Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
106 lines
3.2 KiB
106 lines
3.2 KiB
4 years ago
|
""" generic datetimelike tests """
|
||
|
import numpy as np
|
||
|
import pytest
|
||
|
|
||
|
import pandas as pd
|
||
|
import pandas._testing as tm
|
||
|
|
||
|
from .common import Base
|
||
|
|
||
|
|
||
|
class DatetimeLike(Base):
|
||
|
def test_argmax_axis_invalid(self):
|
||
|
# GH#23081
|
||
|
msg = r"`axis` must be fewer than the number of dimensions \(1\)"
|
||
|
rng = self.create_index()
|
||
|
with pytest.raises(ValueError, match=msg):
|
||
|
rng.argmax(axis=1)
|
||
|
with pytest.raises(ValueError, match=msg):
|
||
|
rng.argmin(axis=2)
|
||
|
with pytest.raises(ValueError, match=msg):
|
||
|
rng.min(axis=-2)
|
||
|
with pytest.raises(ValueError, match=msg):
|
||
|
rng.max(axis=-3)
|
||
|
|
||
|
def test_can_hold_identifiers(self):
|
||
|
idx = self.create_index()
|
||
|
key = idx[0]
|
||
|
assert idx._can_hold_identifiers_and_holds_name(key) is False
|
||
|
|
||
|
def test_shift_identity(self):
|
||
|
|
||
|
idx = self.create_index()
|
||
|
tm.assert_index_equal(idx, idx.shift(0))
|
||
|
|
||
|
def test_str(self):
|
||
|
|
||
|
# test the string repr
|
||
|
idx = self.create_index()
|
||
|
idx.name = "foo"
|
||
|
assert not (f"length={len(idx)}" in str(idx))
|
||
|
assert "'foo'" in str(idx)
|
||
|
assert type(idx).__name__ in str(idx)
|
||
|
|
||
|
if hasattr(idx, "tz"):
|
||
|
if idx.tz is not None:
|
||
|
assert idx.tz in str(idx)
|
||
|
if hasattr(idx, "freq"):
|
||
|
assert f"freq='{idx.freqstr}'" in str(idx)
|
||
|
|
||
|
def test_view(self):
|
||
|
i = self.create_index()
|
||
|
|
||
|
i_view = i.view("i8")
|
||
|
result = self._holder(i)
|
||
|
tm.assert_index_equal(result, i)
|
||
|
|
||
|
i_view = i.view(self._holder)
|
||
|
result = self._holder(i)
|
||
|
tm.assert_index_equal(result, i_view)
|
||
|
|
||
|
def test_map_callable(self):
|
||
|
index = self.create_index()
|
||
|
expected = index + index.freq
|
||
|
result = index.map(lambda x: x + x.freq)
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
# map to NaT
|
||
|
result = index.map(lambda x: pd.NaT if x == index[0] else x)
|
||
|
expected = pd.Index([pd.NaT] + index[1:].tolist())
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
@pytest.mark.parametrize(
|
||
|
"mapper",
|
||
|
[
|
||
|
lambda values, index: {i: e for e, i in zip(values, index)},
|
||
|
lambda values, index: pd.Series(values, index, dtype=object),
|
||
|
],
|
||
|
)
|
||
|
def test_map_dictlike(self, mapper):
|
||
|
index = self.create_index()
|
||
|
expected = index + index.freq
|
||
|
|
||
|
# don't compare the freqs
|
||
|
if isinstance(expected, (pd.DatetimeIndex, pd.TimedeltaIndex)):
|
||
|
expected = expected._with_freq(None)
|
||
|
|
||
|
result = index.map(mapper(expected, index))
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
expected = pd.Index([pd.NaT] + index[1:].tolist())
|
||
|
result = index.map(mapper(expected, index))
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
# empty map; these map to np.nan because we cannot know
|
||
|
# to re-infer things
|
||
|
expected = pd.Index([np.nan] * len(index))
|
||
|
result = index.map(mapper([], []))
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
def test_getitem_preserves_freq(self):
|
||
|
index = self.create_index()
|
||
|
assert index.freq is not None
|
||
|
|
||
|
result = index[:]
|
||
|
assert result.freq == index.freq
|