Steven G. Johnson <stevenj.mit@...> writes:
> >
> > Traceback (most recent call last):
> > File "./toy_all_nlopt.py", line 42, in <module>
> > variables_values = opt.optimize(numpy.array([0]*36, dtype=numpy.double))
> > File "/Library/Python/2.7/site-packages/nlopt.py", line 254, in optimize
> > def optimize(self, *args): return _nlopt.opt_optimize(self, *args)
> > TypeError: <lambda>() takes exactly 1 argument (2 given)
>
> You don't provide your code, but I would guess that the error
message means that you either passed 2
> arguments when 1 was expected or you declared your objective
function with 1 argument when it is
supposed
> to take 2 arguments.
>
>
Hi Steven, thanks for the quick reply!
Sorry for not providing more code, I didn't know what to include.
I haven't (as far as I know) passed 2 arguments anywhere.
Simplifying a little, my code goes like this:
opt = nlopt.opt(nlopt.LN_COBYLA, 36)
def objective(x, grad):
if grad.size > 0:
raise NotImplemented('Gradient requested')
return 1.0 #actually some arithmetic (+/*) over x[i]'s,
#but I get the same error with just 1.0
opt.set_max_objective(objective)
# some constraints like:
opt.add_equality_constraint(lambda x: x[25] - 1)
# [...]
variables_values = opt.optimize(numpy.array([0]*36, dtype=numpy.double))
Any suggestion?
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