Refactor of sampling

reCTBN/src/sampling.rs

@@ -7,10 +7,17 @@ use crate::{
 use rand::SeedableRng;
 use rand_chacha::ChaCha8Rng;
 
-pub trait Sampler: Iterator {
+pub struct Sample {
+    pub t: f64,
+    pub state: Vec<params::StateType>
+}
+
+pub trait Sampler: Iterator<Item = Sample> {
     fn reset(&mut self);
 }
 
+
+
 pub struct ForwardSampler<'a, T>
 where
     T: NetworkProcess,
@@ -43,7 +50,7 @@ impl<'a, T: NetworkProcess> ForwardSampler<'a, T> {
 }
 
 impl<'a, T: NetworkProcess> Iterator for ForwardSampler<'a, T> {
-    type Item = (f64, Vec<params::StateType>);
+    type Item = Sample;
 
     fn next(&mut self) -> Option<Self::Item> {
         let ret_time = self.current_time.clone();
@@ -96,7 +103,7 @@ impl<'a, T: NetworkProcess> Iterator for ForwardSampler<'a, T> {
             self.next_transitions[child] = None;
         }
 
-        Some((ret_time, ret_state))
+        Some(Sample{t: ret_time, state: ret_state})
     }
 }
 

reCTBN/src/tools.rs

@@ -72,15 +72,15 @@ pub fn trajectory_generator<T: process::NetworkProcess>(
         let mut events: Vec<Vec<params::StateType>> = Vec::new();
 
         //Current Time and Current State
-        let (mut t, mut current_state) = sampler.next().unwrap();
+        let mut sample = sampler.next().unwrap();
         //Generate new samples until ending time is reached.
-        while t < t_end {
-            time.push(t);
-            events.push(current_state);
-            (t, current_state) = sampler.next().unwrap();
+        while sample.t < t_end {
+            time.push(sample.t);
+            events.push(sample.state);
+            sample = sampler.next().unwrap();
         }
 
-        current_state = events.last().unwrap().clone();
+        let current_state = events.last().unwrap().clone();
         events.push(current_state);
 
         //Add t_end as last time.