OK I'll take a look :)
On 15 May 2012 21:55, Nathann Cohen wrote:
> Hell Emil !!
>
>> Any chance you could make a patch? :) (I'd volunteer myself, but I
>> would probably mess it up!)
>
> H I could, but this patch is so local that it really is an
> ideal occasion to write your f
Hell Emil !!
> Any chance you could make a patch? :) (I'd volunteer myself, but I
> would probably mess it up!)
H I could, but this patch is so local that it really is an
ideal occasion to write your first patch... Are you sure you do not
want to give it a try ? It is fun to be
On 15 May 2012 15:21, Nathann Cohen wrote:
> Oh, it's usually quite straightforward to implement such things.
> Usually the feature already exists in the solver's C api, and all the
> work that needs to be done is to expose it in Sage :-)
Any chance you could make a patch? :) (I'd volunteer mys
Hellooo !!
> Next issue is that the Gurobi backend doesn't support the copy:
Oops ^^;
> Any idea how much work this would be to do?
Oh, it's usually quite straightforward to implement such things.
Usually the feature already exists in the solver's C api, and all the
work that needs to be do
Next issue is that the Gurobi backend doesn't support the copy:
AttributeError: 'sage.numerical.backends.gurobi_backend.GurobiBacke'
object has no attribute 'copy'
Any idea how much work this would be to do?
(I can now do what I wanted to do before, at least with GLPK.)
Emil
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On 15 May 2012 13:38, john_perry_usm wrote:
>I've found MILP lets you do it this way:
>
> sage: x, y = lp[0], lp[1]
Ahh! Thanks, this is what I need. (Is this documented anywhere?) - Emil
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On Monday, May 14, 2012 7:32:25 PM UTC-5, Emil wrote:
>
> lp = MixedIntegerLinearProgram(maximization=True)
> x = lp.new_variable()
>
> Then I do:
>
> nlp = copy(lp)
> x = nlp.new_variable()
>
> The variable 'x' now seems to contain different variables. So I cannot
> add any constraints that
Hi Nathann,
Thanks for writing the MILP class - it works very well. Now, I can do:
x = lp.new_variable()
Is there any way to do something like
x = lp.get_existing_variables()
?
I'm working on some graph theoretic stuff: I'm solving two LPs for
each graph, for as many graphs as I can. - Emil.
By the way, could I ask you what lead you to create and solve many LP ? I
mean, what are you solving which requires you to do that ? ^^;
Nathann
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Hellooo Emil !!!
Well, I just tried something and it ended upi crashing Sage, so I can just
advise you to create all your variables in the first LP from the start,
*then* to copy the MixedIntegerLinearProgram object. Of course it is a bad
answer :-)
John Perry was the one who needed this c
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