File size: 3,424 Bytes
7885a28 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 |
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)
|