Merge branch 'main' into namedarray_chunkmanager

doc/whats-new.rst

@@ -47,6 +47,12 @@ Bug fixes
   By `Justus Magin <https://github.com/keewis>`_.
 - Promote floating-point numeric datetimes before decoding (:issue:`9179`, :pull:`9182`).
   By `Justus Magin <https://github.com/keewis>`_.
+- Address regression introduced in :pull:`9002` that prevented objects returned
+  by py:meth:`DataArray.convert_calendar` to be indexed by a time index in
+  certain circumstances (:issue:`9138`, :pull:`9192`). By `Mark Harfouche
+  <https://github.com/hmaarrfk>`_ and `Spencer Clark
+  <https://github.com/spencerkclark>`.
+
 - Fiy static typing of tolerance arguments by allowing `str` type (:issue:`8892`, :pull:`9194`).
   By `Michael Niklas <https://github.com/headtr1ck>`_.
 - Dark themes are now properly detected for ``html[data-theme=dark]``-tags (:pull:`9200`).

xarray/coding/calendar_ops.py

@@ -5,7 +5,10 @@
 
 from xarray.coding.cftime_offsets import date_range_like, get_date_type
 from xarray.coding.cftimeindex import CFTimeIndex
-from xarray.coding.times import _should_cftime_be_used, convert_times
+from xarray.coding.times import (
+    _should_cftime_be_used,
+    convert_times,
+)
 from xarray.core.common import _contains_datetime_like_objects, is_np_datetime_like
 
 try:
@@ -222,6 +225,13 @@ def convert_calendar(
         # Remove NaN that where put on invalid dates in target calendar
         out = out.where(out[dim].notnull(), drop=True)
 
+        if use_cftime:
+            # Reassign times to ensure time index of output is a CFTimeIndex
+            # (previously it was an Index due to the presence of NaN values).
+            # Note this is not needed in the case that the output time index is
+            # a DatetimeIndex, since DatetimeIndexes can handle NaN values.
+            out[dim] = CFTimeIndex(out[dim].data)
+
     if missing is not None:
         time_target = date_range_like(time, calendar=calendar, use_cftime=use_cftime)
         out = out.reindex({dim: time_target}, fill_value=missing)

xarray/coding/times.py

@@ -22,7 +22,7 @@
 )
 from xarray.core import indexing
 from xarray.core.common import contains_cftime_datetimes, is_np_datetime_like
-from xarray.core.duck_array_ops import asarray, ravel
+from xarray.core.duck_array_ops import asarray, ravel, reshape
 from xarray.core.formatting import first_n_items, format_timestamp, last_item
 from xarray.core.pdcompat import nanosecond_precision_timestamp
 from xarray.core.utils import emit_user_level_warning
@@ -352,7 +352,7 @@ def decode_cf_datetime(
     else:
         dates = _decode_datetime_with_pandas(flat_num_dates, units, calendar)
 
-    return dates.reshape(num_dates.shape)
+    return reshape(dates, num_dates.shape)
 
 
 def to_timedelta_unboxed(value, **kwargs):
@@ -374,7 +374,7 @@ def decode_cf_timedelta(num_timedeltas, units: str) -> np.ndarray:
     num_timedeltas = np.asarray(num_timedeltas)
     units = _netcdf_to_numpy_timeunit(units)
     result = to_timedelta_unboxed(ravel(num_timedeltas), unit=units)
-    return result.reshape(num_timedeltas.shape)
+    return reshape(result, num_timedeltas.shape)
 
 
 def _unit_timedelta_cftime(units: str) -> timedelta:
@@ -647,7 +647,7 @@ def encode_datetime(d):
         except TypeError:
             return np.nan if d is None else cftime.date2num(d, units, calendar)
 
-    return np.array([encode_datetime(d) for d in ravel(dates)]).reshape(dates.shape)
+    return reshape(np.array([encode_datetime(d) for d in ravel(dates)]), dates.shape)
 
 
 def cast_to_int_if_safe(num) -> np.ndarray:
@@ -809,7 +809,7 @@ def _eagerly_encode_cf_datetime(
                 floor_division = True
 
         num = _division(time_deltas, time_delta, floor_division)
-        num = num.values.reshape(dates.shape)
+        num = reshape(num.values, dates.shape)
 
     except (OutOfBoundsDatetime, OverflowError, ValueError):
         num = _encode_datetime_with_cftime(dates, units, calendar)
@@ -941,7 +941,7 @@ def _eagerly_encode_cf_timedelta(
             floor_division = True
 
     num = _division(time_deltas, time_delta, floor_division)
-    num = num.values.reshape(timedeltas.shape)
+    num = reshape(num.values, timedeltas.shape)
 
     if dtype is not None:
         num = _cast_to_dtype_if_safe(num, dtype)

xarray/tests/test_calendar_ops.py

@@ -1,9 +1,10 @@
 from __future__ import annotations
 
 import numpy as np
+import pandas as pd
 import pytest
 
-from xarray import DataArray, infer_freq
+from xarray import CFTimeIndex, DataArray, infer_freq
 from xarray.coding.calendar_ops import convert_calendar, interp_calendar
 from xarray.coding.cftime_offsets import date_range
 from xarray.testing import assert_identical
@@ -286,3 +287,25 @@ def test_interp_calendar_errors():
         ValueError, match="Both 'source.x' and 'target' must contain datetime objects."
     ):
         interp_calendar(da1, da2, dim="x")
+
+
+@requires_cftime
+@pytest.mark.parametrize(
+    ("source_calendar", "target_calendar", "expected_index"),
+    [("standard", "noleap", CFTimeIndex), ("all_leap", "standard", pd.DatetimeIndex)],
+)
+def test_convert_calendar_produces_time_index(
+    source_calendar, target_calendar, expected_index
+):
+    # https://github.com/pydata/xarray/issues/9138
+    time = date_range("2000-01-01", "2002-01-01", freq="D", calendar=source_calendar)
+    temperature = np.ones(len(time))
+    da = DataArray(
+        data=temperature,
+        dims=["time"],
+        coords=dict(
+            time=time,
+        ),
+    )
+    converted = da.convert_calendar(target_calendar)
+    assert isinstance(converted.indexes["time"], expected_index)