fix bug for record the best genome.

tensorneat/algorithm/neat/species/default.py

@@ -113,9 +113,6 @@ class DefaultSpecies(BaseSpecies):
         return state.pop_nodes, state.pop_conns
 
     def update_species(self, state, fitness):
-        # set nan to -inf
-        fitness = jnp.where(jnp.isnan(fitness), -jnp.inf, fitness)
-
         # update the fitness of each species
         state, species_fitness = self.update_species_fitness(state, fitness)
 

tensorneat/examples/func_fit/xor.py

@@ -19,10 +19,10 @@ if __name__ == "__main__":
                     ),
                     output_transform=Act.sigmoid,  # the activation function for output node
                     mutation=DefaultMutation(
-                        node_add=0.05,
+                        node_add=0.1,
-                        conn_add=0.05,
+                        conn_add=0.1,
-                        node_delete=0.05,
+                        node_delete=0.1,
-                        conn_delete=0.05,
+                        conn_delete=0.1,
                     ),
                 ),
                 pop_size=1000,

tensorneat/pipeline.py

@@ -116,6 +116,9 @@ class Pipeline:
                 state, keys, self.algorithm.forward, pop_transformed
             )
 
+        # replace nan with -inf
+        fitnesses = jnp.where(jnp.isnan(fitnesses), -jnp.inf, fitnesses)
+
         state = self.algorithm.tell(state, fitnesses)
 
         return state.update(randkey=randkey), fitnesses
@@ -149,7 +152,7 @@ class Pipeline:
 
     def analysis(self, state, pop, fitnesses):
 
-        valid_fitnesses = fitnesses[~np.isnan(fitnesses)]
+        valid_fitnesses = fitnesses[~np.isinf(fitnesses)]
 
         max_f, min_f, mean_f, std_f = (
             max(valid_fitnesses),