Renamed `UniformRandomGenerator` to `UniformGraphGenerator`, replaced `CtbnNetwork` requirement with `NetworkProcess` in `RandomGraphGenerator`, some related tweaks

reCTBN/src/tools.rs

@@ -4,7 +4,6 @@ use ndarray::prelude::*;
 use rand::{Rng, SeedableRng};
 use rand_chacha::ChaCha8Rng;
 
-use crate::process::ctbn::CtbnNetwork;
 use crate::process::NetworkProcess;
 use crate::sampling::{ForwardSampler, Sampler};
 use crate::{params, process};
@@ -115,16 +114,16 @@ pub fn trajectory_generator<T: process::NetworkProcess>(
 
 pub trait RandomGraphGenerator {
     fn new(density: f64, seed: Option<u64>) -> Self;
-    fn generate_graph<'a>(&'a mut self, net: &'a mut CtbnNetwork) -> &CtbnNetwork;
+    fn generate_graph<T: NetworkProcess>(&mut self, net: &mut T);
 }
 
-pub struct UniformRandomGenerator {
+pub struct UniformGraphGenerator {
     density: f64,
     rng: ChaCha8Rng,
 }
 
-impl RandomGraphGenerator for UniformRandomGenerator {
+impl RandomGraphGenerator for UniformGraphGenerator {
-    fn new(density: f64, seed: Option<u64>) -> UniformRandomGenerator {
+    fn new(density: f64, seed: Option<u64>) -> UniformGraphGenerator {
         if density < 0.0 || density > 1.0 {
             panic!(
                 "Density value must be between 1.0 and 0.0, got {}.",
@@ -135,10 +134,11 @@ impl RandomGraphGenerator for UniformRandomGenerator {
             Some(seed) => SeedableRng::seed_from_u64(seed),
             None => SeedableRng::from_entropy(),
         };
-        UniformRandomGenerator { density, rng }
+        UniformGraphGenerator { density, rng }
     }
 
-    fn generate_graph<'a>(&'a mut self, net: &'a mut CtbnNetwork) -> &CtbnNetwork {
+    fn generate_graph<T: NetworkProcess>(&mut self, net: &mut T) {
+        net.initialize_adj_matrix();
         let last_node_idx = net.get_node_indices().len();
         for parent in 0..last_node_idx {
             for child in 0..last_node_idx {
@@ -149,6 +149,5 @@ impl RandomGraphGenerator for UniformRandomGenerator {
                 }
             }
         }
-        net
     }
 }

reCTBN/tests/tools.rs

@@ -87,13 +87,13 @@ fn dataset_wrong_shape() {
 #[should_panic]
 fn uniform_random_generator_wrong_density() {
     let density = 2.1;
-    let _structure_generator: UniformRandomGenerator = RandomGraphGenerator::new(density, None);
+    let _structure_generator: UniformGraphGenerator = RandomGraphGenerator::new(density, None);
 }
 
 #[test]
 fn uniform_random_generator_right_densities() {
     for density in [1.0, 0.75, 0.5, 0.25, 0.0] {
-        let _structure_generator: UniformRandomGenerator = RandomGraphGenerator::new(density, None);
+        let _structure_generator: UniformGraphGenerator = RandomGraphGenerator::new(density, None);
     }
 }
 
@@ -109,7 +109,7 @@ fn uniform_random_generator_generate_graph() {
         ).unwrap();
     }
     let density = 1.0/3.0;
-    let mut structure_generator: UniformRandomGenerator = RandomGraphGenerator::new(density, Some(7641630759785120));
+    let mut structure_generator: UniformGraphGenerator = RandomGraphGenerator::new(density, Some(7641630759785120));
     structure_generator.generate_graph(&mut net);
     let mut edges = 0;
     for node in net.get_node_indices(){
@@ -117,8 +117,8 @@ fn uniform_random_generator_generate_graph() {
     }
     let nodes = net.get_node_indices().len() as f64;
     let expected_edges = (density * nodes * (nodes - 1.0)).round() as usize;
-    let tolerance = ((expected_edges as f64)/100.0*5.0) as usize; // ±5% of tolerance
+    let tolerance = ((expected_edges as f64)*0.05) as usize; // ±5% of tolerance
     // As the way `generate_graph()` is implemented we can only reasonably
     // expect the number of edges to be somewhere around the expected value.
-    assert!((expected_edges - tolerance) < edges && edges < (expected_edges + tolerance));
+    assert!((expected_edges - tolerance) <= edges && edges <= (expected_edges + tolerance));
 }