cagpjax.linalg

Linear algebra functions.

Eigh

Bases: Algorithm

Eigh algorithm for eigenvalue decomposition.

Source code in src/cagpjax/linalg/eigh.py

class Eigh(cola.linalg.Algorithm):
    """
    Eigh algorithm for eigenvalue decomposition.
    """

Lanczos

Bases: Algorithm

Lanczos algorithm for approximate partial eigenvalue decomposition.

Parameters:

Name	Type	Description	Default
max_iters	int | None	Maximum number of iterations (number of eigenvalues/vectors to compute). If None, all eigenvalues/eigenvectors are computed.	None
v0	Float[Array, N] | None	Initial vector. If None, a random vector is generated using key.	None
key	PRNGKeyArray | None	Random key for generating a random initial vector if v0 is not provided.	None

Source code in src/cagpjax/linalg/eigh.py

class Lanczos(cola.linalg.Algorithm):
    """Lanczos algorithm for approximate partial eigenvalue decomposition.

    Args:
        max_iters: Maximum number of iterations (number of eigenvalues/vectors to compute).
            If `None`, all eigenvalues/eigenvectors are computed.
        v0: Initial vector. If `None`, a random vector is generated using `key`.
        key: Random key for generating a random initial vector if `v0` is
            not provided.
    """

    max_iters: int | None
    v0: Float[Array, "N"] | None
    key: PRNGKeyArray | None

    def __init__(
        self,
        max_iters: int | None = None,
        /,
        *,
        v0: Float[Array, "N"] | None = None,
        key: PRNGKeyArray | None = None,
    ):
        self.max_iters = max_iters
        self.v0 = v0
        self.key = key

congruence_transform(A, B)

congruence_transform(A: Any, B: Any) -> Any

congruence_transform(A: Diagonal, B: Diagonal) -> Diagonal

congruence_transform(A: BlockDiagonalSparse, B: Diagonal | ScalarMul) -> Diagonal

Congruence transformation A.T @ B @ A.

Parameters:

Name	Type	Description	Default
A	Any	Linear operator or array to be applied.	required
B	Any	Square linear operator or array to be transformed.	required

Source code in src/cagpjax/linalg/congruence.py

@cola.dispatch
def congruence_transform(A: Any, B: Any) -> Any:
    """Congruence transformation ``A.T @ B @ A``.

    Args:
        A: Linear operator or array to be applied.
        B: Square linear operator or array to be transformed.
    """
    pass