On Tue, Nov 2, 2010 at 10:02 PM, Nikolaus Rath <[email protected]> wrote: > Gerrit Holl <[email protected]> writes: >> On 31 October 2010 17:10, Nikolaus Rath <[email protected]> wrote: >>> Hello, >>> >>> I have a couple of numpy arrays which belong together. Unfortunately >>> they have different dimensions, so I can't bundle them into a higher >>> dimensional array. >>> >>> My solution was to put them into a Python list instead. But >>> unfortunately this makes it impossible to use any ufuncs. >>> >>> Has someone else encountered a similar problem and found a nice >>> solution? Something like a numpy list maybe? >> >> You could try a record array with a clever dtype, maybe? > > It seems that this requires more cleverness than I have... Could you > give me an example? How do I replace l in the following code with a > record array? > > l = list() > l.append(np.arange(3)) > l.append(np.arange(42)) > l.append(np.arange(9)) > > for i in range(len(l)): > l[i] += 32
Depending on how you want to use it, it might be more convenient to use masked arrays or fill with nan (like pandas and larry) to get a rectangular array. it might be more convenient for some things, but if the sizes differ a lot then it might not be more efficient. Josef > > Thanks, > > -Nikolaus > > -- > »Time flies like an arrow, fruit flies like a Banana.« > > PGP fingerprint: 5B93 61F8 4EA2 E279 ABF6 02CF A9AD B7F8 AE4E 425C > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
