def completeGraph (*ns):
'''
Returns the complete graph $K_{n_1, n_2, \dots, n_k}$ when passed
the sequence \code {n_1, n_2, \dots, n_k}.
'''
if len (ns) == 1:
return completeGraph ( * ([1] * ns[0]) )
n = sum (ns)
vertices = range (n)
partition_indices = [sum (ns[:i]) for i in range (len (ns))]
partite_sets = [vertices[partition_indices[i]:partition_indices[i+1]]
\
for i in range (len (partition_indices) - 1)]
partite_sets.append (vertices[partition_indices [-1]:] )
edges = []
for i in range (len (partite_sets)):
for j in range (i + 1, len (partite_sets)):
edges.extend ([ (u, v) for u in partite_sets [i] for v in \
partite_sets [j] ])
return graph.Graph (vertices = vertices, edges = edges)
Many thanks!
Graphine does this with the following:
from base import Graph
def K(n):
"""Generates a completely connected undirected graph of size n.
The verticies are numbered [0, n).
The edges are named after the verticies they connect such that
an edge connected verticies 1 and 2 is named (1,2).
"""
# create the graph
k = Graph()
# generate all the nodes
for i in range(n):
k.add_node(i)
# generate all the edges
for i in range(n):
for j in range(i+1, n):
k.add_edge(i, j, (i,j), is_directed=False)
# return the graph
return k
Disclaimer: I'm the author of graphine.
Geremy Condra
Sorry, misread- to generate a k-partite graph, you'll need a bit
more legwork. Give me a bit and I'll add it to graphine.
Geremy Condra
Alright, how does this look:
def k_partite(*partition_sizes):
g = Graph()
for pos, num_nodes in enumerate(partition_sizes):
for i in range(num_nodes):
n = g.add_node(name=(pos,i), partition=pos)
for node1 in g.nodes:
for node2 in g.nodes:
if node1.partition != node2.partition:
g.add_edge(node1, node2, is_directed=False)
return g
Geremy Condra
Not sure exactly how you're representing graphs, this seems like the
simplest way of listing the edges.
def complete_partite(*sizes):
total = sum(sizes)
nodes, edges = range(total), []
for group in xrange(len(sizes)):
low = sum(sizes[:group-1])
high = sum(sizes[:group])
edges.extend((i, j) for i in xrange(low, high)
for j in xrange(high, total))
return nodes, edges
Chard
> Not sure exactly how you're representing graphs, this seems like the
> simplest way of listing the edges.
>
> def complete_partite(*sizes):
> total = sum(sizes)
> nodes, edges = range(total), []
> for group in xrange(len(sizes)):
> low = sum(sizes[:group-1])
> high = sum(sizes[:group])
> edges.extend((i, j) for i in xrange(low, high)
> for j in xrange(high, total))
> return nodes, edges
Thanks! I think this is what I was looking for (unless the collective
wisdom of c.l.py can come up with something *even more* elegant). :-)
I think this has a conceptual off-by-one error. Add
print group, low, high
to see what I mean (especially the first iteration). It still works, but
I think this would be clearer:
low = sum(sizes[:group])
high = sum(sizes[:group + 1])
or to avoid doing essentially the same summation twice:
low = sum(sizes[:group])
high = low + sizes[group]
>> edges.extend((i, j) for i in xrange(low, high)
>> for j in xrange(high, total))
>> return nodes, edges
Here's a variant that uses a running total instead of recomputing the
sum in every iteration, thus getting rid of xrange(len(...)).
def complete_partite(*sizes):
total = sum(sizes)
nodes, edges = range(total), []
curr_total = 0
for size in sizes:
edges.extend((i, j) for i in xrange(curr_total, curr_total+size)
for j in xrange(curr_total+size, total))
curr_total += size
return nodes, edges
Finally, here is a variant that is a bit shorter because it produces the
edges in a different way and hence gets rid of the need for knowing the
total up front and uses total as running total instead. It has the
drawback of not generating the edges in ascending order though, so I
think the previous one is nicer:
def complete_partite(*sizes):
total, edges = 0, []
for size in sizes:
edges.extend((i, j) for i in xrange(total)
for j in xrange(total, total + size))
total += size
return range(total), edges
Finally, here's a variation on the same theme:
def complete_partite(*sizes):
nodes, edges = [], []
for size in sizes:
partition = xrange(len(nodes), len(nodes) + size)
edges.extend((i, j) for i in nodes for j in partition)
nodes.extend(partition)
return nodes, edges
Malte