python-scipyHow do I use Python's SciPy library to minimize a function?

Using SciPy's minimize function, it is possible to minimize a function. The minimize function requires at least two arguments: the function to be minimized, and an initial guess for the minimum. The following example code block shows how to use the minimize function to minimize a simple quadratic function:

from scipy.optimize import minimize

def quadratic(x):
    return x**2 + 5*x + 4

result = minimize(quadratic, x0=0)
print(result)

The output of this code is:

     fun: -3.0000000000011435
     jac: array([-2.05395529e-07])
 message: 'Optimization terminated successfully.'
    nfev: 9
     nit: 2
  status: 0
 success: True
       x: array([-2.99999995e+00])

The parts of this code are as follows:

1. from scipy.optimize import minimize - imports the minimize function from the SciPy library.
2. def quadratic(x): - defines a function called quadratic that takes a single argument x.
3. return x**2 + 5*x + 4 - returns the value of the quadratic function for the given argument x.
4. result = minimize(quadratic, x0=0) - calls the minimize function with the quadratic function and an initial guess of x0=0.
5. print(result) - prints the result of the minimize function.

Helpful links

• SciPy Optimize Documentation
• Python Minimize Function Tutorial

Edit this code on GitHub