def test_tn90p_simple(self, tasmin_series):
i = 366
tas = np.array(range(i))
tas = tasmin_series(tas, start="1/1/2000")
t90 = percentile_doy(tas, per=0.1)
# create cold spell in june
tas[175:180] = 1
out = xci.tn90p(tas, t90, freq="MS")
assert out[0] == 30
assert out[1] == 29
assert out[5] == 25
def test_simple(self, tasmax_series):
i = 3650
A = 10.0
tx = (
np.zeros(i)
+ A * np.sin(np.arange(i) / 365.0 * 2 * np.pi)
+ 0.1 * np.random.rand(i)
)
tx[10:20] += 2
tx = tasmax_series(tx)
tx90 = percentile_doy(tx, per=0.9)
out = xci.warm_spell_duration_index(tx, tx90, freq="YS")
assert out[0] == 10
def test_tg10p_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.tg10p(tas, t10, freq="MS")
assert out[0] == 1
assert out[5] == 5
with pytest.raises(AttributeError):
out = xci.tg10p(tas, tas, freq="MS")
def test_convert_units(self, tasmin_series):
i = 3650
A = 10.0
tn = (
np.zeros(i)
+ A * np.sin(np.arange(i) / 365.0 * 2 * np.pi)
+ 0.1 * np.random.rand(i)
)
tn[10:20] -= 2
tn = tasmin_series(tn + K2C)
tn.attrs["units"] = "C"
tn10 = percentile_doy(tn, per=0.1)
out = atmos.cold_spell_duration_index(tn, tn10, freq="AS-JUL")
assert out[0] == 10
def test_simple(self, tasmin_series):
i = 3650
A = 10.0
tn = (
np.zeros(i)
+ A * np.sin(np.arange(i) / 365.0 * 2 * np.pi)
+ 0.1 * np.random.rand(i)
)
tn[10:20] -= 2
tn = tasmin_series(tn)
tn10 = percentile_doy(tn, per=0.1)
out = xci.cold_spell_duration_index(tn, tn10, freq="YS")
assert out[0] == 10
assert out.units == "days"
def test_nan_presence(self, tasmin_series):
i = 3650
A = 10.0
tn = (
np.zeros(i)
+ K2C
+ A * np.sin(np.arange(i) / 365.0 * 2 * np.pi)
+ 0.1 * np.random.rand(i)
)
tn[10:20] -= 2
tn[9] = np.nan
tn = tasmin_series(tn)
tn10 = percentile_doy(tn, per=0.1)
out = atmos.cold_spell_duration_index(tn, tn10, freq="AS-JUL")
assert np.isnan(out[0])
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_simple(self, tas_series):
tas = tas_series(np.arange(365), start="1/1/2001")
tas = xr.concat((tas, tas), "dim0")
p1 = percentile_doy(tas, window=5, per=0.5)
assert p1.sel(dayofyear=3, dim0=0).data == 2
assert p1.attrs["units"] == "K"
def test_simple(self, tas_series):
tas = tas_series(np.arange(365), start='1/1/2001')
p1 = percentile_doy(tas, window=5, per=.5)
assert p1.sel(dayofyear=3).data == 2
assert p1.attrs['units'] == 'K'
