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sTiles

High-performance tile-based framework for sparse Cholesky factorization, triangular solves, and selected inversion of symmetric positive-definite matrices, spanning the full spectrum from very sparse to fully dense.

This package is the Python interface to the libstiles engine. It is pure ctypes (no compiler required): the correct native library for your platform is downloaded automatically from the project's GitHub Release the first time you use it.

Install

pip install sTiles

Example

import scipy.sparse as sp
from sTiles import sTiles

s = sTiles(Q, cores=4, inverse=True)   # analyze + Cholesky factorize
s.logdet            # log|Q|
s.solve(b)          # solve Q x = b
s.selinv_diag()     # diag(Q^-1), the marginal variances
s.selinv_elm(i, j)  # any inverse element within the factor pattern

Links

Developed at KAUST. Free for research and academic use.

Metadata

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