def test_ns_index(self):
nsamples = 400
ns = int(1e9 / 24414)
dtstart = np.datetime64("2012-09-20T00:00:00")
dt = dtstart + np.arange(nsamples) * np.timedelta64(ns, "ns")
freq = ns * offsets.Nano()
index = DatetimeIndex(dt, freq=freq, name="time")
self.assert_index_parameters(index)
new_index = date_range(start=index[0], end=index[-1], freq=index.freq)
self.assert_index_parameters(new_index)
import numpy as np
import pytest
from pandas import Timedelta, offsets
from pandas._libs.tslibs.timedeltas import delta_to_nanoseconds
@pytest.mark.parametrize(
"obj,expected",
[
(np.timedelta64(14, "D"), 14 * 24 * 3600 * 1e9),
(Timedelta(minutes=-7), -7 * 60 * 1e9),
(Timedelta(minutes=-7).to_pytimedelta(), -7 * 60 * 1e9),
(offsets.Nano(125), 125),
(1, 1),
(np.int64(2), 2),
(np.int32(3), 3),
],
)
def test_delta_to_nanoseconds(obj, expected):
result = delta_to_nanoseconds(obj)
assert result == expected
def test_delta_to_nanoseconds_error():
obj = np.array([123456789], dtype="m8[ns]")
with pytest.raises(TypeError, match="<class 'numpy.ndarray'>"):
delta_to_nanoseconds(obj)
