Fix handling of multiple warnings and update tests

Fix handling of multiple warnings

Update all test __init__ files

Update segmentation pkg

Update the color pkg

Update the exposure pkg

Update the filters pkg

Update the io pkg

Update the measure pkg

Update morphology package

Restructure test setup function

Add expected_warnings to __all__

Update restoration pkg.

Remove explicit filter check since it is done elsewhere

Fix the image test helpers

Update the transform pkg

Fix util pkg

Update viewer pkg

skimage/_shared/_warnings.py

@@ -1,4 +1,4 @@
-__all__ = ['all_warnings']
+__all__ = ['all_warnings', 'expected_warnings']
 
 from contextlib import contextmanager
 import sys
@@ -90,14 +90,16 @@ def expected_warnings(matching):
     """
     with all_warnings() as w:
         yield w
-        remaining = matching
+        remaining = [m for m in matching]
         for warn in w:
             found = False
             for match in matching:
                 if re.search(match, str(warn.message)) is not None:
                     found = True
-                    remaining.remove(match)
+                    if match in remaining:
+                        remaining.remove(match)
             if not found:
                 raise ValueError('Unexpected warning: %s' % str(warn.message))
         if len(remaining) > 0:
-            raise ValueError('No warning raised matching: "%s"' % remaining[0])
+            msg = 'No warning raised matching:\n%s' % '\n'.join(remaining)
+            raise ValueError(msg)

skimage/_shared/testing.py

@@ -9,7 +9,7 @@ from skimage import (
     data, io, img_as_uint, img_as_float, img_as_int, img_as_ubyte)
 from numpy import testing
 import numpy as np
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 import warnings
 
 
@@ -117,24 +117,24 @@ def color_check(plugin, fmt='png'):
     testing.assert_allclose(img2.astype(np.uint8), r2)
 
     img3 = img_as_float(img)
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         r3 = roundtrip(img3, plugin, fmt)
     testing.assert_allclose(r3, img)
 
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         img4 = img_as_int(img)
     if fmt.lower() in (('tif', 'tiff')):
         img4 -= 100
-        with all_warnings():  # sign loss
+        with expected_warnings(['sign loss']):
             r4 = roundtrip(img4, plugin, fmt)
         testing.assert_allclose(r4, img4)
     else:
-        with all_warnings():  # sign loss
+        with expected_warnings(['sign loss']):
             r4 = roundtrip(img4, plugin, fmt)
             testing.assert_allclose(r4, img_as_ubyte(img4))
 
     img5 = img_as_uint(img)
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         r5 = roundtrip(img5, plugin, fmt)
     testing.assert_allclose(r5, img)
 
@@ -154,22 +154,22 @@ def mono_check(plugin, fmt='png'):
     testing.assert_allclose(img2.astype(np.uint8), r2)
 
     img3 = img_as_float(img)
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         r3 = roundtrip(img3, plugin, fmt)
     if r3.dtype.kind == 'f':
         testing.assert_allclose(img3, r3)
     else:
         testing.assert_allclose(r3, img_as_uint(img))
 
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         img4 = img_as_int(img)
     if fmt.lower() in (('tif', 'tiff')):
         img4 -= 100
-        with all_warnings():  # sign loss
+        with expected_warnings(['sign loss']):
             r4 = roundtrip(img4, plugin, fmt)
         testing.assert_allclose(r4, img4)
     else:
-        with all_warnings():  # sign loss
+        with expected_warnings(['sign loss']):
             r4 = roundtrip(img4, plugin, fmt)
             testing.assert_allclose(r4, img_as_uint(img4))
 
@@ -188,9 +188,7 @@ def setup_test():
     warnings.simplefilter('default')
     from scipy import signal, ndimage, special, optimize, linalg
     from scipy.io import loadmat
-    from skimage import filter, viewer, data
-    # trigger PIL warnings
-    data.moon()
+    from skimage import viewer, filter
     np.random.seed(0)
     warnings.simplefilter('error') 
 

skimage/_shared/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/color/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/color/tests/test_adapt_rgb.py

@@ -5,7 +5,7 @@ import numpy as np
 from skimage import img_as_float, img_as_uint
 from skimage import color, data, filters
 from skimage.color.adapt_rgb import adapt_rgb, each_channel, hsv_value
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 # Down-sample image for quicker testing.
 COLOR_IMAGE = data.astronaut()[::5, ::5]
@@ -38,7 +38,7 @@ def smooth_hsv(image, sigma):
 
 @adapt_rgb(hsv_value)
 def edges_hsv_uint(image):
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         return img_as_uint(filters.sobel(image))
 
 

skimage/color/tests/test_colorconv.py

@@ -40,12 +40,10 @@ from skimage.color import (rgb2hsv, hsv2rgb,
                            )
 
 from skimage import data_dir
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 import colorsys
 
