Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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130 lines
3.7 KiB
130 lines
3.7 KiB
from datetime import datetime
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import numpy as np
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import pytest
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from pytz import UTC
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from pandas._libs.tslibs import (
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OutOfBoundsTimedelta,
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conversion,
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iNaT,
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timezones,
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tzconversion,
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)
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from pandas import Timestamp, date_range
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import pandas._testing as tm
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def _compare_utc_to_local(tz_didx):
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def f(x):
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return tzconversion.tz_convert_from_utc_single(x, tz_didx.tz)
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result = tzconversion.tz_convert_from_utc(tz_didx.asi8, tz_didx.tz)
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expected = np.vectorize(f)(tz_didx.asi8)
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tm.assert_numpy_array_equal(result, expected)
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def _compare_local_to_utc(tz_didx, naive_didx):
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# Check that tz_localize behaves the same vectorized and pointwise.
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err1 = err2 = None
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try:
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result = tzconversion.tz_localize_to_utc(naive_didx.asi8, tz_didx.tz)
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err1 = None
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except Exception as err:
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err1 = err
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try:
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expected = naive_didx.map(lambda x: x.tz_localize(tz_didx.tz)).asi8
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except Exception as err:
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err2 = err
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if err1 is not None:
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assert type(err1) == type(err2)
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else:
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assert err2 is None
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tm.assert_numpy_array_equal(result, expected)
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def test_tz_convert_single_matches_tz_convert_hourly(tz_aware_fixture):
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tz = tz_aware_fixture
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tz_didx = date_range("2014-03-01", "2015-01-10", freq="H", tz=tz)
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naive_didx = date_range("2014-03-01", "2015-01-10", freq="H")
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_compare_utc_to_local(tz_didx)
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_compare_local_to_utc(tz_didx, naive_didx)
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@pytest.mark.parametrize("freq", ["D", "A"])
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def test_tz_convert_single_matches_tz_convert(tz_aware_fixture, freq):
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tz = tz_aware_fixture
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tz_didx = date_range("2000-01-01", "2020-01-01", freq=freq, tz=tz)
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naive_didx = date_range("2000-01-01", "2020-01-01", freq=freq)
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_compare_utc_to_local(tz_didx)
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_compare_local_to_utc(tz_didx, naive_didx)
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@pytest.mark.parametrize(
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"arr",
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[
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pytest.param(np.array([], dtype=np.int64), id="empty"),
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pytest.param(np.array([iNaT], dtype=np.int64), id="all_nat"),
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],
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)
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def test_tz_convert_corner(arr):
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result = tzconversion.tz_convert_from_utc(arr, timezones.maybe_get_tz("Asia/Tokyo"))
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tm.assert_numpy_array_equal(result, arr)
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@pytest.mark.parametrize("copy", [True, False])
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@pytest.mark.parametrize("dtype", ["M8[ns]", "M8[s]"])
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def test_length_zero_copy(dtype, copy):
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arr = np.array([], dtype=dtype)
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result = conversion.ensure_datetime64ns(arr, copy=copy)
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assert result.base is (None if copy else arr)
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def test_ensure_datetime64ns_bigendian():
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# GH#29684
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arr = np.array([np.datetime64(1, "ms")], dtype=">M8[ms]")
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result = conversion.ensure_datetime64ns(arr)
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expected = np.array([np.datetime64(1, "ms")], dtype="M8[ns]")
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tm.assert_numpy_array_equal(result, expected)
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def test_ensure_timedelta64ns_overflows():
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arr = np.arange(10).astype("m8[Y]") * 100
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msg = r"Out of bounds for nanosecond timedelta64\[Y\] 900"
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with pytest.raises(OutOfBoundsTimedelta, match=msg):
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conversion.ensure_timedelta64ns(arr)
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class SubDatetime(datetime):
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pass
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@pytest.mark.parametrize(
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"dt, expected",
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[
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pytest.param(
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Timestamp("2000-01-01"), Timestamp("2000-01-01", tz=UTC), id="timestamp"
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),
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pytest.param(
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datetime(2000, 1, 1), datetime(2000, 1, 1, tzinfo=UTC), id="datetime"
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),
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pytest.param(
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SubDatetime(2000, 1, 1),
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SubDatetime(2000, 1, 1, tzinfo=UTC),
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id="subclassed_datetime",
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),
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],
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)
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def test_localize_pydatetime_dt_types(dt, expected):
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# GH 25851
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# ensure that subclassed datetime works with
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# localize_pydatetime
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result = conversion.localize_pydatetime(dt, UTC)
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assert result == expected
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