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from datetime import (
date,
datetime,
time,
timedelta,
)
import numpy as np
import pytest
from pandas._libs import index as libindex
from pandas.compat.numpy import np_long
import pandas as pd
from pandas import (
DatetimeIndex,
Index,
Timestamp,
bdate_range,
date_range,
notna,
)
import pandas._testing as tm
from pandas.tseries.frequencies import to_offset
START, END = datetime(2009, 1, 1), datetime(2010, 1, 1)
class TestGetItem:
def test_getitem_slice_keeps_name(self):
# GH4226
st = Timestamp("2013-07-01 00:00:00", tz="America/Los_Angeles")
et = Timestamp("2013-07-02 00:00:00", tz="America/Los_Angeles")
dr = date_range(st, et, freq="h", name="timebucket")
assert dr[1:].name == dr.name
@pytest.mark.parametrize("tz", [None, "Asia/Tokyo"])
def test_getitem(self, tz):
idx = date_range("2011-01-01", "2011-01-31", freq="D", tz=tz, name="idx")
result = idx[0]
assert result == Timestamp("2011-01-01", tz=idx.tz)
result = idx[0:5]
expected = date_range(
"2011-01-01", "2011-01-05", freq="D", tz=idx.tz, name="idx"
)
tm.assert_index_equal(result, expected)
assert result.freq == expected.freq
result = idx[0:10:2]
expected = date_range(
"2011-01-01", "2011-01-09", freq="2D", tz=idx.tz, name="idx"
)
tm.assert_index_equal(result, expected)
assert result.freq == expected.freq
result = idx[-20:-5:3]
expected = date_range(
"2011-01-12", "2011-01-24", freq="3D", tz=idx.tz, name="idx"
)
tm.assert_index_equal(result, expected)
assert result.freq == expected.freq
result = idx[4::-1]
expected = DatetimeIndex(
["2011-01-05", "2011-01-04", "2011-01-03", "2011-01-02", "2011-01-01"],
dtype=idx.dtype,
freq="-1D",
name="idx",
)
tm.assert_index_equal(result, expected)
assert result.freq == expected.freq
@pytest.mark.parametrize("freq", ["B", "C"])
def test_dti_business_getitem(self, freq):
rng = bdate_range(START, END, freq=freq)
smaller = rng[:5]
exp = DatetimeIndex(rng.view(np.ndarray)[:5], freq=freq)
tm.assert_index_equal(smaller, exp)
assert smaller.freq == exp.freq
assert smaller.freq == rng.freq
sliced = rng[::5]
assert sliced.freq == to_offset(freq) * 5
fancy_indexed = rng[[4, 3, 2, 1, 0]]
assert len(fancy_indexed) == 5
assert isinstance(fancy_indexed, DatetimeIndex)
assert fancy_indexed.freq is None
# 32-bit vs. 64-bit platforms
assert rng[4] == rng[np_long(4)]
@pytest.mark.parametrize("freq", ["B", "C"])
def test_dti_business_getitem_matplotlib_hackaround(self, freq):
rng = bdate_range(START, END, freq=freq)
with pytest.raises(ValueError, match="Multi-dimensional indexing"):
# GH#30588 multi-dimensional indexing deprecated
rng[:, None]
def test_getitem_int_list(self):
dti = date_range(start="1/1/2005", end="12/1/2005", freq="ME")
dti2 = dti[[1, 3, 5]]
v1 = dti2[0]
v2 = dti2[1]
v3 = dti2[2]
assert v1 == Timestamp("2/28/2005")
assert v2 == Timestamp("4/30/2005")
assert v3 == Timestamp("6/30/2005")
# getitem with non-slice drops freq
assert dti2.freq is None
class TestWhere:
def test_where_doesnt_retain_freq(self):
dti = date_range("20130101", periods=3, freq="D", name="idx")
cond = [True, True, False]
expected = DatetimeIndex([dti[0], dti[1], dti[0]], freq=None, name="idx")
result = dti.where(cond, dti[::-1])
tm.assert_index_equal(result, expected)
def test_where_other(self):
# other is ndarray or Index
i = date_range("20130101", periods=3, tz="US/Eastern")
for arr in [np.nan, pd.NaT]:
