Minimization of many-variable function

[gaby287]

Hi, I'm learning python and I'm just trying to minimize a function of many variables, but I have some problems with my code.

import numpy as np
import scipy.optimize as op
from scipy.optimize import minimize

table1_np = np.genfromtxt('Data/tabla1.txt', usecols=0)
#--------------------------
def function(r0, rs):
      r0, rs = parameters
     return (r0*rs**3/table1_np[I])
def function2(parameters):
      return sum(table2_np[I] - function[I])
           x0=np.array[0.7, 1.1]
      res=minimize(function2, x0, method = 'nelder-mead', options={'xtol':1e-8, 'disp':True})

 

[jedishrfu]

Perhaps you could tell us more about the function you want to minimize and the steps you need to take to do it.

 

[jtbell]

I have some problems with my code

What are the symptoms of those problems?

 

[gaby287]

Well I have a table of data (table1_np) and I want to use it to define a function, but the problem is, that I don't know if the definition is correct, because what I need to do sum the elements of other table whit that function and after that minimize the result.

 

[mheslep]

There are some NameErrors in the code as you've likely seen. The tuple 'parameters' I believe you intend to be passed into the first function as it is the second function. Also the index name 'I', 'table2', etc.