eigenfind 0.1.0

A Python library to find eigenvectors by known eigenvalues.

📌 About eigenfind

eigenfind is a lightweight Python library that allows you to compute eigenvectors from known eigenvalues of a square matrix — a task commonly needed in theoretical mathematics, linear algebra education, and symbolic or numerical analysis.

While most libraries like NumPy and SciPy compute eigenvalues and eigenvectors together, eigenfind fills a specific niche: solving the eigenvalue problem in reverse — finding eigenvectors when you already know one or more eigenvalues.

This is achieved by solving the homogeneous linear system:

$$ (A - \lambda I)\mathbf{v} = 0 $$

…which defines the eigenspace for a given eigenvalue λ of matrix A.

---

✅ Key Features

• 🔍 Find eigenvectors corresponding to a given eigenvalue
• 📐 Works with both numeric (NumPy/SciPy) and symbolic (SymPy) matrices
• 📚 Educational use: ideal for students, educators, and math enthusiasts
• 🧠 Supports defective matrices (partial functionality)
• 🧪 Easy to test and integrate into other math tools

---

🚧 Use Cases

• Teaching or learning linear algebra
• Verifying results from numerical solvers
• Debugging or inspecting eigenvalue computations
• Symbolic math derivations
• Building introspection tools for PCA or matrix decompositions