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Update morphology dtypes tests

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Previously, we were testing that any dtype would get converted to uint8
and then correctly processed. Now, since we are using ndimage, we are
directly processing all dtypes. I've updated the tests accordingly.
This commit is contained in:
Juan Nunez-Iglesias
2015-01-05 18:34:46 +11:00
parent 1fa6904c04
commit 04536cc7df
1 changed files with 39 additions and 39 deletions
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skimage/morphology/tests/test_grey.py
+39 -39
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@@ -5,7 +5,7 @@ from numpy import testing
from scipy import ndimage
import skimage
from skimage import data_dir
from skimage import data_dir, img_as_uint
from skimage.morphology import grey, selem
from skimage._shared._warnings import expected_warnings
@@ -208,51 +208,51 @@ def test_2d_ndimage_equivalence():
testing.assert_array_equal(opened, ndimage_opened)
testing.assert_array_equal(closed, ndimage_closed)
class TestDTypes():
# float test images
im = np.array([[ 0.55, 0.72, 0.6 , 0.54, 0.42],
[ 0.65, 0.44, 0.89, 0.96, 0.38],
[ 0.79, 0.53, 0.57, 0.93, 0.07],
[ 0.09, 0.02, 0.83, 0.78, 0.87],
[ 0.98, 0.8 , 0.46, 0.78, 0.12]])
def setUp(self):
k = 5
arrname = '%03i' % k
eroded = np.array([[ 0.55, 0.44, 0.54, 0.42, 0.38],
[ 0.44, 0.44, 0.44, 0.38, 0.07],
[ 0.09, 0.02, 0.53, 0.07, 0.07],
[ 0.02, 0.02, 0.02, 0.78, 0.07],
[ 0.09, 0.02, 0.46, 0.12, 0.12]])
self.disk = selem.disk(k)
dilated = np.array([[ 0.72, 0.72, 0.89, 0.96, 0.54],
[ 0.79, 0.89, 0.96, 0.96, 0.96],
[ 0.79, 0.79, 0.93, 0.96, 0.93],
[ 0.98, 0.83, 0.83, 0.93, 0.87],
[ 0.98, 0.98, 0.83, 0.78, 0.87]])
fname_opening = os.path.join(data_dir, "disk-open-matlab-output.npz")
self.expected_opening = np.load(fname_opening)[arrname]
opened = np.array([[ 0.55, 0.55, 0.54, 0.54, 0.42],
[ 0.55, 0.44, 0.54, 0.44, 0.38],
[ 0.44, 0.53, 0.53, 0.78, 0.07],
[ 0.09, 0.02, 0.78, 0.78, 0.78],
[ 0.09, 0.46, 0.46, 0.78, 0.12]])
fname_closing = os.path.join(data_dir, "disk-close-matlab-output.npz")
self.expected_closing = np.load(fname_closing)[arrname]
closed = np.array([[ 0.72, 0.72, 0.72, 0.54, 0.54],
[ 0.72, 0.72, 0.89, 0.96, 0.54],
[ 0.79, 0.79, 0.79, 0.93, 0.87],
[ 0.79, 0.79, 0.83, 0.78, 0.87],
[ 0.98, 0.83, 0.78, 0.78, 0.78]])
def _test_image(self, image):
with expected_warnings(['precision loss']):
result_opening = grey.opening(image, self.disk)
testing.assert_equal(result_opening, self.expected_opening)
with expected_warnings(['precision loss']):
result_closing = grey.closing(image, self.disk)
testing.assert_equal(result_closing, self.expected_closing)
def test_float(self):
image = skimage.img_as_float(lena)
self._test_image(image)
@testing.decorators.skipif(True)
def test_int(self):
image = skimage.img_as_int(lena)
self._test_image(image)
def test_uint(self):
image = skimage.img_as_uint(lena)
self._test_image(image)
def test_float():
np.testing.assert_allclose(grey.erosion(im), eroded)
np.testing.assert_allclose(grey.dilation(im), dilated)
np.testing.assert_allclose(grey.opening(im), opened)
np.testing.assert_allclose(grey.closing(im), closed)
def test_inplace():
selem = np.ones((3, 3))
image = np.zeros((5, 5))
out = image
for f in (grey.erosion, grey.dilation,
grey.white_tophat, grey.black_tophat):
testing.assert_raises(NotImplementedError, f, image, selem, out=out)
def test_uint16():
im16, eroded16, dilated16, opened16, closed16 = (
map(img_as_uint, [im, eroded, dilated, opened, closed]))
np.testing.assert_allclose(grey.erosion(im16), eroded16)
np.testing.assert_allclose(grey.dilation(im16), dilated16)
np.testing.assert_allclose(grey.opening(im16), opened16)
np.testing.assert_allclose(grey.closing(im16), closed16)
def test_discontiguous_out_array():