update readme

examples/func_fit/xor.py

@@ -1,31 +1,27 @@
 from tensorneat.pipeline import Pipeline
-from tensorneat.algorithm.neat import NEAT
-from tensorneat.genome import DefaultGenome
-from tensorneat.problem.func_fit import XOR3d
-from tensorneat.common import ACT
+from tensorneat import algorithm, genome, problem, common
 
-if __name__ == "__main__":
-    pipeline = Pipeline(
-        algorithm=NEAT(
-            pop_size=10000,
-            species_size=20,
-            survival_threshold=0.01,
-            genome=DefaultGenome(
-                num_inputs=3,
-                num_outputs=1,
-                init_hidden_layers=(),
-                output_transform=ACT.sigmoid,
-            ),
-        ),
-        problem=XOR3d(),
-        generation_limit=500,
-        fitness_target=-1e-6,  # float32 precision
-        seed=42,
-    )
+algorithm = algorithm.NEAT(
+    pop_size=10000,
+    species_size=20,
+    survival_threshold=0.01,
+    genome=genome.DefaultGenome(
+        num_inputs=3,
+        num_outputs=1,
+        output_transform=common.ACT.sigmoid,
+    ),
+)
+problem = problem.XOR3d()
 
-    # initialize state
-    state = pipeline.setup()
-    # run until terminate
-    state, best = pipeline.auto_run(state)
-    # show result
-    pipeline.show(state, best)
+pipeline = Pipeline(
+    algorithm,
+    problem,
+    generation_limit=200,
+    fitness_target=-1e-6,
+    seed=42,
+)
+state = pipeline.setup()
+# run until terminate
+state, best = pipeline.auto_run(state)
+# show result
+pipeline.show(state, best)