-np.random.seed(0)
-
 
 def test_guess_spatial_dimensions():
     im1 = np.zeros((5, 5))
@@ -157,7 +155,7 @@ class TestColorconv(TestCase):
     # RGB<->HED roundtrip with ubyte image
     def test_hed_rgb_roundtrip(self):
         img_rgb = img_as_ubyte(self.img_rgb)
-        with all_warnings():  # precision loss
+        with expected_warnings(['precision loss']):
             new = img_as_ubyte(hed2rgb(rgb2hed(img_rgb)))
         assert_equal(new, img_rgb)
 

skimage/color/tests/test_colorlabel.py

@@ -3,7 +3,7 @@ import itertools
 import numpy as np
 from numpy import testing
 from skimage.color.colorlabel import label2rgb
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 from numpy.testing import (assert_array_almost_equal as assert_close,
                            assert_array_equal, assert_warns)
 
@@ -125,10 +125,9 @@ def test_avg():
 
 
 def test_negative_intensity():
-    with all_warnings():
-        labels = np.arange(100).reshape(10, 10)
-        image = -1 * np.ones((10, 10))
-        assert_warns(UserWarning, label2rgb, labels, image)
+    labels = np.arange(100).reshape(10, 10)
+    image = -1 * np.ones((10, 10))
+    assert_warns(UserWarning, label2rgb, labels, image)
 
 
 if __name__ == '__main__':

skimage/data/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/draw/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/exposure/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/exposure/tests/test_exposure.py

@@ -11,7 +11,7 @@ from skimage import exposure
 from skimage.exposure.exposure import intensity_range
 from skimage.color import rgb2gray
 from skimage.util.dtype import dtype_range
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 # Test integer histograms
@@ -53,7 +53,7 @@ def test_equalize_uint8_approx():
 
 
 def test_equalize_ubyte():
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         img = skimage.img_as_ubyte(test_img)
     img_eq = exposure.equalize_hist(img)
 
@@ -211,7 +211,7 @@ def test_adapthist_grayscale():
     img = skimage.img_as_float(data.astronaut())
     img = rgb2gray(img)
     img = np.dstack((img, img, img))
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         adapted = exposure.equalize_adapthist(img, 10, 9, clip_limit=0.01,
                                               nbins=128)
     assert_almost_equal = np.testing.assert_almost_equal
@@ -229,7 +229,7 @@ def test_adapthist_color():
         warnings.simplefilter('always')
         hist, bin_centers = exposure.histogram(img)
         assert len(w) > 0
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         adapted = exposure.equalize_adapthist(img, clip_limit=0.01)
 
     assert_almost_equal = np.testing.assert_almost_equal
@@ -248,7 +248,7 @@ def test_adapthist_alpha():
     img = skimage.img_as_float(data.astronaut())
     alpha = np.ones((img.shape[0], img.shape[1]), dtype=float)
     img = np.dstack((img, alpha))
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         adapted = exposure.equalize_adapthist(img)
     assert adapted.shape != img.shape
     img = img[:, :, :3]

skimage/feature/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/filters/tests/test_gaussian.py

@@ -1,6 +1,6 @@
 import numpy as np
 from skimage.filters._gaussian import gaussian_filter
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 def test_null_sigma():
@@ -26,7 +26,7 @@ def test_multichannel():
     assert np.allclose([a[..., i].mean() for i in range(3)],
                         [gaussian_rgb_a[..., i].mean() for i in range(3)])
     # Test multichannel = None
-    with all_warnings():  # multichannel
+    with expected_warnings(['multichannel']):
         gaussian_rgb_a = gaussian_filter(a, sigma=1, mode='reflect')
     # Check that the mean value is conserved in each channel
     # (color channels are not mixed together)

skimage/graph/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/io/_plugins/pil_plugin.py

@@ -7,7 +7,6 @@ from PIL import Image
 from skimage.util import img_as_ubyte, img_as_uint
 from skimage.external.tifffile import (
     imread as tif_imread, imsave as tif_imsave)
-from skimage._shared._warnings import expected_warnings
 
 
 def imread(fname, dtype=None, img_num=None, **kwargs):
@@ -48,8 +47,7 @@ def imread(fname, dtype=None, img_num=None, **kwargs):
     im = Image.open(fname)
     try:
         # this will raise an IOError if the file is not readable
-        with expected_warnings(['unclosed file']):
-            im.getdata()[0]
+        im.getdata()[0]
     except IOError:
         site = "http://pillow.readthedocs.org/en/latest/installation.html#external-libraries"
         raise ValueError('Could not load "%s"\nPlease see documentation at: %s' % (fname, site))

skimage/io/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/io/tests/test_pil.py

@@ -10,16 +10,18 @@ from skimage import data_dir
 from skimage.io import (imread, imsave, use_plugin, reset_plugins,
                         Image as ioImage)
 from skimage._shared.testing import mono_check, color_check
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 from six import BytesIO
 
 from PIL import Image
 from skimage.io._plugins.pil_plugin import (
     pil_to_ndarray, ndarray_to_pil, _palette_is_grayscale)
-use_plugin('pil')
 
-np.random.seed(0)
+
+
+def setup():
+    use_plugin('pil')
 
 
 def teardown():
@@ -144,7 +146,7 @@ def test_imsave_filelike():
     s = BytesIO()
 
