xclim 0.48 compatibility

environment-dev.yml

@@ -2,7 +2,7 @@ name: xscen-dev
 channels:
   - conda-forge
 dependencies:
-  - python >=3.9
+  - python >=3.9,<3.13
   # Don't forget to sync changes between environment.yml, environment-dev.yml, and setup.py!
   # Also consider updating the list in xs.utils.show_versions if you add a new package.
   # Main packages
@@ -21,15 +21,15 @@ dependencies:
   - netCDF4
   - numcodecs
   - numpy
-  - pandas >=2.0,<2.2
+  - pandas >=2.2
   - parse
   - pyyaml
   - rechunker
   - scipy
   - shapely >=2.0
   - sparse
   - toolz
-  - xarray <2023.11.0  # FIXME: Remove when pandas 2.2 is released and xclim is fixed.
+  - xarray
   - xclim >=0.46.0
   - xesmf >=0.7
   - zarr

environment.yml

@@ -2,7 +2,7 @@ name: xscen
 channels:
   - conda-forge
 dependencies:
-  - python >=3.9
+  - python >=3.9,<3.13
   # Don't forget to sync changes between environment.yml, environment-dev.yml, and setup.py!
   # Also consider updating the list in xs.utils.show_versions if you add a new package.
   # Main packages
@@ -21,15 +21,15 @@ dependencies:
   - netCDF4
   - numcodecs
   - numpy
-  - pandas >=2.0,<2.2
+  - pandas >=2.2
   - parse
   - pyyaml
   - rechunker
   - scipy
   - shapely >=2.0
   - sparse
   - toolz
-  - xarray <2023.11.0  # FIXME: Remove when pandas 2.2 is released and xclim is fixed.
+  - xarray
   - xclim >=0.46.0
   - xesmf >=0.7
   - zarr

pyproject.toml

@@ -29,7 +29,7 @@ classifiers = [
   "Programming Language :: Python :: 3.9",
   "Programming Language :: Python :: 3.10",
   "Programming Language :: Python :: 3.11",
-  # "Programming Language :: Python :: 3.12",
+  "Programming Language :: Python :: 3.12",
   "Programming Language :: Python :: Implementation :: CPython",
   "Topic :: Scientific/Engineering :: Atmospheric Science"
 ]
@@ -52,7 +52,7 @@ dependencies = [
   "netCDF4",
   "numcodecs",
   "numpy",
-  "pandas>=2.0,<2.2",
+  "pandas>=2.2",
   "parse",
   # Used when opening catalogs.
   "pyarrow",
@@ -62,7 +62,7 @@ dependencies = [
   "shapely>=2.0",
   "sparse",
   "toolz",
-  "xarray<2023.11.0", # FIXME: Remove when pandas 2.2 is released and xclim is fixed.
+  "xarray",
   "xclim>=0.46.0",
   "zarr"
 ]

tests/test_catutils.py

@@ -230,7 +230,7 @@ def test_build_path(samplecat):
 
 def test_build_path_ds():
     ds = xr.tutorial.open_dataset("air_temperature")
-    ds = ds.assign(time=xr.cftime_range("0001-01-01", freq="6H", periods=ds.time.size))
+    ds = ds.assign(time=xr.cftime_range("0001-01-01", freq="6h", periods=ds.time.size))
     ds.attrs.update(source="source", institution="institution")
     new_path = cu.build_path(
         ds,
@@ -240,7 +240,7 @@ def test_build_path_ds():
         },
     )
     assert new_path == Path(
-        "source/institution/air_6H/source_institution_air_6hr_0001-0002"
+        "source/institution/air_6h/source_institution_air_6hr_0001-0002"
     )
 
 

tests/test_diagnostics.py

@@ -125,7 +125,7 @@ def test_variables(self):
             xs.diagnostics.health_checks(ds, variables_and_units={"tas": "degC"})
         with pytest.warns(
             UserWarning,
-            match="Data units kelvin are not compatible with requested mm.",
+            match="are not compatible with requested mm.",
         ):
             xs.diagnostics.health_checks(ds, variables_and_units={"tas": "mm"})
 
@@ -162,7 +162,7 @@ def test_cfchecks(self):
             xs.diagnostics.health_checks(ds, cfchecks=bad_cfcheck)
 
     @pytest.mark.parametrize(
-        "freq, gap", [("D", False), ("MS", False), ("3H", False), ("D", True)]
+        "freq, gap", [("D", False), ("MS", False), ("3h", False), ("D", True)]
     )
     def test_freq(self, freq, gap):
         ds = timeseries(

tests/test_indicators.py

@@ -48,12 +48,12 @@ def test_input_types(self, input):
     def test_level(self, to_level):
         if to_level is None:
             ind_dict = xs.compute_indicators(self.ds, indicators=self.yaml_file)
-            assert "indicators" in ind_dict["AS-JAN"].attrs["cat:processing_level"]
+            assert "indicators" in ind_dict["YS-JAN"].attrs["cat:processing_level"]
         else:
             ind_dict = xs.compute_indicators(
                 self.ds, indicators=self.yaml_file, to_level=to_level
             )
-            assert to_level in ind_dict["AS-JAN"].attrs["cat:processing_level"]
+            assert to_level in ind_dict["YS-JAN"].attrs["cat:processing_level"]
 
