Add cross-breeding functionality to FighterNN

gemla/src/bin/fighter_nn/mod.rs

@@ -4,6 +4,7 @@ use std::{fs, path::PathBuf};
 use fann::{ActivationFunc, Fann};
 use gemla::{core::genetic_node::{GeneticNode, GeneticNodeContext}, error::Error};
 use rand::prelude::*;
+use rand::distributions::{Distribution, Uniform};
 use serde::{Deserialize, Serialize};
 use anyhow::Context;
 use uuid::Uuid;
@@ -135,6 +136,39 @@ impl GeneticNode for FighterNN {
             let mut fann = Fann::from_file(&nn)
                 .with_context(|| format!("Failed to load nn"))?;
 
+            // Load another nn from the current generation and cross breed it with the current nn
+            let cross_nn = self.folder.join(format!("{}", self.generation)).join(format!("{:06}_fighter_nn_{}.net", self.id, to_keep[thread_rng().gen_range(0..survivor_count)]));
+            let cross_fann = Fann::from_file(&cross_nn)
+                .with_context(|| format!("Failed to load cross nn"))?;
+
+            let mut connections = fann.get_connections(); // Vector of connections
+            let cross_connections = cross_fann.get_connections(); // Vector of connections
+            let segment_count: usize = 3; // For example, choose 3 segments to swap
+            let segment_distribution = Uniform::from(1..connections.len() / segment_count); // Ensure segments are not too small
+
+            let mut start_points = vec![];
+
+            for _ in 0..segment_count {
+                let start_point = segment_distribution.sample(&mut rand::thread_rng());
+                start_points.push(start_point);
+            }
+            start_points.sort_unstable(); // Ensure segments are in order
+            
+            for (j, &start) in start_points.iter().enumerate() {
+                let end = if j < segment_count - 1 {
+                    start_points[j + 1]
+                } else {
+                    connections.len()
+                };
+
+                // Swap segments
+                for k in start..end {
+                    connections[k] = cross_connections[k].clone();
+                }
+            }
+
+            fann.set_connections(&connections);
+
             // For each weight in the 5 new nn's there is a 20% chance of a minor mutation (a random number between -0.1 and 0.1 is added to the weight)
             // And a 5% chance of a major mutation (a random number between -0.3 and 0.3 is added to the weight)
             let mut connections = fann.get_connections(); // Vector of connections