From 76fdc9975a927a7f13d4272e0f27f2a2ca44f1fe Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Fran=C3=A7ois=20Boulogne?= Date: Wed, 3 Aug 2016 08:23:13 +0200 Subject: [PATCH] Set up an image for parallel testing --- skimage/filters/rank/tests/test_rank.py | 72 +++++++++++++------------ 1 file changed, 39 insertions(+), 33 deletions(-) diff --git a/skimage/filters/rank/tests/test_rank.py b/skimage/filters/rank/tests/test_rank.py index f3cf7861..4295d841 100644 --- a/skimage/filters/rank/tests/test_rank.py +++ b/skimage/filters/rank/tests/test_rank.py @@ -8,82 +8,88 @@ from skimage import data, util, morphology from skimage.morphology import grey, disk from skimage.filters import rank from skimage._shared._warnings import expected_warnings +from skimage._shared.testing import test_parallel class TestRank(): def setup(self): np.random.seed(0) + # This image is used along with @test_parallel + # to ensure that the same seed is used for each thread. + self.image = np.random.rand(25, 25) + # Set again the seed for the other tests. + np.random.seed(0) def test_all(self): + @test_parallel() def check_all(): - image = np.random.rand(25, 25) selem = morphology.disk(1) refs = np.load(os.path.join(skimage.data_dir, "rank_filter_tests.npz")) assert_equal(refs["autolevel"], - rank.autolevel(image, selem)) + rank.autolevel(self.image, selem)) assert_equal(refs["autolevel_percentile"], - rank.autolevel_percentile(image, selem)) + rank.autolevel_percentile(self.image, selem)) assert_equal(refs["bottomhat"], - rank.bottomhat(image, selem)) + rank.bottomhat(self.image, selem)) assert_equal(refs["equalize"], - rank.equalize(image, selem)) + rank.equalize(self.image, selem)) assert_equal(refs["gradient"], - rank.gradient(image, selem)) + rank.gradient(self.image, selem)) assert_equal(refs["gradient_percentile"], - rank.gradient_percentile(image, selem)) + rank.gradient_percentile(self.image, selem)) assert_equal(refs["maximum"], - rank.maximum(image, selem)) + rank.maximum(self.image, selem)) assert_equal(refs["mean"], - rank.mean(image, selem)) + rank.mean(self.image, selem)) assert_equal(refs["geometric_mean"], - rank.geometric_mean(image, selem)), + rank.geometric_mean(self.image, selem)), assert_equal(refs["mean_percentile"], - rank.mean_percentile(image, selem)) + rank.mean_percentile(self.image, selem)) assert_equal(refs["mean_bilateral"], - rank.mean_bilateral(image, selem)) + rank.mean_bilateral(self.image, selem)) assert_equal(refs["subtract_mean"], - rank.subtract_mean(image, selem)) + rank.subtract_mean(self.image, selem)) assert_equal(refs["subtract_mean_percentile"], - rank.subtract_mean_percentile(image, selem)) + rank.subtract_mean_percentile(self.image, selem)) assert_equal(refs["median"], - rank.median(image, selem)) + rank.median(self.image, selem)) assert_equal(refs["minimum"], - rank.minimum(image, selem)) + rank.minimum(self.image, selem)) assert_equal(refs["modal"], - rank.modal(image, selem)) + rank.modal(self.image, selem)) assert_equal(refs["enhance_contrast"], - rank.enhance_contrast(image, selem)) + rank.enhance_contrast(self.image, selem)) assert_equal(refs["enhance_contrast_percentile"], - rank.enhance_contrast_percentile(image, selem)) + rank.enhance_contrast_percentile(self.image, selem)) assert_equal(refs["pop"], - rank.pop(image, selem)) + rank.pop(self.image, selem)) assert_equal(refs["pop_percentile"], - rank.pop_percentile(image, selem)) + rank.pop_percentile(self.image, selem)) assert_equal(refs["pop_bilateral"], - rank.pop_bilateral(image, selem)) + rank.pop_bilateral(self.image, selem)) assert_equal(refs["sum"], - rank.sum(image, selem)) + rank.sum(self.image, selem)) assert_equal(refs["sum_bilateral"], - rank.sum_bilateral(image, selem)) + rank.sum_bilateral(self.image, selem)) assert_equal(refs["sum_percentile"], - rank.sum_percentile(image, selem)) + rank.sum_percentile(self.image, selem)) assert_equal(refs["threshold"], - rank.threshold(image, selem)) + rank.threshold(self.image, selem)) assert_equal(refs["threshold_percentile"], - rank.threshold_percentile(image, selem)) + rank.threshold_percentile(self.image, selem)) assert_equal(refs["tophat"], - rank.tophat(image, selem)) + rank.tophat(self.image, selem)) assert_equal(refs["noise_filter"], - rank.noise_filter(image, selem)) + rank.noise_filter(self.image, selem)) assert_equal(refs["entropy"], - rank.entropy(image, selem)) + rank.entropy(self.image, selem)) assert_equal(refs["otsu"], - rank.otsu(image, selem)) + rank.otsu(self.image, selem)) assert_equal(refs["percentile"], - rank.percentile(image, selem)) + rank.percentile(self.image, selem)) assert_equal(refs["windowed_histogram"], - rank.windowed_histogram(image, selem)) + rank.windowed_histogram(self.image, selem)) with expected_warnings(['precision loss', 'non-integer|\A\Z']): check_all()