Tessero\Sparse\Linalg\LinearOperator

fromMatrix(array $matrix, string $dtype = 'float64'): self

Wrap an explicit dense matrix A (list of rows). matvec = A x, rmatvec = A^T x.

fromCallbacks(array $shape, callable $matvec, ?callable $rmatvec = null, ?callable $matmat = null, string $dtype = 'float64'): self

Construct from callbacks (as scipy LinearOperator(shape, matvec, rmatvec, matmat)).

shape(): array

dtype(): string

ndim(): int

matvec(array $x): array

Matrix-vector product A x. Accepts a flat list; returns a flat list.

rmatvec(array $y): array

Adjoint (here, transpose) matrix-vector product A^H y.

matmat(array $X): array

Matrix-matrix product A X, X row-major of shape (n, k); returns shape (m, k).

dot(array $x): array

dot(x): matvec if x is 1-D, matmat if x is 2-D (row-major).

adjoint(): self

Adjoint operator A^H (conjugate transpose; for real data this is the transpose).

transpose(): self

Transpose operator A^T (== adjoint for real data).

getH(): self

scipy property aliases.

getT(): self

scale(float $alpha): self

Scalar multiple (alpha * A).

add(Tessero\Sparse\Linalg\LinearOperator $other): self

Operator sum (A + B); shapes must match.

compose(Tessero\Sparse\Linalg\LinearOperator $other): self

Operator composition / product (A @ B): applies B then A.