1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
|
import dataclasses
import datetime
import typing
import pint
import szilagyi
from geopy import geocoders
from metpy import calc
from metpy import units as metunits
from windy import point_forecast, Windy
_L = point_forecast.Level
@dataclasses.dataclass
class Prediction:
time: datetime.datetime
latitude: float
longitude: float
temperature_difference: pint.Quantity
convective_cloud_depth: pint.Quantity
wind: pint.Quantity
low_clouds: float
swi: float
def calculate(config) -> typing.List[Prediction]:
units = metunits.units
windy = Windy(units)
def _calculate(latitude, longitude):
forecasts = windy.point_forecast(
config.key,
latitude, longitude,
point_forecast.Model.ICONEU,
("temp", "dewpoint", "wind", "pressure", "lclouds"),
tuple(_L))
for cast in forecasts:
dt = abs(cast.at("temp", _L.H850) - cast.at("temp", _L.SURFACE))
pressure, _ = calc.lcl(
cast.at("pressure", _L.SURFACE),
cast.at("temp", _L.SURFACE),
cast.at("dewpoint", _L.SURFACE))
lcl = calc.pressure_to_height_std(pressure)
pressure, _ = calc.el(cast["pressure"], cast["temp"], cast["dewpoint"])
el = calc.pressure_to_height_std(pressure)
ccd = (el - lcl).to(units.ft)
clouds = cast["lclouds"].magnitude / 100
try:
swi = szilagyi.calculate_swi(dt, ccd)
except ValueError:
swi = -10
yield Prediction(cast.timestamp, latitude, longitude, dt, ccd, 0, clouds, swi)
predictions = []
locator = geocoders.Nominatim(user_agent="waterspout-radar")
for location in config.locations:
found = locator.geocode(location)
predictions.extend(_calculate(found.latitude, found.longitude))
return predictions
|
