Cosine Similarity Calculator

This project provides a simple implementation to compute the cosine similarity between two feature vectors. Cosine similarity is a measure of similarity between two non-zero vectors that measures the cosine of the angle between them.

Overview

The project includes:

• A Python script to compute cosine similarity between feature vectors
• Support for reading vectors from text files
• Handling for both space and comma-separated values

Requirements

• Python 3.x
• NumPy

Install the required package using:

uv sync

Usage

1. Prepare your feature vectors in a text file (e.g., features.txt):

   • One vector per line
   • Values can be space or comma-separated
   • Example:

     0.5 0.8 0.3 0.9 0.1
     0.2 0.7 0.4 0.6 0.3
     

2. Run the script:

   uv run python main.py

The script will output:

• The input feature vectors
• The computed cosine similarity between them

Formula

Cosine similarity is computed using the formula:

cos(θ) = (A·B) / (||A|| * ||B||)

where:

• A·B is the dot product of vectors A and B
• ||A|| and ||B|| are the L2 norms (magnitudes) of vectors A and B

Error Handling

The script includes error handling for:

• Missing input file
• Invalid file format
• Vectors of different dimensions
• Zero vectors