complete HyperNEAT!

test/unit/test_cartesian_product.py

@@ -0,0 +1,56 @@
+import numpy as np
+
+from algorithm.hyperneat.substrate.tools import cartesian_product
+
+
+def test01():
+    keys1 = np.array([1, 2, 3])
+    keys2 = np.array([4, 5, 6, 7])
+
+    coors1 = np.array([
+        [1, 1, 1],
+        [2, 2, 2],
+        [3, 3, 3]
+    ])
+
+    coors2 = np.array([
+        [4, 4, 4],
+        [5, 5, 5],
+        [6, 6, 6],
+        [7, 7, 7]
+    ])
+
+    target_coors = np.array([
+        [1, 1, 1, 4, 4, 4],
+        [1, 1, 1, 5, 5, 5],
+        [1, 1, 1, 6, 6, 6],
+        [1, 1, 1, 7, 7, 7],
+        [2, 2, 2, 4, 4, 4],
+        [2, 2, 2, 5, 5, 5],
+        [2, 2, 2, 6, 6, 6],
+        [2, 2, 2, 7, 7, 7],
+        [3, 3, 3, 4, 4, 4],
+        [3, 3, 3, 5, 5, 5],
+        [3, 3, 3, 6, 6, 6],
+        [3, 3, 3, 7, 7, 7]
+    ])
+
+    target_keys = np.array([
+        [1, 4],
+        [1, 5],
+        [1, 6],
+        [1, 7],
+        [2, 4],
+        [2, 5],
+        [2, 6],
+        [2, 7],
+        [3, 4],
+        [3, 5],
+        [3, 6],
+        [3, 7]
+    ])
+
+    new_coors, correspond_keys = cartesian_product(keys1, keys2, coors1, coors2)
+
+    assert np.array_equal(new_coors, target_coors)
+    assert np.array_equal(correspond_keys, target_keys)

test/unit/test_graphs.py

@@ -1,7 +1,7 @@
 import jax.numpy as jnp
 
 from algorithm.neat.genome.graph import topological_sort, check_cycles
-from algorithm.neat.utils import I_INT
+from algorithm.utils import I_INT
 
 nodes = jnp.array([
     [0],

test/unit/test_utils.py

@@ -1,5 +1,5 @@
 import jax.numpy as jnp
-from algorithm.neat.utils import unflatten_connections
+from algorithm.utils import unflatten_connections
 
 
 def test_unflatten():