result = i.where(notna(i), other=arr)
expected = i
tm.assert_index_equal(result, expected)
i2 = i.copy()
i2 = Index([pd.NaT, pd.NaT] + i[2:].tolist())
result = i.where(notna(i2), i2)
tm.assert_index_equal(result, i2)
i2 = i.copy()
i2 = Index([pd.NaT, pd.NaT] + i[2:].tolist())
result = i.where(notna(i2), i2._values)
tm.assert_index_equal(result, i2)
def test_where_invalid_dtypes(self):
dti = date_range("20130101", periods=3, tz="US/Eastern")
tail = dti[2:].tolist()
i2 = Index([pd.NaT, pd.NaT] + tail)
mask = notna(i2)
# passing tz-naive ndarray to tzaware DTI
result = dti.where(mask, i2.values)
expected = Index([pd.NaT.asm8, pd.NaT.asm8] + tail, dtype=object)
tm.assert_index_equal(result, expected)
# passing tz-aware DTI to tznaive DTI
naive = dti.tz_localize(None)
result = naive.where(mask, i2)
expected = Index([i2[0], i2[1]] + naive[2:].tolist(), dtype=object)
tm.assert_index_equal(result, expected)
pi = i2.tz_localize(None).to_period("D")
result = dti.where(mask, pi)
expected = Index([pi[0], pi[1]] + tail, dtype=object)
tm.assert_index_equal(result, expected)
tda = i2.asi8.view("timedelta64[ns]")
result = dti.where(mask, tda)
expected = Index([tda[0], tda[1]] + tail, dtype=object)
assert isinstance(expected[0], np.timedelta64)
tm.assert_index_equal(result, expected)
result = dti.where(mask, i2.asi8)
expected = Index([pd.NaT._value, pd.NaT._value] + tail, dtype=object)
assert isinstance(expected[0], int)
tm.assert_index_equal(result, expected)
# non-matching scalar
td = pd.Timedelta(days=4)
result = dti.where(mask, td)
expected = Index([td, td] + tail, dtype=object)
assert expected[0] is td
tm.assert_index_equal(result, expected)
def test_where_mismatched_nat(self, tz_aware_fixture):
tz = tz_aware_fixture
dti = date_range("2013-01-01", periods=3, tz=tz)
cond = np.array([True, False, True])
tdnat = np.timedelta64("NaT", "ns")
expected = Index([dti[0], tdnat, dti[2]], dtype=object)
assert expected[1] is tdnat
result = dti.where(cond, tdnat)
tm.assert_index_equal(result, expected)
def test_where_tz(self):
i = date_range("20130101", periods=3, tz="US/Eastern")
result = i.where(notna(i))
expected = i
tm.assert_index_equal(result, expected)
i2 = i.copy()
i2 = Index([pd.NaT, pd.NaT] + i[2:].tolist())
result = i.where(notna(i2))
expected = i2
tm.assert_index_equal(result, expected)
class TestTake:
@pytest.mark.parametrize("tzstr", ["US/Eastern", "dateutil/US/Eastern"])
def test_dti_take_dont_lose_meta(self, tzstr):
rng = date_range("1/1/2000", periods=20, tz=tzstr)
result = rng.take(range(5))
assert result.tz == rng.tz
assert result.freq == rng.freq
def test_take_nan_first_datetime(self):
index = DatetimeIndex([pd.NaT, Timestamp("20130101"), Timestamp("20130102")])
result = index.take([-1, 0, 1])
expected = DatetimeIndex([index[-1], index[0], index[1]])
tm.assert_index_equal(result, expected)
@pytest.mark.parametrize("tz", [None, "Asia/Tokyo"])
def test_take(self, tz):
# GH#10295
idx = date_range("2011-01-01", "2011-01-31", freq="D", name="idx", tz=tz)
result = idx.take([0])
assert result == Timestamp("2011-01-01", tz=idx.tz)
result = idx.take([0, 1, 2])
expected = date_range(
"2011-01-01", "2011-01-03", freq="D", tz=idx.tz, name="idx"
)
tm.assert_index_equal(result, expected)
assert result.freq == expected.freq
result = idx.take([0, 2, 4])
expected = date_range(
"2011-01-01", "2011-01-05", freq="2D", tz=idx.tz, name="idx"
)
tm.assert_index_equal(result, expected)
