def test_fit(self, tmp_path):
data_path = _create_dummy_precip_data(tmp_path,
start_date='2000-01-01',
end_date='2010-01-01')
czi = ChinaZIndex(data_path / 'chirps_kenya.nc')
variable = 'precip'
czi.fit(variable=variable)
coords = [c for c in czi.index.coords]
vars_ = [v for v in czi.index.variables if v not in coords]
assert "CZI" in vars_, f"Expecting `CZI` variable in `self.index`"
assert np.isclose(czi.index.CZI.median().values, 0, atol=0.1), "" \
"Because values are normally distributed expect CZI median to be" \
"close to 0"
def test_fit_modified(self, tmp_path):
data_path = _create_dummy_precip_data(tmp_path,
start_date="2000-01-01",
end_date="2010-01-01")
czi = ChinaZIndex(data_path / "chirps_kenya.nc")
variable = "precip"
czi.fit(variable=variable, modified=True)
coords = [c for c in czi.index.coords]
vars_ = [v for v in czi.index.variables if v not in coords]
assert "MCZI" in vars_, f"Expecting `CZI` variable in `self.index`"
assert np.isclose(czi.index.MCZI.median().values, 0, atol=0.1), (
""
"Because values are normally distributed expect CZI median to be"
"close to 0")
def test_initialisation(self, tmp_path):
data_path = _create_dummy_precip_data(tmp_path)
czi = ChinaZIndex(data_path / 'chirps_kenya.nc')
assert czi.name == 'china_z_index', f"Expected name"\
f"to be `china_z_index` got: {czi.name}"
with pytest.raises(AttributeError):
# assert error raised because haven't fit
czi.index
# ------------------------------------------------------------- # fit HDSI # ------------------------------------------------------------- from src.analysis.indices.drought_severity_index import DroughtSeverityIndex h = DroughtSeverityIndex(data_path) variable = 'precip' h.fit(variable=variable) # ------------------------------------------------------------- # fit China Z index # ------------------------------------------------------------- from src.analysis.indices.china_z_index import ChinaZIndex c = ChinaZIndex(data_path) variable = 'precip' c.fit(variable=variable) # ------------------------------------------------------------- # fit Decile Index # ------------------------------------------------------------- from src.analysis.indices.decile_index import DecileIndex d= DecileIndex(data_path) variable = 'precip' d.fit(variable=variable) # ------------------------------------------------------------- # fit AnomalyIndex # ------------------------------------------------------------- from src.analysis.indices.anomaly_index import AnomalyIndex