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) 2006-2019 by
#    Aric Hagberg <hagberg@lanl.gov>
#    Dan Schult <dschult@colgate.edu>
#    Pieter Swart <swart@lanl.gov>
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.

--------
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:
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)
return G

def _relabel_copy(G, mapping):
H = G.__class__()
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:
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):
"""Returns 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.

There is no guarantee that the relabeling of nodes to integers will
give the same two integers for two (even identical graphs).
Use the ordering argument to try to preserve the order.

--------
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