On Sat, Jan 30, 2010 at 6:47 PM, Scott <[email protected]> wrote:
> I am currently using scipy.optimize.fsolve to solve a 15 and 420
> equation nonlinear system but I would like to try methods other than
> Powell's hybrid. The answer to the previous become a parameter for
> the next step. The nonlinear system is polynomial and was created in
> sympy.
>
> sympy.nsolve, mpmath.findroots both provide a variety of solvers but
> the interfaces seem to be less friendly regarding passing parameters
> to the residual function and analytical jacobian.
>
> Advice on how to get from :
> >>> def f(x1, x2):
> ... return x1**2 + x2, 5*x1**2 - 3*x1 + 2*x2 - 3
> ...
> >>> findroot(f, (0, 0))
> matrix(
> [['-0.618033988749895'],
> ['-0.381966011250105']])
>
>
> to something like the following would be appreciated.
> >>> def f(x1, x2,a,b):
> ... return a*x1**2 + x2, b*5*x1**2 - 3*x1 + 2*x2 - 3
> ...
> >>> findroot(f, parameters=(a,b),(0, 0))
> matrix(
> [['-0.618033988749895'],
> ['-0.381966011250105']])
Either by modifying our solvers, I think we should provide this
"parameters" argument. If you could send us a patch fixing it, it'd be
awesome.
In the meantime, just use global variables, e.g. something like:
params = [ <whatever you need here> ]
def f(...):
global params
<use params>
global params
params = (a, b)
findroot(f, (0, 0))
Ondrej
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