matplotlib
diff --git a/‎lib/matplotlib/image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/image.py
+8-4Lines changed: 8 additions & 4 deletions b/‎lib/matplotlib/image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/image.py
+8-4Lines changed: 8 additions & 4 deletions
diff --git a/‎lib/matplotlib/tests/test_image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_image.py
+26Lines changed: 26 additions & 0 deletions b/‎lib/matplotlib/tests/test_image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_image.py
+26Lines changed: 26 additions & 0 deletions
@@ -555,11 +555,15 @@ 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)
-                if A.shape[2] == 3:
-                    A = _rgb_to_rgba(A)
                 alpha = self._get_scalar_alpha()
-                output_alpha = _resample(  # resample alpha channel
-                    self, A[..., 3], out_shape, t, alpha=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
 
@@ -268,6 +268,32 @@ def test_image_alpha():
     ax3.imshow(Z, alpha=0.5, interpolation='nearest')
 
 
+@mpl.style.context('mpl20')
+@check_figures_equal(extensions=['png'])
+def test_imshow_alpha(fig_test, fig_ref):
+    np.random.seed(19680801)
+
+    rgbf = np.random.rand(6, 6, 3)
+    rgbu = np.uint8(rgbf * 255)
+    ((ax0, ax1), (ax2, ax3)) = fig_test.subplots(2, 2)
+    ax0.imshow(rgbf, alpha=0.5)
+    ax1.imshow(rgbf, alpha=0.75)
+    ax2.imshow(rgbu, alpha=0.5)
+    ax3.imshow(rgbu, alpha=0.75)
+
+    rgbaf = np.concatenate((rgbf, np.ones((6, 6, 1))), axis=2)
+    rgbau = np.concatenate((rgbu, np.full((6, 6, 1), 255, np.uint8)), axis=2)
+    ((ax0, ax1), (ax2, ax3)) = fig_ref.subplots(2, 2)
+    rgbaf[:, :, 3] = 0.5
+    ax0.imshow(rgbaf)
+    rgbaf[:, :, 3] = 0.75
+    ax1.imshow(rgbaf)
+    rgbau[:, :, 3] = 127
+    ax2.imshow(rgbau)
+    rgbau[:, :, 3] = 191
+    ax3.imshow(rgbau)
+
+
 def test_cursor_data():
     from matplotlib.backend_bases import MouseEvent