alumathblackout 0.1.1

A simple matrix multiplication library mimicking NumPy

alumathblackout

A Python library for advanced matrix operations, specifically designed for efficient matrix multiplication with support for matrices of different dimensions.

Installation

You can install alumathblackout directly from PyPI using pip:

pip install alumathblackout

Alternative Installation Methods

If you encounter any issues with the standard installation, try:

# Install with user permissions
pip install --user alumathblackout

# Upgrade to latest version
pip install --upgrade alumathblackout

# Install specific version
pip install alumathblackout==1.0.0

Quick Start

import alumathblackout as amb

# Create matrices
matrix_a = amb.matrix([[1, 2], [3, 4]])
matrix_b = amb.matrix([[5, 6], [7, 8]])

# Perform matrix multiplication
result = amb.matrix_multiply(matrix_a, matrix_b)
print(result)

# Or use matrix multiplication operator @
result = matrix_a @ matrix_b
print(result)

Features

• Matrix Multiplication: Efficient matrix multiplication for compatible dimensions
• Dimension Validation: Automatic validation of matrix dimensions for multiplication
• Error Handling: Clear error messages for incompatible operations
• Multiple Data Types: Support for integers, floats, and mixed numeric types
• Flexible Input: Accepts nested lists and numpy arrays

Usage Examples

Basic Matrix Multiplication

import alumathblackout as amb

# 2x2 matrices
A = amb.matrix(
     [[1, 2], 
     [3, 4]])

B = amb.matrix(
     [[5, 6], 
     [7, 8]])

result = amb.matrix_multiply(A, B)
# Output: [[19, 22], [43, 50]]

Different Dimensions

import alumathblackout as amb

# 2x3 matrix
A = amb.matrix(
     [[1, 2, 3], 
     [4, 5, 6]])

# 3x2 matrix  
B = amb.matrix(
     [[7, 8], 
     [9, 10], 
     [11, 12]])

result = amb.matrix_multiply(A, B)
# Output: [[58, 64], [139, 154]]

With Floating Point Numbers

import alumathblackout as amb

A = amb.matrix(
     [[1.5, 2.5], 
     [3.5, 4.5]])

B = amb.matrix(
     [[0.5, 1.5], 
     [2.5, 3.5]])

result = amb.matrix_multiply(A, B)
# Output: [[7.0, 11.0], [13.0, 21.0]]

API Reference

matrix_multiply(matrix_a, matrix_b)

Performs matrix multiplication of two matrices.

Parameters:

• matrix_a (list of lists): First matrix (m×n dimensions)
• matrix_b (list of lists): Second matrix (n×p dimensions)

Returns:

• list of lists: Resulting matrix (m×p dimensions)

Raises:

• ValueError: If matrices have incompatible dimensions
• TypeError: If input is not a valid matrix format

Example:

result = amb.matrix_multiply(amb.matrix([[1, 2]]), amb.matrix([[3], [4]]))
# Returns: [[11]]

Requirements

• Python 3.6 or higher
• No external dependencies required

Error Handling

The library provides clear error messages for common issues:

import alumathblackout as amb

# Incompatible dimensions
A = amb.matrix([[1, 2]])      # 1x2
B = amb.matrix([[3, 4, 5]])   # 1x3

try:
    result = amb.matrix_multiply(A, B)
except ValueError as e:
    print(f"Error: {e}")
    # Output: Error: Cannot multiply matrices: columns of first matrix (2) must equal rows of second matrix (1)

Contributing

We welcome contributions! Please feel free to submit issues, feature requests, or pull requests.

Development Setup

1. Clone the repository
2. Install development dependencies
3. Run tests before submitting changes

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

If you encounter any issues or have questions:

1. Check the documentation above
2. Search existing issues on GitHub
3. Create a new issue with detailed information about your problem

Changelog

Version 1.0.0

• Initial release
• Basic matrix multiplication functionality
• Dimension validation
• Error handling

Authors

• Blackout Team - Initial work

Acknowledgments

• Thanks to the ALU community for support and feedback
• Inspired by linear algebra principles and efficient computation methods