From 3c41e75b22a3295e104f96b06cdb965e85ef3cd2 Mon Sep 17 00:00:00 2001 From: Julius Bier Kirekgaard Date: Fri, 28 Aug 2015 20:46:14 +0100 Subject: [PATCH] Added whitespace to comply with pep8 --- skimage/transform/hough_transform.py | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/skimage/transform/hough_transform.py b/skimage/transform/hough_transform.py index e0872a30..1564fb8d 100644 --- a/skimage/transform/hough_transform.py +++ b/skimage/transform/hough_transform.py @@ -152,21 +152,21 @@ def hough_circle(image, radius, normalize=True, full_output=False): Examples -------- >>> from skimage.transform import hough_circle - >>> img = np.zeros((100,100),dtype=np.bool_) - >>> X,Y = np.meshgrid(np.arange(100),np.arange(100)) - >>> x0,y0,radius = 20,35,23 + >>> img = np.zeros((100, 100), dtype=np.bool_) + >>> X, Y = np.meshgrid(np.arange(100), np.arange(100)) + >>> x0, y0, radius = 20, 35, 23 >>> circle = np.abs((X-x0)**2+(Y-y0)**2-radius**2)<5**2 >>> img[circle] = 1 >>> # Find position of circle from known radius: - >>> res = hough_circle(img,np.array([radius]))[0,:,:] - >>> y,x = np.unravel_index(np.argmax(res),res.shape) - >>> x,y + >>> res = hough_circle(img, np.array([radius]))[0, :, :] + >>> y, x = np.unravel_index(np.argmax(res), res.shape) + >>> x, y (20, 35) >>> # Find position and radius by trying a range of radii: - >>> radii_range = np.arange(5,50) - >>> res = hough_circle(img,radii_range) - >>> ridx,y,x = np.unravel_index(np.argmax(res),res.shape) - >>> x,y,radii_range[ridx] + >>> radii_range = np.arange(5, 50) + >>> res = hough_circle(img, radii_range) + >>> ridx, y, x = np.unravel_index(np.argmax(res), res.shape) + >>> x, y, radii_range[ridx] (20, 35, 23) """