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"""Operations on many graphs.
"""
from itertools import zip_longest
import networkx as nx
__all__ = ["union_all", "compose_all", "disjoint_union_all", "intersection_all"]
def union_all(graphs, rename=(None,)):
"""Returns the union of all graphs.
The graphs must be disjoint, otherwise an exception is raised.
Parameters
----------
graphs : list of graphs
List of NetworkX graphs
rename : bool , default=(None, None)
Node names of G and H can be changed by specifying the tuple
rename=('G-','H-') (for example). Node "u" in G is then renamed
"G-u" and "v" in H is renamed "H-v".
Returns
-------
U : a graph with the same type as the first graph in list
Raises
------
ValueError
If `graphs` is an empty list.
Notes
-----
To force a disjoint union with node relabeling, use
disjoint_union_all(G,H) or convert_node_labels_to integers().
Graph, edge, and node attributes are propagated to the union graph.
If a graph attribute is present in multiple graphs, then the value
from the last graph in the list with that attribute is used.
See Also
--------
union
disjoint_union_all
"""
# collect the graphs in case an iterator was passed
graphs = list(graphs)
if not graphs:
raise ValueError("cannot apply union_all to an empty list")
U = graphs[0]
if any(G.is_multigraph() != U.is_multigraph() for G in graphs):
raise nx.NetworkXError("All graphs must be graphs or multigraphs.")
# rename graph to obtain disjoint node labels
def add_prefix(graph, prefix):
if prefix is None:
return graph
def label(x):
if isinstance(x, str):
name = prefix + x
else:
name = prefix + repr(x)
return name
return nx.relabel_nodes(graph, label)
graphs = [add_prefix(G, name) for G, name in zip_longest(graphs, rename)]
if sum(len(G) for G in graphs) != len(set().union(*graphs)):
raise nx.NetworkXError(
"The node sets of the graphs are not disjoint.",
"Use appropriate rename"
"=(G1prefix,G2prefix,...,GNprefix)"
"or use disjoint_union(G1,G2,...,GN).",
)
# Union is the same type as first graph
R = U.__class__()
# add graph attributes, later attributes take precedent over earlier ones
for G in graphs:
R.graph.update(G.graph)
# add nodes and attributes
for G in graphs:
R.add_nodes_from(G.nodes(data=True))
if U.is_multigraph():
for G in graphs:
R.add_edges_from(G.edges(keys=True, data=True))
else:
for G in graphs:
R.add_edges_from(G.edges(data=True))
return R
def disjoint_union_all(graphs):
"""Returns the disjoint union of all graphs.
This operation forces distinct integer node labels starting with 0
for the first graph in the list and numbering consecutively.
Parameters
----------
graphs : list
List of NetworkX graphs
Returns
-------
U : A graph with the same type as the first graph in list
Raises
------
ValueError
If `graphs` is an empty list.
Notes
-----
It is recommended that the graphs be either all directed or all undirected.
Graph, edge, and node attributes are propagated to the union graph.
If a graph attribute is present in multiple graphs, then the value
from the last graph in the list with that attribute is used.
"""
graphs = list(graphs)
if not graphs:
raise ValueError("cannot apply disjoint_union_all to an empty list")
first_labels = [0]
for G in graphs[:-1]:
first_labels.append(len(G) + first_labels[-1])
relabeled = [
nx.convert_node_labels_to_integers(G, first_label=first_label)
for G, first_label in zip(graphs, first_labels)
]
R = union_all(relabeled)
for G in graphs:
R.graph.update(G.graph)
return R
def compose_all(graphs):
"""Returns the composition of all graphs.
Composition is the simple union of the node sets and edge sets.
The node sets of the supplied graphs need not be disjoint.
Parameters
----------
graphs : list
List of NetworkX graphs
Returns
-------
C : A graph with the same type as the first graph in list
Raises
------
ValueError
If `graphs` is an empty list.
Notes
-----
It is recommended that the supplied graphs be either all directed or all
undirected.
Graph, edge, and node attributes are propagated to the union graph.
If a graph attribute is present in multiple graphs, then the value
from the last graph in the list with that attribute is used.
"""
graphs = list(graphs)
if not graphs:
raise ValueError("cannot apply compose_all to an empty list")
U = graphs[0]
if any(G.is_multigraph() != U.is_multigraph() for G in graphs):
raise nx.NetworkXError("All graphs must be graphs or multigraphs.")
R = U.__class__()
# add graph attributes, H attributes take precedent over G attributes
for G in graphs:
R.graph.update(G.graph)
for G in graphs:
R.add_nodes_from(G.nodes(data=True))
if U.is_multigraph():
for G in graphs:
R.add_edges_from(G.edges(keys=True, data=True))
else:
for G in graphs:
R.add_edges_from(G.edges(data=True))
return R
def intersection_all(graphs):
"""Returns a new graph that contains only the nodes and the edges that exist in
all graphs.
Parameters
----------
graphs : list
List of NetworkX graphs
Returns
-------
R : A new graph with the same type as the first graph in list
Raises
------
ValueError
If `graphs` is an empty list.
Notes
-----
Attributes from the graph, nodes, and edges are not copied to the new
graph.
"""
graphs = list(graphs)
if not graphs:
raise ValueError("cannot apply intersection_all to an empty list")
U = graphs[0]
if any(G.is_multigraph() != U.is_multigraph() for G in graphs):
raise nx.NetworkXError("All graphs must be graphs or multigraphs.")
# create new graph
node_intersection = set.intersection(*[set(G.nodes) for G in graphs])
R = U.__class__()
R.add_nodes_from(node_intersection)
if U.is_multigraph():
edge_sets = [set(G.edges(keys=True)) for G in graphs]
else:
edge_sets = [set(G.edges()) for G in graphs]
edge_intersection = set.intersection(*edge_sets)
R.add_edges_from(edge_intersection)
return R
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