SquareQSM

class tinygp.solvers.quasisep.core.SquareQSM(diag: DiagQSM, lower: StrictLowerTriQSM, upper: StrictUpperTriQSM)

Bases: QSM

A general square order (m1, m2) quasiseparable matrix

Parameters:

• diag – The diagonal elements.

• lower – The strictly lower triangular elements with order m1.

• upper – The strictly upper triangular elements with order m2.

gram() → SymmQSM

The inner product of this matrix with itself

If this matrix is called A, the Gram matrix is A.T @ A, and that’s what this method computes. The result is a SymmQSM.

inv() → SquareQSM

The inverse of this matrix

matmul(x: tinygp.helpers.JAXArray, *, parallel: bool = False) → tinygp.helpers.JAXArray

The dot product of this matrix with a dense vector or matrix

Parameters:

• x (n, ...) – A matrix or vector with leading dimension matching this matrix.

• parallel – If True, use a parallel associative-scan algorithm instead of the default sequential scan.

scale(other: tinygp.helpers.JAXArray) → SquareQSM

The multiplication of this matrix times a scalar, as a QSM

property shape: tuple[int, int]

The shape of the matrix

to_dense() → tinygp.helpers.JAXArray

Render this representation to a dense matrix

This implementation is not optimized and should really only ever be used for testing purposes.

transpose() → SquareQSM

The matrix transpose as a QSM