reCTBN/tests/tools.rs

use reCTBN::tools::*;
use reCTBN::network::Network;
use reCTBN::ctbn::*;
use reCTBN::node;
use reCTBN::params;
use std::collections::BTreeSet;
use ndarray::{arr1, arr2, arr3};



#[macro_use]
extern crate approx;

mod utils;

#[test]
fn run_sampling() {
    let mut net = CtbnNetwork::new();
    let n1 = net.add_node(utils::generate_discrete_time_continous_node(String::from("n1"),2)).unwrap();
    let n2 = net.add_node(utils::generate_discrete_time_continous_node(String::from("n2"),2)).unwrap();
    net.add_edge(n1, n2);

    match &mut net.get_node_mut(n1).params {
        params::Params::DiscreteStatesContinousTime(param) => {
            param.set_cim(arr3(&[[[-3.0,3.0],[2.0,-2.0]]]));
        }
    }


    match &mut net.get_node_mut(n2).params {
        params::Params::DiscreteStatesContinousTime(param) => {
            param.set_cim(arr3(&[
                                     [[-1.0,1.0],[4.0,-4.0]],
                                     [[-6.0,6.0],[2.0,-2.0]]]));
        }
    }

    let data = trajectory_generator(&net, 4, 1.0, Some(6347747169756259),);

    assert_eq!(4, data.get_trajectories().len());
    assert_relative_eq!(1.0, data.get_trajectories()[0].get_time()[data.get_trajectories()[0].get_time().len()-1]);
}


#[test]
#[should_panic]
    fn trajectory_wrong_shape() {
    let time = arr1(&[0.0, 0.2]);
    let events = arr2(&[[0,3]]);
    Trajectory::new(time, events);
}


#[test]
#[should_panic]
fn dataset_wrong_shape() {
    let time = arr1(&[0.0, 0.2]);
    let events = arr2(&[[0,3], [1,2]]);
    let t1 = Trajectory::new(time, events);


    let time = arr1(&[0.0, 0.2]);
    let events = arr2(&[[0,3,3], [1,2,3]]);
    let t2 = Trajectory::new(time, events);
    Dataset::new(vec![t1, t2]);
}