     # save to file-like object
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         imsave(s, image)
 
     # read from file-like object
@@ -157,7 +159,7 @@ def test_imsave_filelike():
 def test_imexport_imimport():
     shape = (2, 2)
     image = np.zeros(shape)
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         pil_image = ndarray_to_pil(image)
     out = pil_to_ndarray(pil_image)
     assert out.shape == shape

skimage/io/tests/test_plugin_util.py

@@ -1,5 +1,5 @@
 from skimage.io._plugins.util import prepare_for_display, WindowManager
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 from numpy.testing import *
 import numpy as np
@@ -9,16 +9,16 @@ np.random.seed(0)
 
 class TestPrepareForDisplay:
     def test_basic(self):
-        with all_warnings():  # precision loss
+        with expected_warnings(['precision loss']):
             prepare_for_display(np.random.rand(10, 10))
 
     def test_dtype(self):
-        with all_warnings():  # precision loss
+        with expected_warnings(['precision loss']):
             x = prepare_for_display(np.random.rand(10, 15))
         assert x.dtype == np.dtype(np.uint8)
 
     def test_grey(self):
-        with all_warnings():  # precision loss
+        with expected_warnings(['precision loss']):
             tmp = np.arange(12, dtype=float).reshape((4, 3)) / 11
             x = prepare_for_display(tmp)
         assert_array_equal(x[..., 0], x[..., 2])
@@ -26,21 +26,21 @@ class TestPrepareForDisplay:
         assert x[3, 2, 0] == 255
 
     def test_colour(self):
-        with all_warnings():  # precision loss
+        with expected_warnings(['precision loss']):
             prepare_for_display(np.random.rand(10, 10, 3))
 
     def test_alpha(self):
-        with all_warnings():  # precision loss
+        with expected_warnings(['precision loss']):
             prepare_for_display(np.random.rand(10, 10, 4))
 
     @raises(ValueError)
     def test_wrong_dimensionality(self):
-        with all_warnings():  # precision loss
+        with expected_warnings(['precision loss']):
             prepare_for_display(np.random.rand(10, 10, 1, 1))
 
     @raises(ValueError)
     def test_wrong_depth(self):
-        with all_warnings():  # precision loss
+        with expected_warnings(['precision loss']):
             prepare_for_display(np.random.rand(10, 10, 5))
 
 

skimage/measure/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/measure/tests/test_fit.py

@@ -3,7 +3,7 @@ from numpy.testing import assert_equal, assert_raises, assert_almost_equal
 from skimage.measure import LineModel, CircleModel, EllipseModel, ransac
 from skimage.transform import AffineTransform
 from skimage.measure.fit import _dynamic_max_trials
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 def test_line_model_invalid_input():
@@ -256,7 +256,7 @@ def test_deprecated_params_attribute():
     model.params = (10, 1)
     x = np.arange(-10, 10)
     y = model.predict_y(x)
-    with all_warnings():  # deprecation
+    with expected_warnings(['`_params`']):
         assert_equal(model.params, model._params)
 
 

skimage/measure/tests/test_regionprops.py

@@ -4,7 +4,7 @@ import numpy as np
 import math
 
 from skimage.measure._regionprops import regionprops, PROPS, perimeter
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 SAMPLE = np.array(
@@ -26,16 +26,14 @@ INTENSITY_SAMPLE[1, 9:11] = 2
 def test_all_props():
     region = regionprops(SAMPLE, INTENSITY_SAMPLE)[0]
     for prop in PROPS:
-        with all_warnings():  # deprecation warning
-            assert_equal(region[prop], getattr(region, PROPS[prop]))
+        assert_equal(region[prop], getattr(region, PROPS[prop]))
 
 
 def test_dtype():
     regionprops(np.zeros((10, 10), dtype=np.int))
     regionprops(np.zeros((10, 10), dtype=np.uint))
-    with all_warnings():  # deprecation on dtype
-        assert_raises((TypeError, RuntimeError), regionprops,
-                      np.zeros((10, 10), dtype=np.double))
+    assert_raises((TypeError, RuntimeError), regionprops,
+                   np.zeros((10, 10), dtype=np.double))
 
 
 def test_ndim():
@@ -128,13 +126,13 @@ def test_equiv_diameter():
 
 
 def test_euler_number():
-    with all_warnings():  # deprecation warning
+    with expected_warnings(['`background`']):
         en = regionprops(SAMPLE)[0].euler_number
     assert en == 0
 
     SAMPLE_mod = SAMPLE.copy()
     SAMPLE_mod[7, -3] = 0
-    with all_warnings():  # deprecation warning
+    with expected_warnings(['`background`']):
         en = regionprops(SAMPLE_mod)[0].euler_number
     assert en == -1
 
@@ -374,7 +372,7 @@ def test_equals():
     r2 = regions[0]
     r3 = regions[1]
 
-    with all_warnings():  # deprecation warning
+    with expected_warnings(['`background`']):
         assert_equal(r1 == r2, True, "Same regionprops are not equal")
         assert_equal(r1 != r3, True, "Different regionprops are equal")
 

skimage/morphology/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/morphology/tests/test_binary.py

