A much better way came to my mind: import numpy as np import pylab from skimage.draw import circle_perimeter img = np.zeros((41, 41)) center_r = center_c = 20 rr, cc = circle_perimeter(center_r, center_c, 18) t = np.arctan2(rr - center_r, cc - center_c) t_sorted = np.argsort(t) rr = rr[t_sorted] cc = cc[t_sorted] img[rr[::4], cc[::4]] = 1 pylab.imshow(img, interpolation='nearest') pylab.show() Johannes Schönberger Am 28.05.2013 um 22:40 schrieb Johannes Schönberger <jschoenberger@demuc.de>:

This should do the trick…

import numpy as np import pylab from skimage.draw import circle_perimeter

img = np.zeros((41, 41)) rr, cc = circle_perimeter(20, 20, 18)

SKIP_SIZE = 3

img[rr, cc] = 5

for i in range(4): rri = rr[i::4] cci = cc[i::4] rri_sorted = np.argsort(rri) rri = rri[rri_sorted] cci = cci[rri_sorted] cci_sorted = np.argsort(cci) rri = rri[cci_sorted] cci = cci[cci_sorted] img[rri[::SKIP_SIZE], cci[::SKIP_SIZE]] = 1

pylab.imshow(img, interpolation='nearest') pylab.show()

Johannes Schönberger

Am 28.05.2013 um 18:43 schrieb Dan Farmer <dfarmernv@gmail.com>:

...

Hi Guys,

I'm trying to subsample the points returned by circle_perimeter and I'm having trouble. Since the points are calculated in octants (and reflected?) it makes walking it somewhat confusing (see below) Does anyone know off hand how I could walk this thing clockwise for example (or produce a sensible subsample of e.g., every other point or every 4th point, etc).

To be a little more concrete:

from skimage.draw import circle_perimeter

rr, cc = circle_perimeter(12, 12, 10) im = zeros((40,40)) im[rr[::4],cc[::4]] = 1 imshow(im, cmap=cm.gray) # returns one quadrant of the circle

Still Googling, but I'd appreciate any help =)

Thanks, Dan

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