I am getting 'TypeError: 'numpy.float64' object is not callable'

Question

I have a test function that i am trying to minimize using scipy.optimize but i get the error above.My test function A has for variables which are between 0-100.And the sum of these variables(4) should add up to 100.sum(A)=100.I tried solving the error reading through previous similar cases but I could not.The solution should be 2500,that is the minimum because i solved with gekko optimizer and now am trying to switch to Scipy.Can anyone tell me or show me where am doing wrong?The code is below:

import numpy as np                                                                 
from scipy.optimize import minimize                                                




def test_function(x):                                                              
    return np.dot(x, x)                                                            


A = np.zeros(4)                                                                    
# bnds = ([0, 100], [0, 100], [0, 100], [0, 100])                                  
bnds = tuple((0, 100) for x in range (len(A)))                                     
x0 = [1, 5, 5, 1]                                                                  


def constraint1(A):                                                                
    sum = 100                                                                      
    for i in range(4):                                                             
        sum = sum - A[i]                                                           
    return sum                                                                     


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

sol = minimize(test_function(A), x0, method='SLSQP', bounds=bnds, constraints=con1)

the error is below;

Traceback (most recent call last):
  File "C:/Users/Lenovo/Desktop/truss-opt/optimisation2/test_example.py", line 24, in <module>
    sol = minimize(test_function(A), x0, method='SLSQP', bounds=bnds, constraints=con1)
  File "C:\Users\Lenovo\Anaconda3\envs\practice1\lib\site-packages\scipy\optimize\_minimize.py", line 608, in minimize
    constraints, callback=callback, **options)
  File "C:\Users\Lenovo\Anaconda3\envs\practice1\lib\site-packages\scipy\optimize\slsqp.py", line 399, in _minimize_slsqp
    fx = func(x)
  File "C:\Users\Lenovo\Anaconda3\envs\practice1\lib\site-packages\scipy\optimize\optimize.py", line 326, in function_wrapper
    return function(*(wrapper_args + args))
TypeError: 'numpy.float64' object is not callable

Process finished with exit code 1

Here is an example problem in Gekko and Scipy.optimize.minimize that may also help others looking to translate between the two: https://apmonitor.com/che263/index.php/Main/PythonOptimization — John Hedengren, Jul 15 '22 at 03:22

score 0 · Accepted Answer · answered Jan 25 '20 at 12:41

You need to send the function name to minimize() instead of calling it. The changed code would be

sol = minimize(test_function, x0, method='SLSQP', bounds=bnds, constraints=con1)

if you want to optimize test_function. Replace test_function with constraint1 if you want to optimize for constraint1.

I am getting 'TypeError: 'numpy.float64' object is not callable'

1 Answers1