initialize methods

tensorneat/algorithm/neat/gene/conn/default.py

@@ -26,6 +26,17 @@ class DefaultConnGene(BaseConnGene):
 
     def new_custom_attrs(self):
         return jnp.array([self.weight_init_mean])
+    
+    def new_random_attrs(self, key):
+        return jnp.array([mutate_float(key,
+                            self.weight_init_mean,
+                            self.weight_init_mean,
+                            1.0,
+                            0,
+                            0,
+                            1.0,
+                            )
+        ])
 
     def mutate(self, key, conn):
         input_index = conn[0]

tensorneat/algorithm/neat/gene/node/default.py

@@ -60,6 +60,16 @@ class DefaultNodeGene(BaseNodeGene):
         return jnp.array(
             [self.bias_init_mean, self.response_init_mean, self.activation_default, self.aggregation_default]
         )
+    
+    def new_random_attrs(self, key):   
+        return jnp.array([
+            mutate_float(key, self.bias_init_mean, self.bias_init_mean, self.bias_init_std,
+                         self.bias_mutate_power, self.bias_mutate_rate, self.bias_replace_rate),
+            mutate_float(key, self.response_init_mean, self.response_init_mean, self.response_init_std,
+                         self.response_mutate_power, self.response_mutate_rate, self.response_replace_rate),
+            self.activation_default,
+            self.aggregation_default,
+        ])
 
     def mutate(self, key, node):
         k1, k2, k3, k4 = jax.random.split(key, num=4)