Multiple variables in SciPy's optimize.minimize
Solution 1:
Pack the multiple variables into a single array:
import scipy.optimize as optimize
def f(params):
# print(params) # <-- you'll see that params is a NumPy array
a, b, c = params # <-- for readability you may wish to assign names to the component variables
return a**2 + b**2 + c**2
initial_guess = [1, 1, 1]
result = optimize.minimize(f, initial_guess)
if result.success:
fitted_params = result.x
print(fitted_params)
else:
raise ValueError(result.message)
yields
[ -1.66705302e-08 -1.66705302e-08 -1.66705302e-08]