diff --git a/python/damask/_colormap.py b/python/damask/_colormap.py
index 8a31ceb3c..8bcb076d4 100644
--- a/python/damask/_colormap.py
+++ b/python/damask/_colormap.py
@@ -8,7 +8,6 @@ if os.name == 'posix' and 'DISPLAY' not in os.environ:
     mpl.use('Agg')
 import matplotlib.pyplot as plt
 from matplotlib import cm
-
 from PIL import Image
 
 import damask
@@ -169,11 +168,11 @@ class Colormap(mpl.colors.ListedColormap):
 
         Parameters
         ----------
-        field : numpy 2D array
+        field : np.array of shape(:,:)
             Data to be shaded.
-        bounds : array, optional
+        bounds : iterable of len(2), optional
             Lower and upper bound of value range.
-        gap : scalar, optional
+        gap : field.dtype, optional
             Transparent value. NaN will always be rendered transparent.
 
         Returns
@@ -184,16 +183,17 @@ class Colormap(mpl.colors.ListedColormap):
         """
         N = len(self.colors)
         mask = np.logical_not(np.isnan(field) if gap is None else \
-               np.logical_or (np.isnan(field), field == gap))                                      # mask gap and NaN (if gap present)
+               np.logical_or (np.isnan(field), field == gap))                                       # mask gap and NaN (if gap present)
 
         if bounds is None:
-            bounds = [field[mask].min(),
-                      field[mask].max()]
-        hi,lo = max(bounds),min(bounds)
+            hi,lo = field[mask].min(),field[mask].max()
+        else:
+            hi,lo = bounds[::-1]
+        
         delta,avg = hi-lo,0.5*(hi+lo)
 
-        if delta * 1e8 <= avg:                                                                     # delta around numerical noise
-            hi,lo = hi+0.5*avg,lo-0.5*avg                                                          # extend range to have actual data centered within
+        if delta * 1e8 <= avg:                                                                      # delta around numerical noise
+            hi,lo = hi+0.5*avg,lo-0.5*avg                                                           # extend range to have actual data centered within
 
         return Image.fromarray((np.dstack((self.colors[(np.clip((field-lo)/(hi-lo),0.0,1.0)*(N-1)).astype(np.uint8),:3],
                                            mask.astype(float)))*255).astype(np.uint8), 'RGBA')
diff --git a/python/tests/reference/Colormap/shade.png b/python/tests/reference/Colormap/shade.png
new file mode 100644
index 000000000..a9e5eacea
Binary files /dev/null and b/python/tests/reference/Colormap/shade.png differ
diff --git a/python/tests/test_Colormap.py b/python/tests/test_Colormap.py
index fbe65e2bd..8eebf63ee 100644
--- a/python/tests/test_Colormap.py
+++ b/python/tests/test_Colormap.py
@@ -4,6 +4,8 @@ import time
 
 import numpy as np
 import pytest
+from PIL import Image
+from PIL import ImageChops
 
 import damask
 from damask import Colormap
@@ -129,6 +131,16 @@ class TestColormap:
         c += c
         assert (np.allclose(c.colors[:len(c.colors)//2],c.colors[len(c.colors)//2:]))
 
+    def test_shade(self,reference_dir,update):
+        data = np.add(*np.indices((10, 11)))
+        img_current = Colormap.from_predefined('orientation').shade(data)
+        if update:
+            img_current.save(reference_dir/'shade.png')
+        else:
+            img_reference = Image.open(reference_dir/'shade.png')
+            diff = ImageChops.difference(img_reference.convert('RGB'),img_current.convert('RGB'))
+            assert not diff.getbbox()
+
     def test_list(self):
         Colormap.list_predefined()