Fix multiple resolution when hue variable has no name

Fixes #2452

(cherry picked from commit 008f7e0e030681f8047c7d628e6bb3fc3d23e6ff)

doc/releases/v0.12.0.txt

@@ -18,13 +18,15 @@ v0.12.0 (Unreleased)
 
 - |Enhancement| In :func:`histplot`, added `stat="percent"` as an option for normalization such that bar heights sum to 100 (:pr:`2461`).
 
+- |Enhancement| |Fix| Improved integration with the matplotlib color cycle in most axes-level functions (:pr:`2449`).
+
 - |Fix| In :func:`lineplot, allowed the `dashes` keyword to set the style of a line without mapping a `style` variable (:pr:`2449`).
 
 - |Fix| In :func:`rugplot`, fixed a bug that prevented the use of datetime data (:pr:`2458`).
 
 - |Fix| In :func:`histplot` and :func:`kdeplot`, fixed a bug where the `alpha` parameter was ignored when `fill=False` (:pr:`2460`).
 
-- |Fix| |Enhancement| Improved integration with the matplotlib color cycle in most axes-level functions (:pr:`2449`).
+- |Fix| In :func:`histplot` and :func:`kdeplot`, fixed a bug where the `multiple` was ignored when `hue` was provided a vector without a name (:pr:`2462`).
 
 - Made `scipy` an optional dependency and added `pip install seaborn[all]` as a method for ensuring the availability of compatible `scipy` and `statsmodels` libraries at install time. This has a few minor implications for existing code, which are explained in the Github pull request (:pr:`2398`).
 

seaborn/distributions.py

@@ -132,6 +132,15 @@ def has_xy_data(self):
         # TODO see above points about where this should go
         return bool({"x", "y"} & set(self.variables))
 
+    def _redundant_with_facets(self, var):
+        """Return True if var is assigned and is redundant with faceting variables."""
+        # TODO likely generally useful but only used in this module for now.
+        return any(
+            self.plot_data[var].equals(self.plot_data[facet_var])
+            for facet_var in ["row", "col"]
+            if var in self.plot_data and facet_var in self.plot_data
+        )
+
     def _add_legend(
         self,
         ax_obj, artist, fill, element, multiple, alpha, artist_kws, legend_kws,
@@ -413,11 +422,8 @@ def plot_univariate_histogram(
         else:
             common_norm = False
 
-        # Turn multiple off if no hue or if hue exists but is redundant with faceting
-        facet_vars = [self.variables.get(var, None) for var in ["row", "col"]]
-        if "hue" not in self.variables:
-            multiple = None
-        elif self.variables["hue"] in facet_vars:
+        # Let default alpha look like single histogram if hue is redundant
+        if self._redundant_with_facets("hue"):
             multiple = None
 
         # Estimate the smoothed kernel densities, for use later
@@ -886,6 +892,13 @@ def plot_univariate_density(
         # Input checking
         _check_argument("multiple", ["layer", "stack", "fill"], multiple)
 
+        # Let default alpha look like single density with redundant hue
+        if self._redundant_with_facets("hue"):
+            # Note unlike histplot, we set this to layer rather than None because
+            # default alpha for layer matches default alpha for a single density.
+            # But that's kind of messy and we should rethink.
+            multiple = "layer"
+
         # Always share the evaluation grid when stacking
         subsets = bool(set(self.variables) - {"x", "y"})
         if subsets and multiple in ("stack", "fill"):
@@ -916,9 +929,8 @@ def plot_univariate_density(
         else:
             sticky_support = []
 
-        # XXX unfilled kdeplot is ignoring
         if fill:
-            default_alpha = .25 if multiple == "layer" else .75
+            default_alpha = .25 if multiple in "layer" else .75
         else:
             default_alpha = 1
         alpha = plot_kws.pop("alpha", default_alpha)  # TODO make parameter?

seaborn/tests/test_distributions.py

@@ -1217,6 +1217,17 @@ def test_hue_dodge(self, long_df):
         assert_array_almost_equal(layer_xs[1], dodge_xs[1])
         assert_array_almost_equal(layer_xs[0], dodge_xs[0] - bw / 2)
 
+    def test_hue_as_numpy_dodged(self, long_df):
+        # https://github.com/mwaskom/seaborn/issues/2452
+
+        ax = histplot(
+            long_df,
+            x="y", hue=long_df["a"].to_numpy(),
+            multiple="dodge", bins=1,
+        )
+        # Note hue order reversal
+        assert ax.patches[1].get_x() < ax.patches[0].get_x()
+
     def test_multiple_input_check(self, flat_series):
 
         with pytest.raises(ValueError, match="`multiple` must be"):