def test_get_slice_bound_missing(label, side, kind):
mylist = [2, 4, 6, 8, 10]
index = GenericIndex(mylist)
index_pd = pd.Index(mylist)
assert index.get_slice_bound(label, side,
kind) == index_pd.get_slice_bound(
label, side, kind)
def test_get_slice_bound(testlist, side, kind):
index = GenericIndex(testlist)
index_pd = pd.Index(testlist)
for label in testlist:
assert index.get_slice_bound(label, side,
kind) == index_pd.get_slice_bound(
label, side, kind)
def test_index_comparision():
start, stop = 10, 34
rg = RangeIndex(start, stop)
gi = GenericIndex(np.arange(start, stop))
assert rg.equals(gi)
assert gi.equals(rg)
assert not rg[:-1].equals(gi)
assert rg[:-1].equals(gi[:-1])
def test_get_slice_bound_missing_str(label, side):
# Slicing for monotonic string indices not yet supported
# when missing values are specified (allowed in pandas)
mylist = ["b", "d", "f"]
index = GenericIndex(mylist)
index_pd = pd.Index(mylist)
assert index.get_slice_bound(label, side,
"getitem") == index_pd.get_slice_bound(
label, side, "getitem")
def test_index_rename_preserves_arg():
idx1 = GenericIndex([1, 2, 3], name="orig_name")
# this should be an entirely new object
idx2 = idx1.rename("new_name", inplace=False)
assert idx2.name == "new_name"
assert idx1.name == "orig_name"
# a new object but referencing the same data
idx3 = as_index(idx1, name="last_name")
assert idx3.name == "last_name"
assert idx1.name == "orig_name"
def test_index_rename_inplace():
pds = pd.Index([1, 2, 3], name="asdf")
gds = as_index(pds)
# inplace=False should yield a deep copy
gds_renamed_deep = gds.rename("new_name", inplace=False)
gds._values.data.mem = GenericIndex([2, 3, 4])._values.data.mem
assert (gds_renamed_deep.values == [1, 2, 3]).all()
# inplace=True returns none
gds_to_rename = gds
gds.rename("new_name", inplace=True)
gds._values.data.mem = GenericIndex([3, 4, 5])._values.data.mem
assert (gds_to_rename.values == [3, 4, 5]).all()
def test_index_immutable():
start, stop = 10, 34
rg = RangeIndex(start, stop)
with pytest.raises(TypeError):
rg[1] = 5
gi = GenericIndex(np.arange(start, stop))
with pytest.raises(TypeError):
gi[1] = 5
def test_generic_index(testlist):
index = GenericIndex(testlist)
index_pd = pd.Index(testlist)
assert index.is_unique == index_pd.is_unique
assert index.is_monotonic == index_pd.is_monotonic
assert index.is_monotonic_increasing == index_pd.is_monotonic_increasing
assert index.is_monotonic_decreasing == index_pd.is_monotonic_decreasing
def test_name():
idx = GenericIndex(np.asarray([4, 5, 6, 10]), name="foo")
assert idx.name == "foo"
def test_reductions(func):
x = np.asarray([4, 5, 6, 10])
idx = GenericIndex(np.asarray([4, 5, 6, 10]))
assert func(x) == func(idx)
def test_index_find_label_range():
# Monotonic Index
idx = GenericIndex(np.asarray([4, 5, 6, 10]))
assert idx.find_label_range(4, 6) == (0, 3)
assert idx.find_label_range(5, 10) == (1, 4)
assert idx.find_label_range(0, 6) == (0, 3)
assert idx.find_label_range(4, 11) == (0, 4)
# Non-monotonic Index
idx_nm = GenericIndex(np.asarray([5, 4, 6, 10]))
assert idx_nm.find_label_range(4, 6) == (1, 3)
assert idx_nm.find_label_range(5, 10) == (0, 4)
# Last value not found
with pytest.raises(ValueError) as raises:
idx_nm.find_label_range(0, 6)
raises.match("value not found")
# Last value not found
with pytest.raises(ValueError) as raises:
idx_nm.find_label_range(4, 11)
raises.match("value not found")
