def test_unmix_intervals_tz_fail(hr, freq):
periods = 6 if freq == '1h' else 2
# should not work. 13-0700 is 20Z
index = pd.date_range(
start=f'20190101 {hr:02}-0700', freq=freq, periods=periods)
with pytest.raises(ValueError):
mixed_s = pd.Series([0] * len(index), index=index)
forecast.unmix_intervals(mixed_s)
def test_unmix_intervals_tz(hr, freq):
periods = 6 if freq == '1h' else 2
# should work.
index = pd.date_range(
start=f'20190101 {hr:02}-0700', freq=freq, periods=periods)
# we only care to test tz functionality, not values
mixed_s = pd.Series([0] * len(index), index=index)
out = forecast.unmix_intervals(mixed_s)
expected_s = pd.Series([0] * len(index), index=index)
assert_series_equal(out, expected_s)
def test_unmix_intervals(mixed, expected):
npts = len(mixed)
if npts in [2, 4]:
index = pd.date_range(start='20190101 03Z', freq='3h', periods=npts)
else:
index = pd.date_range(start='20190101 01Z', freq='1h', periods=npts)
mixed_s = pd.Series(mixed, index=index)
out = forecast.unmix_intervals(mixed_s)
expected_s = pd.Series(expected, index=index)
assert_series_equal(out, expected_s)
def _unmix_various_gfs_intervals(init_time, start_floored, end_ceil,
cloud_cover_mixed):
"""unmix intervals for each kind of interval length in GFS forecast"""
end_1h = init_time + pd.Timedelta('120hr')
end_3h = init_time + pd.Timedelta('240hr')
cloud_covers = []
if start_floored < end_1h:
cloud_cover_1h_mixed = cloud_cover_mixed.loc[start_floored:end_1h]
cloud_covers.append(forecast.unmix_intervals(cloud_cover_1h_mixed))
if end_ceil > end_1h and start_floored < end_3h:
cloud_cover_3h_mixed = cloud_cover_mixed.loc[
end_1h+pd.Timedelta('3hr'):end_3h]
cloud_covers.append(forecast.unmix_intervals(cloud_cover_3h_mixed))
if end_ceil > end_3h:
cloud_cover_12h = cloud_cover_mixed.loc[
end_3h+pd.Timedelta('12hr'):end_ceil]
cloud_covers.append(cloud_cover_12h)
cloud_cover = pd.concat(cloud_covers)
return cloud_cover
def gfs_quarter_deg_hourly_to_hourly_mean(latitude,
longitude,
elevation,
init_time,
start,
end,
interval_label,
load_forecast=load_forecast,
*,
__model='gfs_0p25'):
"""
Take 1 hr GFS and convert it to hourly average data.
GHI from NWP model cloud cover. DNI, DHI computed.
Max forecast horizon 120 hours.
Parameters
----------
latitude : float
longitude : float
elevation : float
init_time : pd.Timestamp
Full datetime of a model initialization
start : pd.Timestamp
Forecast start. Forecast is inclusive of this instant if
interval_label is *beginning* and exclusive of this instant if
interval_label is *ending*.
end : pd.Timestamp
Forecast end. Forecast is exclusive of this instant if
interval_label is *beginning* and inclusive of this instant if
interval_label is *ending*.
interval_label : str
Must be *beginning* or *ending*
"""
start_floored, end_ceil = _adjust_gfs_start_end(start, end)
cloud_cover_mixed, air_temperature, wind_speed = load_forecast(
latitude,
longitude,
init_time,
start_floored,
end_ceil,
__model,
variables=('cloud_cover', 'air_temperature', 'wind_speed'))
cloud_cover = forecast.unmix_intervals(cloud_cover_mixed)
return _resample_using_cloud_cover(latitude, longitude, elevation,
cloud_cover, air_temperature,
wind_speed, start, end, interval_label,
'bfill')
def _unmix_various_gefs_intervals(init_time, start_floored, end_ceil,
cloud_cover_mixed):
"""unmix intervals for each kind of interval length in GEFS forecast"""
# 195hr is only in index for post Sept 2020 GEFS
if init_time + pd.Timedelta('195hr') in cloud_cover_mixed.index:
end_3h = init_time + pd.Timedelta('240hr')
else:
end_3h = init_time + pd.Timedelta('192hr')
cloud_covers = []
if start_floored < end_3h:
cloud_cover_3h_mixed = cloud_cover_mixed.loc[start_floored:end_3h]
cloud_covers.append(forecast.unmix_intervals(cloud_cover_3h_mixed))
if end_ceil > end_3h:
cloud_cover_6_or_12h = cloud_cover_mixed.loc[
end_3h+pd.Timedelta('6hr'):end_ceil]
cloud_covers.append(cloud_cover_6_or_12h)
cloud_cover = pd.concat(cloud_covers)
return cloud_cover
def test_unmix_intervals_two_freq():
index = pd.DatetimeIndex(['20190101 01', '20190101 02', '20190101 04'])
mixed_s = pd.Series([1, 1/3, 1/6], index=index)
with pytest.raises(ValueError):
forecast.unmix_intervals(mixed_s)
def test_unmix_intervals_invalidfreq():
index = pd.date_range(start='20190101 01Z', freq='2h', periods=3)
mixed_s = pd.Series([1, 1/3, 1/6], index=index)
with pytest.raises(ValueError):
forecast.unmix_intervals(mixed_s)