[SciPy-User] optimize.minimize - help me understand arrays as variables

[Andrew Nelson]

`calc_f3d` needs to return a single number, the overall 'cost'.

On 12 January 2015 at 11:55, KURT PETERS <peterskurt at msn.com> wrote:

>  I'm trying to use scipy.optimize.minimize.
>   I've tried multiple "multivariate" methods that don't seem to actually
> take multivariate data and derivatives.  Can someone tell me how I can make
> the multivariate part of the solver actually work?
>
> Here's an example:
> My main function the following (typical length for N is 3):
>
>   input guess is a x0=np.array([1,2,3])
>   the optimization function returns:
>   def calc_f3d(...):
>       f3d = np.ones((np.max([3,N]),1)
>       .... do some assignments to f3d[row,0] ....
>       return np.linalg.norm(f3d)   # numpy.array that's 3x1
>
> The jacobian returns a Nx3 matrix:
> def jacob3d(...):
>     df = np.ones((np.max([3,N]),3))
>     ... do some assignments to df[row,col]
>     return df               # note numpy.array that's 3x3
>
> The optimize call is:
>     OptimizeResult = optimize.minimize(
>         fun=tdcalc.calc_f3d,
>         x0=ract,
>         jac=tdcalc.jacob3d,
>         method='BFGS',
>         args=(operdata,),
>         tol=1.0e-8,
>         options={'maxiter': 40000, 'xtol':1e-8})  <--- ops change based on
> whether using Newton-CG or BFGS
>
> When I use BFGS, I get:
> Traceback (most recent call last):
>   File "./tdoa_calc.py", line 664, in <module>
>     options={'maxiter': 40000, 'gtol':1e-8})
>   File "/usr/lib64/python2.7/site-packages/scipy/optimize/_minimize.py",
> line 348, in minimize
>     return _minimize_bfgs(fun, x0, args, jac, callback, **options)
>   File "/usr/lib64/python2.7/site-packages/scipy/optimize/optimize.py",
> line 779, in _minimize_bfgs
>     old_fval, old_old_fval)
>   File "/usr/lib64/python2.7/site-packages/scipy/optimize/linesearch.py",
> line 95, in line_search_wolfe1
>     c1=c1, c2=c2, amax=amax, amin=amin, xtol=xtol)
>   File "/usr/lib64/python2.7/site-packages/scipy/optimize/linesearch.py",
> line 147, in scalar_search_wolfe1
>     alpha1 = min(1.0, 1.01*2*(phi0 - old_phi0)/derphi0)
> ValueError: The truth value of an array with more than one element is
> ambiguous. Use a.any() or a.all()
>
> When I use Newton-CG, I get:
> Traceback (most recent call last):
>   File "./tdoa_calc.py", line 655, in <module>
>     options={'maxiter': 40000, 'xtol':1e-8})
>   File "/usr/lib64/python2.7/site-packages/scipy/optimize/_minimize.py",
> line 351, in minimize
>     **options)
>   File "/usr/lib64/python2.7/site-packages/scipy/optimize/optimize.py",
> line 1320, in _minimize_newtoncg
>     eta = numpy.min([0.5, numpy.sqrt(maggrad)])
>   File "/usr/lib64/python2.7/site-packages/numpy/core/fromnumeric.py",
> line 1982, in amin
>     out=out, keepdims=keepdims)
>   File "/usr/lib64/python2.7/site-packages/numpy/core/_methods.py", line
> 14, in _amin
>     out=out, keepdims=keepdims)
> ValueError: setting an array element with a sequence.
>
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>


-- 
_____________________________________
Dr. Andrew Nelson


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