Walking circle_perimeter

[Johannes Schönberger]

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 at 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 at 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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