refactor timedelta decoding to _numbers_to_timedelta and res-use it w…

…ithin decode_cf_timedelta

xarray/coding/times.py

@@ -458,41 +458,12 @@ def _decode_datetime_with_pandas(
     elif flat_num_dates.dtype.kind in "f":
         flat_num_dates = flat_num_dates.astype(np.float64)
 
-    # keep NaT/nan mask
-    nan = np.isnan(flat_num_dates) | (flat_num_dates == np.iinfo(np.int64).min)
-
-    # in case we need to change the unit, we fix the numbers here
-    # this should be safe, as errors would have been raised above
-    ns_time_unit = _NS_PER_TIME_DELTA[time_unit]
-    ns_ref_date_unit = _NS_PER_TIME_DELTA[ref_date.unit]
-    if ns_time_unit > ns_ref_date_unit:
-        flat_num_dates *= np.int64(ns_time_unit / ns_ref_date_unit)
-        time_unit = ref_date.unit
-
-    # estimate fitting resolution for floating point values
-    # this iterates until all floats are fractionless or time_unit == "ns"
-    if flat_num_dates.dtype.kind == "f" and time_unit != "ns":
-        flat_num_dates, new_time_unit = _check_higher_resolution(
-            flat_num_dates, time_unit
-        )
-        if time_unit != new_time_unit:
-            msg = (
-                f"Can't decode floating point datetime to {time_unit!r} without "
-                f"precision loss, decoding to {new_time_unit!r} instead. "
-                f"To silence this warning use time_unit={new_time_unit!r} in call to "
-                f"decoding function."
-            )
-            emit_user_level_warning(msg, SerializationWarning)
-            time_unit = new_time_unit
-
-    # Cast input ordinals to integers and properly handle NaN/NaT
-    # to prevent casting NaN to int
-    flat_num_dates_int = np.zeros_like(flat_num_dates, dtype=np.int64)
-    flat_num_dates_int[nan] = np.iinfo(np.int64).min
-    flat_num_dates_int[~nan] = flat_num_dates[~nan].astype(np.int64)
+    timedeltas = _numbers_to_timedelta(
+        flat_num_dates, time_unit, ref_date.unit, "datetime"
+    )
 
-    # cast to timedelta64[time_unit] and add to ref_date
-    return ref_date + flat_num_dates_int.astype(f"timedelta64[{time_unit}]")
+    # add timedeltas to ref_date
+    return ref_date + timedeltas
 
 
 def decode_cf_datetime(
@@ -590,21 +561,65 @@ def to_datetime_unboxed(value, **kwargs):
     return result
 
 
+def _numbers_to_timedelta(
+    flat_num: np.ndarray,
+    time_unit: NPDatetimeUnitOptions,
+    ref_unit: PDDatetimeUnitOptions,
+    datatype: str,
+) -> np.ndarray:
+    """Transform numbers to np.timedelta64."""
+    # keep NaT/nan mask
+    nan = np.isnan(flat_num) | (flat_num == np.iinfo(np.int64).min)
+
+    # in case we need to change the unit, we fix the numbers here
+    # this should be safe, as errors would have been raised above
+    ns_time_unit = _NS_PER_TIME_DELTA[time_unit]
+    ns_ref_date_unit = _NS_PER_TIME_DELTA[ref_unit]
+    if ns_time_unit > ns_ref_date_unit:
+        flat_num *= np.int64(ns_time_unit / ns_ref_date_unit)
+        time_unit = ref_unit
+
+    # estimate fitting resolution for floating point values
+    # this iterates until all floats are fractionless or time_unit == "ns"
+    if flat_num.dtype.kind == "f" and time_unit != "ns":
+        flat_num_dates, new_time_unit = _check_higher_resolution(flat_num, time_unit)
+        if time_unit != new_time_unit:
+            msg = (
+                f"Can't decode floating point {datatype} to {time_unit!r} without "
+                f"precision loss, decoding to {new_time_unit!r} instead. "
+                f"To silence this warning use time_unit={new_time_unit!r} in call to "
+                f"decoding function."
+            )
+            emit_user_level_warning(msg, SerializationWarning)
+            time_unit = new_time_unit
+
+    # Cast input ordinals to integers and properly handle NaN/NaT
+    # to prevent casting NaN to int
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore", RuntimeWarning)
+        flat_num = flat_num.astype(np.int64)
+    flat_num[nan] = np.iinfo(np.int64).min
+
+    # cast to wanted type
+    return flat_num.astype(f"timedelta64[{time_unit}]")
+
+
 def decode_cf_timedelta(num_timedeltas, units: str) -> np.ndarray:
     # todo: check, if this works as intended
     """Given an array of numeric timedeltas in netCDF format, convert it into a
     numpy timedelta64 ["s", "ms", "us", "ns"] array.
     """
     num_timedeltas = np.asarray(num_timedeltas)
     unit = _netcdf_to_numpy_timeunit(units)
+
+    timedeltas = _numbers_to_timedelta(num_timedeltas, unit, "s", "timedelta")
+
     as_unit = unit
     if unit not in {"s", "ms", "us", "ns"}:
         # default to ns, when not specified
         as_unit = "ns"
-    result = (
-        pd.to_timedelta(ravel(num_timedeltas), unit=unit).as_unit(as_unit).to_numpy()
-    )
-    return reshape(result, num_timedeltas.shape)
+    result = pd.to_timedelta(ravel(timedeltas)).as_unit(as_unit).to_numpy()
+    return reshape(result, timedeltas.shape)
 
 
 def _unit_timedelta_cftime(units: str) -> timedelta: