Refactor test

Author: briling

tests/test_kernels.py

@@ -49,17 +49,18 @@ def test_batched_local_kernels():
     Y = np.array([[0.09992856, 0.50806631, 0.20024754, 0.74415417], [0.192892  , 0.70084475, 0.29322811, 0.77447945]])
     K_L_good = np.array([[0.48938983, 0.58251676], [0.32374891, 0.31778924]])
 
-    X_huge = np.concatenate([X]*1_000, axis=1)
-    X_huge = np.concatenate([X_huge]*1000, axis=0)
-    Y_huge = np.concatenate([Y]*1_000, axis=1)
-    Y_huge = np.concatenate([Y_huge]*50, axis=0)
-    K_L_good_huge = np.concatenate([K_L_good]*1000, axis=0)
-    K_L_good_huge = np.concatenate([K_L_good_huge]*50, axis=1)
+    X_huge = np.tile(X, (1000,1000))
+    Y_huge = np.tile(Y, (50,1000))
+    K_L_good_huge = np.tile(K_L_good, (1000,50))
 
     local_kernels.RAM_BATCHING_SIZE = 1024**2 * 50  # 50MiB
-    for akernel in ['L_custom_c', 'L_custom_py', 'L', 'L_sklearn']:
-        K = kernel.kernel(X_huge, Y_huge, akernel=akernel, sigma=2.0*1000)
-        assert np.allclose(K, K_L_good_huge)
+
+    K = kernel.kernel(X_huge, Y_huge, akernel='L_custom_py', sigma=2.0*1000)
+    assert np.allclose(K, K_L_good_huge)
+
+    K = kernel.kernel(X_huge.reshape((-1, 50, 80)), Y_huge.reshape((-1, 50, 80)), akernel='L_custom_py', sigma=2.0*1000)
+    assert np.allclose(K, K_L_good_huge)
+
 
 if __name__ == '__main__':
     test_local_kernels()