On Wed, Aug 27, 2014 at 10:01 AM, Robert Kern <robert.k...@gmail.com> wrote:
> On Wed, Aug 27, 2014 at 5:44 PM, Jaime Fernández del Río > <jaime.f...@gmail.com> wrote: > > After reading this stackoverflow question: > > > > > http://stackoverflow.com/questions/25530223/append-a-list-at-the-end-of-each-row-of-2d-array > > > > I was reminded that the `np.concatenate` family of functions do not > > broadcast the shapes of their inputs: > > > >>>> import numpy as np > >>>> a = np.arange(6).reshape(3, 2) > >>>> b = np.arange(6, 8) > >>>> np.concatenate((a, b), axis=1) > > Traceback (most recent call last): > > File "<stdin>", line 1, in <module> > > ValueError: all the input arrays must have same number of dimensions > >>>> np.concatenate((a, b[None]), axis=1) > > Traceback (most recent call last): > > File "<stdin>", line 1, in <module> > > ValueError: all the input array dimensions except for the concatenation > axis > > must match exactly > >>>> np.concatenate((a, np.tile(b[None], (a.shape[0], 1))), axis=1) > > array([[0, 1, 6, 7], > > [2, 3, 6, 7], > > [4, 5, 6, 7]]) > > In my experience, when I get that ValueError, it has usually been a > legitimate error on my part and broadcasting would not have > accomplished what I wanted. Typically, I forgot to transpose > something. If we allowed broadcasting, my most common source of errors > using these functions would silently do something unintended. > That makes sense, I kind of figured there had to be a reason. So though it may be beating a dead horse, perhaps adding a `broadcast=False` argument to the function would do the trick? No side effects unless you ask for them, in which case you had it coming... Jaime -- (\__/) ( O.o) ( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus planes de dominación mundial.
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