Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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90 lines
1.5 KiB
90 lines
1.5 KiB
from textwrap import dedent
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from pandas.util._decorators import doc
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@doc(method="cumsum", operation="sum")
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def cumsum(whatever):
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"""
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This is the {method} method.
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It computes the cumulative {operation}.
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"""
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@doc(
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cumsum,
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dedent(
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"""
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Examples
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--------
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>>> cumavg([1, 2, 3])
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2
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"""
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),
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method="cumavg",
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operation="average",
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)
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def cumavg(whatever):
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pass
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@doc(cumsum, method="cummax", operation="maximum")
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def cummax(whatever):
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pass
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@doc(cummax, method="cummin", operation="minimum")
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def cummin(whatever):
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pass
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def test_docstring_formatting():
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docstr = dedent(
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"""
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This is the cumsum method.
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It computes the cumulative sum.
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"""
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)
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assert cumsum.__doc__ == docstr
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def test_docstring_appending():
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docstr = dedent(
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"""
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This is the cumavg method.
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It computes the cumulative average.
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Examples
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--------
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>>> cumavg([1, 2, 3])
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2
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"""
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)
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assert cumavg.__doc__ == docstr
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def test_doc_template_from_func():
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docstr = dedent(
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"""
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This is the cummax method.
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It computes the cumulative maximum.
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"""
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)
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assert cummax.__doc__ == docstr
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def test_inherit_doc_template():
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docstr = dedent(
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"""
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This is the cummin method.
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It computes the cumulative minimum.
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"""
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)
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assert cummin.__doc__ == docstr
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