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extern crate nalgebra as na;
use na::linalg::SymmetricEigen;
use na::Dynamic;
use na::{DMatrix, DVector};
pub fn generate_diagonal_dominant(dim: usize, sparsity: f64) -> DMatrix<f64> {
let xs = 1..(dim + 1);
let it = xs.map(|x: usize| x as f64);
let vs = DVector::<f64>::from_iterator(dim, it);
let mut arr = DMatrix::<f64>::new_random(dim, dim);
arr += &arr.transpose();
arr *= sparsity;
arr.set_diagonal(&vs);
arr
}
pub fn sort_eigenpairs(
eig: SymmetricEigen<f64, Dynamic>,
ascending: bool,
) -> SymmetricEigen<f64, Dynamic> {
let mut vs: Vec<(f64, usize)> = eig
.eigenvalues
.iter()
.enumerate()
.map(|(idx, &x)| (x, idx))
.collect();
sort_vector(&mut vs, ascending);
let eigenvalues = DVector::<f64>::from_iterator(vs.len(), vs.iter().map(|t| t.0));
let indices: Vec<_> = vs.iter().map(|t| t.1).collect();
let dim_rows = eig.eigenvectors.nrows();
let dim_cols = eig.eigenvectors.ncols();
let mut eigenvectors = DMatrix::<f64>::zeros(dim_rows, dim_cols);
for i in 0..dim_cols {
eigenvectors.set_column(i, &eig.eigenvectors.column(indices[i]));
}
SymmetricEigen {
eigenvalues,
eigenvectors,
}
}
pub fn sort_vector<T: PartialOrd>(vs: &mut Vec<T>, ascending: bool) {
if ascending {
vs.sort_unstable_by(|a, b| a.partial_cmp(b).unwrap());
} else {
vs.sort_unstable_by(|a, b| b.partial_cmp(a).unwrap());
}
}