""" Compute the BelAQI index from concentrations of PM10, PM2.5, O3 and NO2, based on https://www.irceline.be/en/air-quality/measurements/belaqi-air-quality-index/information > to calculate the actual (hour per hour varying) sub-indexes and the global index, the concentration scales of Table 4 > are applied to the latest hourly mean O3 and NO2 concentrations and the running 24-hourly mean PM2.5 and PM10 > concentrations. """ from datetime import datetime, date from typing import Tuple, Dict from src.open_irceline.api import IrcelineRioClient, IrcelineForecastClient from src.open_irceline.data import BelAqiIndex, RioFeature, ForecastFeature def belaqi_index(pm10: float, pm25: float, o3: float, no2: float) -> BelAqiIndex: """ Computes the BelAQI index based on the components Raise ValueError if a component is < 0 :param pm10: PM10 daily mean (or running 24-hourly mean for real-time) (µg/m³) :param pm25: PM2.5 daily mean (or running 24-hourly mean for real-time) (µg/m³) :param o3: O3 max 1-hourly mean per day (or latest hourly mean for real-time) (µg/m³) :param no2: NO2 max 1-hourly mean per day (or latest hourly mean for real-time) (µg/m³) :return: BelAQI index from 1 to 10 (Value of BelAqiIndex enum) """ if pm10 is None or pm25 is None or o3 is None or no2 is None: raise ValueError("All the components should be valued (at lest one is None here)") if pm10 < 0 or pm25 < 0 or o3 < 0 or no2 < 0: raise ValueError("All the components should have a positive value") elif pm10 > 100 or pm25 > 70 or o3 > 320 or no2 > 300: return BelAqiIndex.HORRIBLE elif pm10 > 80 or pm25 > 60 or o3 > 280 or no2 > 250: return BelAqiIndex.VERY_BAD elif pm10 > 70 or pm25 > 50 or o3 > 240 or no2 > 200: return BelAqiIndex.BAD elif pm10 > 60 or pm25 > 40 or o3 > 180 or no2 > 180: return BelAqiIndex.VERY_POOR elif pm10 > 50 or pm25 > 35 or o3 > 160 or no2 > 150: return BelAqiIndex.POOR elif pm10 > 40 or pm25 > 25 or o3 > 120 or no2 > 120: return BelAqiIndex.MODERATE elif pm10 > 30 or pm25 > 15 or o3 > 70 or no2 > 70: return BelAqiIndex.FAIRLY_GOOD elif pm10 > 20 or pm25 > 10 or o3 > 50 or no2 > 50: return BelAqiIndex.GOOD elif pm10 > 10 or pm25 > 5 or o3 > 25 or no2 > 20: return BelAqiIndex.VERY_GOOD elif pm10 >= 0 or pm25 >= 0 or o3 >= 0 or no2 >= 0: return BelAqiIndex.EXCELLENT async def belaqi_index_actual(rio_client: IrcelineRioClient, position: Tuple[float, float], timestamp: datetime | None = None) -> BelAqiIndex: """ Get current BelAQI index value for the given position using the rio_client Raise ValueError if one or more components are not available :param rio_client: client for the RIO WFS service :param position: position for which to get the data :param timestamp: desired time for the data (now if None) :return: BelAQI index value for the position at the time """ if timestamp is None: timestamp = datetime.utcnow() components = await rio_client.get_data( timestamp=timestamp, features=[RioFeature.PM10_24HMEAN, RioFeature.PM25_24HMEAN, RioFeature.O3_HMEAN, RioFeature.NO2_HMEAN], position=position ) return belaqi_index( components.get(RioFeature.PM10_24HMEAN, {}).get('value', -1), components.get(RioFeature.PM25_24HMEAN, {}).get('value', -1), components.get(RioFeature.O3_HMEAN, {}).get('value', -1), components.get(RioFeature.NO2_HMEAN, {}).get('value', -1) ) async def belaqi_index_forecast(forecast_client: IrcelineForecastClient, position: Tuple[float, float], timestamp: date | None = None) -> Dict[date, BelAqiIndex | None]: """ Get forecasted BelAQI index value for the given position using the forecast_client. Data is downloaded for the given day and the four next days Value is None for the date if one or more components cannot be downloaded :param forecast_client: client for the forecast data :param position: position for which to get the data :param timestamp: day at which the forecast are issued :return: dict mapping a day to the forecasted BelAQI index """ if timestamp is None: timestamp = date.today() components = await forecast_client.get_data( timestamp=timestamp, features=[ForecastFeature.PM10_DMEAN, ForecastFeature.PM25_DMEAN, ForecastFeature.O3_MAXHMEAN, ForecastFeature.NO2_MAXHMEAN], position=position ) result = dict() for _, day in components.keys(): try: result[day] = belaqi_index( components.get((ForecastFeature.PM10_DMEAN, day), {}).get('value', -1), components.get((ForecastFeature.PM25_DMEAN, day), {}).get('value', -1), components.get((ForecastFeature.O3_MAXHMEAN, day), {}).get('value', -1), components.get((ForecastFeature.NO2_MAXHMEAN, day), {}).get('value', -1) ) except ValueError: result[day] = None return result