def get_aqi(o3_8h: float = None, no2_1h: float = None, so2_24h: float = None,
co_8h: float = None, pm25_24h: float = None, pm10_24h: float = None, with_level: bool = False) -> (int, {}):
"""
Calculates Singapore PSI (Maximum from individual indexes)
:param o3_8h: O3 average (8h), ppm
:param no2_1h: NO2 average (1h), ppm
:param so2_24h: SO2 average (24h), ppm
:param co_8h: CO average (8h), ppm
:param pm25_24h: PM2.5 average (24h), μg/m3
:param pm10_24h: PM10 average (24h), μg/m3
:param with_level: Boolean distinguishing whether to print AQI level such as 'good' or 'hazardous'
:return: Singapore PSI, dict with tuples (Individual PSI, General message, Risk message)
keys are: o3_8h, no2_1h, so2_24h, co_8h, pm25_24h, pm10_24h
-1 means AQI is not available
"""
aqi_data = {}
if o3_8h:
aqi_data['o3_8h'] = get_psi_o3_8h(o3_8h)
if no2_1h and bool(__round_down(no2_1h, 3)):
aqi_data['no2_1h'] = get_psi_no2_1h(no2_1h)
if so2_24h:
aqi_data['so2_24h'] = get_psi_so2_24h(so2_24h)
if co_8h:
aqi_data['co_8h'] = get_psi_co_8h(co_8h)
if pm25_24h:
aqi_data['pm25_24h'] = get_psi_pm25_24h(pm25_24h)
if pm10_24h:
aqi_data['pm10_24h'] = get_psi_pm10_24h(pm10_24h)
if len(aqi_data) == 0:
return AQI_NOT_AVAILABLE, aqi_data
value = max(list(map(lambda x: x[0], aqi_data.values())))
if not with_level:
return value, aqi_data
return value, {'level': __get_aqi_level(value, SG_PSI, SG_PSI_LEVELS)}
def get_aqhi(o3_3h: float, no2_3h: float, so2_3h: float, pm25_3h: float, pm10_3h: float, with_level: bool = False) -> \
Union[Tuple[int, str, str], Tuple[int, dict]]:
"""
Calculates Hong Kong AQHI
:param o3_3h: O3 average (3h), ppm
:param no2_3h: NO2 average (3h), ppm
:param so2_3h: SO2 average (3h), ppm
:param pm25_3h: PM2.5 average (3h), μg/m3
:param pm10_3h: PM10 average (3h), μg/m3
:param with_level: Boolean distinguishing whether to print AQI level such as 'good' or 'hazardous'
:return: Hong Kong AQHI, Effect message, Caution message
"""
if any(value is None
for value in (o3_3h, no2_3h, so2_3h, pm10_3h, pm25_3h)):
return AQI_NOT_AVAILABLE, "", ""
betas = [
0.0004462559, 0.0001393235, 0.0005116328, 0.0002821751, 0.0002180567
]
if so2_3h == 0:
so2_3h = 0.020 # normal level - to make formula work without SO2
c = [
no2_3h * 1000 * NO2_PPB_UGM3, so2_3h * 1000 * SO2_PPB_UGM3,
o3_3h * 1000 * O3_PPB_UGM3, pm10_3h, pm25_3h
]
ars = list(map(__added_risk, betas, c))
ar_total = sum(ars[0:3]) + max(ars[3:5])
aqhi = len(HK_AR)
for i in range(len(HK_AR)):
if HK_AR[i][0] <= ar_total <= HK_AR[i][1]:
aqhi = i + 1
text1, text2 = __get_aqi_texts(aqhi, HK_AR, HK_AQHI_GENERAL, HK_AQHI_RISK)
if not with_level:
return aqhi, text1, text2
return aqhi, {'level': __get_aqi_level(aqhi, HK_AQHI, HK_AQHI_LEVELS)}
def get_aqhi(
o3_3h: float,
no2_3h: float,
pm25_3h: float,
pm10_3h: float,
with_level: bool = False
) -> Union[Tuple[float, str, str], Tuple[float, dict]]:
"""
Calculates Canada AQHI
:param o3_3h: O3 average (3h), ppm
:param no2_3h: NO2 average (3h), ppm
:param pm25_3h: PM2.5 average (3h), μg/m3
:param pm10_3h: PM10 average (3h), μg/m3
:param with_level: Boolean distinguishing whether to print AQI level such as 'good' or 'hazardous'
:return: CA AQHI, General message, Risk message
"""
if any(value is None for value in (o3_3h, no2_3h, pm10_3h, pm25_3h)):
return AQI_NOT_AVAILABLE, "", ""
betas = [0.000537, 0.000871, 0.000487, 0.000297]
c = [o3_3h * 1000, no2_3h * 1000, pm25_3h, pm10_3h]
ars = list(map(__added_risk, betas, c))
ar_pm25 = sum(ars[0:2]) + ars[2]
pm25 = max(1, min(CA_AQHI[-1][1], round(ar_pm25)))
