db.fb_models import (create_session, FbObservation, Catena)
from db.models import (create_pg_session, Dataset, Observation, Procedure, Phenomenon, Platform)
from db.models import (create_pg_session, Dataset,
Observation, Procedure, Phenomenon, Platform, Format)
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
#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_inclinometer'
# sensor = 'wolfsegg_kb1_0'
platform = 'wolfsegg_kb1_inclinometer'
sensor_env_list = os.getenv('WOLFSEGG_KB1_SENSORS').replace('\n', '')
sensor_list = json.loads(sensor_env_list)
# print(sensor_list)
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()
# this will print elements along with their index value
for sensor_id, sensor in enumerate(sensor_list):
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())
# db_observation = session.query(Observation) \
# .filter_by(name='John Snow').first()
query_count = firebird_session.query(FbObservation).join(FbObservation.catena) \
.filter(FbObservation.sensore == sensor_id) \
.filter(Catena.name == feature_of_interest) \
.filter(
or_(
FbObservation.temperature != None,
FbObservation.pitch != None # this is used to check NULL values
)) \
.count()
# if query_count == 0:
# print(f"sensor {sensor} "
# f"doesn't have any observations with measured values in firebird database!")
# # hop to next for iteration, next sensor in list
# continue
# test = query_count.statement.compile(dialect=firebird.dialect())
firebird_observations: List[FbObservation] = []
if query_count > 0:
query = firebird_session.query(FbObservation).join(FbObservation.catena) \
.filter(FbObservation.sensore == sensor_id) \
.filter(Catena.name == feature_of_interest)
# print (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: Dataset = pg_query.filter(
Phenomenon.sta_identifier == "Roll").first()
# 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()
slope_dataset: Dataset = pg_query.filter(
Phenomenon.sta_identifier == "Slope").first()
temperature_dataset: Dataset = pg_query.filter(
Phenomenon.sta_identifier == "InSystemTemperature").first()
platform_exists = pg_session.query(Platform.id).filter_by(
name=platform.lower()).scalar() is not None
if not platform_exists:
sensor_platform = Platform()
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()
format_exists: bool = pg_session.query(Format.id).filter_by(
definition="http://www.opengis.net/def/observationType/OGC-OM/2.0/OM_Measurement"
).scalar() is not None
if format_exists:
sensor_format = pg_session.query(Format.id) \
.filter(Format.definition ==
"http://www.opengis.net/def/observationType/OGC-OM/2.0/OM_Measurement") \
.first()
slope_dataset.fk_format_id = sensor_format.id
roll_dataset.fk_format_id = sensor_format.id
temperature_dataset.fk_format_id = sensor_format.id
pg_session.commit()
if query_count == 0:
print(f"sensor {sensor} "
f"doesn't have any observations with measured values in firebird database!")
# hop to next for iteration, next sensor in list, don't insert any observations
continue
create_db_observations(firebird_observations, roll_dataset,
slope_dataset, temperature_dataset, pg_session)
# commit new observations:
pg_session.commit()
if len(roll_dataset.observations) > 0:
# if not published yet, publish the roll dataset
if not roll_dataset.is_published:
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"
if len(slope_dataset.observations) > 0:
# if not published yet, publish the roll dataset
if not slope_dataset.is_published:
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"
if len(temperature_dataset.observations) > 0:
# if not published yet, publish the temperature dataset
if not temperature_dataset.is_published:
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()
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
pg_session.commit()
# for loop sensors end
pg_session.close()
# firebird_session.close()
def create_db_observations(firebird_observations: List[FbObservation],
roll_dataset: Dataset,
slope_dataset: Dataset,
temperature_dataset: Dataset,
pg_session: session):
''' insert new observations ito db '''
roll_result = (
pg_session.query(Observation.result_time)
.filter(Observation.fk_dataset_id == roll_dataset.id)
.all()
)
roll_result_time_db_list1: List[str] = list(chain(*roll_result))
roll_result_time_db_list: List[float] = [time.mktime(
date_obj.timetuple()) for date_obj in roll_result_time_db_list1]
slope_result = (
pg_session.query(Observation.result_time)
.filter(Observation.fk_dataset_id == slope_dataset.id)
.all()
)
slope_result_time_db_list1: List[str] = list(chain(*slope_result))
slope_result_time_db_list: List[float] = [time.mktime(
date_obj.timetuple()) for date_obj in slope_result_time_db_list1]
temperature_result = (
pg_session.query(Observation.result_time)
.filter(Observation.fk_dataset_id == temperature_dataset.id)
.all()
)
temperature_result_time_db_list1: List[str] = list(
chain(*temperature_result))
temperature_result_time_db_list: List[float] = [time.mktime(
date_obj.timetuple()) for date_obj in temperature_result_time_db_list1]
# 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)
value = fb_observation.roll
add_observation(roll_dataset, fb_observation,
value, roll_result_time_db_list)
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)
value = fb_observation.pitch
add_observation(slope_dataset, fb_observation,
value, slope_result_time_db_list)
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()
value = fb_observation.temperature
add_observation(temperature_dataset, fb_observation,
value, temperature_result_time_db_list)
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
def add_observation(
dataset: Dataset,
fb_observation: FbObservation,
value: str,
value_identifier_db_list: List[float]):
''' check if observation still extists in db,
otherwise add it to fb'''
# ob_id: str = str(observation_json.get('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
# existing_observation: bool = (
# db_session.query(Observation)
# .filter(Observation.result_time == fb_observation.result_time,
# Observation.fk_dataset_id == dataset.id)
# .one_or_none()
# )
existing_observation: bool = time.mktime(
fb_observation.result_time.timetuple()) in value_identifier_db_list
# Can we insert this observation?
if existing_observation is False:
# insert bew observation
new_observation: Observation = Observation()
new_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_identifier=str(time.mktime(
fb_observation.result_time.timetuple())),
value_quantity=value
)
dataset.observations.append(new_observation)
print(f"new observation with result time {new_observation.result_time} "
f"for inclinometer {dataset.procedure.name} succesfully imported!")
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()
print(f"observation with result time {fb_observation.result_time} "
f"for inclinometer {dataset.procedure.name} already exists!")
# -----------------------------------------------------------------------------
if __name__ == "__main__":
load_dotenv(find_dotenv())
main()

