---------- Forwarded message ----------

From:

**Alexandre Furlan** <[hidden email]>Date: 2016-11-04 14:59 GMT-02:00

Subject: using curve_fit with a fixed parameter

To:

[hidden email]Hi all,

I need to make a least square method of a model function, but a parameter of my

model function is fixed (I don't change it). I my case, I have :

def func(i,rij,eps,sigma) :

where, i is similar "x", rij is a array used to obtain some parameters of the function, and

eps and sigma are parameter that I want to optimize. I order to optimize these parameters I'm doing :

for i in arange(len(rij)/natoms) :

popt,pcov = curve_fit(LJ(i,rij,eps,sigma), x,Ek)

where x = x[i] and Ek[i]. When make it, I have :

TypeError('{!r} is not a Python function'.format(func))

TypeError: -0.019566048015813797 is not a Python function

Do you known how to do this type of optmization using curve_fit ?

many thanks for all

Best

Alexandre

_______________________________________________

SciPy-User mailing list

[hidden email]
https://mail.scipy.org/mailman/listinfo/scipy-user