For an arbitrary numpy array 'a', what does 'a.flags.owndata' indicate? 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. The numpybook's documentation of owndata could perhaps be a bit clearer on the subject: """ OWNDATA (O) the array owns the memory it uses or if it borrows it from another object (if this is False, the base attribute retrieves a reference to the object this array obtained its data from) """ >From my reading, owndata has nothing to do with the 'viewness' of an array. Is this correct? What is the intent of this flag, then? Its wording could perhaps be improved: owndata is True iff (1) the array owns the memory it uses or (2) the array borrows it from another object. The second clause seems to indicate that the array **does not** own its data since it is borrowing it from another object. However, flags.owndata will be true in this case. If I cannot use flags.owndata, what is a reliable way to determine whether or not an array is a view? _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
