4 releases (1 stable)
1.0.0 | Apr 12, 2024 |
---|---|
0.1.2 | Apr 7, 2023 |
0.1.1 | Apr 6, 2023 |
0.1.0 | Apr 6, 2023 |
#598 in Math
175KB
573 lines
GMRES: Generalized minimum residual method
A sparse linear system solver using the GMRES iterative method.
This crates provides a solver for Ax=b
linear problems using the GMRES method.
Sparse matrices are a common representation for many real-world problems commonly
found in engineering and scientific applications. This implementation of the
GMRES method is specifically tailored to sparse matrices, making it an efficient
and effective tool for solving large linear systems arising from real-world
problems.
Example:
Solve a linear system
use gmres;
use rsparse::data::Sprs;
fn main() {
// Define an arbitrary matrix `A`
let a = Sprs::new_from_vec(&[
vec![0.888641, 0.477151, 0.764081, 0.244348, 0.662542],
vec![0.695741, 0.991383, 0.800932, 0.089616, 0.250400],
vec![0.149974, 0.584978, 0.937576, 0.870798, 0.990016],
vec![0.429292, 0.459984, 0.056629, 0.567589, 0.048561],
vec![0.454428, 0.253192, 0.173598, 0.321640, 0.632031],
]);
// Define a vector `b`
let b = vec![0.104594, 0.437549, 0.040264, 0.298842, 0.254451];
// Provide an initial guess
let mut x = vec![0.; b.len()];
// Solve for `x`
gmres::gmres(&a, &b, &mut x, 100, 1e-5).unwrap();
// Check if the result is correct
gmres::test_utils::assert_eq_f_vec(
&x,
&vec![0.037919, 0.888551, -0.657575, -0.181680, 0.292447],
1e-5,
);
}
Dependencies
~655KB