class EnvirocarSensorStatisticModel(db.Model):
__tablename__ = ec_tables['sensors_statistics']
logger.info('table name for sensor statistics: {}'.format(__tablename__))
hash_id = db.Column(db.CHAR(length=32), primary_key=True, unique=True)
sensor_id = db.Column(db.String,
db.ForeignKey('{}.sensor_id'.format(
ec_tables['sensors'])),
nullable=False,
index=True)
phenomenon_name = db.Column(db.String,
db.ForeignKey('{}.name'.format(
ec_tables['phenomenons'])),
nullable=False,
index=True)
max = db.Column(db.Float(asdecimal=True), nullable=True)
avg = db.Column(db.Float(asdecimal=True), nullable=True)
min = db.Column(db.Float(asdecimal=True), nullable=True)
# Now some statistics --> numb = number of … used for the statistics
numb_measurements = db.Column(db.Integer, nullable=True)
numb_tracks = db.Column(db.Integer, nullable=True)
numb_users = db.Column(db.Integer, nullable=True)
numb_sensors = db.Column(db.Integer, nullable=True)
def __repr__(self):
return '<sensor statistics with id {}>'.format(self.sensor_id)
def __hash__(self):
return hash(self.sensor_id)
class EnvirocarAverageVehicleTypeStatisticModel(db.Model):
__tablename__ = ec_tables['average_vehicle_type_statistics']
hash_id = db.Column(db.CHAR(length=32), primary_key=True, unique=True)
vehicle_type = db.Column(db.String, nullable=False, index=True)
fuel_type = db.Column(db.String, nullable=False, index=True)
phenomenon_name = db.Column(db.String,
db.ForeignKey('{}.name'.format(
ec_tables['phenomenons'])),
nullable=False,
index=True)
max = db.Column(db.Float(asdecimal=True))
average = db.Column(db.Float(asdecimal=True))
min = db.Column(db.Float(asdecimal=True))
measurements = db.Column(db.Integer, nullable=False)
numb_sensors = db.Column(db.Integer, nullable=False)
class EnvirocarTrackMeasurementModel(db.Model):
__tablename__ = ec_tables['tracks_measurements']
logger.info('table name for track measurements: {}'.format(__tablename__))
hash_id = db.Column(db.CHAR(length=32), primary_key=True, unique=True)
track_measurement_id = db.Column(db.String,
db.ForeignKey(
'{}.track_measurement_id'.format(
ec_tables['tracks_features'])),
nullable=False,
index=True)
track_id = db.Column(db.String,
db.ForeignKey('{}.track_id'.format(
ec_tables['tracks'])),
nullable=False,
index=True)
sensor_id = db.Column(db.String,
db.ForeignKey('{}.sensor_id'.format(
ec_tables['sensors'])),
nullable=False,
index=True)
phenomenon_name = db.Column(db.String,
db.ForeignKey('{}.name'.format(
ec_tables['phenomenons'])),
nullable=False,
index=True)
phenomenon_value = db.Column(db.Float(asdecimal=True), nullable=True)
date = db.Column(db.DateTime, nullable=False, index=True)
def __repr__(self):
return '<track measurements with id {}>'.format(self.track_id)
def __hash__(self):
return hash(self.track_id)
class EnvirocarTrackModel(db.Model):
__tablename__ = ec_tables['tracks']
logger.info('table name for tracks: {}'.format(__tablename__))
track_id = db.Column(db.String, unique=True, primary_key=True, index=True)
sensor_id = db.Column(db.String,
db.ForeignKey('{}.sensor_id'.format(
ec_tables['sensors'])),
nullable=False,
index=True)
track_length = db.Column(db.Float(asdecimal=True))
geom = db.Column(Geometry(geometry_type='LINESTRING',
srid=4326,
spatial_index=True),
nullable=True)
tracks_statistics = db.relationship('EnvirocarTrackStatisticModel',
backref='{}'.format(
ec_tables['tracks']),
lazy='dynamic')
tracks_measurements = db.relationship('EnvirocarTrackMeasurementModel',
backref='{}'.format(
ec_tables['tracks']),
lazy='dynamic')
tracks_features = db.relationship('EnvirocarTrackFeatureModel',
backref='{}'.format(ec_tables['tracks']),
lazy='dynamic')
def __repr__(self):
return '<track {}>'.format(self.track_id)
def __hash__(self):
return hash(self.track_id)