尝试使用scipy.optimize.curve_fit拟合2D高斯。引发错误，说N不能超过M

Question

我是Python的新手。我正在尝试使用给定的数据点拟合2D高斯。这是我的代码：

import scipy.optimize as opt
import numpy as np
import pylab as plt
from fftfits import get_image


filename = 
'../astro_data/trial23_LSST_convolved_noise0.fits'
image = get_image(filename)
limits = [0,3541,0,3541]

def twod_gaussian(xy, amplitude, x0, y0, sigma_x, sigma_y):                                                      
    '''Calculating 2D Gaussian from 2D data.'''                                     
    return amplitude * np.exp(-((xy[0]- 
    x0)**2/(2*sigma_x**2)+(xy[1]-y0)**2/(2*sigma_y**2)))

side_x = np.linspace(limits[0],limits[1],3542)
side_y = np.linspace(limits[2],limits[3],3542)
X,Y = np.meshgrid(side_x, side_y)
size = X.shape
x1d = np.reshape(X,(1,np.prod(size)))
y1d = np.reshape(Y,(1,np.prod(size)))
xydata = np.vstack((x1d, y1d))
zdata = np.reshape(image,(1,np.prod(size)))
popt, pcov = opt.curve_fit(twod_gaussian, xydata, zdata)

print(popt)

数据大小为3542 * 3542。引发的错误是这样的：

    raise TypeError('Improper input: N=%s must not exceed M=%s' % (n, m))

TypeError: Improper input: N=5 must not exceed M=1

我知道计算机抱怨有5个变量和只有1个数据点，但是在查看其他人发布的类似问题后，我仍然找不到我做错了什么地方：（