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124 lines
3.3 KiB
Python
124 lines
3.3 KiB
Python
import numpy as np
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import pytest
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from pandas._libs.tslibs import (
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iNaT,
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to_offset,
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)
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from pandas._libs.tslibs.period import (
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extract_ordinals,
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get_period_field_arr,
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period_asfreq,
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period_ordinal,
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)
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import pandas._testing as tm
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def get_freq_code(freqstr: str) -> int:
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off = to_offset(freqstr, is_period=True)
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# error: "BaseOffset" has no attribute "_period_dtype_code"
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code = off._period_dtype_code # type: ignore[attr-defined]
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return code
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@pytest.mark.parametrize(
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"freq1,freq2,expected",
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[
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("D", "h", 24),
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("D", "min", 1440),
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("D", "s", 86400),
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("D", "ms", 86400000),
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("D", "us", 86400000000),
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("D", "ns", 86400000000000),
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("h", "min", 60),
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("h", "s", 3600),
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("h", "ms", 3600000),
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("h", "us", 3600000000),
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("h", "ns", 3600000000000),
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("min", "s", 60),
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("min", "ms", 60000),
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("min", "us", 60000000),
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("min", "ns", 60000000000),
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("s", "ms", 1000),
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("s", "us", 1000000),
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("s", "ns", 1000000000),
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("ms", "us", 1000),
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("ms", "ns", 1000000),
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("us", "ns", 1000),
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],
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)
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def test_intra_day_conversion_factors(freq1, freq2, expected):
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assert (
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period_asfreq(1, get_freq_code(freq1), get_freq_code(freq2), False) == expected
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)
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@pytest.mark.parametrize(
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"freq,expected", [("Y", 0), ("M", 0), ("W", 1), ("D", 0), ("B", 0)]
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)
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def test_period_ordinal_start_values(freq, expected):
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# information for Jan. 1, 1970.
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assert period_ordinal(1970, 1, 1, 0, 0, 0, 0, 0, get_freq_code(freq)) == expected
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@pytest.mark.parametrize(
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"dt,expected",
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[
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((1970, 1, 4, 0, 0, 0, 0, 0), 1),
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((1970, 1, 5, 0, 0, 0, 0, 0), 2),
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((2013, 10, 6, 0, 0, 0, 0, 0), 2284),
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((2013, 10, 7, 0, 0, 0, 0, 0), 2285),
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],
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)
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def test_period_ordinal_week(dt, expected):
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args = dt + (get_freq_code("W"),)
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assert period_ordinal(*args) == expected
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@pytest.mark.parametrize(
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"day,expected",
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[
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# Thursday (Oct. 3, 2013).
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(3, 11415),
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# Friday (Oct. 4, 2013).
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(4, 11416),
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# Saturday (Oct. 5, 2013).
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(5, 11417),
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# Sunday (Oct. 6, 2013).
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(6, 11417),
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# Monday (Oct. 7, 2013).
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(7, 11417),
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# Tuesday (Oct. 8, 2013).
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(8, 11418),
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],
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)
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def test_period_ordinal_business_day(day, expected):
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# 5000 is PeriodDtypeCode for BusinessDay
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args = (2013, 10, day, 0, 0, 0, 0, 0, 5000)
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assert period_ordinal(*args) == expected
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class TestExtractOrdinals:
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def test_extract_ordinals_raises(self):
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# with non-object, make sure we raise TypeError, not segfault
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arr = np.arange(5)
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freq = to_offset("D")
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with pytest.raises(TypeError, match="values must be object-dtype"):
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extract_ordinals(arr, freq)
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def test_extract_ordinals_2d(self):
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freq = to_offset("D")
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arr = np.empty(10, dtype=object)
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arr[:] = iNaT
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res = extract_ordinals(arr, freq)
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res2 = extract_ordinals(arr.reshape(5, 2), freq)
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tm.assert_numpy_array_equal(res, res2.reshape(-1))
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def test_get_period_field_array_raises_on_out_of_range():
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msg = "Buffer dtype mismatch, expected 'const int64_t' but got 'double'"
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with pytest.raises(ValueError, match=msg):
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get_period_field_arr(-1, np.empty(1), 0)
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