|
| 1 | +import unittest |
| 2 | + |
| 3 | +import numpy as np |
| 4 | + |
| 5 | +import tdamapper.utils.metrics as metrics |
| 6 | + |
| 7 | + |
| 8 | +class TestMetrics(unittest.TestCase): |
| 9 | + |
| 10 | + def test_euclidean(self): |
| 11 | + d = metrics.euclidean() |
| 12 | + a = np.array([1.0, 0.0]) |
| 13 | + b = np.array([0.0, 1.0]) |
| 14 | + ab = d(a, b) |
| 15 | + self.assertGreaterEqual(ab, 1.414) |
| 16 | + self.assertLessEqual(ab, 1.415) |
| 17 | + |
| 18 | + def test_manhattan(self): |
| 19 | + d = metrics.manhattan() |
| 20 | + a = np.array([1.0, 0.0]) |
| 21 | + b = np.array([0.0, 1.0]) |
| 22 | + ab = d(a, b) |
| 23 | + self.assertEqual(ab, 2.0) |
| 24 | + |
| 25 | + def test_chebyshev(self): |
| 26 | + d = metrics.chebyshev() |
| 27 | + a = np.array([1.0, 0.0]) |
| 28 | + b = np.array([0.0, 1.0]) |
| 29 | + ab = d(a, b) |
| 30 | + self.assertEqual(ab, 1.0) |
| 31 | + |
| 32 | + def test_cosine(self): |
| 33 | + d = metrics.cosine() |
| 34 | + a = np.array([1.0, 0.0]) |
| 35 | + b = np.array([0.0, 1.0]) |
| 36 | + c = np.array([0.0, 2.0]) |
| 37 | + ab = d(a, b) |
| 38 | + self.assertGreaterEqual(ab, 1.414) |
| 39 | + self.assertLessEqual(ab, 1.415) |
| 40 | + bc = d(b, c) |
| 41 | + self.assertEqual(bc, 0.0) |
| 42 | + |
| 43 | + def test_get_metric(self): |
| 44 | + self.assertEqual(metrics.euclidean(), metrics.get_metric('euclidean')) |
| 45 | + self.assertEqual(metrics.euclidean(), metrics.get_metric('minkowski')) |
| 46 | + self.assertEqual(metrics.chebyshev(), metrics.get_metric('chebyshev')) |
| 47 | + self.assertEqual(metrics.chebyshev(), metrics.get_metric('minkowski', p=np.inf)) |
| 48 | + self.assertEqual(metrics.chebyshev(), metrics.get_metric('minkowski', p=float('inf'))) |
| 49 | + self.assertEqual(metrics.manhattan(), metrics.get_metric('manhattan')) |
| 50 | + self.assertEqual(metrics.manhattan(), metrics.get_metric('minkowski', p=1)) |
| 51 | + self.assertEqual(metrics.cosine(), metrics.get_metric('cosine')) |
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