forked from TheAlgorithms/Python
-
Notifications
You must be signed in to change notification settings - Fork 0
/
newton_raphson.py
45 lines (37 loc) · 1.53 KB
/
newton_raphson.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
# Implementing Newton Raphson method in Python
# Author: Syed Haseeb Shah (github.com/QuantumNovice)
# The Newton-Raphson method (also known as Newton's method) is a way to
# quickly find a good approximation for the root of a real-valued function
from __future__ import annotations
from decimal import Decimal
from sympy import diff, lambdify, symbols
def newton_raphson(func: str, a: float | Decimal, precision: float = 1e-10) -> float:
"""Finds root from the point 'a' onwards by Newton-Raphson method
>>> newton_raphson("sin(x)", 2)
3.1415926536808043
>>> newton_raphson("x**2 - 5*x + 2", 0.4)
0.4384471871911695
>>> newton_raphson("x**2 - 5", 0.1)
2.23606797749979
>>> newton_raphson("log(x) - 1", 2)
2.718281828458938
"""
x = symbols("x")
f = lambdify(x, func, "math")
f_derivative = lambdify(x, diff(func), "math")
x_curr = a
while True:
x_curr = Decimal(x_curr) - Decimal(f(x_curr)) / Decimal(f_derivative(x_curr))
if abs(f(x_curr)) < precision:
return float(x_curr)
if __name__ == "__main__":
import doctest
doctest.testmod()
# Find value of pi
print(f"The root of sin(x) = 0 is {newton_raphson('sin(x)', 2)}")
# Find root of polynomial
print(f"The root of x**2 - 5*x + 2 = 0 is {newton_raphson('x**2 - 5*x + 2', 0.4)}")
# Find value of e
print(f"The root of log(x) - 1 = 0 is {newton_raphson('log(x) - 1', 2)}")
# Find root of exponential function
print(f"The root of exp(x) - 1 = 0 is {newton_raphson('exp(x) - 1', 0)}")