Merge pull request #10 from mooscaliaproject/fix/crowding_distance_w_…

…dups

CHORE: test for edge case

tests/test_survival.py

@@ -0,0 +1,126 @@
+import numpy as np
+
+try:
+    from pymoode.cython.pruning_cd import calc_pcd
+
+    do_test = True
+except ModuleNotFoundError:
+    print('Module not found for Cython pruning_cd')
+    do_test = False
+    calc_pcd = None
+
+
+def test_edgecase_pcd():
+    X = np.array([
+        [0.44107087, -0.39376368, -0.35701034],
+        [0.43660261, -0.38772938, -0.35929946],
+        [0.44107087, -0.39376368, -0.35701034],
+        [0.43791779, -0.3895055, -0.35862569],
+        [0.44053895, -0.39304534, -0.35728285],
+        [0.43786142, -0.38942938, -0.35865456],
+        [0.43964992, -0.39184472, -0.3577383],
+        [0.43999904, -0.3923162, -0.35755945],
+        [0.43447003, -0.38484936, -0.36039199],
+        [0.43631468, -0.38734053, -0.35944697],
+        [0.43207851, -0.38161963, -0.36161718],
+        [0.43174801, -0.3811733, -0.3617865],
+        [0.4373249, -0.38870481, -0.35892943],
+        [0.43829797, -0.39001893, -0.35843091],
+        [0.43336635, -0.38335885, -0.36095741],
+        [0.43480479, -0.38530144, -0.36022049],
+        [0.43306025, -0.38294546, -0.36111423],
+        [0.4366501, -0.3877935, -0.35927513],
+        [0.43741487, -0.38882631, -0.35888333],
+        [0.43853913, -0.39034461, -0.35830737],
+        [0.43672522, -0.38789495, -0.35923664],
+        [0.43588172, -0.38675582, -0.35966877],
+        [0.43909541, -0.39109586, -0.35802238],
+        [0.4396585, -0.39185631, -0.35773391],
+        [0.43584245, -0.38670279, -0.35968889],
+        [0.43348672, -0.3835214, -0.36089575],
+        [0.43123517, -0.38048072, -0.36204923],
+        [0.43516766, -0.38579149, -0.36003459],
+        [0.43546305, -0.38619041, -0.35988326],
+        [0.43867936, -0.39053399, -0.35823553],
+        [0.4409444, -0.3935929, -0.35707513],
+        [0.435545, -0.38630108, -0.35984128],
+        [0.43851132, -0.39030706, -0.35832161],
+        [0.43436811, -0.38471171, -0.36044421],
+        [0.43914191, -0.39115866, -0.35799856],
+        [0.43708624, -0.38838251, -0.35905169],
+        [0.4384717, -0.39025355, -0.35834191],
+        [0.43205424, -0.38158686, -0.36162962],
+        [0.44088654, -0.39351476, -0.35710477],
+        [0.43243631, -0.38210284, -0.36143388],
+        [0.43979464, -0.39204016, -0.35766416],
+        [0.43381116, -0.38395956, -0.36072954],
+        [0.43370379, -0.38381456, -0.36078454],
+        [0.43269153, -0.38244751, -0.36130313],
+        [0.43924092, -0.39129237, -0.35794784],
+        [0.43872278, -0.39059263, -0.35821328],
+        [0.43903785, -0.39101812, -0.35805187],
+        [0.43411261, -0.38436667, -0.3605751],
+        [0.43423356, -0.38453, -0.36051314],
+        [0.44024805, -0.39265249, -0.35743188],
+        [0.44087024, -0.39349274, -0.35711313],
+        [0.43305819, -0.38294268, -0.36111529],
+    ])
+    res = np.array([
+        np.inf,
+        0.03410153,
+        np.inf,
+        0.0443843,
+        0.06325797,
+        0.05113217,
+        0.04245589,
+        0.04609897,
+        0.04439749,
+        0.07329366,
+        0.03884496,
+        0.08327485,
+        0.03341132,
+        0.05631684,
+        0.04335893,
+        0.07092818,
+        0.03133131,
+        0.01246547,
+        0.05454877,
+        0.01708464,
+        0.04434333,
+        0.0480121,
+        0.01057988,
+        0.01471335,
+        0.03423474,
+        0.03430807,
+        np.inf,
+        0.0669258,
+        0.03836405,
+        0.01867222,
+        0.01874031,
+        0.03857378,
+        0.00685487,
+        0.0240425,
+        0.01479437,
+        0.06096955,
+        0.02169136,
+        0.03360176,
+        0.00754014,
+        0.06232631,
+        0.03462236,
+        0.04156483,
+        0.03298651,
+        0.06322694,
+        0.05164993,
+        0.03644734,
+        0.03788544,
+        0.04294547,
+        0.0259765,
+        0.05489302,
+        0.03533971,
+        0.03748806,
+    ])
+
+    d = calc_pcd(X)
+    assert np.all(np.isclose(res, d, atol=1e-4)), (
+        'Wrong results for crowding distances on edge case'
+    )