def parse_graph_inputs(*graph):
# TODO: Maybe I could write it a little more elegantly here?
if len(graph) == 0:
graph = None
elif len(graph) == 1:
graph, = graph
if isinstance(graph, BaseGraph):
...
elif sp.isspmatrix(graph):
graph = Graph(graph)
elif isinstance(graph, dict):
return Graph(**graph)
elif is_list_like(graph):
# TODO: multi graph
...
else:
raise ValueError(f"Unrecognized inputs {graph}.")
else:
if sp.isspmatrix(graph[0]):
graph = Graph(*graph)
elif is_list_like(graph[0]):
# TODO: multi graph
...
else:
raise ValueError(f"Unrecognized inputs {graph}.")
return graph
def asintarr(x, dtype: str = None):
"""Convert `x` to interger Numpy array.
Parameters:
----------
x: Tensor, Scipy sparse matrix,
Numpy array-like, etc.
Returns:
----------
Integer Numpy array with dtype or `graphgallery.intx()`
"""
if dtype is None:
dtype = intx()
if is_tensor(x):
if x.dtype != dtype:
kind = backend().kind
if kind == "T":
x = tf.cast(x, dtype=dtype)
else:
x = x.to(getattr(torch, dtype))
return x
if is_interger_scalar(x):
x = np.asarray([x], dtype=dtype)
elif is_list_like(x) or isinstance(x, (np.ndarray, np.matrix)):
x = np.asarray(x, dtype=dtype)
else:
raise ValueError(
f"Invalid input which should be either array-like or integer scalar, but got {type(x)}."
)
return x
def files_exist(files):
if is_list_like(files):
return len(files) != 0 and all([osp.exists(f) for f in files])
else:
return osp.exists(files)
def files_exist(files: Union[List[str], Tuple[str]]):
if is_list_like(files):
return len(files) != 0 and all([osp.exists(f) for f in files])
else:
return osp.exists(files)