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unimath — Mathematical Environment Library in Python

unimath is a Python library that provides an abstract mathematical environment designed to represent and manipulate sets, intervals, and number systems in a symbolic and intuitive way.

The project is continuously growing, with new mathematical structures and operations being added every day.

Developed and maintained by a Mathematics undergraduate student at Marmara University, unimath aims to combine mathematical theory with computational representation, creating a bridge between abstract reasoning and code implementation.


Features

  • Abstract representation of Sets, Intervals, and Number Systems

  • Support for Vector operations and linear algebra concepts

  • Symbolic and numerical computation environment

  • Integration with matplotlib for visualization

  • Intuitive class structures and error handling for mathematical rigor


Vector

  • Magnitude

  • Specific vector information

  • Inner product

  • Angle between two vectors

  • Visualization with matplotlib

  • Find unit vector

  • Cosine value between two vectors

  • Projection around two vectors


Matrix

  • Precisely defined mathematically

  • Transpose

  • Special matrix definitions

  • Determinant

  • Hadamard and classical product

  • Symbolic Matris

  • (3,3) Sarrus Method


Combinatorics

  • Permutation

  • Combination

  • Posibilty


Calculus

  • Find Supremum İnfrimum value

  • Σ and Π operations

  • Transformation

  • Monotonicity of the series

  • Symbolid sequance


Physics

  • Wave equation analysis and visualization

$$ \psi(x,y) = \frac{2}{\sqrt{L_x L_y}} \sin\left(\frac{n_x \pi x}{L_x}\right) \sin\left(\frac{n_y \pi y}{L_y}\right) $$

  • Energy levels of a particle in a two-dimensional cubic box

$$ E = \frac{\pi^2 \hbar^2}{2m} (n_x^2 + n_y^2 + n_z^2) $$

Wave_Equation(Lx=2.0, Ly=1.5, nx=4, ny=1, N=100)

Visualization

unimath includes built-in vector visualization features using matplotlib, allowing users to plot and analyze vector relationships directly in Python. This helps bridge the gap between symbolic manipulation and geometric intuition.

Installation / Download

PyPI (Recommended)

pip install unimath

Git

git clone https://github.com/Jolankaa/unimath

cd unimath

pip install .

Few Examples

import unimath

# Example: Creating a vector

  

v = unimath.Vector([1,2,3])

  

print("Magnitude:", v.magnitude())

# For visualization

v.Visualization()

  

# Example: Creating a matrix

  

m = unimath.Matrix([[1,2],[3,4]])

print("Determinant:", m.determinant())

Metadata

Release files for unimath 1.4.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for unimath 1.4.5
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Built distribution (wheel)

Table of built distributions (wheels) for unimath 1.4.5
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unimath-1.4.5-py3-none-any.whl Python 3 none any Details

Total release size: 31.4 kB

Release files / unimath-1.4.5.tar.gz

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