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