@@ -4,7 +4,7 @@ from numpy import testing
 from skimage import data, color
 from skimage.util import img_as_bool
 from skimage.morphology import binary, grey, selem
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 from scipy import ndimage
 
 
@@ -15,7 +15,7 @@ bw_img = img > 100
 def test_non_square_image():
     strel = selem.square(3)
     binary_res = binary.binary_erosion(bw_img[:100, :200], strel)
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         grey_res = img_as_bool(grey.erosion(bw_img[:100, :200], strel))
     testing.assert_array_equal(binary_res, grey_res)
 
@@ -23,7 +23,7 @@ def test_non_square_image():
 def test_binary_erosion():
     strel = selem.square(3)
     binary_res = binary.binary_erosion(bw_img, strel)
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         grey_res = img_as_bool(grey.erosion(bw_img, strel))
     testing.assert_array_equal(binary_res, grey_res)
 
@@ -31,7 +31,7 @@ def test_binary_erosion():
 def test_binary_dilation():
     strel = selem.square(3)
     binary_res = binary.binary_dilation(bw_img, strel)
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         grey_res = img_as_bool(grey.dilation(bw_img, strel))
     testing.assert_array_equal(binary_res, grey_res)
 
@@ -39,7 +39,7 @@ def test_binary_dilation():
 def test_binary_closing():
     strel = selem.square(3)
     binary_res = binary.binary_closing(bw_img, strel)
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         grey_res = img_as_bool(grey.closing(bw_img, strel))
     testing.assert_array_equal(binary_res, grey_res)
 
@@ -47,7 +47,7 @@ def test_binary_closing():
 def test_binary_opening():
     strel = selem.square(3)
     binary_res = binary.binary_opening(bw_img, strel)
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         grey_res = img_as_bool(grey.opening(bw_img, strel))
     testing.assert_array_equal(binary_res, grey_res)
 
@@ -57,7 +57,7 @@ def test_selem_overflow():
     img = np.zeros((20, 20))
     img[2:19, 2:19] = 1
     binary_res = binary.binary_erosion(img, strel)
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         grey_res = img_as_bool(grey.erosion(img, strel))
     testing.assert_array_equal(binary_res, grey_res)
 

skimage/morphology/tests/test_ccomp.py

@@ -1,22 +1,16 @@
 import numpy as np
 from numpy.testing import assert_array_equal, run_module_suite
 
-from skimage.morphology import label as _label
+from skimage.measure import label
 import skimage.measure._ccomp as ccomp
-from skimage._shared.utils import all_warnings
-np.random.seed(0)
+from skimage._shared._warnings import expected_warnings
+
 
 # The background label value
 # is supposed to be changed to 0 soon
 BG = -1
 
 
-def label(*args, **kwargs):
-    """Wrap the label function to avoid deprecation warning"""
-    with all_warnings():
-        return _label(*args, **kwargs)
-
-
 class TestConnectedComponents:
     def setup(self):
         self.x = np.array([[0, 0, 3, 2, 1, 9],
@@ -30,7 +24,8 @@ class TestConnectedComponents:
                                 [6, 5, 5, 7, 8, 9]])
 
     def test_basic(self):
-        assert_array_equal(label(self.x), self.labels)
+        with expected_warnings(['`background`']):
+            assert_array_equal(label(self.x), self.labels)
 
         # Make sure data wasn't modified
         assert self.x[0, 2] == 3
@@ -38,7 +33,7 @@ class TestConnectedComponents:
     def test_random(self):
         x = (np.random.rand(20, 30) * 5).astype(np.int)
 
-        with all_warnings():
+        with expected_warnings(['`background`']):
             labels = label(x)
 
         n = labels.max()
@@ -50,13 +45,13 @@ class TestConnectedComponents:
         x = np.array([[0, 0, 1],
                       [0, 1, 0],
                       [1, 0, 0]])
-        with all_warnings():
+        with expected_warnings(['`background`']):
             assert_array_equal(label(x), x)
 
     def test_4_vs_8(self):
         x = np.array([[0, 1],
                       [1, 0]], dtype=int)
-        with all_warnings():
+        with expected_warnings(['`background`']):
             assert_array_equal(label(x, 4),
                                [[0, 1],
                                 [2, 3]])
@@ -69,7 +64,7 @@ class TestConnectedComponents:
                       [1, 1, 5],
                       [0, 0, 0]])
 
-        with all_warnings():
+        with expected_warnings(['`background`']):
             assert_array_equal(label(x), [[0, 1, 1],
                                           [0, 0, 2],
                                           [3, 3, 3]])
@@ -105,7 +100,7 @@ class TestConnectedComponents:
                       [0, 0, 6],
                       [5, 5, 5]])
 
-        with all_warnings():
+        with expected_warnings(['`background`']):
             assert_array_equal(label(x, return_num=True)[1], 4)
 
         assert_array_equal(label(x, background=0, return_num=True)[1], 3)
@@ -147,7 +142,8 @@ class TestConnectedComponents3d:
                                    [10, 5, 7, 7, 7]])
 
     def test_basic(self):
-        labels = label(self.x)
+        with expected_warnings(['`background`']):
+            labels = label(self.x)
         assert_array_equal(labels, self.labels)
 
         assert self.x[0, 0, 2] == 2, \
@@ -156,7 +152,7 @@ class TestConnectedComponents3d:
     def test_random(self):
         x = (np.random.rand(20, 30) * 5).astype(np.int)
 
