Allow for no exceptions to be raised and cleanup

Allow for no exceptions to be raised

Add some helpful comments

Remove doctest skips

Remove TODO note

Cleanup and skip failing doctest

TODO.txt

@@ -15,7 +15,7 @@ Version 0.13
 Version 0.12
 ------------
 * Change `label` to mark background as 0, not -1, which is consistent with
-  SciPy's labelling.  Also remove doctest skip in _ccomp.pyx `label`.
+  SciPy's labelling.
 * Remove `skimage.morphology.label` from `skimage.morphology.__init__`--it now
   lives in `skimage.measure.label`.
 * Remove deprecated `reverse_map` parameter of `skimage.transform.warp`

skimage/_shared/_warnings.py

@@ -85,12 +85,15 @@ def expected_warnings(matching):
     Uses `all_warnings` to ensure all warnings are raised.
     Upon exiting, it checks the recorded warnings for the desired matching
     string.  Raises a warning if the match was not found or an Unexpected
-    warning is found.
+    warning is found.  You can pass an empty regex as on of the matches
+    to allow for no matches: "\A\Z".
 
     """
     with all_warnings() as w:
+        # enter context
         yield w
-        remaining = [m for m in matching]
+        # exited user context, check the recorded warnings
+        remaining = [m for m in matching if not '\A\Z' in m.split('|')]
         for warn in w:
             found = False
             for match in matching:

skimage/_shared/testing.py

@@ -117,7 +117,7 @@ def color_check(plugin, fmt='png'):
     testing.assert_allclose(img2.astype(np.uint8), r2)
 
     img3 = img_as_float(img)
-    with expected_warnings(['precision loss']):
+    with expected_warnings(['precision loss|unclosed file']):
         r3 = roundtrip(img3, plugin, fmt)
     testing.assert_allclose(r3, img)
 
@@ -129,12 +129,12 @@ def color_check(plugin, fmt='png'):
             r4 = roundtrip(img4, plugin, fmt)
         testing.assert_allclose(r4, img4)
     else:
-        with expected_warnings(['sign loss']):
+        with expected_warnings(['sign loss|precision loss|unclosed file']):
             r4 = roundtrip(img4, plugin, fmt)
             testing.assert_allclose(r4, img_as_ubyte(img4))
 
     img5 = img_as_uint(img)
-    with expected_warnings(['precision loss']):
+    with expected_warnings(['precision loss|unclosed file']):
         r5 = roundtrip(img5, plugin, fmt)
     testing.assert_allclose(r5, img)
 
@@ -154,7 +154,7 @@ def mono_check(plugin, fmt='png'):
     testing.assert_allclose(img2.astype(np.uint8), r2)
 
     img3 = img_as_float(img)
-    with expected_warnings(['precision loss']):
+    with expected_warnings(['precision|unclosed file|\A\Z']):
         r3 = roundtrip(img3, plugin, fmt)
     if r3.dtype.kind == 'f':
         testing.assert_allclose(img3, r3)
@@ -165,11 +165,11 @@ def mono_check(plugin, fmt='png'):
         img4 = img_as_int(img)
     if fmt.lower() in (('tif', 'tiff')):
         img4 -= 100
-        with expected_warnings(['sign loss']):
+        with expected_warnings(['sign loss|\A\Z']):
             r4 = roundtrip(img4, plugin, fmt)
         testing.assert_allclose(r4, img4)
     else:
-        with expected_warnings(['sign loss']):
+        with expected_warnings(['precision loss|sign loss|unclosed file']):
             r4 = roundtrip(img4, plugin, fmt)
             testing.assert_allclose(r4, img_as_uint(img4))
 

skimage/_shared/utils.py

@@ -163,4 +163,3 @@ def assert_nD(array, ndim, arg_name='image'):
         ndim = [ndim]
     if not array.ndim in ndim:
         raise ValueError(msg % (arg_name, '-or-'.join([str(n) for n in ndim])))
-

skimage/io/_io.py

@@ -193,7 +193,7 @@ def show():
     >>> import skimage.io as io
 
     >>> for i in range(4):
-    ...     io.imshow(np.random.rand(50, 50))  # doctest: +SKIP
+    ...     io.imshow(np.random.rand(50, 50))
     >>> io.show() # doctest: +SKIP
 
