s only the lower half
>like below.
>1
>6��� 7
>11 12 13
>�- - -��� -� etc
How about saving numpy.concatenate([x[i,:i+1] for i in range(x.shape[0])])
instead? If you remove the concatenate, you'll get the individual
arrays that have the data you need
On Sat, Jun 15, 2013 at 12:29:11AM -0400, Kumar Appaiah wrote:
> I now see that the polynomial structure is intended to be "rich", as
> opposed to the naïve function that I proposed. In the least, though,
> the documentation could reflect the example you gave me. I could send
That could replace the cast method in a nice way.
I now see that the polynomial structure is intended to be "rich", as
opposed to the naïve function that I proposed. In the least, though,
the documentation could reflect the example you gave me. I could send
a patch that adds an examp
On Fri, Jun 14, 2013 at 08:59:03PM -0400, Kumar Appaiah wrote:
> Dear Numpy Users,
>
> I am trying to find out a way by which I can easily generate the n-th
> order "special" polynomial, where "special" could refer to Hermite,
> Chebyshev etc. Numpy 1.7
tch all the polynomial modules
to generate such polynomials, if you could tell me appropriate
function names for such convenience functions.
Thanks!
Kumar
--
Kumar Appaiah
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