tinypy

A tiny linear algebra library that I wrote to teach myself numerical linear algebra. It does not depend on any third party libraries.

Check out examples.ipynb to see what this library can do.

Features

Supports two data types - Matrix and Vector.

The Matrix type has several useful methods like

Method	Function
trace()	$\text{trace}(A)$
det()	$\text{det}(A)$
inv()	$A^{-1}$
rank()	$\text{rank}(A)$
conjugate()	$\overline{A}$
transpose()	$A^{T}$
solve(b)	Finds $x$ for $Ax=b$
qr_decomposition	Finds $Q$ and $R$ for $A = QR$
_hessenberg()	Finds the upper Hessenberg form of $A$
eig()	Finds the eigenvalues for $A$

The library supports the usual basic binary operations between matrices, scalars and vectors.

The Vector type supports the following methods:

Method	Function
dot()	$\mathbf{a} \cdot \mathbf{b}$
norm()	$|\mathbf{a}|$
normalize()	$\dfrac{\mathbf{a}}{|\mathbf{a}|}$

Benchmarks for fun

Matrix multiplication

Yeah, tinypy is slow.

Notes

While I have thoroughly tested the correctness of the library against numpy, it is not meant to be used in any kind of production environment. Just use the standard alternatives.

Not publishing on any package repository for practical reasons.

This project was inspired by the playlist Linear Algebra in C++.