Mathematical Functions in Python
THIS ARTICLE IS STILL IN EDITING MODE
Contents
Introduction
Python has a built-in module math which defines various mathematical functions. In addition to math module, there is a fundamental package for scientific computing in Python named NumPy (Numerical Python). It is an open source Python library and contains multidimensional array and matrix data structures. In this section, examples of both methods will be presented.
For using math, we must first import this module:
import math
For using `NumPy`, we must first install it. There is no prerequisite for installing NumPy except Python itself. We can use `pip` or `conda` for this purpose:
'pip'
pip install numpy
'conda'
conda install numpy
We must import `numpy` to access it and its functions. We also shorten the imported name to `np` for better readability of code using NumPy:
import numpy as np
Mathematical Functions
Basic Functions
Some basic functions for my fellow students. Some functions need the module `math`. Please check out the introduction at the top. :)
math | Description |
---|---|
math.ceil(x) | Rounds the number x up to the next integer |
math.floor(x) | Rounds the number x down to the next integer |
math.com (n,k) | Binomial Coefficient: number of possible k choose n without order |
math,factorial(n) | Returns n factorial if n >= 0 |
abs(x) | Returns the absolute value of x |
math.ceil(5.3) 6
math.floor(173.123) 173
math.factorial(4) 24
abs(-17.2) 17.2
Power Functions
built-in function | math | numpy | Description |
---|---|---|---|
pow(x, y, mod) | math.pow(x, y, mod) | np.power(x1, x2,...) | x to the power of y. x1, x2 array_like |
Examples
pow (2,2)=4 ##Square
pow (2,3)=8 ##=Cube
pow (3,4, mode: 10) The value of (3**4) % 10 is = 1
##The exponents of two 1-Darray ar1 = [3, 5, 7, 2, 4] ar2 = [6, 2, 5, 3, 5] arr = np.power(ar1,ar2) arr: array([ 729, 25, 16807, 8, 1024], dtype=int32)
##The power vales of 2-D array ar1 = np.array([[3,4,3],[6,7,5]]) ar2 =np.array([[4,2,7],[4,2,1]]) arr = np.power(ar1,ar2) arr: array([[ 81, 16, 2187], [1296, 49, 5]], dtype=int32)
Root Functions
To implement root funtions in python we can use the built-in power function. Alternatively we can use 'math' or 'numpy'.
built-in power function | math | numpy | Description |
---|---|---|---|
x**(1/2) | math.sqrt(x) | np.sqrt(x) | Returns the square root of x |
x**(1/3) | math.powe(x, 1/3) | np.cbrt(x) | Returns the cube root of x |
x**(1/n) | math.pow(x, 1/n) | np.power(x, 1/n) | Returns the nth root of x |
Examples
- 'built-in function'
0** (1/2) 0.0
9** (1/3) 2.0
120** (1/10) 1.6140542384620635
- 'math'
math.sqrt(0) 0.0
math.pow(9, 1/3) 2.0
math.pow(120, 1/10) 1.6140542384620635
- 'numpy'
np.sqrt(0) 0.0
np.cbrt(9) 2.0
np.power(120, 1/10) 1.6140542384620635