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automatic_inclinometer/import_observations_wolfsegg_kb1_old.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_kb1_inclinometer'
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()

195
automatic_inclinometer/insert_sensors/import_sensors_ampflwang.py Normal file
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# -*- coding: utf-8 -*-
"""This module does blah blah."""
from ast import List
import requests
# from insert_sensor.transactional import insert_sensor
from insert_sensor.wrapper import (Offering, FoI, Procedure, SensorType)
# import json
class Sos():
"""
A class to represent a sos service.
...
Attributes
----------
sosurl : str
first name of the person
token : str
token to access soso service
"""
def __init__(self, url, token=''):
self.sosurl = str(url) # url to access the SOS
self.token = str(token) # security token, optional
# Test if URL exists
try:
test = requests.get(self.sosurl)
test.raise_for_status()
except requests.HTTPError:
print("The URL is not valid")
# Python3 code here creating class
class Sensor:
"""
A class to represent an input sensor.
...
Attributes
----------
name : str
first name of the person
x : float
token to access soso service
y : float
token to access soso service
"""
def __init__(self, name: str, x_coord: float, y_coord: float):
self.name = name
self.x_coord = x_coord
self.y_coord = y_coord
def main():
"""
main function
"""
sos_url = 'https://geomon.geologie.ac.at/52n-sos-webapp/service'
# creating list
sensor_list: List[Sensor] = []
# appending instances to list 48.0889892,13.5583703
sensor_list.append(
Sensor('ampflwang_kb1_0', 13.5583703, 48.0889892))
sensor_list.append(
Sensor('ampflwang_kb1_1', 13.5583703, 48.0889892))
sensor_list.append(
Sensor('ampflwang_kb1_2', 13.5583703, 48.0889892))
sensor_list.append(
Sensor('ampflwang_kb1_3', 13.5583703, 48.0889892))
sensor_list.append(
Sensor('ampflwang_kb1_4', 13.5583703, 48.0889892))
sensor_list.append(
Sensor('ampflwang_kb1_5', 13.5583703, 48.0889892))
sensor_list.append(
Sensor('ampflwang_kb1_6', 13.5583703, 48.0889892))
sensor_list.append(
Sensor('ampflwang_kb1_7', 13.5583703, 48.0889892))
sensor_list.append(
Sensor('ampflwang_kb1_8', 13.5583703, 48.0889892))
sensor_list.append(
Sensor('ampflwang_kb1_9', 13.5583703, 48.0889892))
sensor: Sensor
for sensor in sensor_list:
# platform ampflwang_kb1_inclinometer
offering = Offering(
"https://geomon.geologie.ac.at/52n-sos-webapp/api/offerings/",
sensor.name,
"Bohrloch, Ampflwang Inklinometer"
)
procedure = Procedure(sensor.name, sensor.name)
foi = FoI("degree", "m", (sensor.x_coord, sensor.y_coord, 0.0),
"GSA02A-010-1210", "Ampflwang KB1")
# now insert sensor via rest service:
sensor_type=SensorType("inclinometer")
post_data=insert_sensor(offering, procedure, foi, sensor_type)
# print(post_data)
headers={'Accept': 'application/json'}
request=requests.post(sos_url, headers = headers, json = post_data)
print(request.text)
def insert_sensor(offering, procedure, foi, sensor_type):
"""
Prepares the body of a InsertSensor request for JSON biding.
:param offering: an instance of class Offering.Type object.
:param Procedure: instance of class Procedure. type object.
:param foi: feature of interest. Instance of FoI
:param sensor_type: SensorType object
