Matrix Insight — Visualizing Linear Algebra

An interactive web app that helps users understand matrix operations visually using NumPy.

What This Project Does

• Input 2×2 or 3×3 matrices manually or generate them randomly
• Perform key linear algebra operations: Multiply, Transpose, Determinant, Inverse
• Visualize results as interactive matrix grids
• See step-by-step breakdowns for matrix multiplication
• Clear error messages for invalid operations (e.g., singular matrices)

Project Structure

matrix-visualizer/
│
├── backend/
│   ├── main.py          # Test runner — calls operations and prints results
│   ├── operations.py    # Core NumPy functions for matrix math
│
├── frontend/
│   ├── index.html       # App layout and structure
│   ├── style.css        # Design system, variables, layout
│   ├── script.js        # Matrix input handling, UI logic, fetch calls
│
├── README.md
├── requirements.txt

Setup

1. Install Python dependencies

pip install -r requirements.txt

2. Run backend test

python backend/main.py

3. Open the frontend

Open frontend/index.html in your browser — no server needed for Version 1.

Tech Stack

Layer	Technology
Frontend	HTML, CSS, Vanilla JS
Backend	Python + NumPy

Operations Implemented

Operation	Function	Description
Multiply	multiply_matrices(A, B)	A × B dot product
Transpose	transpose_matrix(A)	Flip rows and columns
Determinant	determinant_matrix(A)	Scalar value det(A)
Inverse	inverse_matrix(A)	A⁻¹ if det(A) ≠ 0, else error

Learning Goals

• Understand matrix operations conceptually, not just computationally
• See how NumPy abstracts complex math into clean Python functions
• Develop intuition through visual grid-based representations

Future Versions

• Version 2: Flask REST API backend + Fetch integration
• Version 3: React frontend with D3.js visualization
• Version 4: Step-by-step animation for row reduction (Gaussian elimination)