# Source code for networkx.algorithms.operators.all

```
"""Operations on many graphs.
"""
from itertools import chain, repeat
import networkx as nx
__all__ = ["union_all", "compose_all", "disjoint_union_all", "intersection_all"]
[docs]def union_all(graphs, rename=()):
"""Returns the union of all graphs.
The graphs must be disjoint, otherwise an exception is raised.
Parameters
----------
graphs : iterable
Iterable of NetworkX graphs
rename : iterable , optional
Node names of graphs 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". Infinite generators (like itertools.count)
are also supported.
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
"""
R = None
seen_nodes = set()
# rename graph to obtain disjoint node labels
def add_prefix(graph, prefix):
if prefix is None:
return graph
def label(x):
return f"{prefix}{x}"
return nx.relabel_nodes(graph, label)
rename = chain(rename, repeat(None))
graphs = (add_prefix(G, name) for G, name in zip(graphs, rename))
for i, G in enumerate(graphs):
G_nodes_set = set(G.nodes)
if i == 0:
# Union is the same type as first graph
R = G.__class__()
elif G.is_multigraph() != R.is_multigraph():
raise nx.NetworkXError("All graphs must be graphs or multigraphs.")
elif not seen_nodes.isdisjoint(G_nodes_set):
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).",
)
seen_nodes |= G_nodes_set
R.graph.update(G.graph)
R.add_nodes_from(G.nodes(data=True))
R.add_edges_from(
G.edges(keys=True, data=True) if G.is_multigraph() else G.edges(data=True)
)
if R is None:
raise ValueError("cannot apply union_all to an empty list")
return R
[docs]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 : iterable
Iterable 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.
"""
def yield_relabeled(graphs):
first_label = 0
for G in graphs:
yield nx.convert_node_labels_to_integers(G, first_label=first_label)
first_label += len(G)
R = union_all(yield_relabeled(graphs))
return R
[docs]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 : iterable
Iterable 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.
"""
R = None
# add graph attributes, H attributes take precedent over G attributes
for i, G in enumerate(graphs):
if i == 0:
# create new graph
R = G.__class__()
elif G.is_multigraph() != R.is_multigraph():
raise nx.NetworkXError("All graphs must be graphs or multigraphs.")
R.graph.update(G.graph)
R.add_nodes_from(G.nodes(data=True))
R.add_edges_from(
G.edges(keys=True, data=True) if G.is_multigraph() else G.edges(data=True)
)
if R is None:
raise ValueError("cannot apply compose_all to an empty list")
return R
[docs]def intersection_all(graphs):
"""Returns a new graph that contains only the nodes and the edges that exist in
all graphs.
Parameters
----------
graphs : iterable
Iterable 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.
"""
R = None
for i, G in enumerate(graphs):
G_nodes_set = set(G.nodes)
G_edges_set = set(G.edges(keys=True) if G.is_multigraph() else G.edges())
if i == 0:
# create new graph
R = G.__class__()
node_intersection = G_nodes_set
edge_intersection = G_edges_set
elif G.is_multigraph() != R.is_multigraph():
raise nx.NetworkXError("All graphs must be graphs or multigraphs.")
else:
node_intersection &= G_nodes_set
edge_intersection &= G_edges_set
R.graph.update(G.graph)
if R is None:
raise ValueError("cannot apply intersection_all to an empty list")
R.add_nodes_from(node_intersection)
R.add_edges_from(edge_intersection)
return R
```