class TestVectorFilters(unittest.TestCase):
def setUp(self):
self.V = []
self.V.append((numpy.array([0]), 'data1', 0.4))
self.V.append((numpy.array([1]), 'data2', 0.9))
self.V.append((numpy.array([2]), 'data3', 1.4))
self.V.append((numpy.array([3]), 'data4', 2.1))
self.V.append((numpy.array([4]), 'data5', 0.1))
self.V.append((numpy.array([5]), 'data6', 8.7))
self.V.append((numpy.array([6]), 'data7', 3.4))
self.V.append((numpy.array([7]), 'data8', 2.8))
self.threshold_filter = DistanceThresholdFilter(1.0)
self.nearest_filter = NearestFilter(5)
self.unique = UniqueFilter()
def test_thresholding(self):
result = self.threshold_filter.filter_vectors(self.V)
self.assertEqual(len(result), 3)
self.assertIn(self.V[0], result)
self.assertIn(self.V[1], result)
self.assertIn(self.V[4], result)
def test_nearest(self):
result = self.nearest_filter.filter_vectors(self.V)
self.assertEqual(len(result), 5)
self.assertIn(self.V[0], result)
self.assertIn(self.V[1], result)
self.assertIn(self.V[4], result)
self.assertIn(self.V[2], result)
self.assertIn(self.V[3], result)
def test_unique(self):
W = self.V
W.append((numpy.array([7]), 'data8', 2.8))
W.append((numpy.array([0]), 'data1', 2.8))
W.append((numpy.array([1]), 'data2', 2.8))
W.append((numpy.array([6]), 'data7', 2.8))
result = self.unique.filter_vectors(W)
self.assertEqual(len(result), 8)
class TestVectorFilters(unittest.TestCase):
def setUp(self):
self.V = []
self.V.append((numpy.array([0]), 'data1', 0.4))
self.V.append((numpy.array([1]), 'data2', 0.9))
self.V.append((numpy.array([2]), 'data3', 1.4))
self.V.append((numpy.array([3]), 'data4', 2.1))
self.V.append((numpy.array([4]), 'data5', 0.1))
self.V.append((numpy.array([5]), 'data6', 8.7))
self.V.append((numpy.array([6]), 'data7', 3.4))
self.V.append((numpy.array([7]), 'data8', 2.8))
self.threshold_filter = DistanceThresholdFilter(1.0)
self.nearest_filter = NearestFilter(5)
self.unique = UniqueFilter()
def test_thresholding(self):
result = self.threshold_filter.filter_vectors(self.V)
self.assertEqual(len(result), 3)
self.assertTrue(self.V[0] in result)
self.assertTrue(self.V[1] in result)
self.assertTrue(self.V[4] in result)
def test_nearest(self):
result = self.nearest_filter.filter_vectors(self.V)
self.assertEqual(len(result), 5)
self.assertTrue(self.V[0] in result)
self.assertTrue(self.V[1] in result)
self.assertTrue(self.V[4] in result)
self.assertTrue(self.V[2] in result)
self.assertTrue(self.V[3] in result)
def test_unique(self):
W = self.V
W.append((numpy.array([7]), 'data8', 2.8))
W.append((numpy.array([0]), 'data1', 2.8))
W.append((numpy.array([1]), 'data2', 2.8))
W.append((numpy.array([6]), 'data7', 2.8))
result = self.unique.filter_vectors(W)
self.assertEqual(len(result), 8)
