Cleanup

doc/source/references/release_notes.rst

@@ -6,6 +6,12 @@ Release history
 [maint] Made Frequency part of SliceMode union.
 [fix] slice_mode seasonal samplings was giving wrong results for quite a few indices. This has been fixed and the performances should also be improved by the fix.
 However, now seasonal slice_mode does not allow to use xclim missing values mechanisms.
+[fix] user_index ExtremeMode config was not properly parsed when a string was used.
+[fix] user_index Anomaly operator was not properly using the `ref_time_range` to setup a reference period as it should.
+[fix] user_index Sum and Mean operators were broken due to a previous refactoring and a lack of unit tests, it is now fixed and tested.
+[maint] Changed how `rechunker` dependency is pinned to add flexibility. We want a version above '0.3' but not the '0.4'.
+[maint] For the newly generate API, on `custom_index` function, the parameter `user_index` is now mandatory.
+
 
 5.2.0
 -----

icclim/main.py

@@ -107,9 +107,6 @@ def indice(*args, **kwargs):
     return index(*args, **kwargs)
 
 
-# TODO extract the custom index doc in a different doc than icclim.index
-
-
 def index(
     in_files: str | list[str] | Dataset | DataArray,
     index_name: str | None = None,  # optional when computing user_indices
@@ -260,12 +257,6 @@ def index(
         chunk_it=chunk_it,
     )
     if user_index is not None:
-        if (rtr := user_index.get("ref_time_range", None)) is not None:
-            # setup anomaly todo: put that elsewhere
-            rtr = [x.strftime("%Y-%m-%d") for x in rtr]
-            config._cf_variables[0].reference_da = ds[var_name].sel(
-                time=slice(rtr[0], rtr[1])
-            )
         result_ds = _compute_user_index_dataset(config=config, user_index=user_index)
     else:
         result_ds = _compute_ecad_index_dataset(

icclim/models/constants.py

@@ -27,6 +27,13 @@
 MODIFIABLE_THRESHOLD = "MODIFIABLE_THRESHOLD"  # fields: threshold
 MODIFIABLE_QUANTILE_WINDOW = "MODIFIABLE_QUANTILE_WINDOW"  # fields: window_width
 
-
 # Map of months index to their short name, used to get a pandas frequency anchor
 MONTHS_MAP = {1:"JAN",  2:"FEB", 3:"MAR", 4:"APR", 5:"MAY", 6:"JUN", 7:"JUL", 8:"AUG", 9:"SEP", 10:"OCT", 11:"NOV", 12:"DEC" }
+
+# Season defined by their month numbers
+AMJJAS_MONTHS = [*range(4, 9)]
+ONDJFM_MONTHS = [10, 11, 12, 1, 2, 3]
+DJF_MONTHS = [12, 1, 2]
+MAM_MONTHS = [*range(3, 6)]
+JJA_MONTHS = [*range(6, 9)]
+SON_MONTHS = [*range(9, 12)]

icclim/models/frequency.py

@@ -16,19 +16,15 @@
 from xarray.core.dataarray import DataArray
 
 from icclim.icclim_exceptions import InvalidIcclimArgumentError
-from icclim.models.constants import MONTHS_MAP
-
-AMJJAS_MONTHS = [*range(4, 9)]
-ONDJFM_MONTHS = [10, 11, 12, 1, 2, 3]
-DJF_MONTHS = [12, 1, 2]
-MAM_MONTHS = [*range(3, 6)]
-JJA_MONTHS = [*range(6, 9)]
-SON_MONTHS = [*range(9, 12)]
-
-
-def get_season_sampling_freq(month_list: list[int]) -> str:
-    # Must be used with month_filter to properly create a season
-    return f"{len(month_list)}MS"
+from icclim.models.constants import (
+    AMJJAS_MONTHS,
+    DJF_MONTHS,
+    JJA_MONTHS,
+    MAM_MONTHS,
+    MONTHS_MAP,
+    ONDJFM_MONTHS,
+    SON_MONTHS,
+)
 
 
 def get_month_filter(month_list: list[int]) -> Callable:

icclim/models/user_index_config.py

@@ -157,6 +157,10 @@ def __init__(
             )
         self.save_percentile = save_percentile
         self.ref_time_range = ref_time_range
+        if (rtr := ref_time_range) is not None:
+            rtr = [x.strftime("%Y-%m-%d") for x in rtr]
+            for cf_var in cf_vars:
+                cf_var.reference_da = cf_var.study_da.sel(time=slice(rtr[0], rtr[1]))
 
 
 def get_nb_event_conf(

icclim/tests/test_frequency.py

@@ -64,13 +64,6 @@ def test_winter(self):
         assert freq.accepted_values == []
         assert freq.post_processing is not None
 
-    # def test_between_dates(self):
-    #     freq = Frequency.lookup(["dates", ["15-06", "28 aout"] ])
-    #     assert freq == Frequency.CUSTOM
-    #     assert freq.panda_freq == "75D"
-    #     assert freq.accepted_values == []
-    #     assert freq.post_processing is not None
-
 
 class Test_filter_months:
     def test_simple(self):
@@ -113,14 +106,3 @@ def test_winter(self):
             time_bds_res[1].data[1]
             == pd.to_datetime("2043-02") - pd.tseries.offsets.Day()
         )
-
-    # def test_season_date_to_date(self):
-    #     # WHEN
-    #     da_res, time_bds_res = get_seasonal_time_updater(1, 4)(stub_tas())
-    #     # THEN
-    #     np.testing.assert_array_equal(1, da_res)
-    #     assert time_bds_res[0].data[0] == pd.to_datetime("2042-01")
-    #     assert (
-    #         time_bds_res[0].data[1]
-    #         == pd.to_datetime("2042-05") - pd.tseries.offsets.Day()
-    #     )