arithmetic_analysis/newton_raphson.py

@@ -1,8 +1,7 @@
 # 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.
-# https://en.wikipedia.org/wiki/Newton%27s_method
+# quickly find a good approximation for the root of a real-valued function
 from __future__ import annotations
 
 from sympy import diff, symbols, sympify
@@ -20,22 +19,7 @@ def newton_raphson(
     2.23606797749979
     >>> newton_raphson("log(x)- 1", 2)
     2.718281828458938
-    >>> from scipy.optimize import newton
-    >>> all(newton_raphson("log(x)- 1", 2) == newton("log(x)- 1", 2)
-    ...     for precision in (10, 100, 1000, 10000))
-    True
-    >>> newton_raphson("log(x)- 1", 2, 0)
-    Traceback (most recent call last):
-        ...
-    ValueError: precision must be greater than zero
-    >>> newton_raphson("log(x)- 1", 2, -1)
-    Traceback (most recent call last):
-        ...
-    ValueError: precision must be greater than zero
     """
-    if precision <= 0:
-        raise ValueError("precision must be greater than zero")
-
     x = start_point
     symbol = symbols("x")
 
@@ -54,7 +38,7 @@ def newton_raphson(
         if abs(function_value) < precision:
             return float(x)
 
-        x -= function_value / derivative_value
+        x = x - (function_value / derivative_value)
 
     return float(x)