Random mutations

src/formula.rs

@@ -22,11 +22,13 @@ impl Formula {
         }
         outputs
     }
-    pub fn mutate(&mut self) {}
 
     pub fn modify_tree(&mut self) -> NodeModifier {
         self.tree.modify_tree()
     }
+    pub fn modify_random_node(&mut self) -> NodeModifier {
+        self.tree.modify_node()
+    }
     pub fn display_tree(&self) {
         self.display_recursion(0, vec![&self.tree]);
     }

src/learner.rs

@@ -1,4 +1,10 @@
 use crate::formula::Formula;
+use rand::random_range;
+
+const ACTION_ADD: u8 = 0;
+const ACTION_REMOVE: u8 = 1;
+const ACTION_INSERT: u8 = 2;
+const ACTION_MUTATE: u8 = 3;
 
 pub struct Learner {
     best_algorithm: Formula,
@@ -49,7 +55,19 @@ impl Learner {
             .0
             .clone()
     }
-    fn mutate_formula_randomly(formula: &mut Formula) {}
+    fn mutate_formula_randomly(formula: &mut Formula) {
+        let mut editor = formula.modify_random_node();
+        let decided_action = random_range(0..3);
+        if decided_action == ACTION_ADD {
+            editor.add_node(editor.get_random_node());
+        } else if decided_action == ACTION_REMOVE {
+            editor.remove_node(None);
+        } else if decided_action == ACTION_INSERT {
+            editor.insert_node(editor.get_random_node(), None);
+        } else if decided_action == ACTION_MUTATE {
+            editor.mutate_node();
+        }
+    }
     fn get_similarity(expected_output: &Vec<f64>, real_output: &Vec<f64>) -> Result<f64, ()> {
         if expected_output.len() != real_output.len() {
             return Err(());