使用python 3.x从scipy使用** curve_fit **函数拟合多个高斯

Question

I am trying to trimodal gaussian functions using scipy and python 3.x. I think I'm really almost there but I'm scratching my head here because I can't quite figure out what is going wrong with it.

        data =np.loadtxt('mock.txt')
        my_x=data[:,0]
        my_y=data[:,1]

        def gauss(x,mu,sigma,A):
            return A*np.exp(-(x-mu)**2/2/sigma**2)
        def trimodal_gauss(x,mu1,sigma1,A1,mu2,sigma2,A2,mu3,sigma3,A3):
            return gauss(x,mu1,sigma1,A1)+gauss(x,mu2,sigma2,A2)+gauss(x,mu3,sigma3,A3)



        """""
        Gaussian fitting parameters recognized in each file
        """""
        first_centroid=(10180.4*2+9)/9
        second_centroid=(10180.4*2+(58.6934*1)+7)/9
        third_centroid=(10180.4*2+(58.6934*2)+5)/9
        centroid=[]
        centroid+=(first_centroid,second_centroid,third_centroid)

        apparent_resolving_power=1200
        sigma=[]
        for i in range(len(centroid)):
            sigma.append(centroid[i]/((apparent_resolving_power)*2.355))

        height=[1,1,1]

        p=[]    

        p = [list(t) for t in zip(centroid, sigma, height)] 


        for i in range(9):
            popt, pcov = curve_fit(trimodal_gauss,my_x,my_y,p0=p[i]) 

Using this code, I get the following error.

TypeError: trimodal_gauss() missing 6 required positional arguments: 'mu2', 'sigma2', 'A2', 'mu3', 'sigma3', and 'A3'

I understand what the error message is saying but I don't think I understand how I'm not providing the 6 initial guesses.

I appreciate your input!

Answer 1

It looks like you are trying to call curve_fit nine separate times, and give it a different initial parameter guess by specifying p0=p[i] (which is probably not what your code does, because p is a nested list).

You should make sure that p is a one-dimensional array with 9 elements, and call curve_fit only once. Something like

p = np.array([list(t) for t in zip(centroid, sigma, height)]).flatten()
popt, pcov = curve_fit(trimodal_gauss,my_x,my_y,p0=p]) 

might work.