How to do the Bisection method in Python

Question

I want to make a Python program that will run a bisection method to determine the root of:

f(x) = -26 + 85x - 91x2 +44x3 -8x4 + x5

The Bisecti

Answer 1

I'm trying to make some modifications :

1. While loop : the tolerance and the number of iterations performed by the algorithm
2. save in addition to the root approach, the vector of points generated by the algorithm xn (all c points), the vector of all images f(c)
3. Assuming Xs is a given approximation of the root, save the absolute error np.linalg.norm(Xs-xn)
4. Save the approximate error : np.linalg.norm(xn+1 - xn).

This is my code:

import numpy as np
def bisection3(f,x0,x1,tol,max_iter):
    c = (x0+x1)/2.0
    x0 = c
    Xs = 0.3604217029603
    err_Abs = np.linalg.norm(x0-Xs)
    itr = 0
    f_x0 = f(x0)
    f_x1 = f(x1)
    xp = [] # sucesion que converge a la raiz
    errores_Abs = []
    errores_Aprox = []
    fs = [] # esta sucecion debe converger a cero 
    while(((x1-x0)/2.0 > tol) and (itr< max_iter)):
        if f(c) == 0:
            return c
        elif f(x0)*f(c) < 0:
            x1 = c
        else :
            x0 = c
        c = (x0+x1)/2.0    
        itr +=1
        err_Abs = np.linalg.norm(x0-Xs)
        err_Aprox = np.linalg.norm(x1 - x0)
        fs.append(f(c))
        xp.append(c)
        errores_Abs.append(err_Abs)
        errores_Aprox.append(err_Aprox)
    return x0,errores_Abs, errores_Aprox,fs,xp

And i have an example of execution :

f  = lambda x : 3*x + np.sin(x) - np.exp(x)
X0_r1 ,  err_Abs_r1,err_Aprox_r1, fs_r1 , xp_r1 =   bisection3(f,0,0.5,1e-5,100)