How to use optimizer in Scipy how does root works in scipy

This recipe helps you use optimizer in Scipy how does root works in scipy

Recipe Objective - How to use optimizer in Scipy, how does root works in scipy?

SciPy optimizers are a set of procedures which provides functions for minimizing the function value and roots of the function. It includes the non-linear problems, root finding and curve fitting.

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Minimizing the Function:

We can use "scipy.optimize.minimize()" function for minimizing

Arguments used inside the minimize() function:

1.fun:- function represents the equation.

2.x0:- initial guess for roots

3.method:- name of method e.g. - 'CG', 'BGFS', 'Newton-CG', 'L-BFGS-B'.

Example:- Minimize the function "x^2 + x + 3" with BFGS:

from scipy.optimize import minimize

def eqan(x):
  return x**2 + x + 3

min_val = minimize(eqan, 0, method='BFGS')

print(min_val)

Roots of the Equation

Scipy is very useful for finding the roots for non-linear equations.

And For that we can use scipy's "optimze.root" function.

Arguments used inside the minimize() function:

This function takes two arguments.

1.fun:- function represents the equation.

2.x0:- initial guess for roots

Example:- Find root of the equation x + sin(x):

from scipy.optimize import root
from math import sin

def eqan(x):
  return x + sin(x)

root_val = root(eqan, 0)

print(root_val.x)

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