From ea989e2456d8e9aee7521a410f475ccb1f53ebdb Mon Sep 17 00:00:00 2001 From: Juan Nunez-Iglesias Date: Thu, 22 Jan 2015 11:28:13 +1100 Subject: [PATCH] Fix a few typos --- skimage/filters/rank/README.rst | 2 +- skimage/filters/rank/tests/test_rank.py | 1 - 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/skimage/filters/rank/README.rst b/skimage/filters/rank/README.rst index 2d6bfb25..6e063ec2 100644 --- a/skimage/filters/rank/README.rst +++ b/skimage/filters/rank/README.rst @@ -26,7 +26,7 @@ update the local histogram. The histogram size is 8-bit (256 bins) for 8-bit images and 2 to 16-bit for 16-bit images depending on the maximum value of the image. -The filter is applied up to the image border, the neighboorhood used is +The filter is applied up to the image border, the neighborhood used is adjusted accordingly. The user may provide a mask image (same size as input image) where non zero values are the part of the image participating in the histogram computation. By default the entire image is filtered. diff --git a/skimage/filters/rank/tests/test_rank.py b/skimage/filters/rank/tests/test_rank.py index 0fda186c..78a97e56 100644 --- a/skimage/filters/rank/tests/test_rank.py +++ b/skimage/filters/rank/tests/test_rank.py @@ -87,7 +87,6 @@ def check_all(): def test_random_sizes(): # make sure the size is not a problem - niter = 10 elem = np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]], dtype=np.uint8) for m, n in np.random.random_integers(1, 100, size=(10, 2)): mask = np.ones((m, n), dtype=np.uint8)