PERT fit with curve_fit function

Hello,

I tried to use the curve_fit function to find the low, peak, high and lmb
parameters that minimize the error of the probability function of the PERT
distribution, but I'm having some trouble.

I can't see my error, and I keep getting [1. 1. 1. 1.] outputs for the
parameters.

Do you have any idea?

Thanks in advance,

Below my code :

>
> *import numpy as np*
> *from scipy.optimize import curve_fit*
> *from scipy.special import gamma as gamma*
> *from scipy.special import beta**from scipy.stats import beta as
> beta_dist*



> *def pdf_pert(x, low, peak, high, lmb):*
> *    alpha = 1+ lmb*((peak-low)/(high-low))*
> *    beta = 1+ lmb*((high-peak)/(high-low))**    return gamma(alpha+beta)
> * ((x-low)**(alpha-1)) * ((high-x)**(beta-1)) / (gamma(alpha)*gamma(beta) *
> ((high-low)**(alpha+beta-1)))*



> *x = tfd.PERT(1, 2, 10).sample(1000000)*
> *hist = np.histogram(x, density=True)*
> *y = hist[0]**x = (hist[1][1:]+hist[1][:-1])/2*



> *popt2,pcov2 = curve_fit(pertfunc,x,y)**print(popt2)*

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