use nalgebra::{Matrix2, OMatrix, Vector2, U2, U3};
use nalgebra_mvn::MultivariateNormal;

fn main() {
    // specify mean and covariance of our multi-variate normal
    let mu = Vector2::from_row_slice(&[9.0, 1.0]);
    let sigma = Matrix2::from_row_slice(&[1.0, 0.0, 0.0, 1.0]);

    let mvn = MultivariateNormal::from_mean_and_covariance(&mu, &sigma).unwrap();

    // input samples are row vectors vertically stacked
    let xs = OMatrix::<_, U3, U2>::new(8.9, 1.0, 9.0, 1.0, 9.1, 1.0);

    // evaluate the density at each of our samples.
    let result = mvn.pdf(&xs);

    // result is a vector with num samples rows
    assert!(result.nrows() == xs.nrows());
}