Optimizing with more variables in Python

Question

I have two simple arrays in Python and I would like to minimize the sumproduct of these arrays with respect to given target value by changing the values in the first array. Here is an example:

import numpy as np
from scipy.optimize import fmin

def func2(params):
    a, b, c = params
    arr1 = [a, b, c]
    arr2 = [150, 200, 230]
    res = sum(np.multiply(arr1, arr2))
    tar = 2
    error = res - tar
    return error

initial_guess = [0.0025, 0.0030, 0.0035]
finarr = fmin(func2, initial_guess) 
print(finarr)

The code above runs but I receive wrong results because the numbers in first array should be ~ 0.0027, 0.0033 and 0.0040. I would be grateful if someone can help me. Thank you.

Why should the solution be [0.0027, 0.0033, 0.0040] and not [0, 0.01, 0]? — mkrieger1
– mkrieger1, Commented Sep 15, 2021 at 15:04

Wael Reda · Accepted Answer · 2021-09-15 15:24:56Z

1

You need to return the absolute value of the error in func2.

error = abs(res - tar)

edited Sep 15, 2021 at 15:24

answered Sep 15, 2021 at 15:15

Wael Reda

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2 Comments

Wael Reda Over a year ago

You're welcome. notice that output depends on your initial guess. for instance, if you negate all elements in the initial guess, you would get different results as the error is independent of the sign of the result in comparison with the target value.

nicktrent Over a year ago

For me, that is an important additional information. Many thanks for that.

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