Merge branch 'use-more-caching' into repo-suggestions

CHANGELOG.rst

@@ -46,6 +46,21 @@ Internal changes
 CI changes
 ^^^^^^^^^^
 * The `pip` cache, `tox` environments, and the `xclim-testdata` cache are now saved between workflow runs (using `actions/cache`) to reduce the time spent installing dependencies and downloading testing data. (:pull:`1906`).
+v0.52.2 (2024-09-16)
+--------------------
+Contributors to this version: Pascal Bourgault (:user:`aulemahal`).
+
+Bug fixes
+^^^^^^^^^
+* Fixed ``decimal_year`` import, fixed functions ``rate2amount``, ``amount2rate``, ``time_bnds`` and ``stack_periods``  for `xarray` version 2024.09.0. Removed ``datetime_to_decimal_year`` as the mirrored `xarray` function was replaced by ``ds.time.dt.decimal_year``. (:pull:`1920`).
+
+v0.52.1 (2024-09-11)
+--------------------
+Contributors to this version: Trevor James Smith (:user:`Zeitsperre`).
+
+Bug fixes
+^^^^^^^^^
+* Adjusted the required base version of `pyarrow` to be `v10.0.1` to address an environment resolution error on conda-forge. (:pull:`1918`).
 
 v0.52.0 (2024-08-08)
 --------------------

environment.yml

@@ -52,6 +52,7 @@ dependencies:
   - nbsphinx
   - nbval >=0.11.0
   - nc-time-axis >=1.4.1
+  - netcdf4  # Required for some Jupyter notebooks
   - notebook
   - pandas-stubs >=2.2
   - pooch >=1.8.0

pyproject.toml

@@ -48,7 +48,7 @@ dependencies = [
   "packaging >=24.0",
   "pandas >=2.2",
   "pint >=0.18",
-  "pyarrow >=15.0.0", # Strongly encouraged for pandas v2.2.0+
+  "pyarrow >=10.0.1", # Strongly encouraged for pandas v2.2.0+
   "pyyaml >=6.0.1",
   "scikit-learn >=0.21.3",
   "scipy >=1.9.0",
@@ -136,7 +136,7 @@ target-version = [
 ]
 
 [tool.bumpversion]
-current_version = "0.52.1-dev.5"
+current_version = "0.52.3-dev.0"
 commit = true
 commit_args = "--no-verify"
 tag = false

tests/test_testing_utils.py

@@ -37,9 +37,6 @@ def file_md5_checksum(f_name):
             hash_md5.update(f.read())
         return hash_md5.hexdigest()
 
-    @pytest.mark.skip(
-        "This test has been significantly modified. Will adjust when #1889 is merged."
-    )
     @pytest.mark.requires_internet
     def test_open_testdata(
         self,

xclim/__init__.py

@@ -13,7 +13,7 @@
 
 __author__ = """Travis Logan"""
 __email__ = "[email protected]"
-__version__ = "0.52.1-dev.5"
+__version__ = "0.52.3-dev.0"
 
 
 with _resources.as_file(_resources.files("xclim.data")) as _module_data:

xclim/core/calendar.py

@@ -773,7 +773,7 @@ def time_bnds(  # noqa: C901
         time = time.indexes[time.name]
     elif isinstance(time, (DataArrayResample, DatasetResample)):
         for grouper in time.groupers:
-            if "time" in grouper.dims:
+            if isinstance(grouper.grouper, xr.groupers.TimeResampler):
                 datetime = grouper.unique_coord.data
                 freq = freq or grouper.grouper.freq
                 if datetime.dtype == "O":
@@ -1354,13 +1354,13 @@ def stack_periods(
     for _, strd_slc in da.resample(time=strd_frq).groups.items():
         win_resamp = time2.isel(time=slice(strd_slc.start, None)).resample(time=win_frq)
         # Get slice for first group
-        win_slc = win_resamp._group_indices[0]
+        win_slc = list(win_resamp.groups.values())[0]
         if min_length < window:
             # If we ask for a min_length period instead is it complete ?
             min_resamp = time2.isel(time=slice(strd_slc.start, None)).resample(
                 time=minl_frq
             )
-            min_slc = min_resamp._group_indices[0]
+            min_slc = list(min_resamp.groups.values())[0]
             open_ended = min_slc.stop is None
         else:
             # The end of the group slice is None if no outside-group value was found after the last element
@@ -1545,7 +1545,7 @@ def _reconstruct_time(_time_as_delta, _start):
     periods = []
     for i, (start, length) in enumerate(zip(starts.values, lengths.values)):
         real_time = _reconstruct_time(time_as_delta, start)
-        slices = real_time.resample(time=strd_frq)._group_indices
+        slices = list(real_time.resample(time=strd_frq).groups.values())
         if i == 0:
             slc = slice(slices[0].start, min(slices[mid].stop, length))
         elif i == da.period.size - 1:

xclim/core/units.py

@@ -17,6 +17,7 @@
 
 import cf_xarray.units
 import numpy as np
+import pandas as pd
 import pint
 import xarray as xr
 from boltons.funcutils import wraps
@@ -650,7 +651,10 @@ def _rate_and_amount_converter(
             start = time.indexes[dim][0]
             if not start_anchor:
                 # Anchor is on the end of the period, subtract 1 period.
-                start = start - xr.coding.cftime_offsets.to_offset(freq)
+                if isinstance(start, pd.Timestamp):
+                    start = start - pd.tseries.frequencies.to_offset(freq)
+                else:
+                    start = start - xr.coding.cftime_offsets.to_offset(freq)
                 # In the diff below, assign to upper label!
                 label = "upper"
             # We generate "time" with an extra element, so we do not need to repeat the last element below.

xclim/indices/helpers.py

@@ -16,9 +16,15 @@
 import numba as nb
 import numpy as np
 import xarray as xr
-from xarray.coding.calendar_ops import (
-    _datetime_to_decimal_year as datetime_to_decimal_year,
-)
+
+try:
+    from xarray.coding.calendar_ops import (
+        _datetime_to_decimal_year as datetime_to_decimal_year,
+    )
+except ImportError:
+    XR2409 = True
+else:
+    XR2409 = False
 
 from xclim.core import Quantified
 from xclim.core.calendar import ensure_cftime_array, get_calendar
@@ -70,7 +76,10 @@ def day_angle(time: xr.DataArray):
     the beginning of the year up to that timestep. Also called the "julian day fraction".
     See :py:func:`~xclim.core.calendar.datetime_to_decimal_year`.
     """
-    decimal_year = datetime_to_decimal_year(times=time, calendar=time.dt.calendar)
+    if XR2409:
+        decimal_year = time.dt.decimal_year
+    else:
+        decimal_year = datetime_to_decimal_year(times=time, calendar=time.dt.calendar)
     return ((decimal_year % 1) * 2 * np.pi).assign_attrs(units="rad")