assert result.freq == expected.freq
result = idx.take([7, 4, 1])
expected = date_range(
"2011-01-08", "2011-01-02", freq="-3D", tz=idx.tz, name="idx"
)
tm.assert_index_equal(result, expected)
assert result.freq == expected.freq
result = idx.take([3, 2, 5])
expected = DatetimeIndex(
["2011-01-04", "2011-01-03", "2011-01-06"],
dtype=idx.dtype,
freq=None,
name="idx",
)
tm.assert_index_equal(result, expected)
assert result.freq is None
result = idx.take([-3, 2, 5])
expected = DatetimeIndex(
["2011-01-29", "2011-01-03", "2011-01-06"],
dtype=idx.dtype,
freq=None,
name="idx",
)
tm.assert_index_equal(result, expected)
assert result.freq is None
def test_take_invalid_kwargs(self):
idx = date_range("2011-01-01", "2011-01-31", freq="D", name="idx")
indices = [1, 6, 5, 9, 10, 13, 15, 3]
msg = r"take\(\) got an unexpected keyword argument 'foo'"
with pytest.raises(TypeError, match=msg):
idx.take(indices, foo=2)
msg = "the 'out' parameter is not supported"
with pytest.raises(ValueError, match=msg):
idx.take(indices, out=indices)
msg = "the 'mode' parameter is not supported"
with pytest.raises(ValueError, match=msg):
idx.take(indices, mode="clip")
# TODO: This method came from test_datetime; de-dup with version above
@pytest.mark.parametrize("tz", [None, "US/Eastern", "Asia/Tokyo"])
def test_take2(self, tz):
dates = [
datetime(2010, 1, 1, 14),
datetime(2010, 1, 1, 15),
datetime(2010, 1, 1, 17),
datetime(2010, 1, 1, 21),
]
idx = date_range(
start="2010-01-01 09:00",
end="2010-02-01 09:00",
freq="h",
tz=tz,
name="idx",
)
expected = DatetimeIndex(dates, freq=None, name="idx", dtype=idx.dtype)
taken1 = idx.take([5, 6, 8, 12])
taken2 = idx[[5, 6, 8, 12]]
for taken in [taken1, taken2]:
tm.assert_index_equal(taken, expected)
assert isinstance(taken, DatetimeIndex)
assert taken.freq is None
assert taken.tz == expected.tz
assert taken.name == expected.name
def test_take_fill_value(self):
# GH#12631
idx = DatetimeIndex(["2011-01-01", "2011-02-01", "2011-03-01"], name="xxx")
result = idx.take(np.array([1, 0, -1]))
expected = DatetimeIndex(["2011-02-01", "2011-01-01", "2011-03-01"], name="xxx")
tm.assert_index_equal(result, expected)
# fill_value
result = idx.take(np.array([1, 0, -1]), fill_value=True)
expected = DatetimeIndex(["2011-02-01", "2011-01-01", "NaT"], name="xxx")
tm.assert_index_equal(result, expected)
# allow_fill=False
result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
expected = DatetimeIndex(["2011-02-01", "2011-01-01", "2011-03-01"], name="xxx")
tm.assert_index_equal(result, expected)
msg = (
"When allow_fill=True and fill_value is not None, "
"all indices must be >= -1"
)
with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -2]), fill_value=True)
with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -5]), fill_value=True)
msg = "out of bounds"
with pytest.raises(IndexError, match=msg):
idx.take(np.array([1, -5]))
def test_take_fill_value_with_timezone(self):
idx = DatetimeIndex(
["2011-01-01", "2011-02-01", "2011-03-01"], name="xxx", tz="US/Eastern"
)
result = idx.take(np.array([1, 0, -1]))
expected = DatetimeIndex(
["2011-02-01", "2011-01-01", "2011-03-01"], name="xxx", tz="US/Eastern"
)
tm.assert_index_equal(result, expected)
# fill_value
result = idx.take(np.array([1, 0, -1]), fill_value=True)
expected = DatetimeIndex(
["2011-02-01", "2011-01-01", "NaT"], name="xxx", tz="US/Eastern"
)
tm.assert_index_equal(result, expected)
