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:
tm.assert_numpy_array_equal(tree.get_loc(p),
np.array([0], dtype='int64'))
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, match=str(p)):
tree.get_loc(p)
else:
result = tree.get_loc(p)
expected = np.array([0], 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:
tm.assert_numpy_array_equal(tree.get_loc(p),
np.array([0], dtype='int64'))
def test_get_loc_closed(self):
for closed in ['left', 'right', 'both', 'neither']:
tree = IntervalTree([0], [1], closed=closed)
for p, errors in [(0, tree.open_left), (1, tree.open_right)]:
if errors:
with self.assertRaises(KeyError):
tree.get_loc(p)
else:
self.assert_numpy_array_equal(tree.get_loc(p),
np.array([0], dtype='int64'))
def test_get_indexer_non_unique_overflow(self, dtype, target_value, target_dtype):
left, right = np.array([0, 2], dtype=dtype), np.array([1, 3], dtype=dtype)
tree = IntervalTree(left, right)
target = np.array([target_value], dtype=target_dtype)
result_indexer, result_missing = tree.get_indexer_non_unique(target)
expected_indexer = np.array([-1], dtype="intp")
tm.assert_numpy_array_equal(result_indexer, expected_indexer)
expected_missing = np.array([0], dtype="intp")
tm.assert_numpy_array_equal(result_missing, expected_missing)
def test_duplicates(self):
tree = IntervalTree([0, 0, 0], [1, 1, 1])
tm.assert_numpy_array_equal(np.sort(tree.get_loc(0.5)),
np.array([0, 1, 2], dtype='int64'))
with pytest.raises(KeyError):
tree.get_indexer(np.array([0.5]))
indexer, missing = tree.get_indexer_non_unique(np.array([0.5]))
tm.assert_numpy_array_equal(np.sort(indexer),
np.array([0, 1, 2], dtype='int64'))
tm.assert_numpy_array_equal(missing, np.array([], dtype='int64'))
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))
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))
def test_inf_bound_infinite_recursion(self, left, right, expected):
# GH 46658
tree = IntervalTree(left * 101, right * 101)
result = tree.root.pivot
assert result == expected
def test_is_overlapping_endpoints(self, closed, order):
"""shared endpoints are marked as overlapping"""
# GH 23309
left, right = np.arange(3, dtype="int64"), np.arange(1, 4)
tree = IntervalTree(left[order], right[order], closed=closed)
result = tree.is_overlapping
expected = closed == "both"
assert result is expected
def setUp(self):
gentree = lambda dtype: IntervalTree(np.arange(5, dtype=dtype),
np.arange(5, dtype=dtype) + 2)
self.tree = gentree('int64')
self.trees = {
dtype: gentree(dtype)
for dtype in ['int32', 'int64', 'float32', 'float64']
}
def test_interval_tree_error_and_warning(self):
# GH 40245
msg = (
"Deprecated argument `closed` cannot "
"be passed if argument `inclusive` is not None"
)
with pytest.raises(ValueError, match=msg):
left, right = np.arange(10), [np.iinfo(np.int64).max] * 10
IntervalTree(left, right, closed="both", inclusive="both")
msg = "Argument `closed` is deprecated in favor of `inclusive`"
with tm.assert_produces_warning(
FutureWarning, match=msg, check_stacklevel=False
):
left, right = np.arange(10), [np.iinfo(np.int64).max] * 10
IntervalTree(left, right, closed="both")
def test_duplicates(self, dtype):
left = np.array([0, 0, 0], dtype=dtype)
tree = IntervalTree(left, left + 1)
with pytest.raises(
KeyError, match="'indexer does not intersect a unique set of intervals'"
):
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_indexer_closed(self):
x = np.arange(1000, dtype='intp')
found = x
not_found = (-1 * np.ones(1000)).astype('intp')
for leaf_size in [1, 10, 100, 10000]:
for closed in ['left', 'right', 'both', 'neither']:
tree = IntervalTree(x, x + 0.5, closed=closed,
leaf_size=leaf_size)
self.assert_numpy_array_equal(found,
tree.get_indexer(x + 0.25))
expected = found if tree.closed_left else not_found
self.assert_numpy_array_equal(expected,
tree.get_indexer(x + 0.0))
expected = found if tree.closed_right else not_found
self.assert_numpy_array_equal(expected,
tree.get_indexer(x + 0.5))
def test_construction_overflow(self):
# GH 25485
left, right = np.arange(101, dtype="int64"), [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
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_duplicates(self):
tree = IntervalTree([0, 0, 0], [1, 1, 1])
tm.assert_numpy_array_equal(np.sort(tree.get_loc(0.5)),
np.array([0, 1, 2], dtype='int64'))
with pytest.raises(KeyError):
tree.get_indexer(np.array([0.5]))
indexer, missing = tree.get_indexer_non_unique(np.array([0.5]))
tm.assert_numpy_array_equal(np.sort(indexer),
np.array([0, 1, 2], dtype='int64'))
tm.assert_numpy_array_equal(missing, np.array([], dtype='int64'))
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 _engine(self):
left = self._maybe_convert_i8(self.left)
right = self._maybe_convert_i8(self.right)
return IntervalTree(left, right, closed=self.closed)
def _engine(self):
return IntervalTree(self.left, self.right, closed=self.closed)
def gentree(dtype):
left = np.arange(5, dtype=dtype)
right = left + 2
return IntervalTree(left, right)
def tree(request, leaf_size):
left = request.param
return IntervalTree(left, left + 2, leaf_size=leaf_size)
def tree(dtype):
left = np.arange(5, dtype=dtype)
return IntervalTree(left, left + 2)
def tree(request, leaf_size):
left = request.param
return IntervalTree(left, left + 2, leaf_size=leaf_size, inclusive="right")
def _engine(self) -> IntervalTree: # type: ignore[override]
left = self._maybe_convert_i8(self.left)
right = self._maybe_convert_i8(self.right)
return IntervalTree(left, right, closed=self.closed)
def test_is_overlapping_trivial(self, closed, left, right):
# GH 23309
tree = IntervalTree(left, right, closed=closed)
assert tree.is_overlapping is False
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