-        with all_warnings():
+        with expected_warnings(['`background`']):
             labels = label(x)
 
         n = labels.max()
@@ -169,7 +165,7 @@ class TestConnectedComponents3d:
         x[0, 2, 2] = 1
         x[1, 1, 1] = 1
         x[2, 0, 0] = 1
-        with all_warnings():
+        with expected_warnings(['`background`']):
             assert_array_equal(label(x), x)
 
     def test_4_vs_8(self):
@@ -178,7 +174,7 @@ class TestConnectedComponents3d:
         x[1, 0, 0] = 1
         label4 = x.copy()
         label4[1, 0, 0] = 2
-        with all_warnings():
+        with expected_warnings(['`background`']):
             assert_array_equal(label(x, 4), label4)
             assert_array_equal(label(x, 8), x)
 
@@ -206,7 +202,7 @@ class TestConnectedComponents3d:
                           [BG, 0,   1],
                           [BG, BG, BG]])
 
-        with all_warnings():
+        with expected_warnings(['`background`']):
             assert_array_equal(label(x), lnb)
 
         assert_array_equal(label(x, background=0), lb)
@@ -244,7 +240,7 @@ class TestConnectedComponents3d:
                       [0, 0, 6],
                       [5, 5, 5]])
 
-        with all_warnings():
+        with expected_warnings(['`background`']):
             assert_array_equal(label(x, return_num=True)[1], 4)
 
         assert_array_equal(label(x, background=0, return_num=True)[1], 3)
@@ -258,7 +254,8 @@ class TestConnectedComponents3d:
                     (1, xlen, 1), (xlen, 1, 1), (1, 1, xlen))
         for reshape in reshapes:
             x2 = x.reshape(reshape)
-            labelled = label(x2)
+            with expected_warnings(['`background`']):
+                labelled = label(x2)
             assert_array_equal(y, labelled.flatten())
 
     def test_nd(self):

skimage/morphology/tests/test_grey.py

@@ -7,7 +7,7 @@ from scipy import ndimage
 import skimage
 from skimage import data_dir
 from skimage.morphology import grey, selem
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 lena = np.load(os.path.join(data_dir, 'lena_GRAY_U8.npy'))
@@ -172,10 +172,10 @@ def test_3d_fallback_white_tophat():
     image[3, 2:5, 2:5] = 1
     image[4, 3:5, 3:5] = 1
 
-    with all_warnings():  # scipy upstream warning
+    with expected_warnings(['operator.*deprecated']):
         new_image = grey.white_tophat(image)
     footprint = ndimage.generate_binary_structure(3,1)
-    with all_warnings():  # scipy upstream warning
+    with expected_warnings(['operator.*deprecated']):
         image_expected = ndimage.white_tophat(image,footprint=footprint)
     testing.assert_array_equal(new_image, image_expected)
 
@@ -185,10 +185,10 @@ def test_3d_fallback_black_tophat():
     image[3, 2:5, 2:5] = 0
     image[4, 3:5, 3:5] = 0
 
-    with all_warnings():  # scipy upstream warning
+    with expected_warnings(['operator.*deprecated']):
         new_image = grey.black_tophat(image)
     footprint = ndimage.generate_binary_structure(3,1)
-    with all_warnings():  # scipy upstream warning
+    with expected_warnings(['operator.*deprecated']):
         image_expected = ndimage.black_tophat(image,footprint=footprint)
     testing.assert_array_equal(new_image, image_expected)
 
@@ -223,11 +223,11 @@ class TestDTypes():
         self.expected_closing = np.load(fname_closing)[arrname]
 
     def _test_image(self, image):
-        with all_warnings():  # precision loss
+        with expected_warnings(['precision loss']):
             result_opening = grey.opening(image, self.disk)
         testing.assert_equal(result_opening, self.expected_opening)
 
-        with all_warnings():  # precision loss
+        with expected_warnings(['precision loss']):
             result_closing = grey.closing(image, self.disk)
         testing.assert_equal(result_closing, self.expected_closing)
 

skimage/restoration/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/restoration/tests/test_unwrap.py

@@ -7,7 +7,7 @@ from numpy.testing import (run_module_suite, assert_array_almost_equal_nulp,
 import warnings
 
 from skimage.restoration import unwrap_phase
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 def assert_phase_almost_equal(a, b, *args, **kwargs):
@@ -133,7 +133,7 @@ def test_mask():
         assert_array_almost_equal_nulp(image_unwrapped[:, -1], image[i, -1])
 
         # Same tests, but forcing use of the 3D unwrapper by reshaping
-        with all_warnings():  # 1 dimension
+        with expected_warnings(['length 1 dimension']):
             shape = (1,) + image_wrapped.shape
             image_wrapped_3d = image_wrapped.reshape(shape)
             image_unwrapped_3d = unwrap_phase(image_wrapped_3d)

skimage/segmentation/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/segmentation/tests/test_random_walker.py

