Use correct dtype for RGB image alpha channel

doc/gallery/plot_rasterio_rgb.py

@@ -26,9 +26,6 @@
 # Read the data
 da = xr.open_rasterio('RGB.byte.tif')
 
-# Normalize the image
-da = da / 255
-
 # The data is in UTM projection. We have to set it manually until
 # https://github.com/SciTools/cartopy/issues/813 is implemented
 crs = ccrs.UTM('18N')

xarray/plot/plot.py

@@ -710,8 +710,12 @@ def imshow(x, y, z, ax, **kwargs):
         # missing data transparent.  We therefore add an alpha channel if
         # there isn't one, and set it to transparent where data is masked.
         if z.shape[-1] == 3:
-            z = np.ma.concatenate((z, np.ma.ones(z.shape[:2] + (1,))), 2)
-        z = z.copy()
+            alpha = np.ma.ones(z.shape[:2] + (1,), dtype=z.dtype)
+            if np.issubdtype(z.dtype, np.integer):
+                alpha *= 255
+            z = np.ma.concatenate((z, alpha), axis=2)
+        else:
+            z = z.copy()
         z[np.any(z.mask, axis=-1), -1] = 0
 
     primitive = ax.imshow(z, **defaults)

xarray/tests/test_plot.py

@@ -1146,6 +1146,13 @@ def test_normalize_rgb_one_arg_error(self):
         for kwds in [dict(vmax=-1, vmin=-1.2), dict(vmin=2, vmax=2.1)]:
             da.plot.imshow(**kwds)
 
+    def test_imshow_rgb_values_in_valid_range(self):
+        da = DataArray(np.arange(75, dtype='uint8').reshape((5, 5, 3)))
+        _, ax = plt.subplots()
+        out = da.plot.imshow(ax=ax).get_array()
+        assert out.dtype == np.uint8
+        assert (out[..., :3] == da.values).all()  # Compare without added alpha
+
 
 class TestFacetGrid(PlotTestCase):
     def setUp(self):