def read_upper_air_iastate(date):
try:
data = IAStateUpperAir().request_all_data(date)
except ValueError:
#print("ERROR: no data available for ",date)
#print(" Trying previous synoptic time")
return None
#date = date - timedelta(hours = 12)
#data = IAStateUpperAir().request_all_data(date)
data = add_station_lat_lon(data)
return data
def test_add_lat_lon_station_data():
"""Test for when the METAR does not correspond to a station in the dictionary."""
df = pd.DataFrame({'station': ['KOUN', 'KVPZ', 'KDEN', 'PAAA']})
df = add_station_lat_lon(df, 'station')
assert_almost_equal(df.loc[df.station == 'KOUN'].latitude.values[0], 35.25)
assert_almost_equal(df.loc[df.station == 'KOUN'].longitude.values[0], -97.47)
assert_almost_equal(df.loc[df.station == 'KVPZ'].latitude.values[0], 41.45)
assert_almost_equal(df.loc[df.station == 'KVPZ'].longitude.values[0], -87)
assert_almost_equal(df.loc[df.station == 'KDEN'].latitude.values[0], 39.85)
assert_almost_equal(df.loc[df.station == 'KDEN'].longitude.values[0], -104.65)
assert_almost_equal(df.loc[df.station == 'PAAA'].latitude.values[0], np.nan)
assert_almost_equal(df.loc[df.station == 'PAAA'].longitude.values[0], np.nan)
def test_add_lat_lon_station_data_optional():
"""Test for when only one argument is passed."""
df = pd.DataFrame({'station': ['KOUN', 'KVPZ', 'KDEN', 'PAAA']})
df = add_station_lat_lon(df)
assert_almost_equal(df.loc[df.station == 'KOUN'].latitude.values[0], 35.25)
def test_add_lat_lon_station_data_not_found():
"""Test case where key cannot be inferred."""
df = pd.DataFrame({'location': ['KOUN']})
with pytest.raises(KeyError):
add_station_lat_lon(df)
import cartopy.crs as ccrs from metpy.io import add_station_lat_lon from metpy.plots import declarative from metpy.units import units from siphon.simplewebservice.iastate import IAStateUpperAir import pandas as pd # ## Read Data # Set date for desired UPA data date = datetime(2020, 2, 29, 12) # Request data using Siphon request for data from Iowa State Archive df = IAStateUpperAir.request_all_data(date) df = add_station_lat_lon(df, 'station') df['dewpoint_depression'] = df['temperature'] - df['dewpoint'] # ## Plot Upperair Map # Set a format specifier for the geoptential height # This formatter takes a value 9300 -> 930 height_format = lambda v: format(v, '.0f')[1:] # Plot desired data obs = declarative.PlotObs() obs.data = df obs.time = date obs.level = 850 * units.hPa obs.fields = ['temperature', 'dewpoint_depression', 'height']