from __future__ import division from itertools import permutations import numpy as np import pytest from pandas._libs.interval import IntervalTree from pandas import compat import pandas.util.testing as tm def skipif_32bit(param): """ Skip parameters in a parametrize on 32bit systems. Specifically used here to skip leaf_size parameters related to GH 23440. """ marks = pytest.mark.skipif(compat.is_platform_32bit(), reason='GH 23440: int type mismatch on 32bit') return pytest.param(param, marks=marks) @pytest.fixture( scope='class', params=['int32', 'int64', 'float32', 'float64', 'uint64']) def dtype(request): return request.param @pytest.fixture(params=[skipif_32bit(1), skipif_32bit(2), 10]) def leaf_size(request): """ Fixture to specify IntervalTree leaf_size parameter; to be used with the tree fixture. """ return request.param @pytest.fixture(params=[ np.arange(5, dtype='int64'), np.arange(5, dtype='int32'), np.arange(5, dtype='uint64'), np.arange(5, dtype='float64'), np.arange(5, dtype='float32'), np.array([0, 1, 2, 3, 4, np.nan], dtype='float64'), np.array([0, 1, 2, 3, 4, np.nan], dtype='float32')]) def tree(request, leaf_size): left = request.param return IntervalTree(left, left + 2, leaf_size=leaf_size) class TestIntervalTree(object): def test_get_loc(self, tree): result = tree.get_loc(1) expected = np.array([0], dtype='intp') tm.assert_numpy_array_equal(result, expected) result = np.sort(tree.get_loc(2)) expected = np.array([0, 1], dtype='intp') tm.assert_numpy_array_equal(result, expected) with pytest.raises(KeyError): tree.get_loc(-1) def test_get_indexer(self, tree): result = tree.get_indexer(np.array([1.0, 5.5, 6.5])) expected = np.array([0, 4, -1], dtype='intp') tm.assert_numpy_array_equal(result, expected) with pytest.raises(KeyError): tree.get_indexer(np.array([3.0])) def test_get_indexer_non_unique(self, tree): indexer, missing = tree.get_indexer_non_unique( np.array([1.0, 2.0, 6.5])) result = indexer[:1] expected = np.array([0], dtype='intp') tm.assert_numpy_array_equal(result, expected) result = np.sort(indexer[1:3]) expected = np.array([0, 1], dtype='intp') tm.assert_numpy_array_equal(result, expected) result = np.sort(indexer[3:]) expected = np.array([-1], dtype='intp') tm.assert_numpy_array_equal(result, expected) result = missing expected = np.array([2], dtype='intp') tm.assert_numpy_array_equal(result, expected) def test_duplicates(self, dtype): left = np.array([0, 0, 0], dtype=dtype) tree = IntervalTree(left, left + 1) result = np.sort(tree.get_loc(0.5)) expected = np.array([0, 1, 2], dtype='intp') tm.assert_numpy_array_equal(result, expected) with pytest.raises(KeyError): tree.get_indexer(np.array([0.5])) indexer, missing = tree.get_indexer_non_unique(np.array([0.5])) result = np.sort(indexer) expected = np.array([0, 1, 2], dtype='intp') tm.assert_numpy_array_equal(result, expected) result = missing expected = np.array([], dtype='intp') tm.assert_numpy_array_equal(result, expected) def test_get_loc_closed(self, closed): tree = IntervalTree([0], [1], closed=closed) for p, errors in [(0, tree.open_left), (1, tree.open_right)]: if errors: with pytest.raises(KeyError): tree.get_loc(p) else: result = tree.get_loc(p) expected = np.array([0], dtype='intp') tm.assert_numpy_array_equal(result, expected) @pytest.mark.parametrize('leaf_size', [ skipif_32bit(1), skipif_32bit(10), skipif_32bit(100), 10000]) def test_get_indexer_closed(self, closed, leaf_size): x = np.arange(1000, dtype='float64') found = x.astype('intp') not_found = (-1 * np.ones(1000)).astype('intp') tree = IntervalTree(x, x + 0.5, closed=closed, leaf_size=leaf_size) tm.assert_numpy_array_equal(found, tree.get_indexer(x + 0.25)) expected = found if tree.closed_left else not_found tm.assert_numpy_array_equal(expected, tree.get_indexer(x + 0.0)) expected = found if tree.closed_right else not_found tm.assert_numpy_array_equal(expected, tree.get_indexer(x + 0.5)) @pytest.mark.parametrize('left, right, expected', [ (np.array([0, 1, 4]), np.array([2, 3, 5]), True), (np.array([0, 1, 2]), np.array([5, 4, 3]), True), (np.array([0, 1, np.nan]), np.array([5, 4, np.nan]), True), (np.array([0, 2, 4]), np.array([1, 3, 5]), False), (np.array([0, 2, np.nan]), np.array([1, 3, np.nan]), False)]) @pytest.mark.parametrize('order', map(list, permutations(range(3)))) def test_is_overlapping(self, closed, order, left, right, expected): # GH 23309 tree = IntervalTree(left[order], right[order], closed=closed) result = tree.is_overlapping assert result is expected @pytest.mark.parametrize('order', map(list, permutations(range(3)))) def test_is_overlapping_endpoints(self, closed, order): """shared endpoints are marked as overlapping""" # GH 23309 left, right = np.arange(3), np.arange(1, 4) tree = IntervalTree(left[order], right[order], closed=closed) result = tree.is_overlapping expected = closed is 'both' assert result is expected @pytest.mark.parametrize('left, right', [ (np.array([], dtype='int64'), np.array([], dtype='int64')), (np.array([0], dtype='int64'), np.array([1], dtype='int64')), (np.array([np.nan]), np.array([np.nan])), (np.array([np.nan] * 3), np.array([np.nan] * 3))]) def test_is_overlapping_trivial(self, closed, left, right): # GH 23309 tree = IntervalTree(left, right, closed=closed) assert tree.is_overlapping is False @pytest.mark.skipif(compat.is_platform_32bit(), reason='GH 23440') def test_construction_overflow(self): # GH 25485 left, right = np.arange(101), [np.iinfo(np.int64).max] * 101 tree = IntervalTree(left, right) # pivot should be average of left/right medians result = tree.root.pivot expected = (50 + np.iinfo(np.int64).max) / 2 assert result == expected