Add expected_warnings to the tests using threshold_otsu

skimage/filters/tests/test_thresholding.py

@@ -3,6 +3,7 @@ from numpy.testing import assert_equal, assert_almost_equal
 
 import skimage
 from skimage import data
+from skimage._shared._warnings import expected_warnings
 from skimage.filters.thresholding import (threshold_adaptive,
                                           threshold_otsu,
                                           threshold_li,
@@ -158,11 +159,13 @@ def test_otsu_coins_image_as_float():
 
 def test_otsu_lena_image():
     img = skimage.img_as_ubyte(data.lena())
-    assert 140 < threshold_otsu(img) < 142
+    with expected_warnings(['grayscale']):
+        assert 140 < threshold_otsu(img) < 142
 
 def test_otsu_astro_image():
     img = skimage.img_as_ubyte(data.astronaut())
-    assert 109 < threshold_otsu(img) < 111
+    with expected_warnings(['grayscale']):
+        assert 109 < threshold_otsu(img) < 111
 
 def test_li_camera_image():
     camera = skimage.img_as_ubyte(data.camera())

skimage/filters/thresholding.py

@@ -122,11 +122,11 @@ def threshold_otsu(image, nbins=256):
 
     Notes
     -----
-    The input image must be Grayscale.
+    The input image must be grayscale.
     """
     if image.shape[-1] in (3, 4):
         msg = "threshold_otsu is expected to work correctly only for " \
-              "grayscale images; image shape {} looks like an RGB image"
+              "grayscale images; image shape {0} looks like an RGB image"
         warnings.warn(msg.format(image.shape))
 
     hist, bin_centers = histogram(image.ravel(), nbins)