89 lines
3.2 KiB
Python
89 lines
3.2 KiB
Python
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"""Tests for Interval-Interval operations, such as overlaps, contains, etc."""
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import numpy as np
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import pytest
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from pandas import Interval, IntervalIndex, Timedelta, Timestamp
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import pandas._testing as tm
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from pandas.core.arrays import IntervalArray
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@pytest.fixture(params=[IntervalArray, IntervalIndex])
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def constructor(request):
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"""
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Fixture for testing both interval container classes.
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"""
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return request.param
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@pytest.fixture(
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params=[
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(Timedelta("0 days"), Timedelta("1 day")),
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(Timestamp("2018-01-01"), Timedelta("1 day")),
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(0, 1),
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],
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ids=lambda x: type(x[0]).__name__,
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)
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def start_shift(request):
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"""
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Fixture for generating intervals of different types from a start value
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and a shift value that can be added to start to generate an endpoint.
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"""
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return request.param
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class TestOverlaps:
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def test_overlaps_interval(self, constructor, start_shift, closed, other_closed):
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start, shift = start_shift
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interval = Interval(start, start + 3 * shift, other_closed)
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# intervals: identical, nested, spanning, partial, adjacent, disjoint
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tuples = [
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(start, start + 3 * shift),
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(start + shift, start + 2 * shift),
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(start - shift, start + 4 * shift),
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(start + 2 * shift, start + 4 * shift),
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(start + 3 * shift, start + 4 * shift),
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(start + 4 * shift, start + 5 * shift),
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]
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interval_container = constructor.from_tuples(tuples, closed)
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adjacent = interval.closed_right and interval_container.closed_left
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expected = np.array([True, True, True, True, adjacent, False])
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result = interval_container.overlaps(interval)
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tm.assert_numpy_array_equal(result, expected)
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@pytest.mark.parametrize("other_constructor", [IntervalArray, IntervalIndex])
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def test_overlaps_interval_container(self, constructor, other_constructor):
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# TODO: modify this test when implemented
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interval_container = constructor.from_breaks(range(5))
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other_container = other_constructor.from_breaks(range(5))
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with pytest.raises(NotImplementedError, match="^$"):
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interval_container.overlaps(other_container)
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def test_overlaps_na(self, constructor, start_shift):
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"""NA values are marked as False"""
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start, shift = start_shift
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interval = Interval(start, start + shift)
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tuples = [
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(start, start + shift),
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np.nan,
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(start + 2 * shift, start + 3 * shift),
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]
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interval_container = constructor.from_tuples(tuples)
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expected = np.array([True, False, False])
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result = interval_container.overlaps(interval)
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tm.assert_numpy_array_equal(result, expected)
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@pytest.mark.parametrize(
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"other",
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[10, True, "foo", Timedelta("1 day"), Timestamp("2018-01-01")],
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ids=lambda x: type(x).__name__,
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)
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def test_overlaps_invalid_type(self, constructor, other):
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interval_container = constructor.from_breaks(range(5))
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msg = f"`other` must be Interval-like, got {type(other).__name__}"
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with pytest.raises(TypeError, match=msg):
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interval_container.overlaps(other)
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