On Tue, Jul 20, 2010 at 5:11 AM, Gael Varoquaux <gael.varoqu...@normalesup.org> wrote: > Is there in numpy a function that does: > > np.concatenate([a_[np.newaxis] for a_ in a]) > > ? > > ie: add a dimension in front and stack along this dimension, just like > > np.array(a) > > would do, but more efficient. > > This is something that do all the time. Am I the only one? >
Will one of the stack functions do? I take it your a looks something like a = [np.arange(1000), np.arange(1000), np.arange(1000)] np.all(np.vstack(a) == np.concatenate([a_[None] for a_ in a])) # True It's about the same speed-wise as concatenate, but it's more terse and faster than np.array if you already have a list of arrays. Skipper _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
