MBCn minimal test

tests/test_sdba/test_adjustment.py

@@ -6,6 +6,7 @@
 import xarray as xr
 from scipy.stats import genpareto, norm, uniform
 
+from xclim.core.calendar import stack_periods
 from xclim.core.options import set_options
 from xclim.core.units import convert_units_to
 from xclim.sdba import adjustment
@@ -14,6 +15,7 @@
  DetrendedQuantileMapping,
  EmpiricalQuantileMapping,
  ExtremeValues,
+ MBCn,
  PrincipalComponents,
  QuantileDeltaMapping,
  Scaling,
@@ -554,6 +556,44 @@ def test_add_dims(self, use_dask, open_dataset):
  assert scen2.sel(location=["Kugluktuk", "Vancouver"]).isnull().all()
 
 
+@pytest.mark.slow
+class TestMBCn:
+ @pytest.mark.parametrize("use_dask", [True, False])
+ @pytest.mark.parametrize("group, window", [["time", 1], ["time.dayofyear", 31]])
+ @pytest.mark.parametrize("period_dim", [None, "period"])
+ def test_simple(self, open_dataset, use_dask, group, window, period_dim):
+ group, window, period_dim, use_dask = "time", 1, None, False
+ with set_options(sdba_encode_cf=use_dask):
+ if use_dask:
+ chunks = {"location": -1}
+ else:
+ chunks = None
+ ref, dsim = (
+ open_dataset(
+ f"sdba/{file}",
+ chunks=chunks,
+ drop_variables=["lat", "lon"],
+ )
+ .isel(location=1, drop=True)
+ .expand_dims(location=["Amos"])
+ for file in ["ahccd_1950-2013.nc", "CanESM2_1950-2100.nc"]
+ )
+ ref, hist = (ds.sel(time=slice("1981", "2010")) for ds in [ref, dsim])
+ sim = stack_periods(dsim).isel(period=slice(1, 2))
+
+ ref, hist, sim = (stack_variables(ds) for ds in [ref, hist, sim])
+
+ MBCN = MBCn.train(
+ ref,
+ hist,
+ base_kws=dict(nquantiles=50, group=Grouper(group, window)),
+ adj_kws=dict(interp="linear"),
+ )
+ p = MBCN.adjust(sim=sim, ref=ref, hist=hist, period_dim=period_dim)
+ # 'does it run' test
+ p.load()
+
+
 class TestPrincipalComponents:
  @pytest.mark.parametrize(
  "group", (Grouper("time.month"), Grouper("time", add_dims=["lon"]))