ar_pm10 = sum(ars[0:2]) + ars[3]
pm10 = max(1, min(CA_AQHI[-1][1], round(ar_pm10)))
aqhi = max(pm25, pm10)
text1, text2 = __get_aqi_texts(aqhi, CA_AQHI, CA_AQHI_GENERAL,
CA_AQHI_RISK)
if not with_level:
return aqhi, text1, text2
return aqhi, {'level': __get_aqi_level(aqhi, CA_AQHI, CA_AQHI_LEVELS)}
def get_caqi(co_1h: float = None,
o3_max_1h: float = None,
no2_max_1h: float = None,
pm25_24h: float = None,
pm25_1h: float = None,
pm10_1h: float = None,
pm10_24h: float = None,
so2_max_1h: float = None,
with_level: bool = False) -> (int, {}):
"""
Calculates CAQI Europe (Maximum from individual indexes)
:param co_1h: CO average (1h), ppm
:param o3_max_1h: O3 maximum (max in 1h), ppm
:param no2_max_1h: NO2 maximum (max in 1h), ppm
:param pm25_1h: PM2.5 average (1h), μg/m3
:param pm25_24h: PM2.5 average (24h), μg/m3
:param pm10_1h: PM10 average (1h), μg/m3
:param pm10_24h: PM10 average (24h), μg/m3
:param so2_max_1h: SO2 maximum (max in 1h), ppm
:param with_level: Boolean distinguishing whether to print AQI level such as 'good' or 'hazardous'
:return: CAQI Europe, dict with aqi values
keys are: no2_1h, so2_1h, o3_1h, co_1h, pm25_1h, pm25_24h, pm10_1h, pm10_24h
-1 means AQI is not available
"""
aqi_data = {}
if no2_max_1h:
aqi_data['no2_1h'] = get_caqi_no2_1h(no2_max_1h)
if so2_max_1h:
aqi_data['so2_1h'] = get_caqi_so2_1h(so2_max_1h)
if o3_max_1h:
aqi_data['o3_1h'] = get_caqi_o3_1h(o3_max_1h)
if co_1h:
aqi_data['co_1h'] = get_caqi_co_1h(co_1h)
if pm25_1h:
aqi_data['pm25_1h'] = get_caqi_pm25_1h(pm25_1h)
if pm25_24h:
aqi_data['pm25_24h'] = get_caqi_pm25_24h(pm25_24h)
if pm10_1h:
aqi_data['pm10_1h'] = get_caqi_pm10_1h(pm10_1h)
if pm10_24h:
aqi_data['pm10_24h'] = get_caqi_pm10_24h(pm10_24h)
if len(aqi_data) == 0:
return AQI_NOT_AVAILABLE, aqi_data
value = max(list(map(lambda x: x, aqi_data.values())))
if not with_level:
return value, aqi_data
return value, {'level': __get_aqi_level(value, EU_CAQI, EU_CAQI_LEVELS)}
def get_aqi(o3_8h: float = None,
co_8h: float = None,
pm25_24h: float = None,
pm10_24h: float = None,
so2_24h: float = None,
no2_24h: float = None,
nh3_24h: float = None,
pb_24h: float = None,
with_level: bool = False) -> (int, {}):
"""
Calculates India AQI (Maximum from individual indexes)
:param o3_8h: O3 average (8h), ppm
:param co_8h: CO average (8h), ppm
:param pm25_24h: PM2.5 average (24h), μg/m3
:param pm10_24h: PM10 average (24h), μg/m3
:param so2_24h: SO2 average (24h), ppm
:param no2_24h: NO2 average (24h), ppm
:param nh3_24h: HN3 average (24h), ppm
:param pb_24h: Pb average (24h), ppm
:param with_level: Boolean distinguishing whether to print AQI level such as 'good' or 'hazardous'
:return: India AQI, dict with tuples (Individual aqi, Effect message, Caution message)
keys are: o3_8h, co_8h, pm25_24h, pm10_24h, so2_24h, no2_24h, nh3_24h, pb_24h
-1 means AQI is not available
"""
aqi_data = {}
if o3_8h:
aqi_data['o3_8h'] = get_aqi_o3_8h(o3_8h)
if co_8h:
aqi_data['co_8h'] = get_aqi_co_8h(co_8h)
if pm25_24h:
aqi_data['pm25_24h'] = get_aqi_pm25_24h(pm25_24h)
if pm10_24h:
aqi_data['pm10_24h'] = get_aqi_pm10_24h(pm10_24h)
if so2_24h:
aqi_data['so2_24h'] = get_aqi_so2_24h(so2_24h)
if no2_24h:
aqi_data['no2_24h'] = get_aqi_no2_24h(no2_24h)
if nh3_24h:
aqi_data['nh3_24h'] = get_aqi_nh3_24h(nh3_24h)
if pb_24h:
aqi_data['pb_24h'] = get_aqi_pb_24h(pb_24h)
if len(aqi_data) == 0:
return AQI_NOT_AVAILABLE, aqi_data
value = max(list(map(lambda x: x[0], aqi_data.values())))
if not with_level:
return value, aqi_data
return value, {'level': __get_aqi_level(value, IN_AQI, IN_AQI_LEVELS)}