获取Scipy Livessq中的变量以使用它们

Question

我需要获取拟合结果，以在每个最小值_sq运行中创建的每个参数。 谁能指导我从scipy distsq中的函数参数推断出的参数名称？

Answer 1

**好消息！
使用 lmfit 如此出色的包装！**

from scipy.optimize import least_squares
from matplotlib.pylab import plt
import numpy as np
from numpy import exp, linspace, random
from lmfit import Model


def gaussian(x, amp, cen, wid):
    return amp * np.exp(-(x-cen)**2 / wid)


x = linspace(-10, 10, 101)
y = gaussian(x, 2.33, 0.21, 1.51) + random.normal(0, 0.2, len(x))

gmodel = Model(gaussian)
params = gmodel.make_params()
print('parameter names: {}'.format(gmodel.param_names))
print('independent variables: {}'.format(gmodel.independent_vars))
result = gmodel.fit(y, params, x=x, amp=5, cen=5, wid=1)
print(result.fit_report())
[n many cases we might want to extract parameters and standard error estimates programatically rather than by reading the fit report][1]