@@ -1,7 +1,14 @@
 import numpy as np
 from skimage.segmentation import random_walker
 from skimage.transform import resize
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
+from skimage._shared.version_requirements import is_installed
+
+
+if is_installed('pyamg'):
+    PYAMG_EXPECTED_WARNING = []
+else:
+    PYAMG_EXPECTED_WARNING = ['pyamg']
 
 
 def make_2d_syntheticdata(lx, ly=None):
@@ -75,11 +82,11 @@ def test_2d_cg():
     lx = 70
     ly = 100
     data, labels = make_2d_syntheticdata(lx, ly)
-    with all_warnings():  # cg mode
+    with expected_warnings(['"cg" mode']):
         labels_cg = random_walker(data, labels, beta=90, mode='cg')
     assert (labels_cg[25:45, 40:60] == 2).all()
     assert data.shape == labels.shape
-    with all_warnings():  # cg mode
+    with expected_warnings(['"cg" mode']):
         full_prob = random_walker(data, labels, beta=90, mode='cg',
                                   return_full_prob=True)
     assert (full_prob[1, 25:45, 40:60] >=
@@ -92,11 +99,11 @@ def test_2d_cg_mg():
     lx = 70
     ly = 100
     data, labels = make_2d_syntheticdata(lx, ly)
-    with all_warnings():  # pyamg optional
+    with expected_warnings(PYAMG_EXPECTED_WARNING):
         labels_cg_mg = random_walker(data, labels, beta=90, mode='cg_mg')
     assert (labels_cg_mg[25:45, 40:60] == 2).all()
     assert data.shape == labels.shape
-    with all_warnings():  # pyamg optional
+    with expected_warnings(PYAMG_EXPECTED_WARNING):
         full_prob = random_walker(data, labels, beta=90, mode='cg_mg',
                               return_full_prob=True)
     assert (full_prob[1, 25:45, 40:60] >=
@@ -111,7 +118,7 @@ def test_types():
     data, labels = make_2d_syntheticdata(lx, ly)
     data = 255 * (data - data.min()) // (data.max() - data.min())
     data = data.astype(np.uint8)
-    with all_warnings():  # pyamg optional
+    with expected_warnings(PYAMG_EXPECTED_WARNING):
         labels_cg_mg = random_walker(data, labels, beta=90, mode='cg_mg')
     assert (labels_cg_mg[25:45, 40:60] == 2).all()
     assert data.shape == labels.shape
@@ -145,7 +152,7 @@ def test_3d():
     n = 30
     lx, ly, lz = n, n, n
     data, labels = make_3d_syntheticdata(lx, ly, lz)
-    with all_warnings():  # cg mode
+    with expected_warnings(['"cg" mode']):
         labels = random_walker(data, labels, mode='cg')
     assert (labels.reshape(data.shape)[13:17, 13:17, 13:17] == 2).all()
     assert data.shape == labels.shape
@@ -159,7 +166,7 @@ def test_3d_inactive():
     old_labels = np.copy(labels)
     labels[5:25, 26:29, 26:29] = -1
     after_labels = np.copy(labels)
-    with all_warnings():  # cg mode
+    with expected_warnings(['"cg" mode']):
         labels = random_walker(data, labels, mode='cg')
     assert (labels.reshape(data.shape)[13:17, 13:17, 13:17] == 2).all()
     assert data.shape == labels.shape
@@ -170,11 +177,11 @@ def test_multispectral_2d():
     lx, ly = 70, 100
     data, labels = make_2d_syntheticdata(lx, ly)
     data = data[..., np.newaxis].repeat(2, axis=-1)  # Expect identical output
-    with all_warnings():  # cg mode
+    with expected_warnings(['"cg" mode']):
         multi_labels = random_walker(data, labels, mode='cg',
                                      multichannel=True)
     assert data[..., 0].shape == labels.shape
-    with all_warnings():  # cg mode
+    with expected_warnings(['"cg" mode']):
         single_labels = random_walker(data[..., 0], labels, mode='cg')
     assert (multi_labels.reshape(labels.shape)[25:45, 40:60] == 2).all()
     assert data[..., 0].shape == labels.shape
@@ -186,11 +193,11 @@ def test_multispectral_3d():
     lx, ly, lz = n, n, n
     data, labels = make_3d_syntheticdata(lx, ly, lz)
     data = data[..., np.newaxis].repeat(2, axis=-1)  # Expect identical output
-    with all_warnings():  # cg mode
+    with expected_warnings(['"cg" mode']):
         multi_labels = random_walker(data, labels, mode='cg', 
                                      multichannel=True)
     assert data[..., 0].shape == labels.shape
-    with all_warnings():  # cg mode
+    with expected_warnings(['"cg" mode']):
         single_labels = random_walker(data[..., 0], labels, mode='cg')
     assert (multi_labels.reshape(labels.shape)[13:17, 13:17, 13:17] == 2).all()
     assert (single_labels.reshape(labels.shape)[13:17, 13:17, 13:17] == 2).all()
@@ -217,7 +224,7 @@ def test_spacing_0():
                  lz // 4 - small_l // 8] = 2
 
