Hi,

i would prefer to raise an error promoting the use of change_ring (same
for matrices), which allows more tuning on the base ring.

By the way, note that the best approx with floating-point coefficients
(e.g. for the sup norm on [-1,1]), is not necessarilly obtained with the
best approx on each coefficients.

Ciao,
Thierry



On Thu, May 30, 2019 at 11:38:45AM +0200, Vincent Delecroix wrote:
> Dear devs,
> 
> Is it fine if I implement numerical_approx on polynomials by calling
> it recursively on coefficients? For example, we would have
> 
> sage: x = polygen(QQ)
> sage: p = 1343235439458/23 * x^2 - 234 / 143425*x + 1432/6512
> sage: p.numerical_approx()
> 5.84015408460000e10*x^2 - 0.00163151472895241*x + 0.219901719901720
> 
> Right now, it does raise a TypeError (raised inside the generic
> numerical_approx).
> 
> It would fit with what we have for matrices
> 
> sage: matrix(2, [11/23, -5/3, 132/7, 77/12]).n()
> [0.478260869565217 -1.66666666666667]
> [ 18.8571428571429  6.41666666666667]
> 
> Best
> Vincent
> 
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