我试图用Lmfit库拟合一组由外部模拟获取并存储在向量中的数据。在

下面是我的代码：import numpy as np

import matplotlib.pyplot as plt

from lmfit import Model

from lmfit import Parameters

def DGauss3Par(x,I1,sigma1,sigma2):

I2 = 2.63 - I1

return (I1/np.sqrt(2*np.pi*sigma1))*np.exp(-(x*x)/(2*sigma1*sigma1)) + (I2/np.sqrt(2*np.pi*sigma2))*np.exp(-(x*x)/(2*sigma2*sigma2))

#TAKE DATA

xFull = []

yFull = []

fileTypex = np.dtype([('xFull', np.float)])

fileTypey = np.dtype([('yFull', np.float)])

fDatax = "xValue.dat"

fDatay = "yValue.dat"

xFull = np.loadtxt(fDatax, dtype=fileTypex)

yFull = np.loadtxt(fDatay, dtype=fileTypey)

xGauss = xFull[:]["xFull"]

yGauss = yFull[:]["yFull"]

#MODEL'S DEFINITION

gmodel = Model(DGauss3Par)

params = Parameters()

params.add('I1', value=1.66)

params.add('sigma1', value=1.04)

params.add('sigma2', value=1.2)

result3 = gmodel.fit(yGauss, x=xGauss, params=params)

#PLOTS

plt.plot(xGauss, result3.best_fit, 'y-')

plt.show()

当我运行它时，我得到一个错误：

^{pr2}$

以下是矢量xGauss(与x轴相关)中包含的数据值：[-3.88 -3.28 -3.13 -3.08 -3.03 -2.98 -2.93 -2.88 -2.83 -2.78 -2.73 -2.68

-2.63 -2.58 -2.53 -2.48 -2.43 -2.38 -2.33 -2.28 -2.23 -2.18 -2.13 -2.08

-2.03 -1.98 -1.93 -1.88 -1.83 -1.78 -1.73 -1.68 -1.63 -1.58 -1.53 -1.48

-1.43 -1.38 -1.33 -1.28 -1.23 -1.18 -1.13 -1.08 -1.03 -0.98 -0.93 -0.88

-0.83 -0.78 -0.73 -0.68 -0.63 -0.58 -0.53 -0.48 -0.43 -0.38 -0.33 -0.28

-0.23 -0.18 -0.13 -0.08 -0.03 0.03 0.08 0.13 0.18 0.23 0.28 0.33

0.38 0.43 0.48 0.53 0.58 0.63 0.68 0.73 0.78 0.83 0.88 0.93

0.98 1.03 1.08 1.13 1.18 1.23 1.28 1.33 1.38 1.43 1.48 1.53

1.58 1.63 1.68 1.73 1.78 1.83 1.88 1.93 1.98 2.03 2.08 2.13

2.18 2.23 2.28 2.33 2.38 2.43 2.48 2.53 2.58 2.63 2.68 2.73

2.78 2.83 2.88 2.93 2.98 3.03 3.08 3.13 3.28 3.88]

这些是矢量yGauss中的那些(与y轴有关)：[0.00173977 0.00986279 0.01529543 0.0242624 0.0287456 0.03238484

0.03285927 0.03945234 0.04615091 0.05701618 0.0637672 0.07194268

0.07763934 0.08565687 0.09615262 0.1043281 0.11350606 0.1199406

0.1260062 0.14093328 0.15079665 0.16651464 0.18065023 0.1938894

0.2047541 0.21794024 0.22806706 0.23793043 0.25164404 0.2635118

0.28075974 0.29568682 0.30871501 0.3311846 0.34648062 0.36984661

0.38540666 0.40618835 0.4283945 0.45002014 0.48303911 0.50746062

0.53167057 0.5548792 0.57835128 0.60256181 0.62566436 0.65704847

0.68289386 0.71332794 0.73258027 0.769608 0.78769989 0.81407275

0.83358852 0.85210239 0.87109068 0.89456217 0.91618782 0.93760247

0.95680234 0.96919757 0.9783219 0.98486193 0.9931429 0.9931429

0.98486193 0.9783219 0.96919757 0.95680234 0.93760247 0.91618782

0.89456217 0.87109068 0.85210239 0.83358852 0.81407275 0.78769989

0.769608 0.73258027 0.71332794 0.68289386 0.65704847 0.62566436

0.60256181 0.57835128 0.5548792 0.53167057 0.50746062 0.48303911

0.45002014 0.4283945 0.40618835 0.38540666 0.36984661 0.34648062

0.3311846 0.30871501 0.29568682 0.28075974 0.2635118 0.25164404

0.23793043 0.22806706 0.21794024 0.2047541 0.1938894 0.18065023

0.16651464 0.15079665 0.14093328 0.1260062 0.1199406 0.11350606

0.1043281 0.09615262 0.08565687 0.07763934 0.07194268 0.0637672

0.05701618 0.04615091 0.03945234 0.03285927 0.03238484 0.0287456

0.0242624 0.01529543 0.00986279 0.00173977]

我还尝试打印函数返回的值，看看是否真的有一些NaN值：params = Parameters()

params.add('I1', value=1.66)

params.add('sigma1', value=1.04)

params.add('sigma2', value=1.2)

func = DGauss3Par(xGauss,I1,sigma1,sigma2)

print func

但我得到的是：[0.04835225 0.06938855 0.07735839 0.08040181 0.08366964 0.08718237

0.09096169 0.09503048 0.0994128 0.10413374 0.10921938 0.11469669

0.12059333 0.12693754 0.13375795 0.14108333 0.14894236 0.15736337

0.16637406 0.17600115 0.18627003 0.19720444 0.20882607 0.22115413

0.23420498 0.24799173 0.26252377 0.27780639 0.29384037 0.3106216

0.32814069 0.34638266 0.3653266 0.38494543 0.40520569 0.42606735

0.44748374 0.46940149 0.49176057 0.51449442 0.5375301 0.56078857

0.58418507 0.60762948 0.63102687 0.65427809 0.6772804 0.69992818

0.72211377 0.74372824 0.76466232 0.78480729 0.80405595 0.82230355

0.83944875 0.85539458 0.87004937 0.88332762 0.89515085 0.90544838

0.91415806 0.92122688 0.92661155 0.93027889 0.93220625 0.93220625

0.93027889 0.92661155 0.92122688 0.91415806 0.90544838 0.89515085

0.88332762 0.87004937 0.85539458 0.83944875 0.82230355 0.80405595

0.78480729 0.76466232 0.74372824 0.72211377 0.69992818 0.6772804

0.65427809 0.63102687 0.60762948 0.58418507 0.56078857 0.5375301

0.51449442 0.49176057 0.46940149 0.44748374 0.42606735 0.40520569

0.38494543 0.3653266 0.34638266 0.32814069 0.3106216 0.29384037

0.27780639 0.26252377 0.24799173 0.23420498 0.22115413 0.20882607

0.19720444 0.18627003 0.17600115 0.16637406 0.15736337 0.14894236

0.14108333 0.13375795 0.12693754 0.12059333 0.11469669 0.10921938

0.10413374 0.0994128 0.09503048 0.09096169 0.08718237 0.08366964

0.08040181 0.07735839 0.06938855 0.04835225]

所以似乎不存在NaN值，我不明白它返回错误的原因是什么。

谁能帮帮我吗？谢谢！在