On 17 February 2014 21:18, "André Walker-Loud <walksl...@gmail.com>"
<walksl...@gmail.com> wrote:
>
> What I am trying to avoid is having to write a special case for each order of
> polynomial I want. I tried the following
>
> def poly(x,pars):
> val = 0.
> for i,ci in enumerate(pars):
> val += x**i * ci
> return val
> def f_lambda(x,pars):
> return lambda x,*pars: poly(x,*pars)
> x = np.array([1,2,3])
> f = f_lambda(x,[-.5,2.])
> f(x,[-.5,2.])
> array([ 1.5, 3.5, 5.5])
>
> f(x,[-.5,3.])
> array([ 2.5, 5.5, 8.5])
> etc.
>
> This function correctly gives me a polynomial of arbitrary order, but
>
> f.func_code.co_varnames
> ('x', 'pars')
>
> so I can not pass this to the third party minimizer, as it does not know how
> to interpret 'pars'. You can probably see trying to replicate the lambda
> function method for an arbitrary polynomial is what naturally led to the
> string/exec option.
This particular case is easily solved:
def f_lambda(x,pars):
return lambda x: poly(x,*pars)
You let the closure take care of pars and return a function that takes
exactly one argument x.
Oscar
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