pythematics 2.0.1

Python Math library for Matrix and Polynomial manipulation extending to the complex plane

Pythematics

Pythematics is a zero-dependency math library for Python that aims to extend some Mathematical fields that are seemingly abandoned by other libraries while offering a fully Pythonic experience.

The main field that this library aims to enhance to Python is Polynomials in a way that allows for super-complicated and high degree equations to be solved giving all Real and Complex Solutions as well as combining it with fields such as Linear Algebra and allowing for Matrix-Polynomial Manipulation methods like finding Eigenvalues and Eigenvectors.

Pythematics can also be used as an ordinary math module since it contains various sub-packages for computations in Trigonometry, Number Theory and other fields such as Random Number Generation or Calculus

The thing that makes this library unique is the ability to Interact will Polynomials at the following format:

import pythematics.polynomials as pl

x = pl.x

side_1 = x*(3*x**2 + 5*x**4 - x**5) #The first side of our equation
side_2 = x**2 * (x+1) #The second side
final_polynomial = side_1 - side_2 #Bring Everything to one side
roots = final_polynomial.roots(iterations=50) #Find the roots of the resulting Polynomial
for root in roots:
    print(f'{root} : {final_polynomial.getFunction()(root)}')

And the system will then find all the roots of the reduced Polynomial Complex and Real

(5.07012959493235-3.189748897278739e-31j) : (4.575895218295045e-12+1.0966369421494688e-27j)
(-8.873587068586144e-08-1.5544092660081612e-08j) : (-7.63243719853339e-15-2.7586379192868285e-15j)
(-0.223346113995466-0.6883968692907642j) : (-5.551115123125783e-17+0j)
(-0.22334611399546603+0.6883968692907642j) : (-5.551115123125783e-17+0j)
(0.3765626330585808-5.3106647549566e-139j) : -2.946986968335106e-139j
(8.873587068586141e-08+1.554409266008162e-08j) : (-7.632434660972042e-15-2.758636465569371e-15j)

In the Left Side are the solutions to the equation while on the right are these values substituted into the equation, and the numbers you see here are some number raise to a high negative power like e-139 which is infinitesimal and very close to zero

Linear Algebra is another huge part of this module which was, in fact the Inspiration for it's creation

Here is an example of solving a Linear System of equations of Dimensions 3x3

A = Matrix([ #The Matrix
    [1,2,3], 
    [4,7,8],
    [5,10,11]
])

unknowns = ('x','y','z') #Our Varaibles
Output = Vector([10,15,25]) #Our Target Output

print(A.solve(Output,unknowns)) #Using Cramer's rule of the determinants
print(A.solve(Output,unknowns,useRef=True)) #Using Row Reduction

And as expected the results are identical dispite a small floating point error

{'x': -8.75, 'y': 0.0, 'z': 6.25}
{'x': -8.749999999999993, 'y': -6.217248937900877e-15, 'z': 6.250000000000002}

if you seem interested in this library you can check the documentation on Github