matmath module

A high-performance and efficient module for matrix and vector manipulation, powered by C extensions.

Downloads

Performance

matmath 4.0.0+ uses CPython extensions to provide near-native performance for all mathematical operations. This makes it suitable for applications ranging from simple geometry to complex numerical simulations where speed is critical.

Installing

To install the matmath module, ensure you have Python 3.9 or above.

pip install matmath

To upgrade:

pip install --upgrade matmath

Features and Usage

Vector Operations

The Vector class represents an N-dimensional vector and supports a wide range of operations.

Operator Support

Operation	Description
Addition	Element-wise addition (`v1 + v2`)
Subtraction	Element-wise subtraction (`v1 - v2`)
Multiplication	Scalar multiplication (`v1 * scalar`)
Multiplication	Element-wise multiplication (`v1 * v2`)
Division	Scalar division (`v1 / scalar`)
Division	Element-wise division (`v1 / v2`)
Cross Product	Uses `@` operator for cross product (2D/3D) (`v1 @ v2`)
Modulus	Returns the magnitude of the vector (`abs(v1)`)
Indexing	Access elements by index (`v1[i]`)
Length	Returns the number of elements (`len(v1)`)
Comparison	Equality checks (`v1 == v2`, `v1 != v2`)
Truth Value	`bool(v1)` returns `False` if all elements are zero
Hashing	Vectors are hashable and can be used as dictionary keys
Copy	Returns a copy of the vector (`v1.copy()`)

Vector Methods

Method	Description
`.modulus()`	Returns the magnitude of the vector.
`.argument()`	Returns the argument (angles) of the vector.
`.unit_vector()`	Returns a unit vector in the same direction.
`.magnify(m)`	Magnifies the vector by factor `m`.
`.rotate_2d(theta, radians=True)`	Rotates a 2D vector by `theta`.
`.rotate_3d(theta, axis, radians=True)`	Rotates a 3D vector around an `axis` using Rodrigues' formula.
`.dot_product(v)`	Returns the dot product with vector `v`.
`.cross_product(v)`	Returns the cross product with vector `v`.
`.is_unit()`	Checks if the magnitude is 1.
`.is_parallel(v)`	Checks if the vector is parallel to `v`.
`.is_orthogonal(v)`	Checks if the vector is orthogonal to `v`.
`.copy()`	Returns a copy of the vector.
`.to_list()`	Converts the vector to a Python list.

Vector Aliases

Original Method	Alias
`.modulus()`	`.mod()`
`.argument()`	`.arg()`
`.dot_product(v)`	`.dot(v)`
`.cross_product(v)`	`.cross(v)`

Matrix Operations

The Matrix class represents an M x N matrix.

Operator Support

Operation	Description
Addition	Matrix addition (`m1 + m2`)
Subtraction	Matrix subtraction (`m1 - m2`)
Scalar Mul	Multiplies all elements by scalar (`m1 * scalar`)
Element-wise	Hadamard (element-wise) multiplication (`m1 * m2`)
Matrix Mul	Standard matrix multiplication (`m1 @ m2`)
Division	Scalar division (`m1 / scalar`)
Division	Element-wise division (`m1 / m2`)
Floor Div	Element-wise floor division (`m1 // m2`)
Indexing	Access rows by index (`m1[i]`)
Iteration	Iterate over rows (`for row in m1`)
Length	Returns the number of rows (`len(m1)`)
Comparison	Equality checks (`m1 == m2`, `m1 != m2`)

Matrix Methods

Method	Description
`.transpose()`	Returns the transpose of the matrix.
`.determinant()`	Returns the determinant of a square matrix.
`.trace()`	Returns the sum of diagonal elements.
`.order` (property)	Returns `(rows, cols)` of the matrix.
`.is_square()`	Returns `True` if rows == cols.
`.is_symmetric()`	Checks if the matrix is symmetric.
`.is_diagonal()`	Checks if the matrix is diagonal.
`.is_identity()`	Checks if the matrix is identity.
`.is_invertible()`	Checks if the matrix is invertible.
`.is_null()`	Checks if the matrix is a null matrix.
`.is_skew_symmetric()`	Checks if the matrix is skew-symmetric.
`.is_lower_triangular()`	Checks if the matrix is lower triangular.
`.is_upper_triangular()`	Checks if the matrix is upper triangular.
`.cut(i, j)`	Returns a new matrix after removing row `i` and/or column `j`.
`.minor(i, j)`	Returns the minor of element `(i, j)`.
`.cofactor(i, j)`	Returns the cofactor of element `(i, j)`.
`.adjoint()`	Returns the adjoint of the matrix.
`.inverse()`	Returns the inverse of the matrix.
`.pow(p)`	Returns the matrix raised to the power `p`.
`.rotate(turns)`	Rotates the matrix clockwise by 90-degree `turns`.
`.copy()`	Returns a copy of the matrix.
`.to_list()`	Converts the matrix to a list of lists.

Matrix Static Methods

Method	Description
`Matrix.identity(n)`	Returns an `n x n` identity matrix.
`Matrix.zero(order)`	Returns a zero matrix of the given `order` (r, c).
`Matrix.fill(val, order)`	Returns a matrix of the given `order` filled with `val`.

Matrix Aliases

Original Method	Alias
`.determinant()`	`.det()`
`.order`	`.size`
`.adjoint()`	`.adj()`
`.inverse()`	`.inv()`
`.is_diagonal()`	`.is_diagonal_dominant()`
`.is_lower_triangular()`	`.is_lower_hessenberg()`
`.is_upper_triangular()`	`.is_upper_hessenberg()`

Contact

Please feel free to reach out if you have any questions:

Name: Siddhesh Agarwal
Email: siddhesh.agarwal@gmail.com
GitHub: Siddhesh-Agarwal

License

MIT License

Copyright (c) 2021 [Siddhesh-Agarwal](https://www.github.com/Siddhesh-Agarwal)

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

Release files for matmath 4.0.0

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

Source distribution (sdist)

Source distribution for matmath 4.0.0
File	Size	Uploaded
matmath-4.0.0.tar.gz	25.0 kB	Mar 15, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for matmath 4.0.0
File	Interpreter	ABI	Platform	Reset
matmath-4.0.0-cp312-cp312-win_amd64.whl 63.8 kB Mar 15, 2026	CPython 3.12	CPython 3.12	Windows x86-64	Details

Total release size: 88.7 kB

Release files / matmath-4.0.0.tar.gz

Download URL	matmath-4.0.0.tar.gz
Size	25.0 kB
Tags	Source
SHA-256 checksum How to use checksums	`fa341b3a859f620d7ce66a244945feace7bcad439e67d94188c18a7a29e0e496`
BLAKE2b-256 checksum How to use checksums	`4085d4029be332444b3616b9694e5a29e9e008e5784082aa1c6f489b4c858eeb`
Upload date	Mar 15, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`uv/0.8.23`

Release files / matmath-4.0.0-cp312-cp312-win_amd64.whl

Download URL	matmath-4.0.0-cp312-cp312-win_amd64.whl
Size	63.8 kB
Tags	CPython 3.12 Windows x86-64
SHA-256 checksum How to use checksums	`9bd2e101cc23c41bc76e7cc3d998315cf14e0c38c5440d9b343e70ae82f5ae5d`
BLAKE2b-256 checksum How to use checksums	`0321a47101582e4b154f410e8d526cc7da9a6806edea4e7a5bcb8e0eaba5225c`
Upload date	Mar 15, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`uv/0.8.23`