On Tue, Feb 28, 2012 at 11:01 PM, Kurt Smith <kwmsm...@gmail.com> wrote: > For an arbitrary numpy array 'a', what does 'a.flags.owndata' indicate?
I think what it really indicates is whether a's destructor should call free() on a's data pointer. > I originally thought that owndata is False iff 'a' is a view. But > that is incorrect. > > Consider the following: > > In [119]: a = np.zeros((3,3)) > > In [120]: a.flags.owndata # should be True; zeros() creates and > returns a non-view array. > Out[120]: True > > In [121]: a_view1 = a[2:, :] > > In [122]: a_view1.flags.owndata # expected to be False > Out[122]: False > > In [123]: a_fancy1 = a[[0,1], :] > > In [124]: a_fancy1.flags.owndata # expected to be True, a_fancy1 is a > fancy-indexed array. > Out[124]: True > > In [125]: a_fancy2 = a[:, [0,1]] > > In [126]: a_fancy2.flags.owndata # expected to be True, a_fancy2 is a > fancy-indexed array. > Out[126]: False > > So when I query an array's flags.owndata, what is it telling me? What > I want to know is whether an array is a view or not. If flags.owndata > has nothing to do with the 'viewness' of an array, how would I > determine if an array is a view? > > In the previous example, a_fancy2 does not own its data, as indicated > by 'owndata' being False. But when I modify a_fancy2, 'a' is not > modified, as expected, but contrary to what 'owndata' would seem to > indicate. It looks like the fancy indexing code in this case actually creates a new array, and then instead of returning it directly, returns a (reshaped) view on this new array. If you look at a_fancy2.base, you'll see this new array. So: a_fancy2 *is* a view... it's just not a view of 'a'. It's a view of this other array. > If I cannot use flags.owndata, what is a reliable way to determine > whether or not an array is a view? owndata *is* a reliable way to determine whether or not an array is a view; it just turns out that this is not a very useful question to ask. What are you actually trying to do? There's probably another way to accomplish it. -- Nathaniel _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
