I just drafted different versions of the `gridspace` function: https://tmp23.tmpnb.org/user/1waoqQ8PJBJ7/notebooks/2015-05%20gridspace.ipynb
Beste Grüße, Stefan On Sun, May 10, 2015 at 1:40 PM, Stefan Otte <stefan.o...@gmail.com> wrote: > Hey, > > 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) > > fancy_function(X) > > 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? > > > Best, > Stefan > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
