[SciPy-dev] Multiple constraints in fmin_cobyla
Nils Wagner
nwagner at mecha.uni-stuttgart.de
Tue Nov 8 09:14:40 CST 2005
Robert Kern wrote:
>Nils Wagner wrote:
>
>>Robert Kern wrote:
>>
>>
>>>Nils Wagner wrote:
>>>
>>>
>>>
>>>>Hi all,
>>>>
>>>>How can I apply multiple constraints (e.g. all design variables x \in
>>>>\mathds{R}^n should be positive) in fmin_cobyla ?
>>>>
>>>>x_opt=optimize.fmin_cobyla(func, x, cons, args=(), consargs=(),maxfun=1200)
>>>>
>>>>def cons(x):
>>>>
>>>> ?????
>>>>
>>>>
>>>The documentation is pretty clear:
>>>
>>> cons -- a list of functions that all must be >=0 (a single function
>>> if only 1 constraint)
>>>
>>I am aware of the help function :-)
>>Anyway, how do I define a l i s t of functions ?
>>
>
>It's a regular Python list which contains functions. I can't make it any
>clearer than that. This is pretty fundamental stuff.
>
>def cons0(x):
> return x[0]
>
>def cons1(x):
> return x[1]
>
>x_opt = optimize.fmin_cobyla(func, x, [cons0, cons1])
>
>
Thank you for the note.
Now assume that we have 10^3 constraints. Is there any better way than
typing
def cons0(x):
return x[0]
.
.
.
def cons999(x):
return x[999]
Nils
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