:return: valid body for an InsertSensor request.
"""
# shortName = offering.name # string
# longName = 'Sibratsgfall test' # string
# Offering values
gml_id='\"' + str(procedure.id) + '\"' # Offering name, double quoted
offering_name=offering.name
offering_label=offering.label
# offID = offering.fullId # URL format of full id
# featureName = featureID = cordX = cordY = height = h_unit = z_unit = coordinates = ""
# check if feature of interest should be declare
if foi is not None:
# feature_id = 'https://geomon.geologie.ac.at/52n-sos-webapp/api/features/' + \
# str(foi.fid) # URL format
cord_x=str(foi.x) # longitude degrees, float
cord_y=str(foi.y) # latitude degrees, float
coordinates=cord_x + " " + cord_y
height=str(foi.z) # altitude in meters, float
# h_unit = foi.Hunit # units for horizontal coordinates
# z_unit = foi.Vunit # units for altitude
feature_id=foi.fid # "feature location"
feature_name=foi.name # "feature location"
else:
pass
procedure_name=procedure.name
procedure_identifier=procedure.id # URL,
obs_types=[]
output_list='' # output list element for describe procedure
properties_list=[]
for attr in sensor_type.pattern["attributes"]:
obs_prop_name='\"' + attr[0] + '\"' # attribute name
# print(obs_prop_name)
unit_name=sensor_type.om_types[attr[1]] # om type
# magnitud = a # ??
obs_name=obs_prop_name.replace('\"', '')
obs_name="".join(obs_name.split()) # observable property name
output='<sml:output name=' + obs_prop_name + '><swe:Quantity definition=' + \
'\"' + (obs_name) + '\"' + \
'></swe:Quantity></sml:output>'
output_list=output_list + output
# add property identifier to the list.
properties_list.append(obs_name)
# prepare list of measurement types
# A sensor can not registry duplicated sensor types.
this_type="http://www.opengis.net/def/observationType/OGC-OM/2.0/"+unit_name
if this_type not in obs_types: # when new type appears
obs_types.append(this_type)
else:
continue
# Unit of measurement:
unit_name='\"' + procedure.name + '\"' # double quoted string
# unit = omType # one of the MO measurement types
body={
"request": "InsertSensor",
"service": "SOS",
"version": "2.0.0",
"procedureDescriptionFormat": "http://www.opengis.net/sensorml/2.0",
"procedureDescription": f'<sml:PhysicalSystem gml:id={gml_id} xmlns:swes=\"http://www.opengis.net/swes/2.0\" xmlns:sos=\"http://www.opengis.net/sos/2.0\" xmlns:swe=\"http://www.opengis.net/swe/2.0\" xmlns:sml=\"http://www.opengis.net/sensorml/2.0\" xmlns:gml=\"http://www.opengis.net/gml/3.2\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xmlns:xsi=\"http://www.w3.org/2001/XMLSchema-instance\" xmlns:gco=\"http://www.isotc211.org/2005/gco\" xmlns:gmd=\"http://www.isotc211.org/2005/gmd\"><gml:identifier codeSpace=\"uniqueID\">{procedure_identifier}</gml:identifier><sml:identification><sml:IdentifierList><sml:identifier><sml:Term definition=\"urn:ogc:def:identifier:OGC:1.0:longName\"><sml:label>longName</sml:label><sml:value>{procedure_name}</sml:value></sml:Term></sml:identifier><sml:identifier><sml:Term definition=\"urn:ogc:def:identifier:OGC:1.0:shortName\"><sml:label>shortName</sml:label><sml:value>{procedure_name}</sml:value></sml:Term></sml:identifier></sml:IdentifierList></sml:identification><sml:capabilities name=\"offerings\"><sml:CapabilityList><sml:capability name=\"offeringID\"><swe:Text definition=\"urn:ogc:def:identifier:OGC:offeringID\"><swe:label>{offering_label}</swe:label><swe:value>{offering_name}</swe:value></swe:Text></sml:capability></sml:CapabilityList></sml:capabilities><sml:capabilities name=\"metadata\"><sml:CapabilityList><!