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_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_get_indexer_overflow(self, dtype, target_value, target_dtype):
left, right = np.array([0, 1], dtype=dtype), np.array([1, 2], dtype=dtype)
tree = IntervalTree(left, right)
result = tree.get_indexer(np.array([target_value], dtype=target_dtype))
expected = np.array([-1], 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)
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_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)
