192 lines
		
	
	
		
			6.9 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			192 lines
		
	
	
		
			6.9 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
from itertools import permutations
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import numpy as np
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import pytest
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from pandas._libs.interval import IntervalTree
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from pandas.compat import IS64
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import pandas._testing as tm
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def skipif_32bit(param):
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    """
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    Skip parameters in a parametrize on 32bit systems. Specifically used
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    here to skip leaf_size parameters related to GH 23440.
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    """
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    marks = pytest.mark.skipif(not IS64, reason="GH 23440: int type mismatch on 32bit")
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    return pytest.param(param, marks=marks)
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@pytest.fixture(scope="class", params=["int64", "float64", "uint64"])
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def dtype(request):
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    return request.param
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@pytest.fixture(params=[skipif_32bit(1), skipif_32bit(2), 10])
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def leaf_size(request):
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    """
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    Fixture to specify IntervalTree leaf_size parameter; to be used with the
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    tree fixture.
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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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        np.arange(5, dtype="int64"),
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        np.arange(5, dtype="uint64"),
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        np.arange(5, dtype="float64"),
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        np.array([0, 1, 2, 3, 4, np.nan], dtype="float64"),
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    ]
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)
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def tree(request, leaf_size):
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    left = request.param
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    return IntervalTree(left, left + 2, leaf_size=leaf_size)
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class TestIntervalTree:
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    def test_get_indexer(self, tree):
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        result = tree.get_indexer(np.array([1.0, 5.5, 6.5]))
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        expected = np.array([0, 4, -1], dtype="intp")
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        tm.assert_numpy_array_equal(result, expected)
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        with pytest.raises(
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            KeyError, match="'indexer does not intersect a unique set of intervals'"
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        ):
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            tree.get_indexer(np.array([3.0]))
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    @pytest.mark.parametrize(
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        "dtype, target_value, target_dtype",
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        [("int64", 2**63 + 1, "uint64"), ("uint64", -1, "int64")],
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    )
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    def test_get_indexer_overflow(self, dtype, target_value, target_dtype):
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        left, right = np.array([0, 1], dtype=dtype), np.array([1, 2], dtype=dtype)
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        tree = IntervalTree(left, right)
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        result = tree.get_indexer(np.array([target_value], dtype=target_dtype))
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        expected = np.array([-1], dtype="intp")
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        tm.assert_numpy_array_equal(result, expected)
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    def test_get_indexer_non_unique(self, tree):
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        indexer, missing = tree.get_indexer_non_unique(np.array([1.0, 2.0, 6.5]))
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        result = indexer[:1]
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        expected = np.array([0], dtype="intp")
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        tm.assert_numpy_array_equal(result, expected)
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        result = np.sort(indexer[1:3])
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        expected = np.array([0, 1], dtype="intp")
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        tm.assert_numpy_array_equal(result, expected)
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        result = np.sort(indexer[3:])
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        expected = np.array([-1], dtype="intp")
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        tm.assert_numpy_array_equal(result, expected)
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        result = missing
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        expected = np.array([2], dtype="intp")
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        tm.assert_numpy_array_equal(result, expected)
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    @pytest.mark.parametrize(
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        "dtype, target_value, target_dtype",
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        [("int64", 2**63 + 1, "uint64"), ("uint64", -1, "int64")],
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    )
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    def test_get_indexer_non_unique_overflow(self, dtype, target_value, target_dtype):
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        left, right = np.array([0, 2], dtype=dtype), np.array([1, 3], dtype=dtype)
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        tree = IntervalTree(left, right)
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        target = np.array([target_value], dtype=target_dtype)
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        result_indexer, result_missing = tree.get_indexer_non_unique(target)
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        expected_indexer = np.array([-1], dtype="intp")
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        tm.assert_numpy_array_equal(result_indexer, expected_indexer)
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        expected_missing = np.array([0], dtype="intp")
