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']])
V/R
Scott
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