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Add more competition functions

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This commit is contained in:
Jensun Ravichandran
2021-06-01 12:37:21 +02:00
parent 8227525c82
commit 946cda00d2
2 changed files with 131 additions and 27 deletions
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54
tests/test_functions.py
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@@ -125,7 +125,7 @@ class TestCompetitions(unittest.TestCase):
decimal=5)
self.assertIsNone(mismatch)
def test_stratified_min_simple(self):
def test_stratified_min_trivial(self):
d = torch.tensor([[0.0, 2.0, 3.0], [8.0, 0, 1]])
labels = torch.tensor([0, 1, 2])
actual = competitions.stratified_min(d, labels)
@@ -135,6 +135,58 @@ class TestCompetitions(unittest.TestCase):
decimal=5)
self.assertIsNone(mismatch)
def test_stratified_max(self):
d = torch.tensor([[1.0, 0.0, 2.0, 3.0, 9.0], [9.0, 8.0, 0, 1, 7.0]])
labels = torch.tensor([0, 0, 3, 2, 0])
actual = competitions.stratified_max(d, labels)
desired = torch.tensor([[9.0, 3.0, 2.0], [9.0, 1.0, 0.0]])
mismatch = np.testing.assert_array_almost_equal(actual,
desired,
decimal=5)
self.assertIsNone(mismatch)
def test_stratified_max_one_hot(self):
d = torch.tensor([[1.0, 0.0, 2.0, 3.0, 9.0], [9.0, 8.0, 0, 1, 7.0]])
labels = torch.tensor([0, 0, 2, 1, 0])
labels = torch.nn.functional.one_hot(labels, num_classes=3)
actual = competitions.stratified_max(d, labels)
desired = torch.tensor([[9.0, 3.0, 2.0], [9.0, 1.0, 0.0]])
mismatch = np.testing.assert_array_almost_equal(actual,
desired,
decimal=5)
self.assertIsNone(mismatch)
def test_stratified_sum(self):
d = torch.tensor([[1.0, 0.0, 2.0, 3.0], [9.0, 8.0, 0, 1]])
labels = torch.LongTensor([0, 0, 1, 2])
actual = competitions.stratified_sum(d, labels)
desired = torch.tensor([[1.0, 2.0, 3.0], [17.0, 0.0, 1.0]])
mismatch = np.testing.assert_array_almost_equal(actual,
desired,
decimal=5)
self.assertIsNone(mismatch)
def test_stratified_sum_one_hot(self):
d = torch.tensor([[1.0, 0.0, 2.0, 3.0], [9.0, 8.0, 0, 1]])
labels = torch.tensor([0, 0, 1, 2])
labels = torch.eye(3)[labels]
actual = competitions.stratified_sum(d, labels)
desired = torch.tensor([[1.0, 2.0, 3.0], [17.0, 0.0, 1.0]])
mismatch = np.testing.assert_array_almost_equal(actual,
desired,
decimal=5)
self.assertIsNone(mismatch)
def test_stratified_prod(self):
d = torch.tensor([[1.0, 0.0, 2.0, 3.0, 9.0], [9.0, 8.0, 0, 1, 7.0]])
labels = torch.tensor([0, 0, 3, 2, 0])
actual = competitions.stratified_prod(d, labels)
desired = torch.tensor([[0.0, 3.0, 2.0], [504.0, 1.0, 0.0]])
mismatch = np.testing.assert_array_almost_equal(actual,
desired,
decimal=5)
self.assertIsNone(mismatch)
def test_knnc_k1(self):
d = torch.tensor([[2.0, 3.0, 1.99, 3.01], [2.0, 3.0, 2.01, 3.0]])
labels = torch.tensor([0, 1, 2, 3])