R. = GF(2)[]
f = x^5+x^2+1
fx = ntl.GF2X(f)
gives error:
Traceback (most recent call last):fx
File "ntl_GF2X.pyx", line 141, in
sage.libs.ntl.ntl_GF2X.ntl_GF2X.__init__
AttributeError: 'sage.rings.polynomial.polynomial_modn_dense_ntl.Po'
object has no attribute '_Polynomial_dense_mod_n_
Thanks. I've made a trac ticket for this:
http://trac.sagemath.org/sage_trac/ticket/2090
On Feb 7, 2008 11:30 AM, Marshall Buck <[EMAIL PROTECTED]> wrote:
>
> (sage 2.10 on X86 linux.)
>
> Suppose you define the ring of polynomials over GF(2):
>
> R. = GF(2)[]
>
> Then a simple polynomial lik
On Feb 7, 2008 11:56 AM, Kate <[EMAIL PROTECTED]> wrote:
>
> In sage-2.10.1
>
> sage: F. = GF(2^20)
> sage: F.gens()
> (a,)
>
> What is a?
A bug. Thanks for the report:
http://trac.sagemath.org/sage_trac/ticket/2089
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In sage-2.10.1
sage: F. = GF(2^20)
sage: F.gens()
(a,)
What is a?
Kate
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Is there a better way to do this w/out creating a function?
def Binomial_Vector(n):
return [binomial(n,i) for i in range(n+1)]
Binomial_Vector(5)
[1, 5, 10, 10, 5, 1]
In particular, what Python goodness could I add to the
sage.rings.arith binomial def to accomplish this?
binomial(5).
(sage 2.10 on X86 linux.)
Suppose you define the ring of polynomials over GF(2):
R. = GF(2)[]
Then a simple polynomial like
f = x^32000
takes time quadratic in the degree to construct.
Meanwhile, the left shift operator will construct the polynomial
almost instantly:
f = x << (32000 - 1)
Al
Dear sage team,
sorry that i asked, because the solution is easy:
Instead of saying
> gcc -c -fPIC -I/usr/local/include/python2.5/ -o Tensors.o Tensors.c
i should have said
> gcc -c -fPIC -I/usr/local/sage-2.8.6/local/include/python2.5/ -o Tensors.o
> Tensors.c
Now my module Tensors.so works.
Simon King wrote:
>
> Dear sage team,
Hi Simon,
> i wrote some module defining a class "Tensor" (just a quick hack), and
> if this is in a file Tensors.spyx, then
> sage: attach Tensors.spyx
> works perfectly.
>
> Now, i changed it to a file Tensors.pyx, and created Tensors.so like
> this:
>>
Dear sage team,
i wrote some module defining a class "Tensor" (just a quick hack), and
if this is in a file Tensors.spyx, then
sage: attach Tensors.spyx
works perfectly.
Now, i changed it to a file Tensors.pyx, and created Tensors.so like
this:
> sage -cython Tensors.pyx
> gcc -c -fPIC -I/usr/
Dear William,
I'm not shure if this is really a python issue of feature,
I cannot reproduce this error message in Python, it's possible to
define a class, create an instance of it and cPickle it all in the
same file,
the problem here is that the function save does not work if it's
executed in a sc
> Is there a workaround? If no, are there plans to remove that limitation?
That's a bummer, but I don't know any workaround (one could try M2 though) or
how to remove that limitation quickly.
One option is to use the toy Buchberger implementation (which needs some
patches to be truly independ
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