Scipy curve_fit无法为LED数据找到最优拟合参数求助

我使用scipy的curve_fit工具对5组LED数据执行高斯拟合，其中472nm、505nm、525nm三组数据拟合正常，但588nm和611nm的两组数据持续报错。已尝试调整初始参数、增大maxfev值、简化高斯函数（移除d和f相关的线性项与常数项），均未解决问题，报错信息如下：

RuntimeError: Optimal parameters not found: Number of calls to function has reached maxfev = 1200

相关代码：

error472 = data472y ** 0.5 
error505 = data505y ** 0.5 
error525 = data525y ** 0.5 
error588 = data588y ** 0.5 
error611 = data611y ** 0.5 

def GausFunc(x,a,b,c,d,f):
    return(a*np.exp(-(x-b)**2 / (2*c**2))+(d*x)+f)

popt472, pcov472 = curve_fit(GausFunc, data472x, data472y, [0.8,470,50,-10,6], error472, True)
popt505, pcov505 = curve_fit(GausFunc, data505x, data505y, [0.8,470,50,-10,6], error505, True)
popt525, pcov525 = curve_fit(GausFunc, data525x, data525y, [0.8,470,50,-10,6], error525, True)
popt588, pcov588 = curve_fit(GausFunc, data588x, data588y, [0.387,589,5,1,1], error588, True)
#popt611, pcov611 = curve_fit(GausFunc, data611x, data611y, [0.8,470,50,-10,6], error611, True)

附588nm组异常数据的拟合图像：

内容的提问来源于stack exchange，提问作者retro-rocket