Option to output datasets

CHANGES.rst

@@ -19,6 +19,7 @@ New features and enhancements
 * Validate YAML indicators description before trying to build module. (:issue:`1523`, :issue:`1595`, :pull:`1560`, :pull:`1596`, :pull:`1600`).
 * Support ``indexer`` keyword in YAML indicator description. (:issue:`1522`, :pull:`1561`).
 * New ``xclim.core.calendar.stack_periods`` and ``unstack_periods`` for performing ``rolling(time=...).construct(..., stride=...)`` but with non-uniform temporal periods like years or months. They replace ``xclim.sdba.processing.construct_moving_yearly_window`` and ``unpack_moving_yearly_window`` which are deprecated and will be removed in a future release.
+* New ``as_dataset`` options for ``xclim.set_options``. When True, indicators will output Datasets instead of DataArrays. (:issue:`1257`, :pull:`1625`).
 
 Breaking changes
 ^^^^^^^^^^^^^^^^

docs/notebooks/usage.ipynb

@@ -233,7 +233,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Finally, `xclim` also allows us to call indicators using datasets and variable names."
+    "`xclim` also allows us to call indicators using datasets and variable names."
    ]
   },
   {
@@ -255,6 +255,26 @@
     "gdd"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finally, we can also get datasets as an output with the `as_dataset` option."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with xclim.set_options(as_dataset=True, cf_compliance=\"log\"):\n",
+    "    gdd_ds = xclim.atmos.growing_degree_days(\n",
+    "        tas=daily_ds.air, thresh=\"10 degC\", freq=\"YS\", date_bounds=(\"04-01\", \"09-30\")\n",
+    "    )\n",
+    "gdd_ds"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -367,9 +387,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.10"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

tests/test_indicators.py

@@ -198,6 +198,28 @@ def test_keep_attrs(tasmin_series, tasmax_series, xcopt, xropt, exp):
     assert "bing" not in tg.attrs
 
 
+def test_as_dataset(tasmax_series, tasmin_series):
+    tx = tasmax_series(np.arange(360.0))
+    tn = tasmin_series(np.arange(360.0))
+    tx.attrs.update(something="blabla", bing="bang", foo="bar")
+    tn.attrs.update(something="blabla", bing="bong")
+    dsin = xr.Dataset({"tasmax": tx, "tasmin": tn}, attrs={"fou": "barre"})
+    with xclim.set_options(keep_attrs=True, as_dataset=True):
+        dsout = multiOptVar(ds=dsin)
+    assert isinstance(dsout, xr.Dataset)
+    assert dsout.attrs["fou"] == "barre"
+    assert dsout.multiopt.attrs.get("something") == "blabla"
+
+
+def test_as_dataset_multi(tas_series):
+    tg = tas_series(np.arange(360.0))
+    with xclim.set_options(as_dataset=True):
+        dsout = multiTemp(tas=tg, freq="YS")
+    assert isinstance(dsout, xr.Dataset)
+    assert "tmin" in dsout.data_vars
+    assert "tmax" in dsout.data_vars
+
+
 def test_opt_vars(tasmin_series, tasmax_series):
     tn = tasmin_series(np.zeros(365))
     tx = tasmax_series(np.zeros(365))

xclim/core/indicator.py

@@ -144,6 +144,7 @@
     read_locale_file,
 )
 from .options import (
+    AS_DATASET,
     CHECK_MISSING,
     KEEP_ATTRS,
     METADATA_LOCALES,
@@ -810,7 +811,7 @@ def __call__(self, *args, **kwds):
         if self._version_deprecated:
             self._show_deprecation_warning()  # noqa
 
-        das, params = self._parse_variables_from_call(args, kwds)
+        das, params, dsattrs = self._parse_variables_from_call(args, kwds)
 
         if OPTIONS[KEEP_ATTRS] is True or (
             OPTIONS[KEEP_ATTRS] == "xarray"
@@ -882,6 +883,20 @@ def __call__(self, *args, **kwds):
             out.attrs.update(attrs)
             out.name = var_name
 
+        if OPTIONS[AS_DATASET]:
+            out = Dataset({o.name: o for o in outs})
+            if OPTIONS[KEEP_ATTRS] is True or (
+                OPTIONS[KEEP_ATTRS] == "xarray"
+                and xarray.core.options._get_keep_attrs(False)
+            ):
+                out.attrs.update(dsattrs)
+            out.attrs["history"] = update_history(
+                self._history_string(das, params),
+                out,
+                new_name=self.identifier,
+            )
+            return out
+
         # Return a single DataArray in case of single output, otherwise a tuple
         if self.n_outs == 1:
             return outs[0]
@@ -913,7 +928,9 @@ def _parse_variables_from_call(self, args, kwds) -> tuple[OrderedDict, dict]:
             else:
                 params[name] = param.value
 
