53 lines
1.7 KiB
Python
53 lines
1.7 KiB
Python
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import numpy as np
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from numpy.testing import assert_equal
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import pandas as pd
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from statsmodels.stats.base import HolderTuple
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def test_holdertuple():
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ht = HolderTuple(statistic=5, pvalue=0.1, text="just something",
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extra=[1, 2, 4])
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assert_equal(len(ht), 2)
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assert_equal(ht[:], [5, 0.1])
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p, v = ht
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assert_equal([p, v], [5, 0.1])
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p, v = ht[0], ht[1]
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assert_equal([p, v], [5, 0.1])
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assert_equal(list(ht), [5, 0.1])
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assert_equal(np.asarray(ht), [5, 0.1])
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assert_equal(np.asarray(ht).dtype, np.float64)
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x = np.zeros((2, 2))
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x[0] = ht
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assert_equal(x, [[5, 0.1], [0, 0]])
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assert_equal(pd.Series(ht).values, [5, 0.1])
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assert_equal(pd.DataFrame([ht, ht]).values, [[5, 0.1], [5, 0.1]])
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assert_equal(ht.statistic, 5)
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assert_equal(ht.pvalue, 0.1)
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assert_equal(ht.extra, [1, 2, 4])
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assert_equal(ht.text, "just something")
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def test_holdertuple2():
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ht = HolderTuple(tuple_=("statistic", "extra"), statistic=5, pvalue=0.1,
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text="just something", extra=[1, 2, 4])
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assert_equal(len(ht), 2)
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assert_equal(ht[:], [5, [1, 2, 4]])
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p, v = ht
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assert_equal([p, v], [5, [1, 2, 4]])
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p, v = ht[0], ht[1]
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assert_equal([p, v], [5, [1, 2, 4]])
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assert_equal(list(ht), [5, [1, 2, 4]])
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x = np.asarray(ht, dtype=object)
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assert_equal(x, np.asarray([5, [1, 2, 4]], dtype=object))
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assert_equal(x.dtype, np.dtype('O'))
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# assert_equal(pd.Series(ht).values, [5, [1, 2, 4]])
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# assert_equal(pd.Series(ht).dtype, np.dtype('O'))
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assert_equal(ht.statistic, 5)
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assert_equal(ht.pvalue, 0.1)
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assert_equal(ht.extra, [1, 2, 4])
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assert_equal(ht.text, "just something")
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