# allow_fill=False
result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
expected = DatetimeIndex(
["2011-02-01", "2011-01-01", "2011-03-01"], name="xxx", tz="US/Eastern"
)
tm.assert_index_equal(result, expected)
msg = (
"When allow_fill=True and fill_value is not None, "
"all indices must be >= -1"
)
with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -2]), fill_value=True)
with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -5]), fill_value=True)
msg = "out of bounds"
with pytest.raises(IndexError, match=msg):
idx.take(np.array([1, -5]))
class TestGetLoc:
def test_get_loc_key_unit_mismatch(self):
idx = date_range("2000-01-01", periods=3)
key = idx[1].as_unit("ms")
loc = idx.get_loc(key)
assert loc == 1
assert key in idx
def test_get_loc_key_unit_mismatch_not_castable(self):
dta = date_range("2000-01-01", periods=3)._data.astype("M8[s]")
dti = DatetimeIndex(dta)
key = dta[0].as_unit("ns") + pd.Timedelta(1)
with pytest.raises(
KeyError, match=r"Timestamp\('2000-01-01 00:00:00.000000001'\)"
):
dti.get_loc(key)
assert key not in dti
def test_get_loc_time_obj(self):
# time indexing
idx = date_range("2000-01-01", periods=24, freq="h")
result = idx.get_loc(time(12))
expected = np.array([12])
tm.assert_numpy_array_equal(result, expected, check_dtype=False)
result = idx.get_loc(time(12, 30))
expected = np.array([])
tm.assert_numpy_array_equal(result, expected, check_dtype=False)
@pytest.mark.parametrize("offset", [-10, 10])
def test_get_loc_time_obj2(self, monkeypatch, offset):
# GH#8667
size_cutoff = 50
n = size_cutoff + offset
key = time(15, 11, 30)
start = key.hour * 3600 + key.minute * 60 + key.second
step = 24 * 3600
with monkeypatch.context():
monkeypatch.setattr(libindex, "_SIZE_CUTOFF", size_cutoff)
idx = date_range("2014-11-26", periods=n, freq="s")
ts = pd.Series(np.random.default_rng(2).standard_normal(n), index=idx)
locs = np.arange(start, n, step, dtype=np.intp)
result = ts.index.get_loc(key)
tm.assert_numpy_array_equal(result, locs)
tm.assert_series_equal(ts[key], ts.iloc[locs])
left, right = ts.copy(), ts.copy()
left[key] *= -10
right.iloc[locs] *= -10
tm.assert_series_equal(left, right)
def test_get_loc_time_nat(self):
# GH#35114
# Case where key's total microseconds happens to match iNaT % 1e6 // 1000
tic = time(minute=12, second=43, microsecond=145224)
dti = DatetimeIndex([pd.NaT])
loc = dti.get_loc(tic)
expected = np.array([], dtype=np.intp)
tm.assert_numpy_array_equal(loc, expected)
def test_get_loc_nat(self):
# GH#20464
index = DatetimeIndex(["1/3/2000", "NaT"])
assert index.get_loc(pd.NaT) == 1
assert index.get_loc(None) == 1
assert index.get_loc(np.nan) == 1
assert index.get_loc(pd.NA) == 1
assert index.get_loc(np.datetime64("NaT")) == 1
with pytest.raises(KeyError, match="NaT"):
index.get_loc(np.timedelta64("NaT"))
@pytest.mark.parametrize("key", [pd.Timedelta(0), pd.Timedelta(1), timedelta(0)])
def test_get_loc_timedelta_invalid_key(self, key):
# GH#20464
dti = date_range("1970-01-01", periods=10)
msg = "Cannot index DatetimeIndex with [Tt]imedelta"
with pytest.raises(TypeError, match=msg):
dti.get_loc(key)
def test_get_loc_reasonable_key_error(self):
# GH#1062
index = DatetimeIndex(["1/3/2000"])
with pytest.raises(KeyError, match="2000"):
index.get_loc("1/1/2000")
def test_get_loc_year_str(self):
rng = date_range("1/1/2000", "1/1/2010")
result = rng.get_loc("2009")
expected = slice(3288, 3653)
