def get_WHO_exceedances(location, pollutant='PM 2.5', frequency='daily'):
'''
Returns exceedances based on the WHO limit
'''
device_code = code_locations_dict[location]
end_date = datetime.now()
start_date = end_date - timedelta(days=29)
records = get_filtered_data(device_code, helpers.date_to_str(start_date),
helpers.date_to_str(end_date), frequency,
pollutant)
if pollutant == 'NO2':
exceedance_sum = sum(
1 for i in range(len(records))
if records[i]['characteristics']['no2Conc']['value'] > 40)
elif pollutant == 'PM 10':
exceedance_sum = sum(
1 for i in range(len(records))
if records[i]['characteristics']['pm10ConcMass']['value'] > 50)
else:
exceedance_sum = sum(
1 for i in range(len(records))
if records[i]['characteristics']['pm2_5ConcMass']['value'] > 25.0)
return exceedance_sum
def calculate_average_daily_measurements_for_last_28_days():
ms = monitoring_site.MonitoringSite()
gr = graph.Graph()
monitoring_sites = list(
app.mongo.db.monitoring_site.find({}, {
"DeviceCode": 1,
"Parish": 1,
"LocationCode": 1,
"Division": 1,
"_id": 0
}))
devices_historical_records = []
for monitoring_site_device in monitoring_sites:
print(monitoring_site_device)
code = monitoring_site_device['DeviceCode']
historical_results = []
records = []
pm25_daily_values = []
average_pm25 = 0
if code: #check if code is not empty
print(code)
parish = monitoring_site_device['Parish']
division = monitoring_site_device['Division']
location_code = monitoring_site_device['LocationCode']
created_at = helpers.str_to_date(
helpers.date_to_str(datetime.now()))
endtime = helpers.date_to_str(datetime.now())
starttime = helpers.date_to_str(datetime.now() -
timedelta(days=28))
monitoring_site_measurements_cursor = gr.get_filtered_data(
code, starttime, endtime, 'daily', 'PM 2.5')
#monitoring_site_measurements_cursor = ms.get_device_past_28_days_measurements(code)
for site in monitoring_site_measurements_cursor:
record = {
'pm2_5_value': int(site['pollutant_value']),
'time': site["time"]
}
records.append(record)
pm25_daily_values.append(int(site['pollutant_value']))
historical_results.append(site)
if len(pm25_daily_values) > 0:
average_pm25 = np.mean(pm25_daily_values)
historical_record = {
'deviceCode': code,
'average_pm25': average_pm25,
'historical_records': records,
'Parish': parish,
'Division': division,
'LocationCode': location_code,
'created_at': created_at
}
devices_historical_records.append(historical_record)
mongo_helpers.save_device_daily_historical_averages(
devices_historical_records)
return jsonify({'response': 'all new hourly measurements saved'}), 200
def get_device_past_28_days_measurements():
ms = monitoring_site.MonitoringSite()
gr = graph.Graph()
if request.method == 'GET':
device_code = request.args.get('device_code')
if device_code:
historical_results = []
records = []
pm25_daily_values = []
endtime = helpers.date_to_str(datetime.now())
starttime = helpers.date_to_str(datetime.now() -
timedelta(days=28))
monitoring_site_measurements_cursor = gr.get_filtered_data(
device_code, starttime, endtime, 'daily', 'PM 2.5')
#monitoring_site_measurements_cursor = ms.get_device_past_28_days_measurements(device_code)
for site in monitoring_site_measurements_cursor:
record = {
'pm2_5_value': int(site['pollutant_value']),
'time': site["time"]
}
records.append(record)
pm25_daily_values.append(int(site['pollutant_value']))
historical_results.append(site)
return jsonify({
"historical_measurements": historical_results,
"records": records,
"pm25_values": pm25_daily_values
})
else:
return jsonify({
"error msg":
"device code wasn't supplied in the query string parameter."
})
def get_device_past_28_days_measurements(self, device_code):
"""
Gets all the daily measurements for the deviceo for the past 28 days from current day.
Args:
device_code: the code of the devices whose measurements are to be returned.
Returns:
A list of the daily measurements for the past 28 days.
"""
endtime = helpers.date_to_str(datetime.now())
starttime = helpers.date_to_str(datetime.now() - timedelta(days=28))
results = mongo_helpers.get_filtered_data(device_code,starttime, endtime,'daily','PM 2.5')
#results = list(app.mongo.db..find({"deviceCode":device_code}))
return results
def get_all_devices_past_28_days_exceedences(self,
pollutant='PM 2.5',
standard='AQI'):
"""
Gets all the exceedences for all the locations in the past 28 days from current day.
Args:
pollutant: the pollutant whose exceedences are to be returned.
standard: the standard to use to get the exceedences.
Returns:
A list of the number of daily exceedences for the specified pollutant and standard in the past 28 days.
