66 lines
2.3 KiB
Python
66 lines
2.3 KiB
Python
import unittest
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import numpy as np
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from scipy.sparse import csr_matrix
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import quapy as qp
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class LabelCollectionTestCase(unittest.TestCase):
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def test_split(self):
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x = np.arange(100)
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y = np.random.randint(0,5,100)
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data = qp.data.LabelledCollection(x,y)
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tr, te = data.split_random(0.7)
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check_prev = tr.prevalence()*0.7 + te.prevalence()*0.3
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self.assertEqual(len(tr), 70)
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self.assertEqual(len(te), 30)
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self.assertEqual(np.allclose(check_prev, data.prevalence()), True)
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self.assertEqual(len(tr+te), len(data))
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def test_join(self):
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x = np.arange(50)
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y = np.random.randint(2, 5, 50)
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data1 = qp.data.LabelledCollection(x, y)
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x = np.arange(200)
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y = np.random.randint(0, 3, 200)
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data2 = qp.data.LabelledCollection(x, y)
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x = np.arange(100)
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y = np.random.randint(0, 6, 100)
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data3 = qp.data.LabelledCollection(x, y)
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combined = qp.data.LabelledCollection.join(data1, data2, data3)
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self.assertEqual(len(combined), len(data1)+len(data2)+len(data3))
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self.assertEqual(all(combined.classes_ == np.arange(6)), True)
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x = np.random.rand(10, 3)
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y = np.random.randint(0, 1, 10)
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data4 = qp.data.LabelledCollection(x, y)
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with self.assertRaises(Exception):
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combined = qp.data.LabelledCollection.join(data1, data2, data3, data4)
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x = np.random.rand(20, 3)
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y = np.random.randint(0, 1, 20)
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data5 = qp.data.LabelledCollection(x, y)
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combined = qp.data.LabelledCollection.join(data4, data5)
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self.assertEqual(len(combined), len(data4)+len(data5))
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x = np.random.rand(10, 4)
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y = np.random.randint(0, 1, 10)
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data6 = qp.data.LabelledCollection(x, y)
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with self.assertRaises(Exception):
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combined = qp.data.LabelledCollection.join(data4, data5, data6)
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data4.instances = csr_matrix(data4.instances)
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with self.assertRaises(Exception):
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combined = qp.data.LabelledCollection.join(data4, data5)
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data5.instances = csr_matrix(data5.instances)
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combined = qp.data.LabelledCollection.join(data4, data5)
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self.assertEqual(len(combined), len(data4) + len(data5))
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if __name__ == '__main__':
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unittest.main()
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