P-unit_model/introduction/test_minimize.py
2020-02-14 14:33:58 +01:00

18 lines
367 B
Python

from scipy.optimize import minimize
import numpy as np
def main():
guess = np.zeros(3)
fmin = minimize(fun=cost1, x0=guess, args=(3, 20, -25), method="Nelder-Mead")
print(np.mean(fmin["final_simplex"][0], axis=0))
print(fmin)
def cost1(X, a=2, b=9, c=15):
return (X[0]-a)**2 + (X[1]-b)**2 + (X[2]-c)**2
if __name__ == '__main__':
main()