Here is an example of using the scipy minimize function for optimization:
python from scipy.optimize import minimize
Define the objective function to be minimized def objectivefunction(x): return x02 x12
Initial guess for the optimization initialguess 1, 1
Perform the optimization using the minimize function result minimize(objectivefunction, initialguess, method'Nelder-Mead')
Print the optimized result print(result.x)
In this example, we define an objective function that we want to minimize (in this case, a simple quadratic function). We then provide an initial guess for the optimization and use the minimize function from scipy to find the optimal solution.
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