Support xclim 0.53.1

CHANGELOG.rst

@@ -15,10 +15,16 @@ New features and enhancements
 Breaking changes
 ^^^^^^^^^^^^^^^^
 * ``xs.get_warming_level`` has been renamed to ``xs.get_period_from_warming_level``. Its argument `return_horizon` was reversed and renamed `return_central_year` (:pull:`474`).
+* Removed support for the deprecated `xclim` function `change_significance` in `ensemble_stats`. (:pull:`482`).
 
 Bug fixes
 ^^^^^^^^^
 * ``xs.io.save_to_table`` now correctly handles the case where the input is a `DataArray` or a `Dataset` with a single variable. (:pull:`473`).
+* Fixed a bug in ``xs.utils.change_units`` where the original dataset was modified. (:pull:`482`).
+
+Internal changes
+^^^^^^^^^^^^^^^^
+* Bumped the version of `xclim` to 0.53.1. (:pull:`482`).
 
 v0.10.0 (2024-09-30)
 --------------------

environment-dev.yml

@@ -30,7 +30,7 @@ dependencies:
   - sparse
   - toolz
   - xarray >=2023.11.0, !=2024.6.0
-  - xclim >=0.52.2, <0.53
+  - xclim >=0.53.1, <0.54
   - xesmf >=0.7
   - zarr >=2.13
   # Opt

environment.yml

@@ -30,7 +30,7 @@ dependencies:
   - sparse
   - toolz
   - xarray >=2023.11.0, !=2024.6.0
-  - xclim >=0.52.2, <0.53
+  - xclim >=0.53.1, <0.54
   - xesmf >=0.7
   - zarr >=2.13
   # To install from source

pyproject.toml

@@ -65,7 +65,7 @@ dependencies = [
   "sparse",
   "toolz",
   "xarray >=2023.11.0, !=2024.6.0",
-  "xclim >=0.52.2, <0.53",
+  "xclim >=0.53.1, <0.54",
   "zarr >=2.13"
 ]
 

src/xscen/ensembles.py

@@ -108,7 +108,7 @@ def ensemble_stats(  # noqa: C901
     # if input files are .zarr, change the engine automatically
     if isinstance(datasets, list) and isinstance(datasets[0], str | os.PathLike):
         path = Path(datasets[0])
-        if path.suffix == ".zarr":
+        if path.suffix in [".zarr", ".zip"]:
             create_kwargs.setdefault("engine", "zarr")
 
     if not isinstance(datasets, xr.Dataset):
@@ -137,6 +137,7 @@ def ensemble_stats(  # noqa: C901
 
         # Workaround for robustness_categories
         real_stat = None
+        categories_kwargs = {}
         if stat == "robustness_categories":
             real_stat = "robustness_categories"
             stat = "robustness_fractions"
@@ -155,20 +156,10 @@ def ensemble_stats(  # noqa: C901
                     f"Weighting is not supported for '{stat}'. The results may be incorrect."
                 )
 
-        # FIXME: change_significance is deprecated and will be removed in xclim 0.49.
         if stat in [
-            "change_significance",
             "robustness_fractions",
             "robustness_categories",
         ]:
-            # FIXME: This can be removed once change_significance is removed.
-            #  It's here because the 'ref' default was removed for change_significance in xclim 0.47.
-            stats_kwargs.setdefault("ref", None)
-            if (stats_kwargs.get("ref") is not None) and len(statistics_to_compute) > 1:
-                raise ValueError(
-                    f"The input requirements for '{stat}' when 'ref' is specified are not compatible with other statistics."
-                )
-
             # These statistics only work on DataArrays
             for v in ens.data_vars:
                 with xr.set_options(keep_attrs=True):
@@ -188,22 +179,6 @@ def ensemble_stats(  # noqa: C901
                     # Call the function
                     tmp = getattr(ensembles, stat)(ens_v, **stats_kwargs)
 
-                    # Manage the multiple outputs of change_significance
-                    # FIXME: change_significance is deprecated and will be removed in xclim 0.49.
-                    if (
-                        stat == "change_significance"
-                        and stats_kwargs.get("p_vals", False) is False
-                    ):
-                        ens_stats[f"{v}_change_frac"], ens_stats[f"{v}_pos_frac"] = tmp
-                    elif stat == "change_significance" and stats_kwargs.get(
-                        "p_vals", False
-                    ):
-                        (
-                            ens_stats[f"{v}_change_frac"],
-                            ens_stats[f"{v}_pos_frac"],
-                            ens_stats[f"{v}_p_vals"],
-                        ) = tmp
-
                     # Robustness categories
                     if real_stat == "robustness_categories":
                         categories = ensembles.robustness_categories(

src/xscen/utils.py

@@ -812,20 +812,26 @@ def change_units(ds: xr.Dataset, variables_and_units: dict) -> xr.Dataset:
                 ).dimensionality.get("[time]")
 
                 if time_in_ds == time_in_out:
-                    ds[v] = units.convert_units_to(ds[v], variables_and_units[v])
+                    ds = ds.assign(
+                        {v: units.convert_units_to(ds[v], variables_and_units[v])}
+                    )
                 elif time_in_ds - time_in_out == 1:
                     # ds is an amount
-                    ds[v] = units.amount2rate(ds[v], out_units=variables_and_units[v])
+                    ds = ds.assign(
+                        {v: units.amount2rate(ds[v], out_units=variables_and_units[v])}
+                    )
                 elif time_in_ds - time_in_out == -1:
                     # ds is a rate
-                    ds[v] = units.rate2amount(ds[v], out_units=variables_and_units[v])
+                    ds = ds.assign(
+                        {v: units.rate2amount(ds[v], out_units=variables_and_units[v])}
+                    )
                 else:
                     raise ValueError(
                         f"No known transformation between {ds[v].units} and {variables_and_units[v]} (temporal dimensionality mismatch)."
                     )
             elif (v in ds) and (ds[v].units != variables_and_units[v]):
                 # update unit name if physical units are equal but not their name (ex. degC vs °C)
-                ds[v] = ds[v].assign_attrs(units=variables_and_units[v])
+                ds = ds.assign({v: ds[v].assign_attrs(units=variables_and_units[v])})
 
     return ds
 

tests/test_ensembles.py

@@ -258,22 +258,6 @@ def test_errors(self):
                 },
             )
 
-        # Error if you try to use a robustness_fractions with a reference dataset, but also specify other statistics
-        with pytest.raises(
-            ValueError, match="The input requirements for 'robustness_fractions'"
-        ):
-            xs.ensemble_stats(
-                ens,
-                statistics={
-                    "robustness_fractions": {
-                        "test": "threshold",
-                        "abs_thresh": 2.5,
-                        "ref": ref,
-                    },
-                    "ensemble_mean_std_max_min": None,
-                },
-            )
-
 
 class TestGenerateWeights:
     @staticmethod