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