pg_utils.numerics.linalg.MultiPrecLinSolver

class pg_utils.numerics.linalg.MultiPrecLinSolver(prec: int = 113)

Bases: LinSysSolver

Multi-precision linear solver, built on gmpy2 + flamp, up to arbitrary precision

Variables:

prec (int) – internal calculation precision

__init__(prec: int = 113) → None

Methods

__init__([prec])
eig(A, **kwargs)	Calculate eigenvalues and eigenvectors of a matrix
eig_g(A, B, **kwargs)	Calculate eigenvalues and eigenvectors of a generalized eigenvalue problem; abstract, to be overriden
eigh(A, **kwargs)	Calculate eigenvalues and eigenvectors of a Hermitian matrix
inv(A, **kwargs)	Invert a matrix
solve(A, B[, diag, explicit])	Solve a linear system; this is the final interface for solving linear systems.
solve_diag(A, B, **kwargs)	Solve a diagonal linear system
solve_explicit(A, B, **kwargs)	Solve a linear system via explicit inversion

eig(A: ndarray, **kwargs) → Tuple[ndarray]

Calculate eigenvalues and eigenvectors of a matrix

eig_g(A: ndarray, B: ndarray, **kwargs) → Tuple[ndarray, ndarray]

Calculate eigenvalues and eigenvectors of a generalized eigenvalue problem; abstract, to be overriden

eigh(A: ndarray, **kwargs) → Tuple[ndarray]

Calculate eigenvalues and eigenvectors of a Hermitian matrix

inv(A: ndarray, **kwargs) → ndarray

Invert a matrix

solve(A: ndarray, B: ndarray, diag: bool = False, explicit: bool = True, **kwargs) → ndarray

Solve a linear system; this is the final interface for solving linear systems.

solve_diag(A: ndarray, B: ndarray, **kwargs) → ndarray

Solve a diagonal linear system

solve_explicit(A: ndarray, B: ndarray, **kwargs) → ndarray

Solve a linear system via explicit inversion