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

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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