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_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_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):
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 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)
