From fb6447f79b0b8735af67e47e2357474a15b6416e Mon Sep 17 00:00:00 2001 From: Arno Kaimbacher Date: Tue, 26 Apr 2022 15:14:20 +0200 Subject: [PATCH] - add automatic inclinometer datad for boreholes KB1 and KB2 in Gschliefgraben --- .../import_observations_gschliefgraben_kb1.py | 8 +- .../import_observations_gschliefgraben_kb2.py | 324 ++++++++++++++++++ .../import_sensors_gschliefgraben_kb2.py | 191 +++++++++++ db/fb_models.py | 6 +- 4 files changed, 522 insertions(+), 7 deletions(-) create mode 100644 automatic_inclinometer/import_observations_gschliefgraben_kb2.py create mode 100644 automatic_inclinometer/insert_sensors/import_sensors_gschliefgraben_kb2.py diff --git a/automatic_inclinometer/import_observations_gschliefgraben_kb1.py b/automatic_inclinometer/import_observations_gschliefgraben_kb1.py index 06d72ee..b129505 100644 --- a/automatic_inclinometer/import_observations_gschliefgraben_kb1.py +++ b/automatic_inclinometer/import_observations_gschliefgraben_kb1.py @@ -20,7 +20,7 @@ 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.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, @@ -48,7 +48,7 @@ def main(): # db_observation = session.query(Observation) \ # .filter_by(name='John Snow').first() - query_count = firebird_session.query(FbObservation).join(Catena) \ + query_count = firebird_session.query(FbObservation).join(FbObservation.catena) \ .filter(FbObservation.sensore == sensor_id) \ .filter(Catena.name == feature_of_interest) \ .filter( @@ -66,10 +66,10 @@ def main(): firebird_observations: List[FbObservation] = [] if query_count > 0: - query = firebird_session.query(FbObservation).join(Catena) \ + 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())) + # print (query.statement.compile(dialect=firebird.dialect())) firebird_observations: List[FbObservation] = query.all() firebird_session.close() diff --git a/automatic_inclinometer/import_observations_gschliefgraben_kb2.py b/automatic_inclinometer/import_observations_gschliefgraben_kb2.py new file mode 100644 index 0000000..81f4e0e --- /dev/null +++ b/automatic_inclinometer/import_observations_gschliefgraben_kb2.py @@ -0,0 +1,324 @@ +""" import firebird, export to postgresql: +SELECT dataset_id, dataset_type, observation_type, value_type, fk_procedure_id, fk_phenomenon_id, +fk_offering_id, fk_category_id, fk_feature_id, fk_platform_id, fk_format_id, fk_unit_id, +is_deleted, is_disabled, is_published, is_mobile, is_insitu, is_hidden, origin_timezone, +first_time, last_time, first_value, last_value, fk_first_observation_id, fk_last_observation_id, +decimals, identifier, fk_identifier_codespace_id, name, fk_name_codespace_id, description, +fk_value_profile_id + FROM gba.dataset + where fk_platform_id = 6 and fk_feature_id = 43 + ORDER BY dataset_id ASC; + """ +#!/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 = 'TAC005-013-0521' # Gschliefgraben KB2 + # sensor name in postgis db + # sensor = 'wolfsegg_kb1_0' + platform = 'gschliefgraben_inclinometer' + + sensor_env_list = os.getenv('GSCHLIEFGRABEN_KB2_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() diff --git a/automatic_inclinometer/insert_sensors/import_sensors_gschliefgraben_kb2.py b/automatic_inclinometer/insert_sensors/import_sensors_gschliefgraben_kb2.py new file mode 100644 index 0000000..4f2f712 --- /dev/null +++ b/automatic_inclinometer/insert_sensors/import_sensors_gschliefgraben_kb2.py @@ -0,0 +1,191 @@ +# -*- coding: utf-8 -*- +"""This module does blah blah.""" + +import os +from ast import List +import json +from dotenv import load_dotenv, find_dotenv +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' + + sensor_env_list = os.getenv('GSCHLIEFGRABEN_KB2_SENSORS').replace('\n', '') + sensor_list_tmp = json.loads(sensor_env_list) + + + # creating list + sensor_list: List[Sensor] = [] + # x_coord = 13.816940062459931 + # y_coord =47.883893347112163 + + for sensor in sensor_list_tmp: + # appending instances to list 13.817740197926463, 47.883901327648893 + sensor_list.append( + Sensor(sensor, 13.816940062459931, 47.883893347112163)) + + 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, Gschliefgraben Inklinometer" + ) + procedure = Procedure(sensor.name, sensor.name) + # foi = FoI("degree", "m", (sensor.x_coord, sensor.y_coord, 0.0), + # "TAC003-020-0521", "Gschliefgraben KB1") + foi = FoI("degree", "m", (sensor.x_coord, sensor.y_coord, 0.0), + "bohrloch2-glasfaser-gschliefgraben", + "Glasfaser Untersuchungen am Gschliefgraben (Bohrloch2)") + # 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='' + 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'{procedure_identifier}longName{procedure_name}shortName{procedure_name}{offering_label}{offering_name}truefalsefeaturesOfInterest{feature_id}{feature_name}{coordinates}SlopeRollInSystemTemperature{cord_x}{cord_y}{height}', + "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__': + load_dotenv(find_dotenv()) + main() diff --git a/db/fb_models.py b/db/fb_models.py index c5d19dc..5d13569 100644 --- a/db/fb_models.py +++ b/db/fb_models.py @@ -36,10 +36,10 @@ class FbObservation(Base): roll = Column('ROLL', String) ora = Column('ORA', Time, primary_key=True) sensore = Column('SENSORE', Integer, primary_key=True) - data = Column('DATA', Date) + data = Column('DATA', Date, primary_key=True) temperature = Column('TEMPERATURA', String) - - chiave_id = Column('CATENA', Integer, ForeignKey('CATENE.CHIAVE'), nullable=True) + + chiave_id = Column('CATENA', Integer, ForeignKey('CATENE.CHIAVE'), primary_key=True, nullable=True) catena = relationship( "Catena", back_populates="observations", lazy="joined")