assert result == expected
class TestContains:
def test_dti_contains_with_duplicates(self):
d = datetime(2011, 12, 5, 20, 30)
ix = DatetimeIndex([d, d])
assert d in ix
@pytest.mark.parametrize(
"vals",
[
[0, 1, 0],
[0, 0, -1],
[0, -1, -1],
["2015", "2015", "2016"],
["2015", "2015", "2014"],
],
)
def test_contains_nonunique(self, vals):
# GH#9512
idx = DatetimeIndex(vals)
assert idx[0] in idx
class TestGetIndexer:
def test_get_indexer_date_objs(self):
rng = date_range("1/1/2000", periods=20)
result = rng.get_indexer(rng.map(lambda x: x.date()))
expected = rng.get_indexer(rng)
tm.assert_numpy_array_equal(result, expected)
def test_get_indexer(self):
idx = date_range("2000-01-01", periods=3)
exp = np.array([0, 1, 2], dtype=np.intp)
tm.assert_numpy_array_equal(idx.get_indexer(idx), exp)
target = idx[0] + pd.to_timedelta(["-1 hour", "12 hours", "1 day 1 hour"])
tm.assert_numpy_array_equal(
idx.get_indexer(target, "pad"), np.array([-1, 0, 1], dtype=np.intp)
)
tm.assert_numpy_array_equal(
idx.get_indexer(target, "backfill"), np.array([0, 1, 2], dtype=np.intp)
)
tm.assert_numpy_array_equal(
idx.get_indexer(target, "nearest"), np.array([0, 1, 1], dtype=np.intp)
)
tm.assert_numpy_array_equal(
idx.get_indexer(target, "nearest", tolerance=pd.Timedelta("1 hour")),
np.array([0, -1, 1], dtype=np.intp),
)
tol_raw = [
pd.Timedelta("1 hour"),
pd.Timedelta("1 hour"),
pd.Timedelta("1 hour").to_timedelta64(),
]
tm.assert_numpy_array_equal(
idx.get_indexer(
target, "nearest", tolerance=[np.timedelta64(x) for x in tol_raw]
),
np.array([0, -1, 1], dtype=np.intp),
)
tol_bad = [
pd.Timedelta("2 hour").to_timedelta64(),
pd.Timedelta("1 hour").to_timedelta64(),
"foo",
]
msg = "Could not convert 'foo' to NumPy timedelta"
with pytest.raises(ValueError, match=msg):
idx.get_indexer(target, "nearest", tolerance=tol_bad)
with pytest.raises(ValueError, match="abbreviation w/o a number"):
idx.get_indexer(idx[[0]], method="nearest", tolerance="foo")
@pytest.mark.parametrize(
"target",
[
[date(2020, 1, 1), Timestamp("2020-01-02")],
[Timestamp("2020-01-01"), date(2020, 1, 2)],
],
)
def test_get_indexer_mixed_dtypes(self, target):
# https://github.com/pandas-dev/pandas/issues/33741
values = DatetimeIndex([Timestamp("2020-01-01"), Timestamp("2020-01-02")])
result = values.get_indexer(target)
expected = np.array([0, 1], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
@pytest.mark.parametrize(
"target, positions",
[
([date(9999, 1, 1), Timestamp("2020-01-01")], [-1, 0]),
([Timestamp("2020-01-01"), date(9999, 1, 1)], [0, -1]),
([date(9999, 1, 1), date(9999, 1, 1)], [-1, -1]),
],
)
def test_get_indexer_out_of_bounds_date(self, target, positions):
values = DatetimeIndex([Timestamp("2020-01-01"), Timestamp("2020-01-02")])
result = values.get_indexer(target)
expected = np.array(positions, dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
def test_get_indexer_pad_requires_monotonicity(self):
rng = date_range("1/1/2000", "3/1/2000", freq="B")
# neither monotonic increasing or decreasing
rng2 = rng[[1, 0, 2]]
msg = "index must be monotonic increasing or decreasing"
with pytest.raises(ValueError, match=msg):
rng2.get_indexer(rng, method="pad")
class TestMaybeCastSliceBound:
def test_maybe_cast_slice_bounds_empty(self):
# GH#14354
empty_idx = date_range(freq="1h", periods=0, end="2015")
right = empty_idx._maybe_cast_slice_bound("2015-01-02", "right")
