def wind_speed(self):
"""Return the wind speed."""
if self.hass.config.units.is_metric and self._wind_speed:
return round(
speed_convert(self._wind_speed, SPEED_MILES_PER_HOUR,
SPEED_KILOMETERS_PER_HOUR),
4,
)
return self._wind_speed
def extra_state_attributes(self) -> Mapping[str, Any] | None:
"""Return additional state attributes."""
cloud_cover = self.cloud_cover
attrs = {
ATTR_CLOUD_COVER: cloud_cover,
ATTR_PRECIPITATION_TYPE: self.precipitation_type,
}
if (wind_gust := self.wind_gust) is not None:
attrs[ATTR_WIND_GUST] = round(
speed_convert(wind_gust, SPEED_MILES_PER_HOUR,
self._wind_speed_unit), 4)
def extra_state_attributes(self) -> Mapping[str, Any] | None:
"""Return additional state attributes."""
wind_gust = self.wind_gust
if wind_gust and self.hass.config.units.is_metric:
wind_gust = round(
speed_convert(self.wind_gust, SPEED_MILES_PER_HOUR,
SPEED_KILOMETERS_PER_HOUR),
4,
)
cloud_cover = self.cloud_cover
return {
ATTR_CLOUD_COVER: cloud_cover,
ATTR_WIND_GUST: wind_gust,
ATTR_PRECIPITATION_TYPE: self.precipitation_type,
}
def _forecast_dict(
self,
forecast_dt: datetime,
use_datetime: bool,
condition: int | str,
precipitation: float | None,
precipitation_probability: float | None,
temp: float | None,
temp_low: float | None,
wind_direction: float | None,
wind_speed: float | None,
) -> dict[str, Any]:
"""Return formatted Forecast dict from ClimaCell forecast data."""
if use_datetime:
translated_condition = self._translate_condition(
condition, is_up(self.hass, forecast_dt)
)
else:
translated_condition = self._translate_condition(condition, True)
if self.hass.config.units.is_metric:
if precipitation:
precipitation = round(
distance_convert(precipitation / 12, LENGTH_FEET, LENGTH_METERS)
* 1000,
4,
)
if wind_speed:
wind_speed = round(
speed_convert(
wind_speed, SPEED_MILES_PER_HOUR, SPEED_KILOMETERS_PER_HOUR
),
4,
)
data = {
ATTR_FORECAST_TIME: forecast_dt.isoformat(),
ATTR_FORECAST_CONDITION: translated_condition,
ATTR_FORECAST_PRECIPITATION: precipitation,
ATTR_FORECAST_PRECIPITATION_PROBABILITY: precipitation_probability,
ATTR_FORECAST_TEMP: temp,
ATTR_FORECAST_TEMP_LOW: temp_low,
ATTR_FORECAST_WIND_BEARING: wind_direction,
ATTR_FORECAST_WIND_SPEED: wind_speed,
}
return {k: v for k, v in data.items() if v is not None}
unit_metric=LENGTH_KILOMETERS,
imperial_conversion=lambda val: distance_convert(
val, LENGTH_KILOMETERS, LENGTH_MILES),
),
TomorrowioSensorEntityDescription(
key=TMRW_ATTR_CLOUD_COVER,
name="Cloud Cover",
native_unit_of_measurement=PERCENTAGE,
),
# Data comes in as m/s, convert to mi/h for imperial
TomorrowioSensorEntityDescription(
key=TMRW_ATTR_WIND_GUST,
name="Wind Gust",
unit_imperial=SPEED_MILES_PER_HOUR,
unit_metric=SPEED_METERS_PER_SECOND,
imperial_conversion=lambda val: speed_convert(
val, SPEED_METERS_PER_SECOND, SPEED_MILES_PER_HOUR),
),
TomorrowioSensorEntityDescription(
key=TMRW_ATTR_PRECIPITATION_TYPE,
name="Precipitation Type",
value_map=PrecipitationType,
device_class="tomorrowio__precipitation_type",
icon="mdi:weather-snowy-rainy",
),
# Data comes in as ppb, convert to µg/m^3
# Molecular weight of Ozone is 48
TomorrowioSensorEntityDescription(
key=TMRW_ATTR_OZONE,
name="Ozone",
native_unit_of_measurement=CONCENTRATION_MICROGRAMS_PER_CUBIC_METER,
multiplication_factor=convert_ppb_to_ugm3(48),
