def __setitem__(self, key, values):
if isinstance(values, TriangleSlicer):
if values.array_backend == "sparse":
values = values.set_backend("numpy").values
else:
values = values.values
key = tuple([
slice(item, item + 1) if type(item) is int else item
for item in key
])
if self.obj.array_backend == "sparse":
self.obj.set_backend("numpy", inplace=True)
print(self.obj.values)
self.obj.values.__setitem__(normalize_index(key, self.obj.shape),
values)
self.obj.set_backend("sparse", inplace=True)
else:
self.obj.values.__setitem__(normalize_index(key, self.obj.shape),
values)
def _normalize_index(self, key):
key = normalize_index(key, self.obj.shape)
l = []
for n, i in enumerate(key):
if type(i) is slice:
start = i.start if i.start > 0 else None
stop = i.stop if i.stop > -1 else None
stop = None if stop == self.obj.shape[n] else stop
step = None if start is None and stop is None else i.step
l.append(slice(start, stop, step))
else:
l.append(i)
key = tuple(l)
return key
def format_key(self, key):
key = (key, ) if type(key) is not tuple else key
key_mask = tuple([i if i is Ellipsis else 0 for i in key])
if len(key_mask) < len(self.obj.shape) and Ellipsis not in key_mask:
key_mask = tuple(list(key_mask) + [Ellipsis])
key_mask = list(normalize_index(key_mask, self.obj.shape))
key = [item for item in key if item is not Ellipsis]
for i in range(len(self.obj.shape)):
if key_mask[i] == 0:
key_mask[i] = key[0]
key.pop(0)
key = key_mask
# Support for multi-index
default = slice(None, None, None)
norm = lambda k: type(k) is slice and (k.start == 0 or k == default)
filter_idx = None
if not norm(key[0]) and not type(key[0]) is pd.Series:
idx = self.obj.index.reset_index().set_index(self.obj.key_labels)
sliced = idx.loc[key[0]]
if type(sliced) is pd.Series:
sliced = sliced.to_frame().T
sliced.index.rename(idx.index.name, inplace=True)
sliced = sliced.iloc[:, 0]
key[0] = sliced.to_list()
filter_idx = list(sliced.reset_index().drop("index", 1).columns)
filter_idx = idx.reset_index()[filter_idx]
def normalize(key, idx):
mapper = {1: "columns", 2: "origin", 3: "development"}
out = key[idx]
if not norm(key[idx]) and not isinstance(key, pd.Series):
s = pd.Series(getattr(self.obj,
mapper[idx])).to_frame().reset_index()
out = s.set_index(mapper[idx]).loc[key[idx]].values.flatten()
return out
key = [key[0]
] + [normalize(key, 1),
normalize(key, 2),
normalize(key, 3)]
return key, filter_idx
def __setitem__(self, key, values):
key = normalize_index(key, self.obj.shape)
super().__setitem__(key, values)
def __getitem__(self, key):
return self.get_idx(normalize_index(key, self.obj.shape))