exp = Timestamp("2015-01-02 23:59:59.999999999")
assert right == exp
left = empty_idx._maybe_cast_slice_bound("2015-01-02", "left")
exp = Timestamp("2015-01-02 00:00:00")
assert left == exp
def test_maybe_cast_slice_duplicate_monotonic(self):
# https://github.com/pandas-dev/pandas/issues/16515
idx = DatetimeIndex(["2017", "2017"])
result = idx._maybe_cast_slice_bound("2017-01-01", "left")
expected = Timestamp("2017-01-01")
assert result == expected
class TestGetSliceBounds:
@pytest.mark.parametrize("box", [date, datetime, Timestamp])
@pytest.mark.parametrize("side, expected", [("left", 4), ("right", 5)])
def test_get_slice_bounds_datetime_within(
self, box, side, expected, tz_aware_fixture
):
# GH 35690
tz = tz_aware_fixture
index = bdate_range("2000-01-03", "2000-02-11").tz_localize(tz)
key = box(year=2000, month=1, day=7)
if tz is not None:
with pytest.raises(TypeError, match="Cannot compare tz-naive"):
# GH#36148 we require tzawareness-compat as of 2.0
index.get_slice_bound(key, side=side)
else:
result = index.get_slice_bound(key, side=side)
assert result == expected
@pytest.mark.parametrize("box", [datetime, Timestamp])
@pytest.mark.parametrize("side", ["left", "right"])
@pytest.mark.parametrize("year, expected", [(1999, 0), (2020, 30)])
def test_get_slice_bounds_datetime_outside(
self, box, side, year, expected, tz_aware_fixture
):
# GH 35690
tz = tz_aware_fixture
index = bdate_range("2000-01-03", "2000-02-11").tz_localize(tz)
key = box(year=year, month=1, day=7)
if tz is not None:
with pytest.raises(TypeError, match="Cannot compare tz-naive"):
# GH#36148 we require tzawareness-compat as of 2.0
index.get_slice_bound(key, side=side)
else:
result = index.get_slice_bound(key, side=side)
assert result == expected
@pytest.mark.parametrize("box", [datetime, Timestamp])
def test_slice_datetime_locs(self, box, tz_aware_fixture):
# GH 34077
tz = tz_aware_fixture
index = DatetimeIndex(["2010-01-01", "2010-01-03"]).tz_localize(tz)
key = box(2010, 1, 1)
if tz is not None:
with pytest.raises(TypeError, match="Cannot compare tz-naive"):
# GH#36148 we require tzawareness-compat as of 2.0
index.slice_locs(key, box(2010, 1, 2))
else:
result = index.slice_locs(key, box(2010, 1, 2))
expected = (0, 1)
assert result == expected
class TestIndexerBetweenTime:
def test_indexer_between_time(self):
# GH#11818
rng = date_range("1/1/2000", "1/5/2000", freq="5min")
msg = r"Cannot convert arg \[datetime\.datetime\(2010, 1, 2, 1, 0\)\] to a time"
with pytest.raises(ValueError, match=msg):
rng.indexer_between_time(datetime(2010, 1, 2, 1), datetime(2010, 1, 2, 5))
@pytest.mark.parametrize("unit", ["us", "ms", "s"])
def test_indexer_between_time_non_nano(self, unit):
# For simple cases like this, the non-nano indexer_between_time
# should match the nano result
rng = date_range("1/1/2000", "1/5/2000", freq="5min")
arr_nano = rng._data._ndarray
arr = arr_nano.astype(f"M8[{unit}]")
dta = type(rng._data)._simple_new(arr, dtype=arr.dtype)
dti = DatetimeIndex(dta)
assert dti.dtype == arr.dtype
tic = time(1, 25)
toc = time(2, 29)
result = dti.indexer_between_time(tic, toc)
expected = rng.indexer_between_time(tic, toc)
tm.assert_numpy_array_equal(result, expected)
# case with non-zero micros in arguments
tic = time(1, 25, 0, 45678)
toc = time(2, 29, 0, 1234)
result = dti.indexer_between_time(tic, toc)
expected = rng.indexer_between_time(tic, toc)
tm.assert_numpy_array_equal(result, expected)