mirror of
https://github.com/m-labs/artiq.git
synced 2024-12-13 05:36:37 +08:00
31 lines
797 B
Python
31 lines
797 B
Python
|
import numpy as np
|
||
|
|
from numba import jit
|
||
|
|
from scipy.optimize import least_squares
|
||
|
|
|
||
|
|
|
||
|
|
@jit(nopython=True)
|
||
|
|
def compute_gaussian(r, img_w, img_h,
|
||
|
|
gaussian_w, gaussian_h,
|
||
|
|
gaussian_cx, gaussian_cy):
|
||
|
|
for y in range(img_h):
|
||
|
|
for x in range(img_w):
|
||
|
|
ds = ((gaussian_cx-x)/gaussian_w)**2
|
||
|
|
ds += ((gaussian_cy-y)/gaussian_h)**2
|
||
|
|
r[x, y] = np.exp(-ds/2)
|
||
|
|
|
||
|
|
|
||
|
|
def fit(data):
|
||
|
|
img_w, img_h = data.shape
|
||
|
|
def err(parameters):
|
||
|
|
r = np.empty((img_w, img_h))
|
||
|
|
compute_gaussian(r, img_w, img_h, *parameters)
|
||
|
|
r -= data
|
||
|
|
return r.ravel()
|
||
|
|
guess = [12, 15, img_w/2, img_h/2]
|
||
|
|
res = least_squares(err, guess)
|
||
|
|
return res.x
|
||
|
|
|
||
|
|
|
||
|
|
def get_and_fit():
|
||
|
|
return fit(controller_driver.get_picture())
|