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.
99 lines
2.6 KiB
99 lines
2.6 KiB
6 months ago
|
"""
|
||
|
|
This file contains a minimal set of tests for compliance with the extension
|
||
|
|
array interface test suite, and should contain no other tests.
|
||
|
|
The test suite for the full functionality of the array is located in
|
||
|
|
`pandas/tests/arrays/`.
|
||
|
|
|
||
|
|
The tests in this file are inherited from the BaseExtensionTests, and only
|
||
|
|
minimal tweaks should be applied to get the tests passing (by overwriting a
|
||
|
|
parent method).
|
||
|
|
|
||
|
|
Additional tests should either be added to one of the BaseExtensionTests
|
||
|
|
classes (if they are relevant for the extension interface for all dtypes), or
|
||
|
|
be added to the array-specific tests in `pandas/tests/arrays/`.
|
||
|
|
|
||
|
|
"""
|
||
|
|
from __future__ import annotations
|
||
|
|
|
||
|
|
from typing import TYPE_CHECKING
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
import pytest
|
||
|
|
|
||
|
|
from pandas.core.dtypes.dtypes import IntervalDtype
|
||
|
|
|
||
|
|
from pandas import Interval
|
||
|
|
from pandas.core.arrays import IntervalArray
|
||
|
|
from pandas.tests.extension import base
|
||
|
|
|
||
|
|
if TYPE_CHECKING:
|
||
|
|
import pandas as pd
|
||
|
|
|
||
|
|
|
||
|
|
def make_data():
|
||
|
|
N = 100
|
||
|
|
left_array = np.random.default_rng(2).uniform(size=N).cumsum()
|
||
|
|
right_array = left_array + np.random.default_rng(2).uniform(size=N)
|
||
|
|
return [Interval(left, right) for left, right in zip(left_array, right_array)]
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.fixture
|
||
|
|
def dtype():
|
||
|
|
return IntervalDtype()
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.fixture
|
||
|
|
def data():
|
||
|
|
"""Length-100 PeriodArray for semantics test."""
|
||
|
|
return IntervalArray(make_data())
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.fixture
|
||
|
|
def data_missing():
|
||
|
|
"""Length 2 array with [NA, Valid]"""
|
||
|
|
return IntervalArray.from_tuples([None, (0, 1)])
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.fixture
|
||
|
|
def data_for_twos():
|
||
|
|
pytest.skip("Interval is not a numeric dtype")
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.fixture
|
||
|
|
def data_for_sorting():
|
||
|
|
return IntervalArray.from_tuples([(1, 2), (2, 3), (0, 1)])
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.fixture
|
||
|
|
def data_missing_for_sorting():
|
||
|
|
return IntervalArray.from_tuples([(1, 2), None, (0, 1)])
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.fixture
|
||
|
|
def data_for_grouping():
|
||
|
|
a = (0, 1)
|
||
|
|
b = (1, 2)
|
||
|
|
c = (2, 3)
|
||
|
|
return IntervalArray.from_tuples([b, b, None, None, a, a, b, c])
|
||
|
|
|
||
|
|
|
||
|
|
class TestIntervalArray(base.ExtensionTests):
|
||
|
|
divmod_exc = TypeError
|
||
|
|
|
||
|
|
def _supports_reduction(self, ser: pd.Series, op_name: str) -> bool:
|
||
|
|
return op_name in ["min", "max"]
|
||
|
|
|
||
|
|
@pytest.mark.xfail(
|
||
|
|
reason="Raises with incorrect message bc it disallows *all* listlikes "
|
||
|
|
"instead of just wrong-length listlikes"
|
||
|
|
)
|
||
|
|
def test_fillna_length_mismatch(self, data_missing):
|
||
|
|
super().test_fillna_length_mismatch(data_missing)
|
||
|
|
|
||
|
|
|
||
|
|
# TODO: either belongs in tests.arrays.interval or move into base tests.
|
||
|
|
def test_fillna_non_scalar_raises(data_missing):
|
||
|
|
msg = "can only insert Interval objects and NA into an IntervalArray"
|
||
|
|
with pytest.raises(TypeError, match=msg):
|
||
|
|
data_missing.fillna([1, 1])
|