use ndarray::prelude::*; use crate::network; use crate::node; use crate::params; use crate::params::Params; pub struct Trajectory { time: Array1, events: Array2 } pub struct Dataset { trajectories: Vec } pub fn trajectory_generator(net: &Box, n_trajectories: u64, t_end: f64) -> Dataset { let mut dataset = Dataset{ trajectories: Vec::new() }; let node_idx: Vec<_> = net.get_node_indices().collect(); for _ in 0..n_trajectories { let mut t = 0.0; let mut time: Vec = Vec::new(); let mut events: Vec> = Vec::new(); let mut current_state: Vec = node_idx.iter().map(|x| { net.get_node(*x).get_random_state_uniform() }).collect(); let mut next_transitions: Vec> = (0..node_idx.len()).map(|_| Option::None).collect(); events.push(current_state.clone()); time.push(t.clone()); while t < t_end { next_transitions.iter_mut().enumerate().map(|(idx, val)| { if let None = val { *val = Some(net.get_node(idx) .get_random_residence_time(net.get_node(idx).state_to_index(¤t_state[idx]), net.get_param_index_network(idx, ¤t_state)).unwrap() + t); } }); let next_node_transition = next_transitions .iter() .enumerate() .min_by(|x, y| x.1.unwrap().partial_cmp(&y.1.unwrap()).unwrap()) .unwrap().0; if next_transitions[next_node_transition].unwrap() > t_end { break } t = next_transitions[next_node_transition].unwrap().clone(); time.push(t.clone()); current_state[next_node_transition] = net.get_node(next_node_transition) .get_random_state( net.get_node(next_node_transition). state_to_index( ¤t_state[next_node_transition]), net.get_param_index_network(next_node_transition, ¤t_state)) .unwrap(); events.push(current_state.clone()); next_transitions[next_node_transition] = None; for child in net.get_children_set(next_node_transition){ next_transitions[child] = None } } } dataset }