     # Test with `spacing` kwarg
-    with all_warnings():  # cg mode
+    with expected_warnings(['"cg" mode']):
         labels_aniso = random_walker(data_aniso, labels_aniso, mode='cg',
                                  spacing=(1., 1., 0.5))
 
@@ -245,7 +252,7 @@ def test_spacing_1():
 
     # Test with `spacing` kwarg
     # First, anisotropic along Y
-    with all_warnings():  # using cg mode
+    with expected_warnings(['"cg" mode']):
         labels_aniso = random_walker(data_aniso, labels_aniso, mode='cg',
                                      spacing=(1., 2., 1.))
     assert (labels_aniso[13:17, 26:34, 13:17] == 2).all()
@@ -265,7 +272,7 @@ def test_spacing_1():
                   lz // 2 - small_l // 4] = 2
 
     # Anisotropic along X
-    with all_warnings():  # cg mode
+    with expected_warnings(['"cg" mode']):
         labels_aniso2 = random_walker(data_aniso,
                                       labels_aniso2,
                                       mode='cg', spacing=(2., 1., 1.))
@@ -277,7 +284,7 @@ def test_trivial_cases():
     img = np.ones((10, 10))
     labels = np.ones((10, 10))
 
-    with all_warnings():  # using provided labels
+    with expected_warnings(["Returning provided labels"]):
         pass_through = random_walker(img, labels)
     np.testing.assert_array_equal(pass_through, labels)
 
@@ -285,7 +292,7 @@ def test_trivial_cases():
     labels[:, :5] = 3
     expected = np.concatenate(((labels == 1)[..., np.newaxis],
                                (labels == 3)[..., np.newaxis]), axis=2)
-    with all_warnings():  # using provided labels
+    with expected_warnings(["Returning provided labels"]):
         test = random_walker(img, labels, return_full_prob=True)
     np.testing.assert_array_equal(test, expected)
 

skimage/transform/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/transform/tests/test_geometric.py

@@ -7,7 +7,7 @@ from skimage.transform import (estimate_transform, matrix_transform,
                                SimilarityTransform, AffineTransform,
                                ProjectiveTransform, PolynomialTransform,
                                PiecewiseAffineTransform)
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 SRC = np.array([
@@ -252,11 +252,11 @@ def test_invalid_input():
 def test_deprecated_params_attributes():
     for t in ('projective', 'affine', 'similarity'):
         tform = estimate_transform(t, SRC, DST)
-        with all_warnings():  # _matrix is deprecated
+        with expected_warnings(['`_matrix`.*deprecated']):
             assert_equal(tform._matrix, tform.params)
 
     tform = estimate_transform('polynomial', SRC, DST, order=3)
-    with all_warnings():  # _params is deprecated
+    with expected_warnings(['`_params`.*deprecated']):
         assert_equal(tform._params, tform.params)
 
 

skimage/transform/tests/test_hough_transform.py

@@ -3,7 +3,7 @@ from numpy.testing import assert_almost_equal, assert_equal
 
 import skimage.transform as tf
 from skimage.draw import line, circle_perimeter, ellipse_perimeter
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 def append_desc(func, description):
@@ -68,7 +68,7 @@ def test_hough_line_peaks():
 
     out, angles, d = tf.hough_line(img)
 
-    with all_warnings():  # _ccomp deprecation
+    with expected_warnings(['`background`']):
         out, theta, dist = tf.hough_line_peaks(out, angles, d)
 
     assert_equal(len(dist), 1)
@@ -81,7 +81,7 @@ def test_hough_line_peaks_dist():
     img[:, 30] = True
     img[:, 40] = True
     hspace, angles, dists = tf.hough_line(img)
-    with all_warnings():  # _ccomp deprecation
+    with expected_warnings(['`background`']):
         assert len(tf.hough_line_peaks(hspace, angles, dists,
                                        min_distance=5)[0]) == 2
         assert len(tf.hough_line_peaks(hspace, angles, dists,
@@ -89,7 +89,7 @@ def test_hough_line_peaks_dist():
 
 
 def test_hough_line_peaks_angle():
-    with all_warnings():  # _ccomp deprecation
+    with expected_warnings(['`background`']):
         check_hough_line_peaks_angle()
 
 
@@ -124,7 +124,7 @@ def test_hough_line_peaks_num():
     img[:, 30] = True
     img[:, 40] = True
     hspace, angles, dists = tf.hough_line(img)
-    with all_warnings():  # _ccomp deprecation
+    with expected_warnings(['`background`']):
         assert len(tf.hough_line_peaks(hspace, angles, dists, min_distance=0,
                                        min_angle=0, num_peaks=1)[0]) == 1
 

skimage/transform/tests/test_warps.py

@@ -10,7 +10,7 @@ from skimage.transform import (warp, warp_coords, rotate, resize, rescale,
                                downscale_local_mean)
 from skimage import transform as tf, data, img_as_float
 from skimage.color import rgb2gray
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 np.random.seed(0)
@@ -198,7 +198,7 @@ def test_swirl():
 
     swirl_params = {'radius': 80, 'rotation': 0, 'order': 2, 'mode': 'reflect'}
     
-    with all_warnings():  # deprecation warning
+    with expected_warnings(['Bi-quadratic.*bug']):
         swirled = tf.swirl(image, strength=10, **swirl_params)
         unswirled = tf.swirl(swirled, strength=-10, **swirl_params)
 

skimage/util/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/util/tests/test_dtype.py

