def _parseids(self, ids):
if isinstance(ids, tuple):
raise IndexError('too many dimensions for array')
if (listable(ids) and checkany(ids, isstring)) or isstring(ids):
return self.idsof(ids, safe=False)
if listable(ids) and checkany(ids, lambda v: isinstance(v, bool)):
return np.where(ids)[0]
if ids is None: return slice(None)
return ids
def delete(self,
pos: Indices2D,
axis: Optional[int] = 0,
inline: bool = False) -> StructuredArray:
narr = self if inline else self.copy()
if isstring(pos):
del narr._arrs[pos]
return narr
sids, aids = self._parseids(pos, axis=axis, mapslice=False)
slic = isinstance(sids, slice) and sids == slice(None)
alic = isinstance(aids,
slice) and aids == slice(None) and (missing(axis)
or axis == 0)
if slic and alic:
narr._arrs = OrderedDict()
narr._length = None
elif slic and not alic:
if listable(aids) and len(aids) == 1 and aids[0] < 0:
aids = aids[
0] # fix the issue that currently negative indices are ignored by np.delete
for k, v in narr._arrs.items():
narr._arrs[k] = np.delete(v, aids)
narr._length = len(narr._arrs[l(narr._arrs.keys())[0]])
elif not slic and alic:
if isinstance(sids, slice) or sids.dtype.kind not in ('S', 'U'):
sids = narr.names[sids]
for k in sids:
del narr._arrs[k]
else:
raise IndexError('unable to delete portion of the array')
return narr
def append(self,
value: Union[str, Iterable[str]],
inline: bool = False) -> NamedIndex:
val = self._parsevals(value)
if not listable(val): val = [val]
nid = self if inline else self.copy()
for i, n in enumerate(val):
nid._nidct[n] = nid.size + i
nid._names = np.hstack([nid._names, val])
if len(nid._names) != len(nid._nidct):
raise KeyError('index names not unique')
return nid
def _parseids(self, idx, axis=None, mapslice=True):
if missing(axis):
sids, aids = (idx, slice(None)) if not isinstance(idx, tuple) else \
(idx[0], slice(None)) if len(idx) == 1 else idx
else:
if isinstance(idx, tuple):
raise IndexError('too many dimensions for array')
if axis not in (0, 1): raise IndexError('invalid axis value')
sids, aids = (idx, slice(None)) if axis == 0 else (slice(None),
idx)
def _wrap(ids):
if ids is None: return slice(None)
if isinstance(ids, slice): return ids
if not listable(ids): return [ids]
return ids
sids, aids = smap((sids, aids), _wrap)
if (isinstance(sids, slice) and mapslice) or (
listable(sids) and checkany(sids, lambda x: not isstring(x))):
sids = self.names[sids]
return sids, aids
def _mapids(ids, names):
if isinstance(ids, NamedIndex): ids = np.array(ids)
if not listable(ids): ids = [ids]
if not checkany(ids, isstring): return ids
if missing(names): raise KeyError('table names not set')
return names.idsof(ids, safe = False)
def _wrap(ids):
if ids is None: return slice(None)
if isinstance(ids, slice): return ids
if not listable(ids): return [ids]
return ids