odify genome for the official release

examples/func_fit/xor.py

@@ -0,0 +1,50 @@
+from pipeline import Pipeline
+from algorithm.neat import *
+
+from problem.func_fit import XOR3d
+from tensorneat.common import ACT_ALL, AGG_ALL, Act, Agg
+
+if __name__ == "__main__":
+    pipeline = Pipeline(
+        algorithm=NEAT(
+            species=DefaultSpecies(
+                genome=DenseInitialize(
+                    num_inputs=3,
+                    num_outputs=1,
+                    max_nodes=50,
+                    max_conns=100,
+                    node_gene=DefaultNodeGene(
+                        activation_default=Act.tanh,
+                        # activation_options=(Act.tanh,),
+                        activation_options=ACT_ALL,
+                        aggregation_default=Agg.sum,
+                        # aggregation_options=(Agg.sum,),
+                        aggregation_options=AGG_ALL,
+                    ),
+                    output_transform=Act.standard_sigmoid,  # the activation function for output node
+                    mutation=DefaultMutation(
+                        node_add=0.1,
+                        conn_add=0.1,
+                        node_delete=0,
+                        conn_delete=0,
+                    ),
+                ),
+                pop_size=10000,
+                species_size=20,
+                compatibility_threshold=2,
+                survival_threshold=0.01,  # magic
+            ),
+        ),
+        problem=XOR3d(),
+        generation_limit=10000,
+        fitness_target=-1e-3,
+    )
+
+    # initialize state
+    state = pipeline.setup()
+    # print(state)
+    # run until terminate
+    state, best = pipeline.auto_run(state)
+    # show result
+    pipeline.show(state, best)
+    pipeline.save(state=state)