Tessero\SparseLinalg

apply(string $name, mixed ...$args): mixed

Call a function by its SciPy/NumPy name: SparseLinalg::apply('log_ndtr', $x).

bicg(mixed $A, mixed $b, mixed $x0 = null, mixed $rtol = 1.0E-5, mixed $atol = 0.0, mixed $maxiter = null): mixed

BiConjugate Gradient for a general square system (scipy.sparse.linalg.bicg).

bicgstab(mixed $A, mixed $b, mixed $x0 = null, mixed $rtol = 1.0E-5, mixed $atol = 0.0, mixed $maxiter = null): mixed

BiCGSTAB for a general square system (scipy.sparse.linalg.bicgstab).

cg(mixed $A, mixed $b, mixed $x0 = null, mixed $rtol = 1.0E-5, mixed $atol = 0.0, mixed $maxiter = null): mixed

Conjugate gradients for a symmetric positive-definite system (scipy.sparse.linalg.cg).

cgs(mixed $A, mixed $b, mixed $x0 = null, mixed $rtol = 1.0E-5, mixed $atol = 0.0, mixed $maxiter = null): mixed

Conjugate Gradient Squared for a general square system (scipy.sparse.linalg.cgs).

eigs(mixed $A, mixed $k = 6, mixed $which = 'LM|LR|SR|LI', mixed $sigma = null, mixed $v0 = null, mixed $ncv = null, mixed $maxiter = null, mixed $tol = 0.0, mixed $returnEigenvectors = true): mixed

k eigenvalues of a general matrix as (real, |imag|) pairs, values only (scipy.sparse.linalg.eigs); vectors / imag sign are out of scope.

eigsh(mixed $A, mixed $k = 6, mixed $which = 'LM|SM|LA|SA|BE', mixed $sigma = null, mixed $v0 = null, mixed $ncv = null, mixed $maxiter = null, mixed $tol = 0.0, mixed $returnEigenvectors = true): mixed

k eigenvalues of a symmetric matrix, ascending, values only (scipy.sparse.linalg.eigsh); vectors are out of scope.

expm(mixed $A): mixed

Matrix exponential of a sparse matrix (scipy.sparse.linalg.expm).

expmMultiply(mixed $A, mixed $B, mixed $start = null, mixed $stop = null, mixed $num = null, mixed $endpoint = null): mixed

Action of the matrix exponential, expm(A) @ B (scipy.sparse.linalg.expm_multiply).

funmMultiplyKrylov(mixed $f, mixed $A, mixed $b): mixed

Krylov (Arnoldi) approximation of f(A) @ b; f is a matrix-function name one of exp/sqrt/log/sin/cos/sinh/cosh/tanh/tan (scipy.sparse.linalg.funm_multiply_krylov).

gcrotmk(mixed $A, mixed $b, mixed $x0 = null, mixed $rtol = 1.0E-5, mixed $atol = 0.0, mixed $maxiter = null, mixed $m = 20, mixed $k = null): mixed

GCROT(m,k) truncated GMRES with recycling for a general square system (scipy.sparse.linalg.gcrotmk).

gmres(mixed $A, mixed $b, mixed $x0 = null, mixed $rtol = 1.0E-5, mixed $atol = 0.0, mixed $maxiter = null, mixed $restart = null): mixed

Restarted GMRES for a general square system (scipy.sparse.linalg.gmres).

inv(mixed $A): mixed

Inverse of a square sparse matrix, returned dense (scipy.sparse.linalg.inv).

isSptriangular(mixed $A): mixed

Whether a sparse matrix is lower/upper triangular (scipy.sparse.linalg.is_sptriangular).

lgmres(mixed $A, mixed $b, mixed $x0 = null, mixed $rtol = 1.0E-5, mixed $atol = 0.0, mixed $maxiter = null, mixed $innerM = 30, mixed $outerK = 3): mixed

LGMRES (GMRES with augmentation) for a general square system (scipy.sparse.linalg.lgmres).

lobpcg(mixed $A, mixed $X, mixed $B = null, mixed $M = null, mixed $Y = null, mixed $tol = null, mixed $maxiter = null, mixed $largest = true): mixed

LOBPCG eigenvalues (ascending) of the k smallest/largest eigenpairs of a symmetric matrix; eigenvectors are non-unique so only the eigenvalues are returned (scipy.sparse.linalg.lobpcg).

lsmr(mixed $A, mixed $b, mixed $damp = 0.0, mixed $atol = 1.0E-6, mixed $btol = 1.0E-6, mixed $conlim = 100000000.0, mixed $maxiter = null): mixed

LSMR least-squares solver for a sparse rectangular system (scipy.sparse.linalg.lsmr).

lsqr(mixed $A, mixed $b, mixed $atol = 1.0E-8, mixed $btol = 1.0E-8, mixed $maxiter = null): mixed

LSQR least-squares solver for a sparse rectangular system (scipy.sparse.linalg.lsqr).

matrixPower(mixed $A, mixed $power): mixed

Integer matrix power of a square sparse matrix (scipy.sparse.linalg.matrix_power).

minres(mixed $A, mixed $b, mixed $x0 = null, mixed $rtol = 1.0E-5, mixed $atol = 0.0, mixed $maxiter = null): mixed

MINRES for a symmetric (possibly indefinite) system (scipy.sparse.linalg.minres).

norm(mixed $x, mixed $ord = null, mixed $axis = null): mixed

Norm of a sparse matrix (scipy.sparse.linalg.norm).

onenormest(mixed $A, mixed $t = 2, mixed $itmax = 5): mixed

Estimate of the matrix 1-norm (scipy.sparse.linalg.onenormest).

qmr(mixed $A, mixed $b, mixed $x0 = null, mixed $rtol = 1.0E-5, mixed $atol = 0.0, mixed $maxiter = null, mixed $M1 = null, mixed $M2 = null): mixed

Quasi-minimal residual for a general square system (scipy.sparse.linalg.qmr).

spbandwidth(mixed $A): mixed

Lower and upper bandwidth of a sparse matrix (scipy.sparse.linalg.spbandwidth).

spsolve(mixed $A, mixed $b, mixed $permcSpec = null, mixed $useUmfpack = true): mixed

Solve a sparse linear system A x = b (scipy.sparse.linalg.spsolve).

spsolveTriangular(mixed $A, mixed $b, mixed $lower = true, mixed $overwriteA = false, mixed $overwriteB = false, mixed $unitDiagonal = false): mixed

Solve a triangular sparse system (scipy.sparse.linalg.spsolve_triangular).

svds(mixed $A, mixed $k = 6, mixed $which = 'LM', mixed $v0 = null, mixed $maxiter = null, mixed $returnSingularVectors = true, mixed $tol = 0.0): mixed

Top-k singular values, ascending, values only (scipy.sparse.linalg.svds); which=LM only, vectors out of scope.

tfqmr(mixed $A, mixed $b, mixed $x0 = null, mixed $rtol = 1.0E-5, mixed $atol = 0.0, mixed $maxiter = null, mixed $M = null): mixed

Transpose-free QMR for a general square system (scipy.sparse.linalg.tfqmr).