Den*_*kir 3 python windows parameters lmfit
我编写了一个程序来拟合一些拉曼光谱峰值。\n我需要返回拟合的参数（位置、幅度、HWHM）。
\n\n我使用 modul lmfit 创建一个带有约束的洛伦兹峰。
\n\n根据我的图形，拟合峰值和原始数据之间有很好的一致性。\n但是当拟合后提取参数时，我遇到了一个问题，程序仅返回初始值。
\n\n我绑定了“report_fit 模块”并更改了初始参数，但没有成功。参数值不会变化。
\n\n令我困扰的是，这个程序在我同事的电脑上运行，但在我的电脑上运行不了。\n所以问题可能出在我的 python 版本上。
\n\n我正在使用spyder 2.3.9，并在Windows 10下使用anaconda安装了python 3.4。\nlmfit模块0.9.3似乎可以部分工作，因为我可以获得一个很好的拟合协议（从图plt.plot中）。\n但是拟合后无法返回参数值。
\n\n这是我的代码：
\n\n#!/usr/bin/python3\n# -*- coding:utf-8 -*-\n\nimport os\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom math import factorial\nfrom scipy.interpolate import interp1d\nfrom lmfit import minimize, Parameters #,report_fit\n\n##############################################################################\n# Fit of Raman peaks\n\ndef fmin150(pars,x,y): \n amp= pars[\'Amp_150\'].value\n cent=pars[\'Cent_150\'].value\n hwhm=pars[\'Wid_150\'].value\n a=pars[\'a_150\'].value\n b=pars[\'b_150\'].value\n peak = (amp*hwhm)/(((x-cent)**2)+(hwhm**2)) + ((a*x)+b)\n return peak - y \n\ndef fmin220(pars,x,y): \n amp= pars[\'Amp_220\'].value\n cent=pars[\'Cent_220\'].value\n hwhm=pars[\'Wid_220\'].value\n a=pars[\'a_220\'].value\n b=pars[\'b_220\'].value\n peak = (amp*hwhm)/(((x-cent)**2)+(hwhm**2)) + ((a*x)+b)\n return peak - y \n\ndef fmin2d(pars,x,y): \n amp= pars[\'Amp_2D\'].value\n cent=pars[\'Cent_2D\'].value\n hwhm=pars[\'Wid_2D\'].value\n a=pars[\'a_2D\'].value\n b=pars[\'b_2D\'].value\n peak = (amp*hwhm)/(((x-cent)**2)+(hwhm**2)) + ((a*x)+b)\n return peak - y \n\n##############################################################################\ndef fit(filename):\n """\n Fit Raman spectrum file\n Return filename, for each peak (*f*whm, position, height) \n PL (Position, Intensity, Area)\n """\n print ("----------------------------")\n print("Treating file : ")\n print(filename)\n try:\n data = np.loadtxt(filename)\n except:\n print("Unable to load file")\n\n xx=data[:,0]\n yy=data[:,1]\n #### Define fitting interval ##### \n # Cu oxides (unit\xc3\xa9s en cm-1)\n xminim150 = 120\n xmaxim150 = 170\n xminim220 = 175\n xmaxim220 = 275\n xminim300 = 280\n xmaxim300 = 340\n xminim640 = 345\n xmaxim640 = 800\n # Graphene\n xminimG = 1540\n xmaximG = 1680\n xminim2D = 2600\n xmaxim2D = 2820\n\n # Definition Baground = place without the fitted peaks\n zone1 = (xx > min(xx)) & (xx < xminim150)\n zone2 = (xx > xmaxim150) & (xx < xminim220)\n zone3 = (xx > xmaxim220) & (xx < xminim300)\n zone4 = (xx > xmaxim300) & (xx < xminim640)\n zone5 = (xx > xmaxim640) & (xx < xminimG)\n zone6 = (xx > xmaximG) & (xx < xminim2D)\n zone7 = (xx > xmaxim2D) & (xx < max(xx))\n\n x_BG = np.concatenate((xx[zone1],xx[zone2],xx[zone3],xx[zone4],xx[zone5],xx[zone6],xx[zone7]))\n y_BG = np.concatenate((yy[zone1],yy[zone2],yy[zone3],yy[zone4],yy[zone5],yy[zone6],yy[zone7]))\n\n\n #Creation de l\'interpolation lineaire\n f1 = interp1d(x_BG, y_BG, kind=\'linear\')\n xinterpmin= x_BG[0] # valeur de x_BG min\n xinterpmax= x_BG[len(x_BG)-1] # valeur de x_BG max\n nbxinterp = len(xx) * 4 #(nb de point en x)* 4 pour une interpolation correcte\n\n xnew = np.linspace(xinterpmin, xinterpmax, num=nbxinterp, endpoint=True)\n ynew= f1(xnew)\n########################## Fit 2D peaks ############################### \n # create a set of Parameters\n pars150 = Parameters()\n pars220 = Parameters()\n pars300 = Parameters()\n pars640 = Parameters()\n parsg = Parameters() \n pars2d = Parameters()\n\n ##### Cu2O pic 150 cm-1 #####\n pars150.add(\'Amp_150\', value=10, min=0.0001, max=100000) # Amplitude ~intensity\n pars150.add(\'Cent_150\', value=150, min=140, max=160) # Center ~position\n pars150.add(\'Wid_150\', value=5, min=4, max=15 ) # Width is the