Make edgecolors and facecolors the same when using stepfilled histogram.

Closes matplotlib#6493

lib/matplotlib/axes/_axes.py

@@ -6281,24 +6281,17 @@ def _normalize_input(inp, ename='input'):
                     xvals.append(x.copy())
                     yvals.append(y.copy())
 
-            if fill:
-                # add patches in reverse order so that when stacking,
-                # items lower in the stack are plottted on top of
-                # items higher in the stack
-                for x, y, c in reversed(list(zip(xvals, yvals, color))):
-                    patches.append(self.fill(
-                        x, y,
-                        closed=True,
-                        facecolor=c,
-                        margins=margins))
-            else:
-                for x, y, c in reversed(list(zip(xvals, yvals, color))):
-                    split = 2 * len(bins)
-                    patches.append(self.fill(
-                        x[:split], y[:split],
-                        closed=False, edgecolor=c,
-                        fill=False,
-                        margins=margins))
+            # add patches in reverse order so that when stacking,
+            # items lower in the stack are plottted on top of
+            # items higher in the stack
+            split = 2 * len(bins)
+            for x, y, c in reversed(list(zip(xvals, yvals, color))):
+                patches.append(self.fill(
+                    x[:split], y[:split],
+                    closed=False,
+                    edgecolor=c,
+                    facecolor=c,
+                    margins=margins))
 
             # we return patches, so put it back in the expected order
             patches.reverse()

lib/matplotlib/tests/test_axes.py

@@ -1151,6 +1151,16 @@ def test_hist_steplog():
     plt.hist(data_big, 100, histtype='stepfilled', log=True, orientation='horizontal')
 
 
+@image_comparison(baseline_images=['hist_step_filled'], extensions=['png'])
+def test_hist_step_empty():
+    np.random.seed(0)    
+    x = np.random.randn(1000, 3)
+    fig, ax = plt.subplots()
+    ax.hist(x, n_bins,  histtype='step', fill=True, stacked=True)
+    patches= ax.patches
+    all([p.get_facecolor() == p.get_edgecolor() for p in patches])
+
+
 @image_comparison(baseline_images=['hist_step_log_bottom'],
                   remove_text=True, extensions=['png'])
 def test_hist_step_log_bottom():