Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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65 lines
1.9 KiB
65 lines
1.9 KiB
from datetime import date, datetime
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from hypothesis import given, strategies as st
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import numpy as np
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import pytest
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from pandas._libs.tslibs import ccalendar
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import pandas as pd
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@pytest.mark.parametrize(
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"date_tuple,expected",
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[
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((2001, 3, 1), 60),
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((2004, 3, 1), 61),
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((1907, 12, 31), 365), # End-of-year, non-leap year.
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((2004, 12, 31), 366), # End-of-year, leap year.
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],
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)
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def test_get_day_of_year_numeric(date_tuple, expected):
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assert ccalendar.get_day_of_year(*date_tuple) == expected
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def test_get_day_of_year_dt():
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dt = datetime.fromordinal(1 + np.random.randint(365 * 4000))
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result = ccalendar.get_day_of_year(dt.year, dt.month, dt.day)
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expected = (dt - dt.replace(month=1, day=1)).days + 1
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assert result == expected
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@pytest.mark.parametrize(
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"input_date_tuple, expected_iso_tuple",
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[
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[(2020, 1, 1), (2020, 1, 3)],
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[(2019, 12, 31), (2020, 1, 2)],
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[(2019, 12, 30), (2020, 1, 1)],
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[(2009, 12, 31), (2009, 53, 4)],
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[(2010, 1, 1), (2009, 53, 5)],
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[(2010, 1, 3), (2009, 53, 7)],
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[(2010, 1, 4), (2010, 1, 1)],
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[(2006, 1, 1), (2005, 52, 7)],
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[(2005, 12, 31), (2005, 52, 6)],
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[(2008, 12, 28), (2008, 52, 7)],
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[(2008, 12, 29), (2009, 1, 1)],
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],
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)
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def test_dt_correct_iso_8601_year_week_and_day(input_date_tuple, expected_iso_tuple):
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result = ccalendar.get_iso_calendar(*input_date_tuple)
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expected_from_date_isocalendar = date(*input_date_tuple).isocalendar()
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assert result == expected_from_date_isocalendar
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assert result == expected_iso_tuple
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@given(
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st.datetimes(
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min_value=pd.Timestamp.min.to_pydatetime(warn=False),
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max_value=pd.Timestamp.max.to_pydatetime(warn=False),
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)
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)
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def test_isocalendar(dt):
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expected = dt.isocalendar()
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result = ccalendar.get_iso_calendar(dt.year, dt.month, dt.day)
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assert result == expected
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