我正在尝试使用2d数据集。我可以毫无问题地绘制它，但是当我尝试适合它时，我总是得到相同的错误信息，我不明白：
def twod_Gaussian(x,y,Amp,x0,y0,sigma_x,sigma_y,Offset):
return Amp*np.exp(-((x-x0)/(2*sigma_x**2)+(y-y0)/(2*sigma_y**2)))+Offset
# get data
filename = '20180503-1455-43_confocal_xy_data.dat'
data = np.genfromtxt(filename, comments='#')
values = open(filename)
val = values.readlines(500)
res = float(val[11][-4:-1])
values.close()
x = [float(i) for i in data[:, 0]]
y = [float(i) for i in data[:, 1]]
count_rate = [float(i) for i in data[:, 3]]
#reshape data
xmax = max(x)
xmin = min(x)
ymax = max(y)
ymin = min(y)
cmax = max(count_rate)
cmin = min(count_rate)
np.percentile(count_rate, 99)
resX = (xmax-xmin)/res
rexY = (ymax-ymin)/res
res2 = len(x)/res
xx = np.array(x).reshape((int(res2), int(res)))
yy = np.array(y).reshape((int(res2), int(res)))
#plot data
count_matrix = np.array(count_rate).reshape((int(res2), int(res)))
fig = plt.figure()
ax = fig.gca(projection='3d')
CS = ax.plot_surface((xx)/1e-6, (yy)/1e-6, count_matrix, cmap='plasma')
plt.ticklabel_format(style='plain', axis='both', scilimits=(0, 0))
ax.set_xlabel(r'X position ($\mathrm{\mu}$m)')
ax.set_ylabel(r'Y position ($\mathrm{\mu}$m)')
fig.colorbar(CS, ax=ax, extend='max', format='%.0e')
plt.show()
#initial guess and trying to fit it
p0=(98e-06,81.5e-06,50000,0.5e-06,0.5e-06,20000)
popt, pcov = curve_fit(twod_Gaussian, x, y, count_rate, p0)
我总是收到错误消息
ValueError：sigma形状不正确。
如果我将最后一行更改为
popt, pcov = curve_fit(twod_Gaussian, (x, y), count_rate, p0)
我收到错误消息：
twod_Gaussian() missing 1 required positional argument: 'Offset'
我不知道为什么形状应该是错的？