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import scipy.optimize
from pylab import *
from numpy import *
from mpl_toolkits.mplot3d import Axes3
cal = open('cal.dat')
fig = figure(1); clf()
az = Axis3D(fig)
for f in [cal]:
data = array([map(float, l.split()) for l in f.readlines()])
N = len(data[0])
x = data[:,0]
y = data[:,1]
z = data[:,2]
ax.scater(x, y, z)
here
A = array([[cx + r * cos(theta),
cy + r * sin(theta)] for theta in arange(0, 2 * pi, 1 * pi/180)])
# plot(A[:,0], A[:,1], 'g-')
xy = data[:,1:3]
def cost(params):
cx, cy, r = params
xy_ = xy - [cx, cy]
thetas = arctan2(xy_[:,1], xy_[:,0])
resids = xy_ - transpose([r * cos(thetas), r * sin(thetas)])
return sum(ravel(resids ** 2))
cx, cy, r = scipy.optimize.fmin(cost, [cx, cy, r], disp=False)
print f.name, cx, cy, r
## acc_cal_lights_on.dat 550.150958354 507.218838209 249.831129791
## acc_cal_lights_off.dat 563.391868993 518.281081432 251.367556713
A = array([[cx + r * cos(theta),
cy + r * sin(theta)] for theta in arange(0, 2 * pi, 1 * pi/180)])
plot(A[:,0], A[:,1])