A linear algebra library written in TypeScript that focuses on generality, extensibility, and ease of use.

• Core:
  • Basic manipulation of vectors and matrices
  • Out-of-the-box support for number and ComplexNumber
  • Extensible to support general scalar types
• Matrix Operations:
  • Matrix determinants
  • Matrix exponentials
  • Elementary row operations
  • Gauss-Jordan elimination
  • Eigenvalue / Eigenvector finding
• Matrix Factorizations:
  • Cholesky Decomposition
  • LU Decomposition
  • QR Decomposition
  • Singular Value Decomposition
• Applications:
  • Calculus: Differentiation via finite differences
  • Statistics: Least-Squares Regression for arbitrary model functions
  • Statistics: Principal component analysis
• Machine learning models
  • Regularized linear regression
  • Logistic Regression
  • Support Vector Machines
• And more to come!

See our Usage Guide for more on how to use Vector in your project.

See our Contribution Guide for contribution guidelines and coding standards.

See the API Documentation