HWHM\n pars150.add(\'a_150\', value=1, min=-100000, max=100000) \n pars150.add(\'b_150\', value=10, min=-100000, max=100000)\n ##### Cu2O pic 220 cm-1 #####\n pars220.add(\'Amp_220\', value=10, min=0.0001, max=100000)\n pars220.add(\'Cent_220\', value=220, min=200, max=230)\n pars220.add(\'Wid_220\', value=5, min=4, max=15 )\n pars220.add(\'a_220\', value=1, min=-100000, max=100000) \n pars220.add(\'b_220\', value=10, min=-100000, max=100000)\n ##### Graphene 2D #####\n pars2d.add(\'Amp_2D\', value=15, min=0.0001, max=100000)\n pars2d.add(\'Cent_2D\', value=2711, min=2670, max=2730)\n pars2d.add(\'Wid_2D\', value=15, min=4, max=25 )\n pars2d.add(\'a_2D\', value=1, min=-100000, max=100000) \n pars2d.add(\'b_2D\', value=10, min=-100000, max=100000)\n\n # define x for each peaks\n interv_150 = (xx > xminim150) & (xx < xmaxim150)\n x_150 = xx[interv_150]\n y_150 = yy[interv_150]\n interv_220 = (xx > xminim220) & (xx < xmaxim220)\n x_220 = xx[interv_220]\n y_220 = yy[interv_220]\n\n interv_2D = (xx > xminim2D) & (xx < xmaxim2D)\n x_2D = xx[interv_2D]\n y_2D = yy[interv_2D]\n ###########################################################\n # Performe FIT with leastsq model ###########\n result_150 = minimize(fmin150, pars150, args=(x_150, y_150))\n result_220 = minimize(fmin220, pars220, args=(x_220, y_220))\n result_2D = minimize(fmin2d, pars2d, args=(x_2D, y_2D))\n\n # calculate final result\n final_150 = y_150 + result_150.residual\n final_220 = y_220 + result_220.residual\n final_2D = y_2D + result_2D.residual\n\n ###########################################################\n # Parameter after fit #\n amp_150= pars150[\'Amp_150\'].value\n cent_150=pars150[\'Cent_150\'].value\n fwhm_150=2*pars150[\'Wid_150\'].value\n\n amp_220= pars220[\'Amp_220\'].value\n cent_220=pars220[\'Cent_220\'].value\n fwhm_220=2*pars220[\'Wid_220\'].value\n\n amp_2D= pars2d[\'Amp_2D\'].value\n cent_2D=pars2d[\'Cent_2D\'].value\n fwhm_2D=2*pars2d[\'Wid_2D\'].value\n\n ###########\n #Plot data#\n plt.plot(xx, yy, \'k+\' ,x_150, final_150, \'r\', x_220, final_220,\'r\', x_2D, final_2D,\'b\')\n plt.xlabel(r\'Raman shift (cm$^{-1}$)\', fontsize=14)\n plt.ylabel(\'Intensity (a.u.)\', fontsize=14)\n plt.xlim(0,3000)\n plt.title(filename, fontsize=16)\n savename=filename[:-4]+".png"\n print(savename)\n plt.savefig(savename)\n plt.clf()\n\n return filename, amp_150, cent_150, fwhm_150, amp_220, cent_220, fwhm_220, amp_2D, cent_2D, fwhm_2D\n\n\ndef main():\n """main program loop"""\n print("----------------------------")\n liste = []\n for filename in os.listdir(os.getcwd()):\n if filename.endswith(".txt"):\n liste.append(filename)\n\n f1 = open("TestFit_all.dat","w")\n header = "Filename\\tI_150\\tCentre_150\\tFWHM_150\\tI_220\\tCentre_220\\tFWHM_220\\tI_300\\tCentre_300\\tFWHM_300\\tI_640\\tCentre_640\\tFWHM_640\\tI_G\\tCentre_G\\tFWHM_G\\tI_2D\\tCentre_2D\\tFWHM_2D\\tI_PL\\tI_PL_err\\tCent_PL\\tCent_PL_err\\tArea1000_PL\\n"\n f1.write(header)\n for i in liste:\n txt=fit(i)\n print(txt)\n #text = str(txt[0])+"\\t"+str(txt[1])+"\\t"+str(txt[2])+"\\t"+str(txt[3])+"\\t"+str(txt[4])+"\\t"+"\\n"\n text = str(txt[0])+"\\t"+str(txt[1])+"\\t"+str(txt[2])+"\\t"+str(txt[3])+"\\t"+str(txt[4])+"\\t"+str(txt[5])+"\\t"+str(txt[6])+"\\t"+str(txt[7])+"\\t"+str(txt[8])+"\\t"+str(txt[9])+"\\t"+"\\t"+"\\n"\n f1.write(text)\n\n f1.close()\n\n print("----------------------------")\n print("Done")\n###################################################################\n# start\n\nif __name__ == "__main__":\n main() \n谢谢你的帮助 ：）
\n\n请将您的回复发送至deniz.cakir@etu.umontpellier.fr
\n您的脚本可以短得多来说明问题。但是，最终的参数被保留result_150.params等等。传入的参数minimize()在拟合中不会改变。
嗯，对于 lmfit 0.9.0 及更高版本来说也是如此。也许您的同事在 lmfit 上有旧版本。
