What is the method for constraining bounded args of the objective in Scipy minimize using the TNC method?

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To constrain bounded arguments of the objective in Scipy minimize using the TNC method, you can use the bounds parameter of the minimize function. Here's an example code snippet:

from scipy.optimize import minimize

# define your objective function here
def objective(x):
    # your objective function code here

# define your bounds here
bounds = [(0, 1), (2, 5), (-10, 10)]  # example bounds

# call the minimize function with the TNC method and bounds parameter
result = minimize(objective, x0, method='TNC', bounds=bounds)

# the result object contains the solution, success status, etc.
print(result)

In the bounds list, each element corresponds to a variable in the objective function. The element is a tuple with two values, the lower and upper bounds for that variable. If you don't want to constrain a variable, you can use None as the lower or upper bound value.