If you want to use the command that Jori gave in Sage, you can use the fact
that nauty_geng just runs geng and appends the option string after the
command. So if you want to generate the last three graphs that are returned
by geng for biconnected graphs on 10 vertices you can do this:
for g in graphs.nauty_geng("10 -C | tail -3"):
print g
Cheers
Nico
Op vr 22 mrt. 2019 om 08:29 schreef David Coudert <david.coud...@gmail.com>:
> Our interface to nauty geng is in Python, but the difficulty is not here.
>
> - It takes time to build graphs from graph6 strings, and also to build
> Sandpiles (12 for each graph)
> - The number of biconnected graphs with 12 nodes is huge: 153.620.333.545
> See https://oeis.org/A002218
>
> Some parallelism could certainly help here, but there will be no miracle.
> A faster method for the tests on Sandpile is needed.
>
>
> Le jeudi 21 mars 2019 19:47:37 UTC+1, Dima Pasechnik a écrit :
>>
>>
>>
>> On Thu, 21 Mar 2019 18:42 Ai Bo, <boai...@gmail.com> wrote:
>>
>>> I found it. Thank you.
>>> I also tried the command listed above.
>>> I am confused. Where is this "I]~~~~~~w"?
>>>
>>
>> This is a particular way to encode graph as a string of characters (8
>> bits per character).
>> Read Sage docs on Graph for details.
>>
>> Is it a file? How did Graph load this?
>>>
>>> In my program, my code looks like this:
>>> i=12
>>> for G in graphs.nauty_geng(str(i) + " -C"):
>>> q = True
>>> for j in range (0,i):
>>> S = Sandpile(G,j)
>>> if S.identity() != S.max_stable():
>>> q = False
>>> break
>>>
>>>
>>>
>>> If I use geng to generate graphs, how should I load them in my for loop
>>> so I can check with Sandpile?
>>>
>>
>> Ideally one should create a fast interface from Python to geng, probably
>> using Cython, if it is not already done.
>>
>>
>>> On Thursday, March 21, 2019 at 8:46:56 AM UTC-7, Dima Pasechnik wrote:
>>>>
>>>> On Thu, Mar 21, 2019 at 3:03 PM Ai Bo <boai...@gmail.com> wrote:
>>>>
>>>> > is this "nauty26r7/geng" a program available?
>>>>
>>>> geng is installed in local/bin/ sub-directory of your Sage
>>>> installation, as a part of Sage's standard package nauty.
>>>>
>>>> > Also, as Python is slow, any part of the nautygen can be written in
>>>> other language, such as C/C++?
>>>>
>>>> it is written in C, so it's quite fast in this sense.
>>>>
>>>> >
>>>> > Thanks,
>>>> > Laura
>>>> >
>>>> > On Wednesday, March 20, 2019 at 11:48:38 PM UTC-7, Jori Mäntysalo
>>>> (TAU) wrote:
>>>> >>
>>>> >> On Thu, 21 Mar 2019, Ai Bo wrote:
>>>> >>
>>>> >> > Is there a way to "random access"? For example, access the nth
>>>> element
>>>> >> > in the "generator", instead of one by one?
>>>> >>
>>>> >> Kind of. As a most time is propably spent by creating Python data
>>>> >> structures for SageMath, you can use nautygen directly to generate
>>>> huge
>>>> >> number of graphs.
>>>> >>
>>>> >> As an example, it takes below 5 seconds to generate all biconnected
>>>> graphs
>>>> >> on 10 vertices, and I took third last one:
>>>> >>
>>>> >> $ nauty26r7/geng 10 -C | tail -3 | head -1
>>>> >> >A /home/jm58660/lat-koe/nauty26r7/geng -Cd2D9 n=10 e=10-45
>>>> >> >Z 9743542 graphs generated in 4.59 sec
>>>> >> I]~~~~~~w
>>>> >>
>>>> >> and now
>>>> >>
>>>> >> sage: g = Graph('I]~~~~~~w', format='graph6')
>>>> >> sage: g.is_biconnected()
>>>> >> True
>>>> >>
>>>> >>
>>>> >> --
>>>> >> Jori Mäntysalo
>>>> >>
>>>> >> Tampereen yliopisto - Ihminen ratkaisee
>>>> >
>>>> > --
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