     '''

skimage/measure/_ccomp.pyx

@@ -430,7 +430,7 @@ def label(input, neighbors=None, background=None, return_num=False,
     ...               [1, 1, 5],
     ...               [0, 0, 0]])
 
-    >>> print(label(x, background=0))  # doctest: +SKIP
+    >>> print(label(x, background=0))
     [[ 0 -1 -1]
      [ 0  0  1]
      [-1 -1 -1]]

skimage/measure/fit.py

@@ -619,10 +619,10 @@ def ransac(data, model_class, min_samples, residual_threshold,
 
     Estimate ellipse model using RANSAC:
 
-    >>> ransac_model, inliers = ransac(data, EllipseModel, 5, 3, max_trials=50)  # doctest: +SKIP
-    >>> ransac_model.params  # doctest: +SKIP
+    >>> ransac_model, inliers = ransac(data, EllipseModel, 5, 3, max_trials=50)
+    >>> ransac_model.params
     array([ 20.12762373,  29.73563063,   4.81499637,  10.4743584 ,   0.05217117])
-    >>> inliers  # doctest: +SKIP
+    >>> inliers
     array([False, False, False, False,  True,  True,  True,  True,  True,
             True,  True,  True,  True,  True,  True,  True,  True,  True,
             True,  True,  True,  True,  True,  True,  True,  True,  True,

skimage/morphology/watershed.py

@@ -119,9 +119,9 @@ def watershed(image, markers, connectivity=None, offset=None, mask=None):
     >>> from skimage.feature import peak_local_max
     >>> local_maxi = peak_local_max(distance, labels=image,
     ...                             footprint=np.ones((3, 3)),
-    ...                             indices=False)  # doctest: +SKIP
-    >>> markers = ndimage.label(local_maxi)[0]  # doctest: +SKIP
-    >>> labels = watershed(-distance, markers, mask=image)  # doctest: +SKIP
+    ...                             indices=False)
+    >>> markers = ndimage.label(local_maxi)[0]
+    >>> labels = watershed(-distance, markers, mask=image)
 
     The algorithm works also for 3-D images, and can be used for example to
     separate overlapping spheres.

skimage/transform/hough_transform.py

@@ -49,8 +49,8 @@ def hough_line_peaks(hspace, angles, dists, min_distance=9, min_angle=10,
     >>> rr, cc = line(0, 14, 14, 0)
     >>> img[cc, rr] = 1
     >>> hspace, angles, dists = hough_line(img)
-    >>> hspace, angles, dists = hough_line_peaks(hspace, angles, dists)  # doctest: +SKIP  
-    >>> len(angles)  # doctest: +SKIP
+    >>> hspace, angles, dists = hough_line_peaks(hspace, angles, dists)
+    >>> len(angles)
     2
 
     """

skimage/util/tests/test_dtype.py

@@ -30,12 +30,8 @@ def test_range():
                         (img_as_uint, np.uint16),
                         (img_as_ubyte, np.ubyte)]:
             
-            try:
-                with expected_warnings(['precision loss|sign loss']):
-                    y = f(x)
-            except ValueError as e:
-                if not 'No warning raised' in str(e):
-                    raise
+            with expected_warnings(['precision loss|sign loss|\A\Z']):
+                y = f(x)
 
             omin, omax = dtype_range[dt]
 
@@ -67,12 +63,8 @@ def test_range_extra_dtypes():
         imin, imax = dtype_range_extra[dtype_in]
         x = np.linspace(imin, imax, 10).astype(dtype_in)
         
-        try:
-            with expected_warnings(['precision loss|sign loss']):
-                y = convert(x, dt)
-        except ValueError as e:
-          if not 'No warning raised' in str(e):
-            raise
+        with expected_warnings(['precision loss|sign loss|\A\Z']):
+            y = convert(x, dt)
 
         omin, omax = dtype_range_extra[dt]
         yield (_verify_range,