[Numpy-discussion] Create a n-D grid; meshgrid alternative
Jaime Fernández del Río
jaime.frio at gmail.com
Sun May 10 17:46:12 EDT 2015
On Sun, May 10, 2015 at 4:40 AM, Stefan Otte <stefan.otte at gmail.com> wrote:
> quite often I want to evaluate a function on a grid in a n-D space.
> What I end up doing (and what I really dislike) looks something like this:
> x = np.linspace(0, 5, 20)
> M1, M2 = np.meshgrid(x, x)
> X = np.column_stack([M1.flatten(), M2.flatten()])
> X.shape # (400, 2)
> I don't think I ever used `meshgrid` in any other way.
> Is there a better way to create such a grid space?
> I wrote myself a little helper function:
> def gridspace(linspaces):
> return np.column_stack([space.flatten()
> for space in np.meshgrid(*linspaces)])
> But maybe something like this should be part of numpy?
Isn't what you are trying to build a cartesian product function? There is a
neat, efficient implementation of such a function in StackOverflow, by our
Perhaps we could make this part of numpy.lib.arraysetops? Isthere room for
other combinatoric generators, i.e. combinations, permutations... as in
( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus planes
de dominación mundial.
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