-- status indicates, whether sensor is insitu (true) or remote (false) --><sml:capability name=\"insitu\"><swe:Boolean definition=\"insitu\"><swe:value>true</swe:value></swe:Boolean></sml:capability><!-- status indicates, whether sensor is mobile (true) or fixed/stationary (false) --><sml:capability name=\"mobile\"><swe:Boolean definition=\"mobile\"><swe:value>false</swe:value></swe:Boolean></sml:capability></sml:CapabilityList></sml:capabilities><sml:featuresOfInterest><sml:FeatureList definition=\"http://www.opengis.net/def/featureOfInterest/identifier\"><swe:label>featuresOfInterest</swe:label><sml:feature><sams:SF_SpatialSamplingFeature xmlns:sams=\"http://www.opengis.net/samplingSpatial/2.0\" gml:id=\"ssf_b3a826dd44012201b01323232323041f7a92e0cc47260eb9888f6a4e9f747\"><gml:identifier codeSpace=\"http://www.opengis.net/def/nil/OGC/0/unknown\">{feature_id}</gml:identifier><gml:name codeSpace=\"http://www.opengis.net/def/nil/OGC/0/unknown\">{feature_name}</gml:name><sf:type xmlns:sf=\"http://www.opengis.net/sampling/2.0\" xlink:href=\"http://www.opengis.net/def/samplingFeatureType/OGC-OM/2.0/SF_SamplingPoint\"/><sf:sampledFeature xmlns:sf=\"http://www.opengis.net/sampling/2.0\" xlink:href=\"http://www.opengis.net/def/nil/OGC/0/unknown\"/><sams:shape><ns:Point xmlns:ns=\"http://www.opengis.net/gml/3.2\" ns:id=\"Point_ssf_b3a826dd44012201b013c90c51da28c041f7a92e0cc47260eb9888f6a4e9f747\"><ns:pos srsName=\"http://www.opengis.net/def/crs/EPSG/0/4326\">{coordinates}</ns:pos></ns:Point></sams:shape></sams:SF_SpatialSamplingFeature></sml:feature></sml:FeatureList></sml:featuresOfInterest><sml:outputs><sml:OutputList><sml:output name=\"Slope\"><swe:Quantity definition=\"Slope\"><swe:label>Slope</swe:label><swe:uom code=\"deg\"/></swe:Quantity></sml:output><sml:output name=\"Roll\"><swe:Quantity definition=\"Roll\"><swe:label>Roll</swe:label><swe:uom code=\"deg\"/></swe:Quantity></sml:output><sml:output name=\"InSystemTemperature\"><swe:Quantity definition=\"InSystemTemperature\"><swe:label>InSystemTemperature</swe:label><swe:uom code=\"degC\"/></swe:Quantity></sml:output></sml:OutputList></sml:outputs><sml:position><swe:Vector referenceFrame=\"urn:ogc:def:crs:EPSG::4326\"><swe:coordinate name=\"easting\"><swe:Quantity axisID=\"x\"><swe:uom code=\"degree\"/><swe:value>{cord_x}</swe:value></swe:Quantity></swe:coordinate><swe:coordinate name=\"northing\"><swe:Quantity axisID=\"y\"><swe:uom code=\"degree\"/><swe:value>{cord_y}</swe:value></swe:Quantity></swe:coordinate><swe:coordinate name=\"altitude\"><swe:Quantity axisID=\"z\"><swe:uom code=\"m\"/><swe:value>{height}</swe:value></swe:Quantity></swe:coordinate></swe:Vector></sml:position></sml:PhysicalSystem>',
"observableProperty": [
"Slope",
"Roll",
"InSystemTemperature"
],
"observationType": [
"http://www.opengis.net/def/observationType/OGC-OM/2.0/OM_Measurement"
],
"featureOfInterestType":
"http://www.opengis.net/def/samplingFeatureType/OGC-OM/2.0/SF_SamplingPoint"
}
return body
if __name__ == '__main__':
main()

