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Project description
primate
, short for Probabalistic Implicit Matrix Trace Estimator, is a Python package that provides estimators of quantities derived from matrix functions; that is, matrices parameterized by functions:
$$ f(A) \triangleq U f(\Lambda) U^{\intercal}, \quad \quad f : [a,b] \to \mathbb{R}$$
Estimator approximations are obtained via the Lanczos[^1] and stochastic Lanczos quadrature[^2] methods, which are well-suited for sparse or structured operators supporting fast $v \mapsto Av$ actions.
Notable features of primate
include:
- Efficient methods for trace, quadrature, and matrix function approximation
- Various distribution / engine choices for random vector generation (the stochastic part!)
- Support for arbitrary matrix functions, i.e.
Callable
's (Python) andinvocable
's[^3] (C++) - Support for arbitrary
LinearOperator
's, e.g. those in SciPy or Pylops - Matrix-free interface to the Lanczos, Golub-Welsch, and Gram Schmidt methods
primate
was partially inspired by the imate
package---for a comparison of the two, see here.
[^1]: Musco, Cameron, Christopher Musco, and Aaron Sidford. (2018) "Stability of the Lanczos method for matrix function approximation." [^2]: Ubaru, S., Chen, J., & Saad, Y. (2017). Fast estimation of tr(f(A)) via stochastic Lanczos quadrature. [^3]: This includes std::function's, C-style function pointers, functors, and lambda expressions.
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