delete useless;

append readme

examples/func_fit/xor.py

@@ -5,6 +5,7 @@ from algorithm.neat.gene import NormalGene, NormalGeneConfig
 from problem.func_fit import XOR, FuncFitConfig
 
 if __name__ == '__main__':
+    # running config
     config = Config(
         basic=BasicConfig(
             seed=42,
@@ -12,13 +13,6 @@ if __name__ == '__main__':
             pop_size=10000
         ),
         neat=NeatConfig(
-            max_nodes=50,
-            max_conns=100,
-            max_species=30,
-            conn_add=0.8,
-            conn_delete=0,
-            node_add=0.4,
-            node_delete=0,
             inputs=2,
             outputs=1
         ),
@@ -27,10 +21,13 @@ if __name__ == '__main__':
             error_method='rmse'
         )
     )
-
+    # define algorithm: NEAT with NormalGene
     algorithm = NEAT(config, NormalGene)
+    # full pipeline
     pipeline = Pipeline(config, algorithm, XOR)
+    # initialize state
     state = pipeline.setup()
-    pipeline.pre_compile(state)
+    # run until terminate
     state, best = pipeline.auto_run(state)
+    # show result
     pipeline.show(state, best)

examples/general_xor.py

@@ -0,0 +1,41 @@
+from config import *
+from pipeline import Pipeline
+from algorithm import NEAT
+from algorithm.neat.gene import NormalGene, NormalGeneConfig
+from problem.func_fit import XOR, FuncFitConfig
+
+def evaluate():
+    pass
+
+
+
+if __name__ == '__main__':
+    config = Config(
+        basic=BasicConfig(
+            seed=42,
+            fitness_target=-1e-2,
+            pop_size=10000
+        ),
+        neat=NeatConfig(
+            max_nodes=50,
+            max_conns=100,
+            max_species=30,
+            conn_add=0.8,
+            conn_delete=0,
+            node_add=0.4,
+            node_delete=0,
+            inputs=2,
+            outputs=1
+        ),
+        gene=NormalGeneConfig(),
+        problem=FuncFitConfig(
+            error_method='rmse'
+        )
+    )
+
+    algorithm = NEAT(config, NormalGene)
+    pipeline = Pipeline(config, algorithm, XOR)
+    state = pipeline.setup()
+    pipeline.pre_compile(state)
+    state, best = pipeline.auto_run(state)
+    pipeline.show(state, best)