     # Periods needed to cover both branches of the if/else in compute_indicators, so no need to test separately.
     @pytest.mark.parametrize(
@@ -76,13 +76,13 @@ def test_output(self, periods):
         assert all(
             xrfreq in ind_dict[xrfreq].attrs["cat:xrfreq"] for xrfreq in ind_dict.keys()
         )
-        assert all(v in ind_dict["AS-JAN"] for v in ["tg_min", "growing_degree_days"])
+        assert all(v in ind_dict["YS-JAN"] for v in ["tg_min", "growing_degree_days"])
         if periods is None:
             assert "time" not in ind_dict["fx"].dims
-            assert len(ind_dict["AS-JAN"].time) == 2
+            assert len(ind_dict["YS-JAN"].time) == 2
         else:
             assert len(ind_dict["fx"].time) == len(periods)
-            assert len(ind_dict["AS-JAN"].time) == 8
+            assert len(ind_dict["YS-JAN"].time) == 8
 
     def test_qs_dec(self):
         indicator = xclim.core.indicator.Indicator.from_dict(
@@ -118,7 +118,7 @@ def test_multiple_outputs(self, periods):
         )
 
         assert all(
-            v in ind_dict["AS-JAN"]
+            v in ind_dict["YS-JAN"]
             for v in [
                 "prcpavg",
                 "rain_season_start",
@@ -130,7 +130,7 @@ def test_multiple_outputs(self, periods):
     @pytest.mark.parametrize("restrict_years", [True, False])
     def test_as_jul(self, restrict_years):
         indicator = xclim.core.indicator.Indicator.from_dict(
-            data={"base": "freezing_degree_days", "parameters": {"freq": "AS-JUL"}},
+            data={"base": "freezing_degree_days", "parameters": {"freq": "YS-JUL"}},
             identifier="degree_days_below_0_annual_start_july",
             module="tests",
         )
@@ -140,8 +140,8 @@ def test_as_jul(self, restrict_years):
             restrict_years=restrict_years,
         )
 
-        assert "AS-JUL" in ind_dict["AS-JUL"].attrs["cat:xrfreq"]
-        out = ind_dict["AS-JUL"]
+        assert "YS-JUL" in ind_dict["YS-JUL"].attrs["cat:xrfreq"]
+        out = ind_dict["YS-JUL"]
         if restrict_years:
             assert len(out.time) == 3  # same length as input ds
             assert out.time[0].dt.strftime("%Y-%m-%d").item() == "2001-07-01"

xscen/CVs/frequency_to_timedelta.json

@@ -1,7 +1,7 @@
 {
-  "1hr": "1H",
-  "3hr": "3H",
-  "6hr": "6H",
+  "1hr": "1h",
+  "3hr": "3h",
+  "6hr": "6h",
   "day": "1D",
   "sem": "1W",
   "2sem": "2W",

xscen/CVs/frequency_to_xrfreq.json

@@ -1,7 +1,7 @@
 {
-  "1hr": "H",
-  "3hr": "3H",
-  "6hr": "6H",
+  "1hr": "h",
+  "3hr": "3h",
+  "6hr": "6h",
   "day": "D",
   "sem": "W",
   "2sem": "2W",

xscen/CVs/xrfreq_to_frequency.json

@@ -1,16 +1,19 @@
 {
   "is_regex": true,
+  "h": "1hr",
   "H": "1hr",
+  "3h": "3hr",
   "3H": "3hr",
+  "6h": "6hr",
   "6H": "6hr",
   "D": "day",
   "W": "sem",
   "2W": "2sem",
-  "14d": "2sem",
+  "14D": "2sem",
   "M.*": "mon",
   "Q.*": "qtr",
   "2Q.*": "6mon",
   "A.*": "yr",
-  "YS": "yr",
+  "Y.*": "yr",
   "fx": "fx"
 }

xscen/CVs/xrfreq_to_timedelta.json

@@ -1,7 +1,10 @@
 {
   "is_regex": true,
+  "h": "1h",
   "H": "1H",
+  "3h": "3h",
   "3H": "3H",
+  "6h": "6h",
   "6H": "6H",
   "D": "1D",
   "W": "7D",
@@ -10,6 +13,6 @@
   "Q.*": "90D",
   "2Q.*": "180D",
   "A.*": "365D",
-  "YS": "365D",
+  "Y.*": "365D",
   "fx": "NAN"
 }

xscen/indicators.py

@@ -170,7 +170,7 @@ def _infer_freq_from_meta(ind):
             else:
                 freq = "fx"
             if freq == "YS":
-                freq = "AS-JAN"  # To fix an inconsistency in xclim default 'freq'
+                freq = "YS-JAN"
 
         else:
             # Multiple time periods to concatenate
@@ -197,7 +197,7 @@ def _infer_freq_from_meta(ind):
                     freq = "fx"
 
                 if freq == "YS":
-                    freq = "AS-JAN"  # To fix an inconsistency in xclim default 'freq'
+                    freq = "YS-JAN"
                 # In order to concatenate time periods, the indicator still needs a time dimension
                 if freq == "fx":
                     tmp = tmp.assign_coords({"time": ds_subset.time[0]})