Allow passing of method keyword to numpy.percentile

lib/iris/analysis/__init__.py

@@ -1296,10 +1296,6 @@ def _calc_percentile(data, percent, fast_percentile_method=False, **kwargs):
     Calculate percentiles along the trailing axis of a 1D or 2D array.
 
     """
-    # Get hold of method keyword to pass it to numpy.percentile, or just remove it
-    # from kwargs so it's ignored for scipy mquantiles.  Note that kwargs always
-    # contains alphap and betap so we can't pass it to numpy.percentile.
-    method = kwargs.pop("method", None)
     if fast_percentile_method:
         if kwargs.pop("error_on_masked", False):
             msg = (
@@ -1313,15 +1309,13 @@ def _calc_percentile(data, percent, fast_percentile_method=False, **kwargs):
                 "ignore",
                 "Warning: 'partition' will ignore the 'mask' of the MaskedArray.",
             )
-            pc_kwargs = dict(axis=-1)
-            if method is not None:
-                pc_kwargs["method"] = method
-
-            result = np.percentile(data, percent, **pc_kwargs)
+            result = np.percentile(data, percent, axis=-1, **kwargs)
 
         result = result.T
     else:
         quantiles = percent / 100.0
+        for key in ["alphap", "betap"]:
+            kwargs.setdefault(key, 1)
         result = scipy.stats.mstats.mquantiles(
             data, quantiles, axis=-1, **kwargs
         )
@@ -1353,9 +1347,9 @@ def _percentile(data, percent, fast_percentile_method=False, **kwargs):
         alternative to the scipy.mstats.mquantiles method. Does not handle
         masked arrays.
 
-    **kwargs
+    **kwargs : dict, optional
         passed to scipy.stats.mstats.mquantiles if fast_percentile_method is
-        False.  Otherwise "method" is extracted and passed to numpy.percentile.
+        False.  Otherwise passed to numpy.percentile.
 
     """
     if not isinstance(percent, Iterable):
@@ -1976,7 +1970,7 @@ def interp_order(length):
 """
 
 
-PERCENTILE = PercentileAggregator(alphap=1, betap=1)
+PERCENTILE = PercentileAggregator()
 """
 A :class:`~iris.analysis.PercentileAggregator` instance that calculates the
 percentile over a :class:`~iris.cube.Cube`, as computed by
@@ -1985,26 +1979,25 @@ def interp_order(length):
 
 **Required** kwargs associated with the use of this aggregator:
 
-* percent (float or sequence of floats):
+percent : float or sequence of floats
     Percentile rank/s at which to extract value/s.
 
 Additional kwargs associated with the use of this aggregator:
 
-* alphap (float):
+alphap : float
     Plotting positions parameter, see :func:`scipy.stats.mstats.mquantiles`.
     Defaults to 1.
-* betap (float):
+betap : float
     Plotting positions parameter, see :func:`scipy.stats.mstats.mquantiles`.
     Defaults to 1.
-* fast_percentile_method (boolean):
+fast_percentile_method : bool
     When set to True, uses :func:`numpy.percentile` method as a faster
-    alternative to the :func:`scipy.stats.mstats.mquantiles` method.  alphap and
-    betap are ignored. An exception is raised if the data are masked and the
-    missing data tolerance is not 0.
-    Defaults to False.
-* method (str, optional):
-    Passed to :func:`numpy.percentile`, if fast_percentile_method is True.
-    Otherwise ignored.
+    alternative to the :func:`scipy.stats.mstats.mquantiles` method.  An
+    exception is raised if the data are masked and the missing data tolerance
+    is not 0.  Defaults to False.
+
+**kwargs : dict, optional
+    Passed to :func:`scipy.stats.mstats.mquantiles` or :func:`numpy.percentile`.
 
 **For example**:
 

lib/iris/tests/unit/analysis/test_PERCENTILE.py

@@ -196,6 +196,13 @@ def test_missing_mandatory_kwarg(self):
         with self.assertRaisesRegex(ValueError, emsg):
             PERCENTILE.aggregate("dummy", axis=0)
 
+    def test_wrong_kwarg(self):
+        # Test we get an error out of scipy if we pass the numpy keyword.
+        data = range(5)
+        emsg = "unexpected keyword argument"
+        with self.assertRaisesRegex(TypeError, emsg):
+            PERCENTILE.aggregate(data, percent=50, axis=0, method="nearest")
+
 
 class Test_fast_aggregate(tests.IrisTest, AggregateMixin):
     """Tests for fast percentile method on real data."""