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        tm.assert_numpy_array_equal(result_missing, expected_missing)
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    def test_duplicates(self, dtype):
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        left = np.array([0, 0, 0], dtype=dtype)
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        tree = IntervalTree(left, left + 1)
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        with pytest.raises(
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            KeyError, match="'indexer does not intersect a unique set of intervals'"
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        ):
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            tree.get_indexer(np.array([0.5]))
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        indexer, missing = tree.get_indexer_non_unique(np.array([0.5]))
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        result = np.sort(indexer)
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        expected = np.array([0, 1, 2], dtype="intp")
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        tm.assert_numpy_array_equal(result, expected)
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        result = missing
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        expected = np.array([], dtype="intp")
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        tm.assert_numpy_array_equal(result, expected)
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    @pytest.mark.parametrize(
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        "leaf_size", [skipif_32bit(1), skipif_32bit(10), skipif_32bit(100), 10000]
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    )
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    def test_get_indexer_closed(self, closed, leaf_size):
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        x = np.arange(1000, dtype="float64")
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        found = x.astype("intp")
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        not_found = (-1 * np.ones(1000)).astype("intp")
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        tree = IntervalTree(x, x + 0.5, closed=closed, leaf_size=leaf_size)
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        tm.assert_numpy_array_equal(found, tree.get_indexer(x + 0.25))
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        expected = found if tree.closed_left else not_found
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        tm.assert_numpy_array_equal(expected, tree.get_indexer(x + 0.0))
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        expected = found if tree.closed_right else not_found
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        tm.assert_numpy_array_equal(expected, tree.get_indexer(x + 0.5))
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    @pytest.mark.parametrize(
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        "left, right, expected",
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        [
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            (np.array([0, 1, 4], dtype="int64"), np.array([2, 3, 5]), True),
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            (np.array([0, 1, 2], dtype="int64"), np.array([5, 4, 3]), True),
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            (np.array([0, 1, np.nan]), np.array([5, 4, np.nan]), True),
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            (np.array([0, 2, 4], dtype="int64"), np.array([1, 3, 5]), False),
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            (np.array([0, 2, np.nan]), np.array([1, 3, np.nan]), False),
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        ],
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    )
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    @pytest.mark.parametrize("order", (list(x) for x in permutations(range(3))))
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    def test_is_overlapping(self, closed, order, left, right, expected):
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        # GH 23309
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        tree = IntervalTree(left[order], right[order], closed=closed)
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        result = tree.is_overlapping
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        assert result is expected
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    @pytest.mark.parametrize("order", (list(x) for x in permutations(range(3))))
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    def test_is_overlapping_endpoints(self, closed, order):
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        """shared endpoints are marked as overlapping"""
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        # GH 23309
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        left, right = np.arange(3, dtype="int64"), np.arange(1, 4)
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        tree = IntervalTree(left[order], right[order], closed=closed)
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        result = tree.is_overlapping
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        expected = closed == "both"
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        assert result is expected
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    @pytest.mark.parametrize(
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        "left, right",
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        [
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            (np.array([], dtype="int64"), np.array([], dtype="int64")),
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            (np.array([0], dtype="int64"), np.array([1], dtype="int64")),
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            (np.array([np.nan]), np.array([np.nan])),
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            (np.array([np.nan] * 3), np.array([np.nan] * 3)),
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        ],
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    )
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    def test_is_overlapping_trivial(self, closed, left, right):
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        # GH 23309
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        tree = IntervalTree(left, right, closed=closed)
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        assert tree.is_overlapping is False
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    @pytest.mark.skipif(not IS64, reason="GH 23440")
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    def test_construction_overflow(self):
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        # GH 25485
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        left, right = np.arange(101, dtype="int64"), [np.iinfo(np.int64).max] * 101
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        tree = IntervalTree(left, right)
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        # pivot should be average of left/right medians
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        result = tree.root.pivot
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        expected = (50 + np.iinfo(np.int64).max) / 2
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        assert result == expected
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