from __future__ import annotations
import numpy as np
import re
from functools import lru_cache
from .._types import Slices
__all__ = ["str_to_slice", "key_repr", "axis_targeted_slicing"]
def _range_to_list(v: str) -> list[int]:
"""
"1,3,5" -> [1,3,5]
"2,4:6,9" -> [2,4,5,6,9]
"""
if ":" in v:
s, e = v.split(":")
return list(range(int(s), int(e)))
else:
return [int(v)]
def _int_or_none(v: str) -> int | None:
if v:
return int(v)
else:
return None
[docs]def str_to_slice(v: str) -> list[int] | slice | int:
v = re.sub(" ", "", v)
if "," in v:
sl = sum((_range_to_list(v) for v in v.split(",")), [])
elif ":" in v:
sl = slice(*map(_int_or_none, v.split(":")))
else:
sl = int(v)
return sl
[docs]def key_repr(key):
keylist = []
if isinstance(key, tuple):
_keys = key
elif hasattr(key, "__array__"):
_keys = ("array",)
else:
_keys = (key,)
for s in _keys:
if isinstance(s, (slice, list, np.ndarray)):
keylist.append("*")
elif s is None:
keylist.append("new")
elif s is ...:
keylist.append("...")
else:
keylist.append(str(s))
return ",".join(keylist)
[docs]@lru_cache
def axis_targeted_slicing(ndim: int, axes: str, string: str) -> Slices:
"""
Make a conventional slices from an axis-targeted slicing string.
Parameters
----------
ndim : int
Number of dimension of the array which will be sliced.
axes : str
Axes of input ndarray.
string : str
Axis-targeted slicing string. If an axis that does not exist in `axes` is contained,
this function will raise ValueError.
Returns
-------
slices
"""
keylist = re.sub(" ", "", string).split(";")
sl_list = [slice(None)]*ndim
for k in keylist:
if k.count("=") != 1:
raise ValueError(f"Informal axis-targeted slicing: {k}")
axis, sl_str = k.split("=")
i = axes.find(axis)
if i < 0:
raise ValueError(f"Axis '{axis}' does not exist ({axes}).")
try:
sl_list[i] = str_to_slice(sl_str)
except ValueError:
raise ValueError(f"Informal axis-targeted slicing: {string}")
return tuple(sl_list)