We didn't really have any expectations about the size of these
automorphism groups (this isn't the central part of the project), so
I'm not sure if this output is reasonable for the given graph. But
here's what search_tree gives:
([[0, 6, 2, 3, 4, 5, 1, 7, 8, 14, 10, 11, 12, 13, 9, 15, 16, 17, 28,
29, 20, 21, 22, 23, 24, 25, 26, 27, 18, 19, 30, 31, 32, 33, 44, 45,
36, 37, 38, 39, 40, 41, 42, 43, 34, 35, 46, 47, 48, 49, 60, 61, 52,
53, 54, 55, 56, 57, 58, 59, 50, 51, 62, 63, 64, 65, 76, 77, 68, 69,
70, 71, 72, 73, 74, 75, 66, 67, 78, 79], [0, 7, 2, 3, 4, 5, 1, 6, 9,
14, 10, 11, 12, 13, 8, 15, 16, 17, 30, 31, 20, 21, 22, 23, 24, 25, 26,
27, 18, 19, 28, 29, 34, 35, 44, 45, 36, 37, 38, 39, 40, 41, 42, 43,
32, 33, 46, 47, 48, 49, 62, 63, 52, 53, 54, 55, 56, 57, 58, 59, 50,
51, 60, 61, 66, 67, 76, 77, 68, 69, 70, 71, 72, 73, 74, 75, 64, 65,
78, 79], [0, 1, 2, 3, 4, 8, 6, 10, 5, 9, 7, 11, 12, 13, 14, 15, 16,
17, 18, 19, 20, 21, 22, 23, 24, 25, 32, 33, 28, 29, 36, 37, 26, 27,
34, 35, 30, 31, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50,
51, 52, 53, 54, 55, 56, 57, 64, 65, 60, 61, 68, 69, 58, 59, 66, 67,
62, 63, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79], [0, 1, 2, 3, 5, 4, 6,
7, 8, 9, 11, 10, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 26,
27, 24, 25, 28, 29, 30, 31, 32, 33, 34, 35, 38, 39, 36, 37, 40, 41,
42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 58, 59, 56,
57, 60, 61, 62, 63, 64, 65, 66, 67, 70, 71, 68, 69, 72, 73, 74, 75,
76, 77, 78, 79], [0, 1, 2, 4, 5, 3, 6, 7, 8, 9, 12, 10, 11, 13, 14,
15, 16, 17, 18, 19, 20, 21, 24, 25, 26, 27, 22, 23, 28, 29, 30, 31,
32, 33, 34, 35, 40, 41, 36, 37, 38, 39, 42, 43, 44, 45, 46, 47, 48,
49, 50, 51, 52, 53, 56, 57, 58, 59, 54, 55, 60, 61, 62, 63, 64, 65,
66, 67, 72, 73, 68, 69, 70, 71, 74, 75, 76, 77, 78, 79], [0, 1, 3, 4,
5, 8, 6, 13, 2, 9, 7, 10, 11, 12, 14, 15, 16, 17, 18, 19, 22, 23, 24,
25, 26, 27, 32, 33, 28, 29, 42, 43, 20, 21, 34, 35, 30, 31, 36, 37,
38, 39, 40, 41, 44, 45, 46, 47, 48, 49, 50, 51, 54, 55, 56, 57, 58,
59, 64, 65, 60, 61, 74, 75, 52, 53, 66, 67, 62, 63, 68, 69, 70, 71,
72, 73, 76, 77, 78, 79]], Graph on 80 vertices)
And here's what the profiler had to say:
ncalls tottime percall cumtime percall
filename:lineno(function)
1 19118.403 19118.403 19118.427 19118.427
{sage.graphs.graph_isom.search_tree}
464 0.011 0.000 0.012 0.000 xgraph.py:
293(edges_iter)
3 0.007 0.002 0.007 0.002 graph.py:1059(relabel)
231 0.002 0.000 0.004 0.000 xgraph.py:116(add_edge)
231 0.001 0.000 0.001 0.000 xgraph.py:
233(has_neighbor)
1 0.001 0.001 0.012 0.012 xgraph.py:439(copy)
231 0.001 0.000 0.002 0.000 xgraph.py:198(has_edge)
463 0.000 0.000 0.000 0.000 {method 'has_key' of
'dict' objects}
253 0.000 0.000 0.000 0.000 {method 'iterkeys' of
'dict' objects}
160 0.000 0.000 0.000 0.000 {method 'iteritems' of
'dict' objects}
233 0.000 0.000 0.000 0.000 {len}
4 0.000 0.000 0.000 0.000 graph.py:1022(vertices)
80 0.000 0.000 0.000 0.000 graph.py:205(add_node)
4 0.000 0.000 0.000 0.000 {sorted}
1 0.000 0.000 19118.427 19118.427 <string>:1(<module>)
1 0.000 0.000 0.000 0.000 graph.py:3173(__init__)
6 0.000 0.000 0.000 0.000 graph.py:292(nodes_iter)
1 0.000 0.000 0.012 0.012 graph.py:3365(copy)
4 0.000 0.000 0.000 0.000 graph.py:
980(vertex_iterator)
2 0.000 0.000 0.000 0.000 graph.py:713(order)
4 0.000 0.000 0.000 0.000 graph.py:
129(prepare_nbunch)
2 0.000 0.000 0.000 0.000 graph.py:316(order)
6 0.000 0.000 0.000 0.000 {isinstance}
3 0.000 0.000 0.000 0.000 {method 'keys' of 'dict'
objects}
1 0.000 0.000 0.000 0.000 graph.py:
3688(edge_iterator)
1 0.000 0.000 0.000 0.000 xgraph.py:100(__init__)
1 0.000 0.000 0.000 0.000 graph.py:92(__iter__)
1 0.000 0.000 0.000 0.000
{sage.structure.element.is_Matrix}
1 0.000 0.000 0.000 0.000 {method 'disable' of
'_lsprof.Profiler' objects}
I'll post a similar graph later today hopefully, although I should
probably be careful when I say "similar". I just mean graphs of the
same size or larger that I've arrived at in the same way (via
projection matrices coming from a class of matrices that I'm trying to
count).
Thanks,
-Dustin Pluta
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