Added various docstrings notes to all rust modules

reCTBN/src/ctbn.rs

@@ -1,3 +1,5 @@
+//! Continuous Time Bayesian Network
+
 use std::collections::BTreeSet;
 
 use ndarray::prelude::*;

reCTBN/src/network.rs

@@ -1,3 +1,5 @@
+//! Defines methods for dealing with Probabilistic Graphical Models like the CTBNs
+
 use std::collections::BTreeSet;
 
 use thiserror::Error;
@@ -11,7 +13,8 @@ pub enum NetworkError {
     NodeInsertionError(String),
 }
 
-/// It defines the required methods for a structure used as a PGM (such as a CTBN).
+/// It defines the required methods for a structure used as a Probabilistic Graphical Models (such
+/// as a CTBN).
 pub trait Network {
     fn initialize_adj_matrix(&mut self);
     fn add_node(&mut self, n: params::Params) -> Result<usize, NetworkError>;

reCTBN/src/parameter_learning.rs

@@ -1,3 +1,5 @@
+//! Module containing methods used to learn the parameters.
+
 use std::collections::BTreeSet;
 
 use ndarray::prelude::*;

reCTBN/src/params.rs

@@ -1,3 +1,5 @@
+//! Module containing methods to define different types of nodes.
+
 use std::collections::BTreeSet;
 
 use enum_dispatch::enum_dispatch;

reCTBN/src/sampling.rs

@@ -1,3 +1,5 @@
+//! Module containing methods for the sampling.
+
 use crate::{
     network::Network,
     params::{self, ParamsTrait},

reCTBN/src/structure_learning.rs

@@ -1,3 +1,5 @@
+//! Learn the structure of the network.
+
 pub mod constraint_based_algorithm;
 pub mod hypothesis_test;
 pub mod score_based_algorithm;

reCTBN/src/structure_learning/constraint_based_algorithm.rs

@@ -1,3 +1,5 @@
+//! Module containing constraint based algorithms like CTPC and Hiton.
+
 //pub struct CTPC {
 //
 //}

reCTBN/src/structure_learning/hypothesis_test.rs

@@ -1,3 +1,5 @@
+//! Module containing an hypothesis test for constraint based algorithms like chi-squared test, F test, etc...
+
 use std::collections::BTreeSet;
 
 use ndarray::{Array3, Axis};

reCTBN/src/structure_learning/score_based_algorithm.rs

@@ -1,3 +1,5 @@
+//! Module containing score based algorithms like Hill Climbing and Tabu Search.
+
 use std::collections::BTreeSet;
 
 use crate::structure_learning::score_function::ScoreFunction;

reCTBN/src/structure_learning/score_function.rs

@@ -1,3 +1,5 @@
+//! Module for score based algorithms containing score functions algorithms like Log Likelihood, BIC, etc...
+
 use std::collections::BTreeSet;
 
 use ndarray::prelude::*;

reCTBN/src/tools.rs

@@ -1,3 +1,5 @@
+//! Contains commonly used methods used across the crate.
+
 use ndarray::prelude::*;
 
 use crate::sampling::{ForwardSampler, Sampler};