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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) 2006-2017 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 = 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(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()) # FIXME this is overwritten below when H.graph is updated if G.name: H.name = "(%s)" % G.name 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) 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, dict((v, k) for k, v in mapping.items()), label_attribute) return H