On Sun, Jul 6, 2014 at 9:35 PM, Daniel da Silva
<var.mail.dan...@gmail.com> wrote:
> The idea is that there be a short-hand for creating arrays as there is for
> matrices:
>
> np.mat('.2 .7 .1; .3 .5 .2; .1 .1 .9')
>
> It was suggested in GitHub issue #4817 in light that it would be beneficial
> to beginners and to presenters during demonstrations. In GitHub pull
> request #484, I implemented this as the np.arr function.
>
> Does anyone have any feedback on the API details? Some examples from my
> implementation follow.
>
>>>> np.arr('3; 4; 5')
> array([[3],
> [4],
> [5]])
>
>>>> np.arr('3; 4; 5', dtype=float)
> array([[ 3.],
> [ 4.],
> [ 5.]])
>
>>>> np.arr('1 0 0; 0 1 0; 0 0 1')
> array([[1, 0, 0],
> [0, 1, 0],
> [0, 0, 1]])
>
>>>> np.arr('4, 5; 6, 7')
> array([[4, 5],
> [6, 7]])
It occurs to me that np.mat always returns a 2d matrix, but for arrays
there are more options.
What should np.arr('1 2 3') return? a 1d array or a 2d row vector?
(Maybe np.arr('1 2 3;') should give the row-vector?)
Should there be some way to write 3d or higher-d arrays?
-n
--
Nathaniel J. Smith
Postdoctoral researcher - Informatics - University of Edinburgh
http://vorpus.org
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