211 lines
6.4 KiB
Python
211 lines
6.4 KiB
Python
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"""Support for IQVIA sensors."""
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import logging
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from statistics import mean
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from homeassistant.components.iqvia import (
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DATA_CLIENT, DOMAIN, SENSORS, TYPE_ALLERGY_FORECAST, TYPE_ALLERGY_OUTLOOK,
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TYPE_ALLERGY_INDEX, TYPE_ALLERGY_TODAY, TYPE_ALLERGY_TOMORROW,
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TYPE_ALLERGY_YESTERDAY, TYPE_ASTHMA_INDEX, TYPE_ASTHMA_TODAY,
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TYPE_ASTHMA_TOMORROW, TYPE_ASTHMA_YESTERDAY, IQVIAEntity)
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from homeassistant.const import ATTR_STATE
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_LOGGER = logging.getLogger(__name__)
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ATTR_ALLERGEN_AMOUNT = 'allergen_amount'
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ATTR_ALLERGEN_GENUS = 'allergen_genus'
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ATTR_ALLERGEN_NAME = 'allergen_name'
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ATTR_ALLERGEN_TYPE = 'allergen_type'
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ATTR_CITY = 'city'
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ATTR_OUTLOOK = 'outlook'
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ATTR_RATING = 'rating'
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ATTR_SEASON = 'season'
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ATTR_TREND = 'trend'
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ATTR_ZIP_CODE = 'zip_code'
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RATING_MAPPING = [{
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'label': 'Low',
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'minimum': 0.0,
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'maximum': 2.4
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}, {
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'label': 'Low/Medium',
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'minimum': 2.5,
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'maximum': 4.8
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}, {
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'label': 'Medium',
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'minimum': 4.9,
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'maximum': 7.2
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}, {
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'label': 'Medium/High',
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'minimum': 7.3,
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'maximum': 9.6
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}, {
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'label': 'High',
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'minimum': 9.7,
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'maximum': 12
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}]
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TREND_INCREASING = 'Increasing'
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TREND_SUBSIDING = 'Subsiding'
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async def async_setup_platform(
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hass, config, async_add_entities, discovery_info=None):
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"""Configure the platform and add the sensors."""
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iqvia = hass.data[DOMAIN][DATA_CLIENT]
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sensors = []
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for kind in iqvia.sensor_types:
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sensor_class, name, icon = SENSORS[kind]
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sensors.append(
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globals()[sensor_class](iqvia, kind, name, icon, iqvia.zip_code))
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async_add_entities(sensors, True)
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def calculate_average_rating(indices):
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"""Calculate the human-friendly historical allergy average."""
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ratings = list(
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r['label'] for n in indices for r in RATING_MAPPING
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if r['minimum'] <= n <= r['maximum'])
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return max(set(ratings), key=ratings.count)
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def calculate_trend(indices):
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"""Calculate the "moving average" of a set of indices."""
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import numpy as np
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def moving_average(data, samples):
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"""Determine the "moving average" (http://tinyurl.com/yaereb3c)."""
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ret = np.cumsum(data, dtype=float)
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ret[samples:] = ret[samples:] - ret[:-samples]
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return ret[samples - 1:] / samples
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increasing = np.all(np.diff(moving_average(np.array(indices), 4)) > 0)
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if increasing:
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return TREND_INCREASING
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return TREND_SUBSIDING
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class ForecastSensor(IQVIAEntity):
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"""Define sensor related to forecast data."""
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async def async_update(self):
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"""Update the sensor."""
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await self._iqvia.async_update()
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if not self._iqvia.data:
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return
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data = self._iqvia.data[self._kind].get('Location')
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if not data:
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return
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indices = [p['Index'] for p in data['periods']]
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average = round(mean(indices), 1)
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[rating] = [
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i['label'] for i in RATING_MAPPING
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if i['minimum'] <= average <= i['maximum']
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]
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self._attrs.update({
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ATTR_CITY: data['City'].title(),
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ATTR_RATING: rating,
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ATTR_STATE: data['State'],
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ATTR_TREND: calculate_trend(indices),
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ATTR_ZIP_CODE: data['ZIP']
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})
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if self._kind == TYPE_ALLERGY_FORECAST:
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outlook = self._iqvia.data[TYPE_ALLERGY_OUTLOOK]
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self._attrs[ATTR_OUTLOOK] = outlook.get('Outlook')
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self._attrs[ATTR_SEASON] = outlook.get('Season')
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self._state = average
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class HistoricalSensor(IQVIAEntity):
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"""Define sensor related to historical data."""
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async def async_update(self):
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"""Update the sensor."""
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await self._iqvia.async_update()
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if not self._iqvia.data:
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return
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data = self._iqvia.data[self._kind].get('Location')
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if not data:
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return
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indices = [p['Index'] for p in data['periods']]
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average = round(mean(indices), 1)
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self._attrs.update({
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ATTR_CITY: data['City'].title(),
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ATTR_RATING: calculate_average_rating(indices),
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ATTR_STATE: data['State'],
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ATTR_TREND: calculate_trend(indices),
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ATTR_ZIP_CODE: data['ZIP']
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})
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self._state = average
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class IndexSensor(IQVIAEntity):
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"""Define sensor related to indices."""
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async def async_update(self):
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"""Update the sensor."""
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await self._iqvia.async_update()
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if not self._iqvia.data:
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return
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data = {}
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if self._kind in (TYPE_ALLERGY_TODAY, TYPE_ALLERGY_TOMORROW,
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TYPE_ALLERGY_YESTERDAY):
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data = self._iqvia.data[TYPE_ALLERGY_INDEX].get('Location')
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elif self._kind in (TYPE_ASTHMA_TODAY, TYPE_ASTHMA_TOMORROW,
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TYPE_ASTHMA_YESTERDAY):
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data = self._iqvia.data[TYPE_ASTHMA_INDEX].get('Location')
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if not data:
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return
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key = self._kind.split('_')[-1].title()
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[period] = [p for p in data['periods'] if p['Type'] == key]
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[rating] = [
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i['label'] for i in RATING_MAPPING
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if i['minimum'] <= period['Index'] <= i['maximum']
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]
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self._attrs.update({
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ATTR_CITY: data['City'].title(),
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ATTR_RATING: rating,
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ATTR_STATE: data['State'],
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ATTR_ZIP_CODE: data['ZIP']
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})
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if self._kind in (TYPE_ALLERGY_TODAY, TYPE_ALLERGY_TOMORROW,
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TYPE_ALLERGY_YESTERDAY):
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for idx, attrs in enumerate(period['Triggers']):
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index = idx + 1
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self._attrs.update({
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'{0}_{1}'.format(ATTR_ALLERGEN_GENUS, index):
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attrs['Genus'],
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'{0}_{1}'.format(ATTR_ALLERGEN_NAME, index):
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attrs['Name'],
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'{0}_{1}'.format(ATTR_ALLERGEN_TYPE, index):
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attrs['PlantType'],
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})
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elif self._kind in (TYPE_ASTHMA_TODAY, TYPE_ASTHMA_TOMORROW,
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TYPE_ASTHMA_YESTERDAY):
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for idx, attrs in enumerate(period['Triggers']):
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index = idx + 1
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self._attrs.update({
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'{0}_{1}'.format(ATTR_ALLERGEN_NAME, index):
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attrs['Name'],
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'{0}_{1}'.format(ATTR_ALLERGEN_AMOUNT, index):
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attrs['PPM'],
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})
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self._state = period['Index']
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