def neighborhood_degree_list(G, nbunch):
"""Return a list of the unique degrees of all neighbors of nodes in
`nbunch`.
Parameters
----------
G : NetworkX graph
An undirected graph.
nbunch :
A single node or iterable container of nodes.
Returns
-------
list
A list of the degrees of all nodes in the neighborhood of the nodes
in `nbunch`.
See Also
--------
closed_neighborhood_degree_list, neighborhood
Examples
--------
>>> import grinpy as gp
>>> G = gp.path_graph(3) # Path on 3 nodes
>>> gp.neighborhood_degree_list(G, 1)
[1, 2]
"""
if isinstance(nodes, collections.abc.Iterable):
return list(set(degree(G, u) for u in set_neighborhood(G, nbunch)))
else:
return list(set(degree(G, u) for u in neighborhood(G, nbunch)))
def is_complete_graph(G):
"""Returns True if *G* is a complete graph, and False otherwise.
Parameters
----------
G : NetworkX graph
An undirected graph.
Returns
-------
boolean
True if G is a complete graph, False otherwise.
"""
V = set(nodes(G))
for v in V:
if not set(neighborhood(G, v)) == V.difference({v}):
return False
return True
def contract_nodes(G, nbunch, new_node=None):
""" Contract the nodes in nbunch.
Contracting a set S of nodes in a graph G first removes the nodes in S from
G then creates a new node *v* with new edges *(v, u)* for all nodes *u* that
are neighbors of a nodes in S.
Parameters
----------
G : NetworkX graph
An undirected graph.
nbunch :
A single node or iterable container of nodes in G.
new_node :
The node to be added. If no node is given, it defaults to the minimum
node in nbunch according to the natural ordering of nodes.
Notes
-----
This method does not return a value. It alters the graph in place.
"""
# check if nbunch is an iterable; if not, convert to a list
try:
_ = (v for v in nbunch)
except:
nbunch = [nbunch]
nbunch = [n for n in nbunch if n in G]
# get all neighbors of nodes in nbunch that are not also in nbunch
N = set().union(*[neighborhood(G, n) for n in nbunch]).difference(nbunch)
# remove the nodes in nbunch from G, then add a new node with approriate edges
G.remove_nodes_from(nbunch)
new_node = new_node or min(nbunch)
G.add_node(new_node)
G.add_edges_from(map(lambda n: (new_node, n), N))
def neighborhood_degree_list(G, nbunch):
# TODO: Add documentation
return [degree(G, u) for u in neighborhood(G, nbunch)]