removed select_inds_for_avail_vars + test for PR

tests/test_indicators.py

@@ -150,35 +150,3 @@ def test_as_jul(self, restrict_years):
             assert len(out.time) == 4
             assert out.time[0].dt.strftime("%Y-%m-%d").item() == "2000-07-01"
             assert out.time[-1].dt.strftime("%Y-%m-%d").item() == "2003-07-01"
-
-    def test_select_inds_for_avail_vars(self):
-        # Test that select_inds_for_avail_vars filters a list of indicators to only those that can be computed with the
-        # variables available in the input dataset.
-        ds = xs.testing.datablock_3d(
-            np.ones((365, 3, 3)),
-            variable="tas",
-            x="lon",
-            x_start=-75,
-            y="lat",
-            y_start=45,
-            x_step=1,
-            y_step=1,
-            start="2001-01-01",
-            freq="D",
-            units="K",
-            as_dataset=True,
-        )
-        indicators = [
-            xclim.core.indicator.Indicator.from_dict(
-                data={"base": "tg_min", "parameters": {"freq": "QS-DEC"}},
-                identifier="tg_min_qs",
-                module="tests"),
-            xclim.core.indicator.Indicator.from_dict(
-                data={"base": "days_over_precip_thresh", "parameters": {"freq": "MS"}},
-                identifier="precip_average_ms",
-                module="tests")
-        ]
-        inds = xs.indicators.select_inds_for_avail_vars(ds=ds, indicators=indicators)
-        assert len(inds) == 1  # the precip-based indicator must be skipped
-        assert inds[0][0] == "tg_min_qs"
-        assert inds[0][1] == indicators[0]

xscen/indicators.py

@@ -19,7 +19,6 @@
 
 logger = logging.getLogger(__name__)
 
-
 __all__ = ["compute_indicators", "load_xclim_module"]
 
 
@@ -231,46 +230,6 @@ def _infer_freq_from_meta(ind):
     return out_dict
 
 
-def select_inds_for_avail_vars(
-    ds: xr.Dataset,
-    indicators: Union[
-        str, Path, Sequence[Indicator], Sequence[tuple[str, Indicator]], ModuleType
-    ],
-) -> Sequence[Indicator]:
-    """Filter the indicators from a YAML file for which the necessary variables are available.
-
-    Parameters
-    ----------
-    ds : xr.Dataset
-        Dataset to use for the indicators.
-    indicators : Union[str, Path, Sequence[Indicator], Sequence[Tuple[str, Indicator]]]
-        Path to a YAML file that instructs on how to calculate missing variables.
-        Can also be only the "stem", if translations and custom indices are implemented.
-        Can be the indicator module directly, or a sequence of indicators or a sequence of
-        tuples (indicator name, indicator) as returned by `iter_indicators()`.
-
-    Returns
-    -------
-    Sequence[Indicator]
-        A sequence of tuples of (indicator name, indicator).
-
-    See Also
-    --------
-    xclim.indicators, xclim.core.indicator.build_indicator_module_from_yaml
-    """
-    if isinstance(indicators, (str, Path)):
-        logger.debug("Loading indicator module.")
-        indicators = load_xclim_module(indicators, reload=True)
-
-    if hasattr(indicators, "iter_indicators"):
-        indicators = [(name, ind) for name, ind in indicators.iter_indicators()]
-
-    available_vars = {var for var in ds.data_vars if var in xc.core.utils.VARIABLES.keys()}
-    available_ind = [(name, ind) for var in available_vars
-                     for name, ind in indicators if var in ind.parameters.keys()]
-    return available_ind
-
-
 def registry_from_module(
     module, registry=None, variable_column="variable"
 ) -> DerivedVariableRegistry: