Done:
http://trac.sagemath.org/sage_trac/ticket/12455
I've added a patch, which should do the job, but it has a few
shortcomings:
1.-The resulting symbolic functions seem to remain on hold:
sage: airy_ai(1.0)
airy_ai(1.00000000000000)
You need to force it to evaluate:
sage: airy_ai(1.0).n()
0.135292416313
2.- This doesn't work:
sage: airy_ai(2.0).n(digits=100)
0.0349241304233
3.- There is no evaluation for airy_ai_prime or airy_bi_prime
4.- I'm not sure about how should the functions be called, some
possible schemes are
{ai,bi,aip,bip} {ai,bai,aip,baip}
{airy_ai,airy_bi,airy_ai_prime,airy_bi_prime}
And also whether the latex representation should be capitalized or
not. I chose the third scheme, and capitalized typesetting.
Cheers!
Oscar
On 6 feb, 19:37, kcrisman <[email protected]> wrote:
> On Feb 6, 4:22 pm, Oscar Lazo <[email protected]> wrote:
>
>
>
>
>
>
>
>
>
> > That worked excelent! I made the following code:
>
> > from sage.symbolic.function import BuiltinFunction
> > class AiryAi(BuiltinFunction):
> > def __init__(self):
> > BuiltinFunction.__init__(self, "ai",
> > latex_name=r"\operatorname{Ai}")
> > def _derivative_(self, x, diff_param=None): return aip(x)
>
> > class AiryAiPrime(BuiltinFunction):
> > def __init__(self):
> > BuiltinFunction.__init__(self, "aip",
> > latex_name=r"\operatorname{Ai}'")
>
> > class AiryBi(BuiltinFunction):
> > def __init__(self):
> > BuiltinFunction.__init__(self, "bi",
> > latex_name=r"\operatorname{Bi}")
> > def _derivative_(self, x, diff_param=None): return bip(x)
>
> > class AiryBiPrime(BuiltinFunction):
> > def __init__(self):
> > BuiltinFunction.__init__(self, "bip",
> > latex_name=r"\operatorname{Bi}'")
>
> > ai=AiryAi()
> > bi=AiryBi()
> > aip=AiryAiPrime()
> > bip=AiryBiPrime()
> > ai(x)+bi(x)+aip(x)+bip(x)
>
> > And now stuff like
> > f=A1*ai(k*x)+B1*bi(k*x)
> > f
> > diff(f,x).subs(x=x0)
>
> > works exactly the way I wanted.
>
> > Thank you!
>
> Great!
>
> Oscar, you have a Trac account, right? Would you mind opening up a
> ticket to make these functions "symbolic", put your code up as a
> "protopatch", add the ticket to an appropriate place
> onhttp://trac.sagemath.org/sage_trac/wiki/symbolics/functions, and cc:
> users kcrisman, burcin, and benjaminfjones on the ticket? Since we
> have robust numerical evaluation for this, we might as well add them
> in this way.
>
> Thanks!
>
> - kcrisman
On 6 feb, 19:37, kcrisman <[email protected]> wrote:
> On Feb 6, 4:22 pm, Oscar Lazo <[email protected]> wrote:
>
>
>
>
>
>
>
>
>
> > That worked excelent! I made the following code:
>
> > from sage.symbolic.function import BuiltinFunction
> > class AiryAi(BuiltinFunction):
> > def __init__(self):
> > BuiltinFunction.__init__(self, "ai",
> > latex_name=r"\operatorname{Ai}")
> > def _derivative_(self, x, diff_param=None): return aip(x)
>
> > class AiryAiPrime(BuiltinFunction):
> > def __init__(self):
> > BuiltinFunction.__init__(self, "aip",
> > latex_name=r"\operatorname{Ai}'")
>
> > class AiryBi(BuiltinFunction):
> > def __init__(self):
> > BuiltinFunction.__init__(self, "bi",
> > latex_name=r"\operatorname{Bi}")
> > def _derivative_(self, x, diff_param=None): return bip(x)
>
> > class AiryBiPrime(BuiltinFunction):
> > def __init__(self):
> > BuiltinFunction.__init__(self, "bip",
> > latex_name=r"\operatorname{Bi}'")
>
> > ai=AiryAi()
> > bi=AiryBi()
> > aip=AiryAiPrime()
> > bip=AiryBiPrime()
> > ai(x)+bi(x)+aip(x)+bip(x)
>
> > And now stuff like
> > f=A1*ai(k*x)+B1*bi(k*x)
> > f
> > diff(f,x).subs(x=x0)
>
> > works exactly the way I wanted.
>
> > Thank you!
>
> Great!
>
> Oscar, you have a Trac account, right? Would you mind opening up a
> ticket to make these functions "symbolic", put your code up as a
> "protopatch", add the ticket to an appropriate place
> onhttp://trac.sagemath.org/sage_trac/wiki/symbolics/functions, and cc:
> users kcrisman, burcin, and benjaminfjones on the ticket? Since we
> have robust numerical evaluation for this, we might as well add them
> in this way.
>
> Thanks!
>
> - kcrisman
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