本文整理汇总了Python中sage.graphs.graph.Graph.neighbor_iterator方法的典型用法代码示例。如果您正苦于以下问题：Python Graph.neighbor_iterator方法的具体用法？Python Graph.neighbor_iterator怎么用？Python Graph.neighbor_iterator使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类sage.graphs.graph.Graph的用法示例。
在下文中一共展示了Graph.neighbor_iterator方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: nauty
# 需要导入模块: from sage.graphs.graph import Graph [as 别名]
# 或者: from sage.graphs.graph.Graph import neighbor_iterator [as 别名]
#.........这里部分代码省略.........
program with some information on the arguments, while a line beginning
with ">E" indicates an error with the input.
- ``options`` -- string (default: ``""``) -- anything else that should
be forwarded as input to Nauty's genbg. See its documentation for more
information : `<http://cs.anu.edu.au/~bdm/nauty/>`_.
.. NOTE::
For genbg the *first class* elements are vertices, and *second
class* elements are the hypergraph's sets.
OUTPUT:
A tuple of tuples.
EXAMPLES:
Small hypergraphs::
sage: list(hypergraphs.nauty(4, 2))
[((), (0,), (1,), (0, 1))]
Only connected ones::
sage: list(hypergraphs.nauty(2, 2, connected=True))
[((0,), (0, 1))]
Non-empty sets only::
sage: list(hypergraphs.nauty(3, 2, set_min_size=1))
[((0,), (1,), (0, 1))]
The Fano Plane, as the only 3-uniform hypergraph with 7 sets and 7
vertices::
sage: fano = next(hypergraphs.nauty(7, 7, uniform=3, max_intersection=1))
sage: print(fano)
((0, 1, 2), (0, 3, 4), (0, 5, 6), (1, 3, 5), (2, 4, 5), (2, 3, 6), (1, 4, 6))
The Fano Plane, as the only 3-regular hypergraph with 7 sets and 7
vertices::
sage: fano = next(hypergraphs.nauty(7, 7, regular=3, max_intersection=1))
sage: print(fano)
((0, 1, 2), (0, 3, 4), (0, 5, 6), (1, 3, 5), (2, 4, 5), (2, 3, 6), (1, 4, 6))
"""
import subprocess
nauty_input = options
if connected:
nauty_input += " -c"
if not multiple_sets:
nauty_input += " -z"
if max_intersection is not None:
nauty_input += " -Z" + str(max_intersection)
# degrees and sizes
if regular is not False:
vertex_max_degree = vertex_min_degree = regular
if vertex_max_degree is None:
vertex_max_degree = number_of_sets
if vertex_min_degree is None:
vertex_min_degree = 0
if uniform is not False:
set_max_size = set_min_size = uniform
if set_max_size is None:
set_max_size = number_of_vertices
if set_min_size is None:
set_min_size = 0
nauty_input += " -d" + str(vertex_min_degree) + ":" + str(set_min_size)
nauty_input += " -D" + str(vertex_max_degree) + ":" + str(set_max_size)
nauty_input += " " + str(number_of_vertices) + " " + str(number_of_sets) + " "
sp = subprocess.Popen("genbg {0}".format(nauty_input), shell=True,
stdin=subprocess.PIPE, stdout=subprocess.PIPE,
stderr=subprocess.PIPE, close_fds=True)
if debug:
yield sp.stderr.readline()
gen = sp.stdout
total = number_of_sets + number_of_vertices
from sage.graphs.graph import Graph
while True:
try:
s = next(gen)
except StopIteration:
# Exhausted list of graphs from nauty geng
return
G = Graph(s[:-1], format='graph6')
yield tuple(tuple(G.neighbor_iterator(v)) for v in range(number_of_vertices, total))