matplotlib
diff --git a/‎lib/matplotlib/image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/image.py
+18-10Lines changed: 18 additions & 10 deletions b/‎lib/matplotlib/image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/image.py
+18-10Lines changed: 18 additions & 10 deletions
diff --git a/‎lib/matplotlib/tests/test_image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_image.py
+11Lines changed: 11 additions & 0 deletions b/‎lib/matplotlib/tests/test_image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_image.py
+11Lines changed: 11 additions & 0 deletions
@@ -553,17 +553,25 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
                 if A.ndim == 2:  # _interpolation_stage == 'rgba'
                     self.norm.autoscale_None(A)
                     A = self.to_rgba(A)
-                alpha = self._get_scalar_alpha()
-                if A.shape[2] == 3:
-                    # No need to resample alpha or make a full array; NumPy will expand
-                    # this out and cast to uint8 if necessary when it's assigned to the
-                    # alpha channel below.
-                    output_alpha = (255 * alpha) if A.dtype == np.uint8 else alpha
+
+                alpha = self.get_alpha()
+                if alpha is not None and np.ndim(alpha) > 0:
+                    output_alpha = _resample(self, alpha, out_shape, t, resample=True)
+                    output = _resample(  # resample rgb channels
+                        # alpha: float, should only be specified when alpha is a scalar
+                        self, _rgb_to_rgba(A[..., :3]), out_shape, t)
                 else:
-                    output_alpha = _resample(  # resample alpha channel
-                        self, A[..., 3], out_shape, t, alpha=alpha)
-                output = _resample(  # resample rgb channels
-                    self, _rgb_to_rgba(A[..., :3]), out_shape, t, alpha=alpha)
+                    alpha = self._get_scalar_alpha()
+                    if A.shape[2] == 3:
+                        # No need to resample alpha or make a full array; NumPy will
+                        # expand this out and cast to uint8 if necessary when it's
+                        # assigned to the alpha channel below.
+                        output_alpha = (255 * alpha) if A.dtype == np.uint8 else alpha
+                    else:
+                        output_alpha = _resample(  # resample alpha channel
+                            self, A[..., 3], out_shape, t, alpha=alpha)
+                    output = _resample(  # resample rgb channels
+                        self, _rgb_to_rgba(A[..., :3]), out_shape, t, alpha=alpha)
                 output[..., 3] = output_alpha  # recombine rgb and alpha
 
             # output is now either a 2D array of normed (int or float) data
 
@@ -1576,3 +1576,14 @@ def test_non_transdata_image_does_not_touch_aspect():
     assert ax.get_aspect() == 1
     ax.imshow(im, transform=ax.transAxes, aspect=2)
     assert ax.get_aspect() == 2
+
+
+@check_figures_equal()
+def test_interpolation_stage_rgba_does_not_respect_array_alpha(fig_test, fig_ref):
+    # GH 28382
+    im = np.arange(9).reshape(3, 3)
+    alpha = np.linspace(0, 1, 9).reshape(3, 3)
+    ax_test = fig_test.subplots()
+    ax_test.imshow(im, alpha=alpha, interpolation='none', interpolation_stage='rgba')
+    ax_ref = fig_ref.subplots()
+    ax_ref.imshow(im, alpha=alpha, interpolation='none')