rslab 0.12.0

Pure-Rust sparse direct solver (symmetric LDLᵀ + unsymmetric LU) and preconditioner, with NumPy/SciPy bindings.

rslab (Python bindings)

NumPy/SciPy bindings for RSLAB, a pure-Rust sparse direct solver and preconditioner: complex/real symmetric LDLᵀ (Bunch-Kaufman) plus unsymmetric LU. A thin wrapper, all numeric work happens in Rust.

Install

pip install rslab

Usage

import numpy as np
import scipy.sparse as sp
import rslab

# Symmetric system (real or complex; the dtype selects the path).
A = sp.random(5000, 5000, density=1e-3, format="csc") + sp.eye(5000) * 10
A = A + A.T
b = np.random.rand(5000)

# One-shot solve.
x = rslab.spsolve(A, b)

# Factor once, solve many right-hand sides.
f = rslab.ldlt(A)
x1 = f.solve(b)
X = f.solve_many(np.random.rand(5000, 8))   # n x nrhs

print(f.n, f.factor_nnz, f.inertia, f.dtype)

Complex-symmetric matrices (EM/FEM, PARDISO mtype 6) work identically:

A = A.astype(np.complex128); A.data += 1j * 0.3 * A.data.real
x = rslab.ldlt(A).solve(np.ones(A.shape[0], dtype=np.complex128))

Unsymmetric matrices use the LU path:

f = rslab.lu(A_general)
x = f.solve(b)

Preconditioner mode

Never-fail static pivoting plus iterative refinement for hard/indefinite systems:

f = rslab.ldlt(A, preconditioner=1e-4)
x = f.solve(b, refine=20)        # refine against the original A

Configuration (keyword arguments)

ldlt, lu and spsolve accept:

kwarg	default	meaning
threads	None (auto)	None = per-matrix auto predictor, capped at 4 workers; int = fixed (0 = all)
preconditioner	None	static-pivot floor (e.g. 1e-4); never-fail, refine to solve
drop_tol	None	incomplete-factor threshold (preconditioner)
method	"left_looking"	"left_looking" or "multifrontal"
memory	"low"	"low" or "eager" factor emit strategy
force_accept	False	accept tiny pivots in exact mode instead of failing

Supported dtypes: float64, float32, complex128, complex64.

License

MIT.