def test_slice_locs_na_raises(self):
index = Index([np.nan, 1, 2])
with pytest.raises(KeyError, match=""):
index.slice_locs(start=1.5)
with pytest.raises(KeyError, match=""):
index.slice_locs(end=1.5)
def test_slice_locs_na(self):
index = Index([np.nan, 1, 2])
assert index.slice_locs(1) == (1, 3)
assert index.slice_locs(np.nan) == (0, 3)
index = Index([0, np.nan, np.nan, 1, 2])
assert index.slice_locs(np.nan) == (1, 5)
def test_slice_locs_dup(self):
index = Index(["a", "a", "b", "c", "d", "d"])
assert index.slice_locs("a", "d") == (0, 6)
assert index.slice_locs(end="d") == (0, 6)
assert index.slice_locs("a", "c") == (0, 4)
assert index.slice_locs("b", "d") == (2, 6)
index2 = index[::-1]
assert index2.slice_locs("d", "a") == (0, 6)
assert index2.slice_locs(end="a") == (0, 6)
assert index2.slice_locs("d", "b") == (0, 4)
assert index2.slice_locs("c", "a") == (2, 6)
def test_slice_locs(self, dtype):
index = Index(np.array([0, 1, 2, 5, 6, 7, 9, 10], dtype=dtype))
n = len(index)
assert index.slice_locs(start=2) == (2, n)
assert index.slice_locs(start=3) == (3, n)
assert index.slice_locs(3, 8) == (3, 6)
assert index.slice_locs(5, 10) == (3, n)
assert index.slice_locs(end=8) == (0, 6)
assert index.slice_locs(end=9) == (0, 7)
# reversed
index2 = index[::-1]
assert index2.slice_locs(8, 2) == (2, 6)
assert index2.slice_locs(7, 3) == (2, 5)
def _calc_slice_param(cls, input_index_value: IndexValue,
pd_index: pd.Index, inp, index: slice,
axis: int) -> Dict:
param = dict()
if input_index_value.has_value():
start, end = pd_index.slice_locs(index.start,
index.stop,
index.step,
kind='loc')
slc = slice(start, end, index.step)
size = calc_sliced_size(inp.shape[axis], slc)
param['shape'] = size
out_index = pd_index[slc]
param['index_value'] = parse_index(out_index, store_data=axis == 1)
if axis == 1:
param['dtypes'] = inp.dtypes[slc]
else:
assert axis == 0
if index.start is None and index.stop is None:
param['shape'] = calc_sliced_size(inp.shape[axis], index)
else:
param['shape'] = np.nan
param['index_value'] = parse_index(pd_index, inp, index)
return param
def test_slice_locs_negative_step(self, in_slice, expected):
index = Index(list("bcdxy"))
s_start, s_stop = index.slice_locs(in_slice.start, in_slice.stop, in_slice.step)
result = index[s_start : s_stop : in_slice.step]
expected = Index(list(expected))
tm.assert_index_equal(result, expected)
def test_slice_locs_dup_numeric(self, dtype):
index = Index(np.array([10, 12, 12, 14], dtype=dtype))
assert index.slice_locs(12, 12) == (1, 3)
assert index.slice_locs(11, 13) == (1, 3)
index2 = index[::-1]
assert index2.slice_locs(12, 12) == (1, 3)
assert index2.slice_locs(13, 11) == (1, 3)
def test_slice_locs_float_locs(self, dtype):
index = Index(np.array([0, 1, 2, 5, 6, 7, 9, 10], dtype=dtype))
n = len(index)
assert index.slice_locs(5.0, 10.0) == (3, n)
assert index.slice_locs(4.5, 10.5) == (3, 8)
index2 = index[::-1]
assert index2.slice_locs(8.5, 1.5) == (2, 6)
assert index2.slice_locs(10.5, -1) == (0, n)
def _calc_slice_param(
cls,
input_index_value: IndexValue,
pd_index: pd.Index,
inp,
index: slice,
axis: int,
) -> Dict:
param = dict()
if is_full_slice(index):
# full slice on this axis
param["shape"] = inp.shape[axis]
param["index_value"] = input_index_value
if axis == 1:
param["dtypes"] = inp.dtypes
elif input_index_value.has_value():
start, end = pd_index.slice_locs(index.start,
index.stop,
index.step,
kind="loc")
slc = slice(start, end, index.step)
size = calc_sliced_size(inp.shape[axis], slc)
param["shape"] = size
out_index = pd_index[slc]
param["index_value"] = parse_index(out_index, store_data=axis == 1)
if axis == 1:
param["dtypes"] = inp.dtypes[slc]
else:
assert axis == 0
if index.start is None and index.stop is None:
param["shape"] = calc_sliced_size(inp.shape[axis], index)
else:
param["shape"] = np.nan
param["index_value"] = parse_index(pd_index, inp, index)
return param