# Copyright (C) 2006-2018 by
# Aric Hagberg <hagberg@lanl.gov>
# Dan Schult <dschult@colgate.edu>
# Pieter Swart <swart@lanl.gov>
# All rights reserved.
# BSD license.
import networkx as nx
__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
--------
To create a new graph with nodes relabeled according to a given
dictionary:
>>> G = nx.path_graph(3)
>>> sorted(G)
[0, 1, 2]
>>> mapping = {0: 'a', 1: 'b', 2: 'c'}
>>> H = nx.relabel_nodes(G, mapping)
>>> sorted(H)
['a', 'b', 'c']
Nodes can be relabeled with any hashable object, including numbers
and strings:
>>> import string
>>> G = nx.path_graph(26) # nodes are integers 0 through 25
>>> sorted(G)[:3]
[0, 1, 2]
>>> mapping = dict(zip(G, string.ascii_lowercase))
>>> G = nx.relabel_nodes(G, mapping) # nodes are characters a through z
>>> sorted(G)[:3]
['a', 'b', 'c']
>>> mapping = dict(zip(G, range(1, 27)))
>>> G = nx.relabel_nodes(G, mapping) # nodes are integers 1 through 26
>>> sorted(G)[:3]
[1, 2, 3]
To perform a partial in-place relabeling, provide a dictionary
mapping only a subset of the nodes, and set the `copy` keyword
argument to False:
>>> 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)
>>> sorted(G, key=str)
[2, 'a', 'b']
A mapping can also be given as a function:
>>> G = nx.path_graph(3)
>>> H = nx.relabel_nodes(G, lambda x: x ** 2)
>>> list(H)
[0, 1, 4]
Notes
-----
Only the nodes specified in the mapping will be relabeled.
The keyword setting copy=False modifies the graph in place.
Relabel_nodes avoids naming collisions by building a
directed graph from ``mapping`` which specifies the order of
relabelings. Naming collisions, such as a->b, b->c, are ordered
such that "b" gets renamed to "c" before "a" gets renamed "b".
In cases of circular mappings (e.g. a->b, b->a), modifying the
graph is not possible in-place and an exception is raised.
In that case, use copy=True.
See Also
--------
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 = {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(nx.selfloop_edges(D))
try:
nodes = reversed(list(nx.topological_sort(D)))
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
if new == old:
continue
try:
G.add_node(new, **G.nodes[old])
except KeyError:
raise KeyError("Node %s is not in the graph" % old)
if multigraph:
new_edges = [(new, new if old == target else target, key, data)
for (_, target, key, data)
in G.edges(old, data=True, keys=True)]
if directed:
new_edges += [(new if old == source else source, new, key, data)
for (source, _, key, data)
in G.in_edges(old, data=True, keys=True)]
else:
new_edges = [(new, new if old == target else target, data)
for (_, target, data) in G.edges(old, data=True)]
if directed:
new_edges += [(new if old == source else source, new, data)
for (source, _, data) in G.in_edges(old, data=True)]
G.remove_node(old)
G.add_edges_from(new_edges)
return G
def _relabel_copy(G, mapping):
H = G.fresh_copy()
H.add_nodes_from(mapping.get(n, n) for n in G)
H._node.update((mapping.get(n, n), d.copy()) for n, d in G.nodes.items())
if G.is_multigraph():
H.add_edges_from((mapping.get(n1, n1), mapping.get(n2, n2), k, d.copy())
for (n1, n2, k, d) in G.edges(keys=True, data=True))
else:
H.add_edges_from((mapping.get(n1, n1), mapping.get(n2, n2), d.copy())
for (n1, n2, d) in G.edges(data=True))
H.graph.update(G.graph)
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.
See Also
--------
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 = sorted(G.nodes())
mapping = dict(zip(nlist, range(first_label, N)))
elif ordering == "increasing degree":
dv_pairs = [(d, n) for (n, d) in G.degree()]
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()]
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)
# create node attribute with the old label
if label_attribute is not None:
nx.set_node_attributes(H, {v: k for k, v in mapping.items()},
label_attribute)
return H