Well, complex spline interpolation does not fit my needs as I am looking
for interpolation by a function of type
(a_8*x^8+a_7*x^7+a_6*x^6+a_5*x^5+a_4*x^4+a_3*x^3+a_2*x^2+a_1*x^1+a_0)/(b_8*x^8+b_7*x^7+b_6*x^6+b_5*x^5+b_4*x^4+b_3*x^3+b_2*x^2+b_1*x^1+b_0).or
(a_7*x^7+a_6*x^6+a_5*x^5+a_4*x^4+a_3*x^3+a_2*x^2+a_1*x^1+a_0)/(b_8*x^8+b_7*x^7+b_6*x^6+b_5*x^5+b_4*x^4+b_3*x^3+b_2*x^2+b_1*x^1+b_0).
Separating.the problem into a problem in four real dimensions sounds
interesting, but how to do it?
If I understand correctly, "model" in find_fit is supposed to be a function
\to\R. If I consider only real part or imaginary part i.e consider points
\in\mathbb{C}x\mathbb{R}, I receive a result that is garbage.
2012/7/16 kcrisman <kcris...@gmail.com>
>
>
> On Monday, July 16, 2012 5:08:34 AM UTC-4, Urs Hackstein wrote:
>>
>> Ok. I overlooked it. Thus is there an alternative to interpolate points
>> (x_1k,x_2k)\in\mathbb{C}x\**mathbb{C} by a function
>> f:\mathbb{C}\to\mathbb{C}?
>>
>>
> I don't know whether
> http://www.sagemath.org/doc/reference/sage/calculus/interpolators.htmlwould
> fit your needs. Actually, maybe not... but anyway worth looking at.
> I don't think that GSL provides this, nor Scipy. I suppose you could
> separate it into a problem in four real dimensions?
>
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