Expand description
§lau-matrix-analysis
Matrix analysis: decompositions, perturbation theory, structured matrices, and matrix functions.
Re-exports§
pub use decompositions::*;pub use norms::*;pub use perturbation::*;pub use positive_definite::*;pub use sparse::*;pub use kronecker::*;pub use matrix_functions::*;pub use structured::*;pub use agent_analysis::*;
Modules§
- agent_
analysis - Agent correlation analysis: eigenvalue methods for agent similarity matrices.
- decompositions
- Matrix decompositions: LU, QR, Cholesky, SVD, eigendecomposition.
- kronecker
- Kronecker products and properties.
- matrix_
functions - Matrix functions: exponential via Padé, logarithm, square root.
- norms
- Matrix norms: operator, Frobenius, nuclear, condition number.
- perturbation
- Perturbation theory: eigenvalue sensitivity, condition number of eigenproblem.
- positive_
definite - Positive definite matrices: verification, nearest PSD, Cholesky.
- sparse
- Sparse matrix basics: COO format, sparse-dense multiplication.
- structured
- Structured matrices: Toeplitz, circulant, Vandermonde — fast algorithms.