def test_altimeter_to_sea_level_pressure_hpa():
"""Test the altimeter to sea level pressure function with hectopascals."""
altim = 1013 * units.hectopascal
elev = 500 * units.m
temp = 0 * units.degC
res = altimeter_to_sea_level_pressure(altim, elev, temp)
truth = 1016.246 * units.hectopascal
assert_almost_equal(res, truth, 3)
def test_altimiter_to_sea_level_pressure_inhg():
"""Test the altimeter to sea level pressure function with inches of mercury."""
altim = 29.8 * units.inHg
elev = 500 * units.m
temp = 30 * units.degC
res = altimeter_to_sea_level_pressure(altim, elev, temp)
truth = 1006.089 * units.hectopascal
assert_almost_equal(res, truth, 3)
def test_altimeter_to_sea_level_pressure_hpa(array_type):
"""Test the altimeter to sea level pressure function with hectopascals."""
mask = [False, True, False, True]
altim = array_type([1000., 1005., 1010., 1013], 'hectopascal', mask=mask)
elev = array_type([2000., 1500., 1000., 500.], 'meter', mask=mask)
temp = array_type([-3., -2., -1., 0.], 'degC')
res = altimeter_to_sea_level_pressure(altim, elev, temp)
truth = array_type([1009.963556, 1013.119712, 1015.885392, 1016.245615],
'hectopascal',
mask=mask)
assert_array_almost_equal(res, truth, 3)
def download_alldata(startts=datetime.datetime(2012, 8, 1),
endts=datetime.datetime(2012, 9, 1)):
"""An alternative method that fetches all available data.
Service supports up to 24 hours worth of data at a time."""
# timestamps in UTC to request data for
#startts = datetime.datetime(2012, 8, 1)
#endts = datetime.datetime(2012, 9, 1)
interval = datetime.timedelta(hours=24)
service = SERVICE + "data=all&tz=Etc/UTC&format=comma&latlon=yes&elev=yes&trace=0.0001&"
now = startts
while now < endts:
thisurl = service
thisurl += now.strftime("year1=%Y&month1=%m&day1=%d&")
thisurl += (now + interval).strftime("year2=%Y&month2=%m&day2=%d&")
print("Downloading: %s" % (now, ))
data = download_data(thisurl)
df = pd.read_csv(data,
skiprows=5,
header=0,
parse_dates=['valid'],
na_values=['M'],
low_memory=False)
# Convert wx codes to numeric values for plotting purposes
df['present_weather'] = wx_code_to_numeric(df['wxcodes'].fillna(''))
# Convert cloud cover strings to numeric values for plotting purposes
df['cloud_cover'] = df.skyc1.fillna('').apply(get_cloud_cover)
# Compute the u (eastward_wind) and v(northward_wind) components
df['eastward_wind'], df['northward_wind'] = mpcalc.wind_components(
df.sknt.values * units.knots, df.drct.values * units.degree)
# Compute the MSLP from the Altimeter reading using MetPy calculation
df['air_pressure_at_sea_level'] = mpcalc.altimeter_to_sea_level_pressure(
df.alti.values * units.inHg, df.elevation.values * units.meters,
df.tmpf.values * units.degF).to('hPa')
# Save CSV version of archive and new variables
df.to_csv(f'surface_data_{now:%Y%m%d}.csv', index=False)
#outfn = "surface_data_%s.txt" % (now.strftime("%Y%m%d"),)
#with open(outfn, "w") as fh:
# fh.write(data)
now += interval
