scipy minimize 'numpy.ndarray' object is not callable

Question

I am having an issue with a section of code I am running. It's purpose is to find the vector that minimizes a function via scipy.opimize's minimize function with a constraint.

However, I keep getting thrown the following error

line 495, in minimize
constraints, callback=callback, **options) line 378, in _minimize_slsqp
fx = func(x), line 292, in function_wrapper
return function(*(wrapper_args + args), TypeError: 'numpy.ndarray' object is not callable

I am a little confused as to what I am doing wrong. The following code contains the function to be minimised and the constrain function.

def constraint1(w):
goal = 1
for i in range(w.shape[0]):
    goal - w[i]
return goal 
def lasso_var(w, *args):
var = w.T.dot(args[0]).dot(w)+args[1]*sum(abs(w))
return var

con1 = {'type': 'eq', 'fun': constraint1}

from scipy.optimize import minimize

sol = minimize(lasso_var(w, *(train_sig, 5)),\
            x0=w_equal,\
           constraints=con1)

where w is a vector and train_sig is a matrix.

Many Thanks for any aid you can give.

llllllllll · Accepted Answer · 2018-02-10 16:27:14Z

1

You should pass the function itself to minimize, instead of a evaluated value.

Your code is not a minimal, complete and verifiable example. So I don't know exactly your intention. But just use like this:

sol = minimize(lambda w: lasso_var(w, *(train_sig, 5)),
        x0=w_equal,
       constraints=con1)

answered Feb 10, 2018 at 16:27

llllllllll

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1 Comment

user8048576 Over a year ago

Excellent. That worked exactly as I'd hoped. Thank you very much. Shame on me for trying to follow online examples so religiously I guess.

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