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84 lines
2.0 KiB
84 lines
2.0 KiB
use ndarray::{arr1, arr2, arr3};
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use reCTBN::ctbn::*;
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use reCTBN::network::Network;
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use reCTBN::params;
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use reCTBN::tools::*;
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#[macro_use]
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extern crate approx;
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mod utils;
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#[test]
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fn run_sampling() {
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#![allow(unused_must_use)]
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let mut net = CtbnNetwork::new();
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let n1 = net
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.add_node(utils::generate_discrete_time_continous_node(
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String::from("n1"),
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2,
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))
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.unwrap();
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let n2 = net
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.add_node(utils::generate_discrete_time_continous_node(
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String::from("n2"),
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2,
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))
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.unwrap();
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net.add_edge(n1, n2);
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match &mut net.get_node_mut(n1) {
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params::Params::DiscreteStatesContinousTime(param) => {
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param.set_cim(arr3(&[
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[
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[-3.0, 3.0],
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[2.0, -2.0]
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],
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]));
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}
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}
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match &mut net.get_node_mut(n2) {
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params::Params::DiscreteStatesContinousTime(param) => {
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param.set_cim(arr3(&[
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[
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[-1.0, 1.0],
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[4.0, -4.0]
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],
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[
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[-6.0, 6.0],
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[2.0, -2.0]
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],
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]));
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}
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}
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let data = trajectory_generator(&net, 4, 1.0, Some(6347747169756259));
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assert_eq!(4, data.get_trajectories().len());
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assert_relative_eq!(
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1.0,
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data.get_trajectories()[0].get_time()[data.get_trajectories()[0].get_time().len() - 1]
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);
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}
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#[test]
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#[should_panic]
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fn trajectory_wrong_shape() {
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let time = arr1(&[0.0, 0.2]);
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let events = arr2(&[[0, 3]]);
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Trajectory::new(time, events);
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}
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#[test]
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#[should_panic]
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fn dataset_wrong_shape() {
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let time = arr1(&[0.0, 0.2]);
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let events = arr2(&[[0, 3], [1, 2]]);
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let t1 = Trajectory::new(time, events);
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let time = arr1(&[0.0, 0.2]);
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let events = arr2(&[[0, 3, 3], [1, 2, 3]]);
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let t2 = Trajectory::new(time, events);
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Dataset::new(vec![t1, t2]);
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}
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