matplotlib
diff --git a/‎lib/matplotlib/backends/backend_pdf.py‎
Lines changed: 4 additions & 0 deletions b/‎lib/matplotlib/backends/backend_pdf.py‎
Lines changed: 4 additions & 0 deletions
diff --git a/‎lib/matplotlib/image.py‎
Lines changed: 14 additions & 4 deletions b/‎lib/matplotlib/image.py‎
Lines changed: 14 additions & 4 deletions
diff --git a/‎lib/matplotlib/tests/baseline_images/test_image/image_alpha.pdf‎
4.48 KB b/‎lib/matplotlib/tests/baseline_images/test_image/image_alpha.pdf‎
4.48 KB
diff --git a/‎lib/matplotlib/tests/baseline_images/test_image/image_alpha.png‎
4.92 KB b/‎lib/matplotlib/tests/baseline_images/test_image/image_alpha.png‎
4.92 KB
@@ -1602,6 +1602,10 @@ def draw_image(self, gc, x, y, im, transform=None):
         if w == 0 or h == 0:
             return
 
+        if transform is None:
+            # If there's no transform, alpha has already been applied
+            gc.set_alpha(1.0)
+
         self.check_gc(gc)
 
         w = 72.0 * w / self.image_dpi
 
@@ -294,6 +294,8 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
                     output[...] = -100.0
                 else:
                     output = np.zeros((out_height, out_width), dtype=A.dtype)
+
+                alpha = 1.0
             elif len(A.shape) == 3:
                 # Always convert to RGBA, even if only RGB input
                 if A.shape[2] == 3:
@@ -302,19 +304,27 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
                     raise ValueError("Invalid dimensions, got %s" % (A.shape,))
 
                 output = np.zeros((out_height, out_width, 4), dtype=A.dtype)
+
+                alpha = self.get_alpha()
+                if alpha is None:
+                    alpha = 1.0
             else:
                 raise ValueError("Invalid dimensions, got %s" % (A.shape,))
 
-            alpha = self.get_alpha()
-            if alpha is None:
-                alpha = 1.0
-
             _image.resample(
                 A, output, t, _interpd_[self.get_interpolation()],
                 self.get_resample(), alpha,
                 self.get_filternorm() or 0.0, self.get_filterrad() or 0.0)
 
             output = self.to_rgba(output, bytes=True, norm=False)
+
+            # Apply alpha *after* if the input was greyscale
+            if len(A.shape) == 2:
+                alpha = self.get_alpha()
+                if alpha is not None and alpha != 1.0:
+                    alpha_channel = output[:, :, 3]
+                    alpha_channel[:] = np.asarray(
+                        np.asarray(alpha_channel, np.float) * alpha, np.uint8)
         else:
             if self._imcache is None:
                 self._imcache = self.to_rgba(A, bytes=True, norm=(A.ndim == 2))