Only support multiple *_n reductions if they have the same n value

datashader/reductions.py

@@ -1672,6 +1672,17 @@ def validate(self, input_dshape):
         for v in self.values:
             v.validate(input_dshape)
 
+        # Check that any included FloatingNReductions have the same n values.
+        n_values = []
+        for v in self.values:
+            if isinstance(v, where):
+                v = v.selector
+            if isinstance(v, FloatingNReduction):
+                n_values.append(v.n)
+        if len(np.unique(n_values)) > 1:
+            raise ValueError(
+                "Using multiple FloatingNReductions with different n values is not supported")
+
     @property
     def inputs(self):
         return tuple(unique(concat(v.inputs for v in self.values)))

datashader/tests/test_pandas.py

@@ -414,6 +414,16 @@ def test_summary_where_n(df):
     assert_eq_ndarray(agg['max_n'].data, sol_max_n_reverse)
 
 
+@pytest.mark.parametrize('df', dfs_pd)
+def test_summary_different_n(df):
+    msg = 'Using multiple FloatingNReductions with different n values is not supported'
+    with pytest.raises(ValueError, match=msg):
+        c.points(df, 'x', 'y', ds.summary(
+            min_n=ds.where(ds.min_n('plusminus', 2)),
+            max_n=ds.where(ds.max_n('plusminus', 3)),
+        ))
+
+
 @pytest.mark.parametrize('df', dfs)
 def test_mean(df):
     out = xr.DataArray(values(df.i32).reshape((2, 2, 5)).mean(axis=2, dtype='f8').T,