On Fri, Jun 5, 2015 at 3:11 PM, Paul Appleby <pap@nowhere.invalid> wrote:
> On Fri, 05 Jun 2015 14:55:11 +0200, Todd wrote: > > > Numpy arrays are not lists, they are numpy arrays. They are two > > different data types with different behaviors. In lists, slicing is a > > copy. In numpy arrays, it is a view (a data structure representing some > > part of another data structure). You need to explicitly copy the numpy > > array using the "copy" method to get a copy rather than a view: > > OK, thanks. I see. > > (I'd have thought that id(a[1]) and id(b[1]) would be the same if they > were the same element via different "views", but the id's seem to change > according to rules that I can't fathom.) > > a[1] and b[1] are NOT views. Slices are views, single elements are not. They are numpy scalars, which are immutable, so returning a view wouldn't make sense in such a case since you can't modify it anyway. Taking a slice creates a new view. It is looking at the same underlying data, but it is a new object. So "a[1:] is b[1:]" is False, as is "a[:] is b".
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