The residence time generation is now seedable

src/params.rs

@@ -36,7 +36,7 @@ pub trait ParamsTrait {
 
     /// Randomly generate a residence time for the given node taking into account the node state
     /// and its parent set.
-    fn get_random_residence_time(&self, state: usize, u: usize) -> Result<f64, ParamsError>;
+    fn get_random_residence_time(&self, state: usize, u: usize, rng: &mut ChaCha8Rng) -> Result<f64, ParamsError>;
 
     /// Randomly generate a possible state for the given node taking into account the node state
     /// and its parent set.
@@ -143,7 +143,7 @@ impl ParamsTrait for DiscreteStatesContinousTimeParams {
         StateType::Discrete(rng.gen_range(0..(self.domain.len())))
     }
 
-    fn get_random_residence_time(&self, state: usize, u: usize) -> Result<f64, ParamsError> {
+    fn get_random_residence_time(&self, state: usize, u: usize, rng: &mut ChaCha8Rng) -> Result<f64, ParamsError> {
         // Generate a random residence time given the current state of the node and its parent set.
         // The method used is described in:
         // https://en.wikipedia.org/wiki/Exponential_distribution#Generating_exponential_variates

src/tools.rs

@@ -56,6 +56,7 @@ pub fn trajectory_generator<T: network::Network>(
                             .get_random_residence_time(
                                 net.get_node(idx).params.state_to_index(&current_state[idx]),
                                 net.get_param_index_network(idx, &current_state),
+                                &mut rng,
                             )
                             .unwrap()
                             + t,

tests/params.rs

@@ -61,7 +61,9 @@ fn test_random_generation_residence_time() {
     let param = create_ternary_discrete_time_continous_param();
     let mut states = Array1::<f64>::zeros(10000);
 
-    states.mapv_inplace(|_| param.get_random_residence_time(1, 0).unwrap());
+    let mut rng = ChaCha8Rng::seed_from_u64(123456);
+
+    states.mapv_inplace(|_| param.get_random_residence_time(1, 0, &mut rng).unwrap());
 
     assert_relative_eq!(1.0 / 5.0, states.mean().unwrap(), epsilon = 0.01);
 }