lmfit 未按预期执行

Question

我正在编写一个脚本，该脚本将用于使用自定义模型拟合一些光致发光光谱，在使用 SciPy 创建脚本后，我了解到如果 lmfit 则设置拟合参数的界限要容易得多(cars9.uchicago.edu/software/python/lmfit/intro.html) 被改用了，所以我决定改用它。下面是我编写的脚本，用于将一个光谱与一个高斯函数拟合（使用 2 个高斯函数更好，但我想从一个更简单的案例开始）。

    from numpy import loadtxt, vstack, average, exp
import matplotlib.pyplot as plt
import lmfit

def sub_BG(data_array):
    naujas_X = data_array[:,1]-average(data_array[1:10,1])
    return vstack((data_array[:,0], naujas_X)).T

def gauss(x, a1, b1, c1):
    return  a1 * exp(-(x- b1)**2/ (2*c1**2))
           #amp * exp(-(x-cen)**2 /wid) 


data="single_spectra.txt"

spectra = loadtxt(open(data, 'r'), skiprows=2)


spectra_beBG = sub_BG(spectra)

plt.plot(spectra_beBG[:,0],spectra_beBG[:,1],'g')


mod1 = lmfit.Model(gauss)

pars = lmfit.Parameters()
#             (Name,  Value,  Vary,   Min,  Max,  Expr)
pars.add_many(('a1', 590, True, None, None, None),
              ('b1', 500, True, None, None, None),
              ('c1', 20, True, None, None , None))

out  = mod1.fit(spectra_beBG[:,0], pars, x=spectra_beBG[:,1])

y = gauss(spectra_beBG[:,0], 
          out.best_values["a1"],
          out.best_values["b1"],
          out.best_values["c1"])


plt.plot(spectra_beBG[:,0], out.best_fit, "r--")
plt.plot(spectra_beBG[:,0], y, "b--")
print(out.fit_report())

这个returns:

[[Model]]
    Model(gauss)
[[Fit Statistics]]
    # function evals   = 77
    # data points      = 1024
    # variables        = 3
    chi-square         = 28469283.530
    reduced chi-square = 27883.725
[[Variables]]
    a1:   561.593868 +/- 8.255604 (1.47%) (init= 590)
    b1:   100.129107 +/- 85.34384 (85.23%) (init= 500)
    c1:   1.3254e+06 +/- 7.23e+05 (54.52%) (init= 20)
[[Correlations]] (unreported correlations are <  0.100)
    C(b1, c1)                    = -0.892 
    C(a1, c1)                    = -0.763 
    C(a1, b1)                    =  0.685

Graph output1

如果我把pars.add_many()改成更接近自然的东西，例如：

pars.add_many(('a1', 590, True, 550, 630, None),
              ('b1', 500, True, 450, 650, None),
              ('c1', 30, True, 20, 70 , None))

我明白了：

[[Model]]
    Model(gauss)
[[Fit Statistics]]
    # function evals   = 147
    # data points      = 1024
    # variables        = 3
    chi-square         = 304708538.428
    reduced chi-square = 298441.272
[[Variables]]
    a1:   629.999937 +/- 0        (0.00%) (init= 590)
    b1:   475.821359 +/- 0        (0.00%) (init= 500)
    c1:   70         +/- 0        (0.00%) (init= 30)
[[Correlations]] (unreported correlations are <  0.100)

Graph output2

帮忙？

Answer 1

嗯，应该是吧

out  = mod1.fit(spectra_beBG[:,1], pars, x=spectra_beBG[:,0])

即你想要拟合"y"，并传入"pars"和"x"数组，以帮助计算具有这些参数和自变量的模型。

lmfit 未按预期执行

lmfit not performing as expected

python

curve-fitting

scipy

lmfit