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()
Am 28.05.2013 um 18:43 schrieb Dan Farmer email@example.com:
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 =)
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