def test_rolling_cumsum(self, tmp_path):
data_path = _create_dummy_precip_data(tmp_path)
ds = xr.open_dataset(data_path / 'chirps_kenya.nc')
cumsum3 = rolling_cumsum(ds, rolling_window=3)
cumsum6 = rolling_cumsum(ds, rolling_window=6)
# assert start in 2nd month (CENTRED WINDOW)
got = pd.to_datetime(cumsum3.isel(time=0).time.values)
expected = pd.to_datetime('1999-02-28')
assert got == expected, "Expected minimum time of Cumsum to be:" \
f"{expected} because centered window with size=3. Got: {got}"
# assert start in 4th month
got = pd.to_datetime(cumsum6.isel(time=0).time.values)
expected = pd.to_datetime('1999-04-30')
assert got == expected, "Expected minimum time of Cumsum to be:"\
f"{expected} because centered window with size=6. Got: {got}"
def test_rolling_cumsum(self, tmp_path):
data_path = _create_dummy_precip_data(tmp_path)
ds = xr.open_dataset(data_path / "data_kenya.nc")
cumsum3 = rolling_cumsum(ds, rolling_window=3)
cumsum6 = rolling_cumsum(ds, rolling_window=6)
# assert start in 3nd month (NON-CENTRED WINDOW)
got = pd.to_datetime(cumsum3.isel(time=0).time.values)
expected = pd.to_datetime("1999-03-31")
assert got == expected, (
"Expected minimum time of Cumsum to be:"
f"{expected} because centered window with size=3. Got: {got}")
# assert start in 4th month
got = pd.to_datetime(cumsum6.isel(time=0).time.values)
expected = pd.to_datetime("1999-06-30")
assert got == expected, (
"Expected minimum time of Cumsum to be:"
f"{expected} because centered window with size=6. Got: {got}")
def test_create_shape_aligned_climatology_season(self, tmp_path):
data_path = _create_dummy_precip_data(tmp_path)
ds = xr.open_dataset(data_path / "data_kenya.nc")
time_period = "season"
ds_window = rolling_cumsum(ds, rolling_window=3)
climatology = ds_window.groupby(f"time.{time_period}").mean(dim="time")
assert climatology.precip.shape[0] == 4, (f"There should be 4 seasons"
f"in the climatology")
clim = create_shape_aligned_climatology(ds_window,
climatology,
variable="precip",
time_period=time_period)
assert ds_window["precip"].shape == clim["precip"].shape, (
f"Expected"
f"the shape of `ds_window` ({ds_window['precip'].shape}) to =="
f"`clim` ({clim['precip'].shape})")
def test_create_shape_aligned_climatology_season(self, tmp_path):
data_path = _create_dummy_precip_data(tmp_path)
ds = xr.open_dataset(data_path / 'chirps_kenya.nc')
time_period = 'season'
ds_window = rolling_cumsum(ds, rolling_window=3)
climatology = (ds_window.groupby(f'time.{time_period}').mean(
dim='time'))
assert climatology.precip.shape[0] == 4, f"There should be 4 seasons" \
f"in the climatology"
clim = create_shape_aligned_climatology(ds_window,
climatology,
variable='precip',
time_period=time_period)
assert ds_window['precip'].shape == clim['precip'].shape, f"Expected" \
f"the shape of `ds_window` ({ds_window['precip'].shape}) to ==" \
f"`clim` ({clim['precip'].shape})"
def test_create_shape_aligned_climatology_month(self, tmp_path):
data_path = _create_dummy_precip_data(tmp_path)
ds = xr.open_dataset(data_path / 'chirps_kenya.nc')
time_period = 'month'
ds_window = rolling_cumsum(ds, rolling_window=3)
mthly_climatology = (ds_window.groupby(f'time.{time_period}').mean(
dim='time'))
assert mthly_climatology.precip.shape[0] == 12, f"There should be 12" \
f"month when calculating monthly climatology"
clim = create_shape_aligned_climatology(ds_window,
mthly_climatology,
variable='precip',
time_period=time_period)
assert ds_window['precip'].shape == clim['precip'].shape, f"Expected" \
f"the shape of `ds_window` ({ds_window['precip'].shape}) to ==" \
f"`clim` ({clim['precip'].shape})"