I have a reasonably simple constrained optimization problem but get different answers depending on how I do it. Let's get the import and a pretty print function out of the way first:
import numpy as np
from scipy.optimize import minimize, LinearConstraint, NonlinearConstraint, SR1
def print_res( res, label ):
print("\n\n ***** ", label, " ***** \n")
print(res.message)
print("obj func value at solution", obj_func(res.x))
print("starting values: ", x0)
print("ending values: ", res.x.astype(int) )
print("% diff", (100.*(res.x-x0)/x0).astype(int) )
print("target achieved?",target,res.x.sum())
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The sample data …
python numpy mathematical-optimization scipy quadratic-programming