@@ -3,7 +3,7 @@ from numpy.testing import assert_equal, assert_raises
 from skimage import img_as_int, img_as_float, \
                     img_as_uint, img_as_ubyte
 from skimage.util.dtype import convert
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 dtype_range = {np.uint8: (0, 255),
@@ -29,9 +29,13 @@ def test_range():
                         (img_as_float, np.float64),
                         (img_as_uint, np.uint16),
                         (img_as_ubyte, np.ubyte)]:
-
-            with all_warnings():  # precision loss
-              y = f(x)
+            
+            try:
+                with expected_warnings(['precision loss|sign loss']):
+                    y = f(x)
+            except ValueError as e:
+                if not 'No warning raised' in str(e):
+                    raise
 
             omin, omax = dtype_range[dt]
 
@@ -62,8 +66,14 @@ def test_range_extra_dtypes():
     for dtype_in, dt in dtype_pairs:
         imin, imax = dtype_range_extra[dtype_in]
         x = np.linspace(imin, imax, 10).astype(dtype_in)
-        with all_warnings():  # sign loss
-          y = convert(x, dt)
+        
+        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
+
         omin, omax = dtype_range_extra[dt]
         yield (_verify_range,
                "From %s to %s" % (np.dtype(dtype_in), np.dtype(dt)),

skimage/util/tests/test_shape.py

@@ -3,7 +3,7 @@ from nose.tools import raises
 from numpy.testing import assert_equal, assert_warns
 
 from skimage.util.shape import view_as_blocks, view_as_windows
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 @raises(TypeError)
@@ -153,9 +153,8 @@ def test_views_non_contiguous():
     A = np.arange(16).reshape((4, 4))
     A = A[::2, :]
 
-    with all_warnings():
-        assert_warns(RuntimeWarning, view_as_blocks, A, (2, 2))
-        assert_warns(RuntimeWarning, view_as_windows, A, (2, 2))
+    assert_warns(RuntimeWarning, view_as_blocks, A, (2, 2))
+    assert_warns(RuntimeWarning, view_as_windows, A, (2, 2))
 
 
 if __name__ == '__main__':

skimage/viewer/tests/__init__.py

@@ -1,2 +1,9 @@
-from skimage._shared.testing import setup_test
-setup_test()
+from skimage._shared.testing import setup_test, teardown_test
+
+
+def setup():
+    setup_test()
+
+
+def tearDown():
+    teardown_test()

skimage/viewer/tests/test_plugins.py

@@ -12,7 +12,7 @@ from skimage.viewer.plugins import (
     PlotPlugin)
 from skimage.viewer.plugins.base import Plugin
 from skimage.viewer.widgets import Slider
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 def setup_line_profile(image, limits='image'):
@@ -67,7 +67,7 @@ def test_line_profile_dynamic():
     assert_almost_equal(np.std(line), 0.229, 3)
     assert_almost_equal(np.max(line) - np.min(line), 0.725, 1)
 
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         viewer.image = skimage.img_as_float(median(image,
                                                    selem=disk(radius=3)))
 
@@ -161,7 +161,7 @@ def test_plugin():
     viewer = ImageViewer(img)
 
     def median_filter(img, radius=3):
-        with all_warnings():  # precision loss
+        with expected_warnings(['precision loss']):
             return median(img, selem=disk(radius=radius))
 
     plugin = Plugin(image_filter=median_filter)

skimage/viewer/tests/test_viewer.py

@@ -8,7 +8,7 @@ from skimage.filters import sobel
 from numpy.testing import assert_equal
 from numpy.testing.decorators import skipif
 from skimage._shared.version_requirements import is_installed
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 @skipif(not viewer_available)
@@ -68,7 +68,7 @@ def test_viewer_with_overlay():
     ov.color = 3
     assert_equal(ov.color, 'yellow')
 
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         viewer.save_to_file(filename)
     ov.display_filtered_image(img)
     assert_equal(ov.overlay, img)

skimage/viewer/tests/test_widgets.py

@@ -8,7 +8,7 @@ from skimage.viewer.plugins.base import Plugin
 from skimage.viewer.qt import QtGui, QtCore
 from numpy.testing import assert_almost_equal, assert_equal
 from numpy.testing.decorators import skipif
-from skimage._shared.utils import all_warnings
+from skimage._shared._warnings import expected_warnings
 
 
 def get_image_viewer():
@@ -100,12 +100,12 @@ def test_save_buttons():
     timer.singleShot(100, QtGui.QApplication.quit)
 
     sv.save_to_stack()
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         sv.save_to_file(filename)
 
     img = data.imread(filename)
 
-    with all_warnings():  # precision loss
+    with expected_warnings(['precision loss']):
         assert_almost_equal(img, img_as_uint(viewer.image))
 
     img = io.pop()