44
automatic_inclinometer/insert_sensors/import_sensors_wolfsegg.py
View File

@ -64,47 +64,47 @@ def main():
# creating list
sensor_list: List[Sensor] = []
# appending instances to list
# appending instances to list 48.1064354,13.6731638
sensor_list.append(
Sensor('wolfsegg_kb1_0', 13.808378638676, 47.882871028831))
# sensor_list.append(
# Sensor('wolfsegg_kb1_1', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_0', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_2', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_1', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_3', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_2', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_4', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_3', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_5', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_4', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_6', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_5', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_7', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_6', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_8', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_7',13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_9', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_8', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_10', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_9', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_11', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_10', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_12', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_11', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_13', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_12', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_14', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_13', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_15', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_14', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_16', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_15', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_17', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_16', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_18', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_17', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_19', 13.808378638676, 47.882871028831))
Sensor('wolfsegg_kb1_18', 13.6731638, 48.1064354))
sensor_list.append(
Sensor('wolfsegg_kb1_19', 13.6731638, 48.1064354))
sensor: Sensor
for sensor in sensor_list:

0
db/insert_initial_values.txt → db/insert_initial_db_values.txt
View File

74
gschliefgraben_glasfaser/import_feature_sensor.py
View File

@ -87,153 +87,153 @@ def main():
sensor_list.append(
Sensor('inclino1_01', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_02', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_03',13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_04', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_05', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_06', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_07', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_08', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_09', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_10', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_11', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_12', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_13', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_14', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_15', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_16', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_17', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_18', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_19', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
sensor_list.append(
Sensor('inclino1_20', 13.816940062459931, 47.883893347112163,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch1)"))
## inclino2_04 bis inclino2_22
sensor_list.append(
Sensor('inclino2_04', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_05', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_06', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_07', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_08', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_09', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_10', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_11', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_12', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_13', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_14', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_15', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_16',13.817740197926463, 47.883901327648893,
"bohrloch1-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_17', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_18',13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_19', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor_list.append(
Sensor('inclino2_20', 13.817740197926463, 47.883901327648893,
"bohrloch2-glasfaser-gschliefgraben",
"Glasfaser Untersuchungen am Gschliefgraben (Gmunden)"))
"Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)"))
sensor: Sensor
for sensor in sensor_list:

2
gschliefgraben_piezometer/import_piezometer_observations_hourly.py
View File

@ -25,7 +25,7 @@ from db.models import (
def main():
''' main method '''
pg_session: session = create_pg_session()
platform_sta_identifier = "pechgraben_piezometer"
platform_sta_identifier = "gschliefgraben_piezometer"
# sensor = "bohrloch1"
# sensor_list = os.environ.get('PIEZOMETER_GSCHLIEFGRABEN_SENSORS', [])
sensor_list = json.loads(os.environ['PIEZOMETER_GSCHLIEFGRABEN_SENSORS'])

1
voegelsberg/import_feature_sensor.py Normal file
View File

@ -0,0 +1 @@
# https://lists.ogc.org/pipermail/sensorml/2008-September/000573.html