You shouldn't be reluctant. It's a fine piece of software in its own
right. I don't think it actually has an LP solver inside it, though; I
believe it uses external solvers.
> But my friend assures me that sine SciPy has a lot more complex Non-linear
> programming solvers, there must be something for Linear Programming in there
> but I am not able to find it.
No, we have no LP solvers in scipy.
--
Robert Kern
"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
-- Umberto Eco
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If all you need is an LP solver, I have had a lot of luck with
lp_solve 5.5 (http://lpsolve.sourceforge.net/5.5/).. It's a mature
package that I use heavily in my research and it works very, very
well. It has a python wrapper, which isn't bad and is quite full
featured. For what I'm doing, though, I've written a (simpler) cython
interface that works directly with numpy arrays and is great to use in
conjunction with numpy/scipy. The documentation is currently rather
sparse, but if you're interested I'll work on that a bit and send it
to you. Note that it's LGPL, not BSD like numpy/scipy.
-- Hoyt
On Sun, Dec 21, 2008 at 9:10 PM, Aditya Sethi <ady.se
But my friend assures me that sine SciPy has a lot more complex
Non-linear programming solvers, there must be something for Linear
Programming in there but I am not able to find it.
> _______________________________________________
> SciPy-user mailing list
> SciPy...@scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>
>
--
++++++++++++++++++++++++++++++++++++++++++++++++
+ Hoyt Koepke
+ University of Washington Department of Statistics
+ http://www.stat.washington.edu/~hoytak/
+ hoy...@gmail.com
++++++++++++++++++++++++++++++++++++++++++
I'd love to see your Cython wrapper. Is it public somewhere?
--
Robert Kern
"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
-- Umberto Eco
LP solvers are much harder to write. Well, "good" implementations of
an LP solver are more complicated than "good" implementations of a
standard nonlinear local optimizer. The comparison isn't really
apples-to-apples, though. A good LP solver can have much higher
dimensionality than a good nonlinear optimizer will deal with. But
because of this, a typical LP *problem* will also have many more
dimensions, too.
I use pulp.py as an interface to produce a file that can be read by
XPRESS (a commercial package) to solve my LP problems. Pulp can also
produce output for GLPK (which if free), CPLex, and, perhaps, symphony
(which is also free), but I did not try the latter. Pulp is, at least
for my purposes, really useful. it allows me to specify the cost
function and the constraint in an efficient and readable way.
bye
Nicky
2008/12/22 Robert Kern <rober...@gmail.com>:
Please keep me informed. I had pulp working within a few minutes, even
though I am not a good python programmer. Hopefully it works for you
too.
bye
Nicky
2008/12/23 Aditya Sethi <ady....@gmail.com>: