下面的python代码没有显示chi2和简化的chi2。它只显示变量和相关性。为什么会这样
代码如下所示
#!/usr/bin/env python
#<examples/doc_model1.py>
from numpy import sqrt, pi, exp, linspace, loadtxt
from lmfit import Model
import matplotlib.pyplot as plt
data = loadtxt('model1d_gauss.dat')
x = data[:, 0]
y = data[:, 1]
def gaussian(x, amp, cen, wid):
"1-d gaussian: gaussian(x, amp, cen, wid)"
return (amp/(sqrt(2*pi)*wid)) * exp(-(x-cen)**2 /(2*wid**2))
gmodel = Model(gaussian)
result = gmodel.fit(y, x=x, amp=5, cen=5, wid=1)
print(result.fit_report())
plt.plot(x, y, 'bo')
plt.plot(x, result.init_fit, 'k--')
plt.plot(x, result.best_fit, 'r-')
plt.show()
#<end examples/doc_model1.py>
输出如下
[[Model]]
Model(gaussian)
[[Variables]]
amp: 8.88021829 +/- 0.113594 (1.28%) (init= 5)
cen: 5.65866102 +/- 0.010304 (0.18%) (init= 5)
wid: 0.69765468 +/- 0.010304 (1.48%) (init= 1)
[[Correlations]] (unreported correlations are < 0.100)
C(amp, wid) = 0.577
是的,很抱歉,这已在git存储库的主分支中修复
您可以获取并打印出模型结果的任何属性的值(请参见https://lmfit.github.io/lmfit-py/model.html#modelresult-attributes),但在版本0.9.6中,这些值未作为拟合报告的一部分正确打印。再次,在主回购协议中修复
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