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https://github.com/microsoft/qlib.git
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fbba768006
* fixed a problem with multi index caused by the default value of groupkey * modify group_key default value * limit pandas verion * format with black * fix docs error * fix docs error * fixed bugs caused by pandas upgrade * remove needless code * reformat with black * limit version & add docs
38 lines
1.7 KiB
Python
38 lines
1.7 KiB
Python
import unittest
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import numpy as np
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from qlib.data import D
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from qlib.tests import TestAutoData
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class TestDataset(TestAutoData):
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def testCSI300(self):
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close_p = D.features(D.instruments("csi300"), ["$close"])
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size = close_p.groupby("datetime", group_keys=False).size()
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cnt = close_p.groupby("datetime", group_keys=False).count()["$close"]
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size_desc = size.describe(percentiles=np.arange(0.1, 1.0, 0.1))
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cnt_desc = cnt.describe(percentiles=np.arange(0.1, 1.0, 0.1))
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print(size_desc)
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print(cnt_desc)
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self.assertLessEqual(size_desc.loc["max"], 305, "Excessive number of CSI300 constituent stocks")
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self.assertGreaterEqual(size_desc.loc["80%"], 290, "Insufficient number of CSI300 constituent stocks")
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self.assertLessEqual(cnt_desc.loc["max"], 305, "Excessive number of CSI300 constituent stocks")
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# FIXME: Due to the low quality of data. Hard to make sure there are enough data
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# self.assertEqual(cnt_desc.loc["80%"], 300, "Insufficient number of CSI300 constituent stocks")
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def testClose(self):
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close_p = D.features(D.instruments("csi300"), ["Ref($close, 1)/$close - 1"])
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close_desc = close_p.describe(percentiles=np.arange(0.1, 1.0, 0.1))
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print(close_desc)
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self.assertLessEqual(abs(close_desc.loc["90%"][0]), 0.1, "Close value is abnormal")
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self.assertLessEqual(abs(close_desc.loc["10%"][0]), 0.1, "Close value is abnormal")
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# FIXME: The yahoo data is not perfect. We have to
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# self.assertLessEqual(abs(close_desc.loc["max"][0]), 0.2, "Close value is abnormal")
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# self.assertGreaterEqual(close_desc.loc["min"][0], -0.2, "Close value is abnormal")
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if __name__ == "__main__":
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unittest.main()
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