-        return das, params
+        ds = ba.arguments.get("ds")
+        dsattrs = ds.attrs if ds is not None else {}
+        return das, params, dsattrs
 
     def _assign_named_args(self, ba):
         """Assign inputs passed as strings from ds."""
@@ -1066,28 +1083,24 @@ def _update_attrs(
             if "cell_methods" in out:
                 attrs["cell_methods"] += " " + out.pop("cell_methods")
 
-        # Use of OrderedDict to ensure inputs (das) get listed before parameters (args).
-        # In the history attr, call signature will be all keywords and might be in a
-        # different order than the real function (but order doesn't really matter with keywords).
-        kwargs = OrderedDict(**das)
-        for k, v in args.items():
-            if self._all_parameters[k].injected:
-                continue
-            if self._all_parameters[k].kind == InputKind.KWARGS:
-                kwargs.update(**v)
-            elif self._all_parameters[k].kind != InputKind.DATASET:
-                kwargs[k] = v
-
         attrs["history"] = update_history(
-            self._history_string(**kwargs),
+            self._history_string(das, args),
             new_name=out.get("var_name"),
             **das,
         )
 
         attrs.update(out)
         return attrs
 
-    def _history_string(self, **kwargs):
+    def _history_string(self, das, params):
+        kwargs = dict(**das)
+        for k, v in params.items():
+            if self._all_parameters[k].injected:
+                continue
+            if self._all_parameters[k].kind == InputKind.KWARGS:
+                kwargs.update(**v)
+            elif self._all_parameters[k].kind != InputKind.DATASET:
+                kwargs[k] = v
         return gen_call_string(self._registry_id, **kwargs)
 
     @staticmethod
@@ -1397,7 +1410,7 @@ def __init__(self, **kwds):
 
         super().__init__(**kwds)
 
-    def _history_string(self, **kwargs):
+    def _history_string(self, das, params):
         if self.missing == "from_context":
             missing = OPTIONS[CHECK_MISSING]
         else:
@@ -1409,7 +1422,7 @@ def _history_string(self, **kwargs):
             if mopts:
                 opt_str += f", missing_options={mopts}"
 
-        return super()._history_string(**kwargs) + opt_str
+        return super()._history_string(das, params) + opt_str
 
     def _get_missing_freq(self, params):
         """Return the resampling frequency to be used in the missing values check."""

xclim/core/options.py

@@ -24,6 +24,7 @@
 SDBA_EXTRA_OUTPUT = "sdba_extra_output"
 SDBA_ENCODE_CF = "sdba_encode_cf"
 KEEP_ATTRS = "keep_attrs"
+AS_DATASET = "as_dataset"
 
 MISSING_METHODS: dict[str, Callable] = {}
 
@@ -37,6 +38,7 @@
     SDBA_EXTRA_OUTPUT: False,
     SDBA_ENCODE_CF: False,
     KEEP_ATTRS: "xarray",
+    AS_DATASET: False,
 }
 
 _LOUDNESS_OPTIONS = frozenset(["log", "warn", "raise"])
@@ -68,6 +70,7 @@ def _valid_missing_options(mopts):
     SDBA_EXTRA_OUTPUT: lambda opt: isinstance(opt, bool),
     SDBA_ENCODE_CF: lambda opt: isinstance(opt, bool),
     KEEP_ATTRS: _KEEP_ATTRS_OPTIONS.__contains__,
+    AS_DATASET: lambda opt: isinstance(opt, bool),
 }
 
 
@@ -176,8 +179,12 @@ class set_options:
     keep_attrs : bool or str
         Controls attributes handling in indicators. If True, attributes from all inputs are merged
         using the `drop_conflicts` strategy and then updated with xclim-provided attributes.
+        If ``as_dataset`` is also True and a dataset was passed to the ``ds`` argument of the Indicator,
+        the dataset's attributes are copied to the indicator's output.
         If False, attributes from the inputs are ignored. If "xarray", xclim will use xarray's `keep_attrs` option.
         Note that xarray's "default" is equivalent to False. Default: ``"xarray"``.
+    as_dataset : bool
+        If True, indicators output datasets. If False, they output DataArrays. Default :``False``.
 
     Examples
     --------