indeed, using RDF time is reduced:
%time
x = srange(1,10,*RDF(0.000001)*)
for k in range(1,len(x)):
if abs(sin(x[k])*x[k]^2 + cos(x[k])*x[k]^2 + x[k] + cos(sin(x[k]))^2) <
0.0001:
print("Valor(y):",sin(x[k])*x[k]^2+cos(x[k])*x[k]^2+x[k]+cos(sin(x[k]))^2,"
. Raiz(x): ",x[k])
print("fim")
out: 33.17s
Em quarta-feira, 23 de março de 2016 09:47:11 UTC-3, Jeroen Demeyer
escreveu:
>
> Arithmetic in RR is slower than arithmetic with native C types. If you
> use RDF instead of RR, Sage will be faster than numpy, especially if you
> use methods instead of global functions:
>
> sage: import numpy as np
> sage: np1 = np.float64('1'); RR1 = 1.0; RDF1 = RDF(1)
> sage: timeit('np.sin(np1)', number=10000, repeat=20)
> 10000 loops, best of 20: 812 ns per loop
> sage: timeit('sin(RR1)', number=10000, repeat=20)
> 10000 loops, best of 20: 3.85 µs per loop
> sage: timeit('sin(RDF1)', number=10000, repeat=20)
> 10000 loops, best of 20: 620 ns per loop
> sage: timeit('RDF1.sin()', number=10000, repeat=20)
> 10000 loops, best of 20: 151 ns per loop
>
>
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