From f4779bc04ae706b0c548e2fe6d7a59efe8b85524 Mon Sep 17 00:00:00 2001
From: Rohit Joshi <34398948+rohitjoshi21@users.noreply.github.com>
Date: Sun, 15 Dec 2019 13:12:07 +0545
Subject: [PATCH] Bug Fixed in newton_raphson_method.py (#1634)

* Bug Fixed

* Fixed newton_raphson_method.py

* Fixed newton_raphson_method.py 2

* Fixed newton_raphson_method.py 3

* Fixed newton_raphson_method.py 4

* Fixed newton_raphson_method.py 5

* Fixed newton_raphson_method.py 6

* Update newton_raphson_method.py

* Update newton_raphson_method.py

* # noqa: F401, F403

* newton_raphson

* newton_raphson

* precision: int=10 ** -10

* return float(x)

* 3.1415926536808043

* Update newton_raphson_method.py

* 2.23606797749979

* Update newton_raphson_method.py

* Rename newton_raphson_method.py to newton_raphson.py
---
 arithmetic_analysis/newton_raphson.py        | 40 ++++++++++++++++++++
 arithmetic_analysis/newton_raphson_method.py | 34 -----------------
 2 files changed, 40 insertions(+), 34 deletions(-)
 create mode 100644 arithmetic_analysis/newton_raphson.py
 delete mode 100644 arithmetic_analysis/newton_raphson_method.py

diff --git a/arithmetic_analysis/newton_raphson.py b/arithmetic_analysis/newton_raphson.py
new file mode 100644
index 000000000..8aa816cd0
--- /dev/null
+++ b/arithmetic_analysis/newton_raphson.py
@@ -0,0 +1,40 @@
+# 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 decimal import Decimal
+from math import *  # noqa: F401, F403
+from sympy import diff
+
+
+def newton_raphson(func: str, a: int, precision: int=10 ** -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 = a
+    while True:
+        x = Decimal(x) - (Decimal(eval(func)) / Decimal(eval(str(diff(func)))))
+        # This number dictates the accuracy of the answer
+        if abs(eval(func)) < precision:
+            return float(x)
+
+
+# Let's Execute
+if __name__ == "__main__":
+    # Find root of trigonometric function
+    # 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 Square Root of 5
+    print(f"The root of log(x) - 1 = 0 is {newton_raphson('log(x) - 1', 2)}")
+    # Exponential Roots
+    print(f"The root of exp(x) - 1 = 0 is {newton_raphson('exp(x) - 1', 0)}")
diff --git a/arithmetic_analysis/newton_raphson_method.py b/arithmetic_analysis/newton_raphson_method.py
deleted file mode 100644
index 646b352a9..000000000
--- a/arithmetic_analysis/newton_raphson_method.py
+++ /dev/null
@@ -1,34 +0,0 @@
-# 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 sympy import diff
-from decimal import Decimal
-
-
-def NewtonRaphson(func, a):
-    """ Finds root from the point 'a' onwards by Newton-Raphson method """
-    while True:
-        c = Decimal(a) - (Decimal(eval(func)) / Decimal(eval(str(diff(func)))))
-
-        a = c
-
-        # This number dictates the accuracy of the answer
-        if abs(eval(func)) < 10 ** -15:
-            return c
-
-
-# Let's Execute
-if __name__ == "__main__":
-    # Find root of trigonometric function
-    # Find value of pi
-    print("sin(x) = 0", NewtonRaphson("sin(x)", 2))
-
-    # Find root of polynomial
-    print("x**2 - 5*x +2 = 0", NewtonRaphson("x**2 - 5*x +2", 0.4))
-
-    # Find Square Root of 5
-    print("x**2 - 5 = 0", NewtonRaphson("x**2 - 5", 0.1))
-
-    # Exponential Roots
-    print("exp(x) - 1 = 0", NewtonRaphson("exp(x) - 1", 0))