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95 lines
3.0 KiB
95 lines
3.0 KiB
mod utils;
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use utils::*;
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use rustyCTBN::parameter_learning::*;
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use rustyCTBN::ctbn::*;
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use rustyCTBN::network::Network;
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use rustyCTBN::node;
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use rustyCTBN::params;
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use rustyCTBN::tools::*;
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use ndarray::arr3;
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use std::collections::BTreeSet;
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#[macro_use]
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extern crate approx;
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#[test]
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fn learn_binary_cim_MLE() {
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let mut net = CtbnNetwork::init();
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let n1 = net
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.add_node(generate_discrete_time_continous_node(String::from("n1"),2))
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.unwrap();
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let n2 = net
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.add_node(generate_discrete_time_continous_node(String::from("n2"),2))
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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).params {
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params::Params::DiscreteStatesContinousTime(param) => {
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param.cim = Some(arr3(&[[[-3.0, 3.0], [2.0, -2.0]]]));
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}
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}
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match &mut net.get_node_mut(n2).params {
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params::Params::DiscreteStatesContinousTime(param) => {
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param.cim = Some(arr3(&[
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[[-1.0, 1.0], [4.0, -4.0]],
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[[-6.0, 6.0], [2.0, -2.0]],
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]));
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}
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}
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let data = trajectory_generator(Box::new(&net), 100, 100.0);
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let mle = MLE{};
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let (CIM, M, T) = mle.fit(Box::new(&net), &data, 1, None);
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print!("CIM: {:?}\nM: {:?}\nT: {:?}\n", CIM, M, T);
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assert_eq!(CIM.shape(), [2, 2, 2]);
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assert_relative_eq!(-1.0, CIM[[0, 0, 0]], epsilon=0.2);
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assert_relative_eq!(-4.0, CIM[[0, 1, 1]], epsilon=0.2);
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assert_relative_eq!(-6.0, CIM[[1, 0, 0]], epsilon=0.2);
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assert_relative_eq!(-2.0, CIM[[1, 1, 1]], epsilon=0.2);
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}
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#[test]
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fn learn_ternary_cim_MLE() {
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let mut net = CtbnNetwork::init();
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let n1 = net
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.add_node(generate_discrete_time_continous_node(String::from("n1"),3))
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.unwrap();
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let n2 = net
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.add_node(generate_discrete_time_continous_node(String::from("n2"),3))
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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).params {
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params::Params::DiscreteStatesContinousTime(param) => {
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param.cim = Some(arr3(&[[[-3.0, 2.0, 1.0],
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[1.5, -2.0, 0.5],
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[0.4, 0.6, -1.0]]]));
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}
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}
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match &mut net.get_node_mut(n2).params {
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params::Params::DiscreteStatesContinousTime(param) => {
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param.cim = Some(arr3(&[
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[[-1.0, 0.5, 0.5], [3.0, -4.0, 1.0], [0.9, 0.1, -1.0]],
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[[-6.0, 2.0, 4.0], [1.5, -2.0, 0.5], [3.0, 1.0, -4.0]],
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[[-1.0, 0.1, 0.9], [2.0, -2.5, 0.5], [0.9, 0.1, -1.0]],
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]));
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}
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}
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let data = trajectory_generator(Box::new(&net), 100, 200.0);
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let mle = MLE{};
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let (CIM, M, T) = mle.fit(Box::new(&net), &data, 1, None);
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print!("CIM: {:?}\nM: {:?}\nT: {:?}\n", CIM, M, T);
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assert_eq!(CIM.shape(), [3, 3, 3]);
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assert_relative_eq!(-1.0, CIM[[0, 0, 0]], epsilon=0.2);
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assert_relative_eq!(-4.0, CIM[[0, 1, 1]], epsilon=0.2);
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assert_relative_eq!(-1.0, CIM[[0, 2, 2]], epsilon=0.2);
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assert_relative_eq!(0.5, CIM[[0, 0, 1]], epsilon=0.2);
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}
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