Just to clarify--this is a multivariate algorithm. I changed the function
Permmin to simply take the absolute value of (xmin, ymin) so that it returns
one value. Unfortunately, the error remains--it still returns this error:
" x, f, d = lbfgsb.fmin_l_bfgs_b(Permmin, x0, Jacobi, params,
bounds=[(.001,100),(-50,-.001)] , maxfun=500)
File "C:\Python24\lib\site-packages\scipy\optimize\lbfgsb.py", line 197,
in fmin_l_bfgs_b
isave, dsave)
ValueError: failed to initialize intent(inout) array -- expected elsize=8
but got 4 -- input 'l' not compatible to 'd'"
"Robert Kern" <[EMAIL PROTECTED]> wrote in message
news:[EMAIL PROTECTED]
> mclaugb wrote:
>> Does anyone out there have a piece of code that demonstrates the use of
>> the
>> lbfgsb multivariate, bounded solver in the scipy.optimize toolkit? An
>> example would get me started because my code below does not seem to work.
>
> You will probably get better/faster/more answers on the scipy-user mailing
> list.
>
> http://www.scipy.org/Mailing_Lists
>
>> Permmin is a function that simply returns a vector array [xmin, ymin]
>
> This is your problem. The function to minimize must return a scalar, not a
> vector. This is not a multi-objective optimizer.
>
> --
> 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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