def test_bootstrap_tn10p(self, tasmin_series, use_dask):
self.bootstrap_testor(
tasmin_series,
2,
lambda x, y, z: tn10p(x, y, freq="MS", bootstrap=z),
use_dask=use_dask,
)
def test_doy_interpolation(self):
pytest.importorskip('xarray', '0.11.4')
# Just a smoke test
fn_clim = os.path.join(
TESTS_DATA, 'CanESM2_365day',
'tasmin_day_CanESM2_rcp85_r1i1p1_na10kgrid_qm-moving-50bins-detrend_2095.nc'
)
fn = os.path.join(
TESTS_DATA, 'HadGEM2-CC_360day',
'tasmin_day_HadGEM2-CC_rcp85_r1i1p1_na10kgrid_qm-moving-50bins-detrend_2095.nc'
)
with xr.open_dataset(fn_clim) as ds:
t10 = percentile_doy(ds.tasmin.isel(lat=0, lon=0), per=.1)
with xr.open_dataset(fn) as ds:
xci.tn10p(ds.tasmin.isel(lat=0, lon=0), t10, freq='MS')
def test_tn10p_simple(self, tas_series):
i = 366
tas = np.array(range(i))
tas = tas_series(tas, start="1/1/2000")
t10 = percentile_doy(tas, per=0.1)
# create cold spell in june
tas[175:180] = 1
out = xci.tn10p(tas, t10, freq="MS")
assert out[0] == 1
assert out[5] == 5