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
isFalse
and the mapping includes overlap between old and new labels.- 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
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'}}}