Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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36 lines
960 B
36 lines
960 B
import numpy as np
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import pytest
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from pandas._libs.tslibs.timedeltas import delta_to_nanoseconds
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from pandas import Timedelta, offsets
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@pytest.mark.parametrize(
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"obj,expected",
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[
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(np.timedelta64(14, "D"), 14 * 24 * 3600 * 1e9),
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(Timedelta(minutes=-7), -7 * 60 * 1e9),
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(Timedelta(minutes=-7).to_pytimedelta(), -7 * 60 * 1e9),
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(offsets.Nano(125), 125),
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(1, 1),
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(np.int64(2), 2),
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(np.int32(3), 3),
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],
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)
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def test_delta_to_nanoseconds(obj, expected):
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result = delta_to_nanoseconds(obj)
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assert result == expected
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def test_delta_to_nanoseconds_error():
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obj = np.array([123456789], dtype="m8[ns]")
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with pytest.raises(TypeError, match="<class 'numpy.ndarray'>"):
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delta_to_nanoseconds(obj)
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def test_huge_nanoseconds_overflow():
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# GH 32402
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assert delta_to_nanoseconds(Timedelta(1e10)) == 1e10
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assert delta_to_nanoseconds(Timedelta(nanoseconds=1e10)) == 1e10
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