relabel_nodes#

relabel_nodes(G, mapping, copy=True)[source]#

Relabel the nodes of the graph G according to a given mapping.

The original node ordering may not be preserved if copy is False and the mapping includes overlap between old and new labels.

When multiple nodes are mapped to the same target node, attribute handling depends on copy kwarg. For predictable attribute handling when combining nodes, consider using contracted_nodes.

Parameters:
Ggraph

A NetworkX graph

mappingdictionary

A dictionary with the old labels as keys and new labels as values. A partial mapping is allowed. Mapping 2 nodes to a single node is allowed. Any non-node keys in the mapping are ignored.

copybool (optional, default=True)

If True return a copy, or if False relabel the nodes in place.

See also

convert_node_labels_to_integers
contracted_nodes

Notes

Only the nodes specified in the mapping will be relabeled. Any non-node keys in the mapping are ignored.

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.

If a relabel operation on a multigraph would cause two or more edges to have the same source, target and key, the second edge must be assigned a new key to retain all edges. The new key is set to the lowest non-negative integer not already used as a key for edges between these two nodes. Note that this means non-numeric keys may be replaced by numeric keys.

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]

In a multigraph, relabeling two or more nodes to the same new node will retain all edges, but may change the edge keys in the process:

>>> G = nx.MultiGraph()
>>> G.add_edge(0, 1, value="a")  # returns the key for this edge
0
>>> G.add_edge(0, 2, value="b")
0
>>> G.add_edge(0, 3, value="c")
0
>>> mapping = {1: 4, 2: 4, 3: 4}
>>> H = nx.relabel_nodes(G, mapping, copy=True)
>>> print(H[0])
{4: {0: {'value': 'a'}, 1: {'value': 'b'}, 2: {'value': 'c'}}}

This works for in-place relabeling too:

>>> G = nx.relabel_nodes(G, mapping, copy=False)
>>> print(G[0])
{4: {0: {'value': 'a'}, 1: {'value': 'b'}, 2: {'value': 'c'}}}
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Additional backends implement this function

cugraph : GPU-accelerated backend.

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