"""
created_at = helpers.str_to_date(
helpers.date_to_str(datetime.now().date()))
# print(created_at)
query = {
'$match': {
'created_at': {
'$gte': created_at
},
'pollutant': pollutant,
'standard': standard
}
}
projection = {'$project': {'_id': 0}}
results = list(
app.mongo.db.device_daily_exceedences.aggregate(
[query, projection]))
return results
def get_device_codes():
devices_codes = list(mongo.db.devices.find({}, {"code": 1, "_id": 0}))
devices_codes_list = []
for device_code in devices_codes[0:2]:
last_time = mongo_helpers.get_last_time_from_device_hourly_measurements(
device_code['code'])
start_time = helpers.date_to_str(
helpers.str_to_date(last_time) + timedelta(hours=1))
devices_codes_list.append({
"code": device_code['code'],
"start time": start_time,
"last time": last_time
})
return jsonify({'device codes': devices_codes_list}), 200
def get_all_devices_past_28_days_measurements(self):
"""
Gets all the daily measurements for the deviceo for the past 28 days from current day.
Args:
device_code: the code of the devices whose measurements are to be returned.
Returns:
A list of the daily measurements for the past 28 days.
"""
created_at = helpers.str_to_date(helpers.date_to_str(datetime.now().date()))
print(created_at)
query = {'$match':{ 'created_at': {'$gte': created_at} }}
projection = { '$project': { '_id': 0 }}
results = list(app.mongo.db.device_daily_historical_averages.aggregate([query, projection]) )
return results
def get_AQI_exceedances(location, pollutant='PM 2.5', frequency='daily'):
'''
Returns exceedances based on the AQI index
'''
device_code = code_locations_dict[location]
end_date = datetime.now()
start_date = end_date - timedelta(days=29)
records = get_filtered_data(device_code, helpers.date_to_str(start_date),
helpers.date_to_str(end_date), frequency,
pollutant)
if pollutant == 'NO2':
UH4SG_sum = sum(
1 for i in range(len(records))
if records[i]['characteristics']['no2Conc']['value'] > 100
and records[i]['characteristics']['no2Conc']['value'] <= 360)
unhealthy_sum = sum(
1 for i in range(len(records))
if records[i]['characteristics']['no2Conc']['value'] > 360
and records[i]['characteristics']['no2Conc']['value'] <= 649)
v_unhealthy_sum = sum(
1 for i in range(len(records))
if records[i]['characteristics']['no2Conc']['value'] > 649
and records[i]['characteristics']['no2Conc']['value'] <= 1249)
hazardous_sum = sum(
1 for i in range(len(records))
if records[i]['characteristics']['no2Conc']['value'] > 1249
and records[i]['characteristics']['no2Conc']['value'] <= 2049)
elif pollutant == 'PM 10':
UH4SG_sum = sum(
1 for i in range(len(records))
if records[i]['characteristics']['pm10ConcMass']['value'] > 154
and records[i]['characteristics']['pm10ConcMass']['value'] <= 254)
unhealthy_sum = sum(
1 for i in range(len(records))
if records[i]['characteristics']['pm10ConcMass']['value'] > 254
and records[i]['characteristics']['pm10ConcMass']['value'] <= 354)
v_unhealthy_sum = sum(
1 for i in range(len(records))
if records[i]['characteristics']['pm10ConcMass']['value'] > 354
and records[i]['characteristics']['pm10ConcMass']['value'] <= 424)
hazardous_sum = sum(
1 for i in range(len(records))
if records[i]['characteristics']['pm10ConcMass']['value'] > 424
and records[i]['characteristics']['pm10ConcMass']['value'] <= 604)
else:
UH4SG_sum = sum(
1 for i in range(len(records))
if records[i]['characteristics']['pm2_5ConcMass']['value'] > 35.4
and records[i]['characteristics']['pm2_5ConcMass']['value'] <= 55.4
)
unhealthy_sum = sum(
1 for i in range(len(records)) if
records[i]['characteristics']['pm2_5ConcMass']['value'] > 55.4 and
records[i]['characteristics']['pm2_5ConcMass']['value'] <= 150.4)
v_unhealthy_sum = sum(
1 for i in range(len(records)) if
records[i]['characteristics']['pm2_5ConcMass']['value'] > 150.4 and
records[i]['characteristics']['pm2_5ConcMass']['value'] <= 250.4)
hazardous_sum = sum(
1 for i in range(len(records)) if
records[i]['characteristics']['pm2_5ConcMass']['value'] > 250.4 and
records[i]['characteristics']['pm2_5ConcMass']['value'] <= 500.4)
#exceedances = {'UHSG':UH4SG_sum, 'Unhealthy':unhealthy_sum, 'Very Unhealthy':v_unhealthy_sum, 'Hazardous':hazardous_sum}
exceedances = [UH4SG_sum, unhealthy_sum, v_unhealthy_sum, hazardous_sum]
return exceedances