Warning

This documents an unmaintained version of NetworkX. Please upgrade to a maintained version and see the current NetworkX documentation.

Source code for networkx.relabel

#    Copyright (C) 2006-2013 by
#    Aric Hagberg <hagberg@lanl.gov>
#    Dan Schult <dschult@colgate.edu>
#    Pieter Swart <swart@lanl.gov>
import networkx as nx
__author__ = """\n""".join(['Aric Hagberg <aric.hagberg@gmail.com>',
'Pieter Swart (swart@lanl.gov)',
'Dan Schult (dschult@colgate.edu)'])
__all__ = ['convert_node_labels_to_integers', 'relabel_nodes']

[docs]def relabel_nodes(G, mapping, copy=True):
"""Relabel the nodes of the graph G.

Parameters
----------
G : graph
A NetworkX graph

mapping : dictionary
A dictionary with the old labels as keys and new labels as values.
A partial mapping is allowed.

copy : bool (optional, default=True)
If True return a copy, or if False relabel the nodes in place.

Examples
--------
>>> G=nx.path_graph(3)  # nodes 0-1-2
>>> mapping={0:'a',1:'b',2:'c'}
>>> H=nx.relabel_nodes(G,mapping)
>>> print(sorted(H.nodes()))
['a', 'b', 'c']

>>> G=nx.path_graph(26) # nodes 0..25
>>> mapping=dict(zip(G.nodes(),"abcdefghijklmnopqrstuvwxyz"))
>>> H=nx.relabel_nodes(G,mapping) # nodes a..z
>>> mapping=dict(zip(G.nodes(),range(1,27)))
>>> G1=nx.relabel_nodes(G,mapping) # nodes 1..26

Partial in-place mapping:

>>> G=nx.path_graph(3)  # nodes 0-1-2
>>> mapping={0:'a',1:'b'} # 0->'a' and 1->'b'
>>> G=nx.relabel_nodes(G,mapping, copy=False)

print(G.nodes())
[2, 'b', 'a']

Mapping as function:

>>> G=nx.path_graph(3)
>>> def mapping(x):
...    return x**2
>>> H=nx.relabel_nodes(G,mapping)
>>> print(H.nodes())
[0, 1, 4]

Notes
-----
Only the nodes specified in the mapping will be relabeled.

The keyword setting copy=False modifies the graph in place.
This is not always possible if the mapping is circular.
In that case use copy=True.

--------
convert_node_labels_to_integers
"""
# you can pass a function f(old_label)->new_label
# but we'll just make a dictionary here regardless
if not hasattr(mapping,"__getitem__"):
m = dict((n, mapping(n)) for n in G)
else:
m = mapping
if copy:
return _relabel_copy(G, m)
else:
return _relabel_inplace(G, m)

def _relabel_inplace(G, mapping):
old_labels = set(mapping.keys())
new_labels = set(mapping.values())
if len(old_labels & new_labels) > 0:
# labels sets overlap
# can we topological sort and still do the relabeling?
D = nx.DiGraph(list(mapping.items()))
D.remove_edges_from(D.selfloop_edges())
try:
nodes = nx.topological_sort(D, reverse=True)
except nx.NetworkXUnfeasible:
raise nx.NetworkXUnfeasible('The node label sets are overlapping '
'and no ordering can resolve the '
'mapping. Use copy=True.')
else:
# non-overlapping label sets
nodes = old_labels

multigraph = G.is_multigraph()
directed = G.is_directed()

for old in nodes:
try:
new = mapping[old]
except KeyError:
continue
try:
except KeyError:
raise KeyError("Node %s is not in the graph"%old)
if multigraph:
new_edges = [(new, old == target and new or target, key, data)
for (_,target,key,data)
in G.edges(old, data=True, keys=True)]
if directed:
new_edges += [(old == source and new or source, new, key, data)
for (source, _, key,data)
in G.in_edges(old, data=True, keys=True)]
else:
new_edges = [(new, old == target and new or target, data)
for (_,target,data) in G.edges(old, data=True)]
if directed:
new_edges += [(old == source and new or source,new,data)
for (source,_,data) in G.in_edges(old, data=True)]
G.remove_node(old)
return G

def _relabel_copy(G, mapping):
H = G.__class__()
H.name = "(%s)" % G.name
if G.is_multigraph():
for (n1,n2,k,d) in G.edges_iter(keys=True, data=True))
else:
for (n1, n2, d) in G.edges_iter(data=True))

H.add_nodes_from(mapping.get(n, n) for n in G)
H.node.update(dict((mapping.get(n, n), d.copy()) for n,d in G.node.items()))
H.graph.update(G.graph.copy())

return H

[docs]def convert_node_labels_to_integers(G, first_label=0, ordering="default",
label_attribute=None):
"""Return a copy of the graph G with the nodes relabeled using
consecutive integers.

Parameters
----------
G : graph
A NetworkX graph

first_label : int, optional (default=0)
An integer specifying the starting offset in numbering nodes.
The new integer labels are numbered first_label, ..., n-1+first_label.

ordering : string
"default" : inherit node ordering from G.nodes()
"sorted"  : inherit node ordering from sorted(G.nodes())
"increasing degree" : nodes are sorted by increasing degree
"decreasing degree" : nodes are sorted by decreasing degree

label_attribute : string, optional (default=None)
Name of node attribute to store old label.  If None no attribute
is created.

Notes
-----
Node and edge attribute data are copied to the new (relabeled) graph.

--------
relabel_nodes
"""
N = G.number_of_nodes()+first_label
if ordering == "default":
mapping = dict(zip(G.nodes(), range(first_label, N)))
elif ordering == "sorted":
nlist = G.nodes()
nlist.sort()
mapping = dict(zip(nlist, range(first_label, N)))
elif ordering == "increasing degree":
dv_pairs = [(d,n) for (n,d) in G.degree_iter()]
dv_pairs.sort() # in-place sort from lowest to highest degree
mapping = dict(zip([n for d,n in dv_pairs], range(first_label, N)))
elif ordering == "decreasing degree":
dv_pairs = [(d,n) for (n,d) in G.degree_iter()]
dv_pairs.sort() # in-place sort from lowest to highest degree
dv_pairs.reverse()
mapping = dict(zip([n for d,n in dv_pairs], range(first_label, N)))
else:
raise nx.NetworkXError('Unknown node ordering: %s'%ordering)
H = relabel_nodes(G, mapping)
H.name = "("+G.name+")_with_int_labels"
# create node attribute with the old label
if label_attribute is not None:
nx.set_node_attributes(H, label_attribute,
dict((v,k) for k,v in mapping.items()))
return H