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Date: Fri, 05 Jun 2015 06:23:53 -0700
From: Gary Herron <gary.herron@islandtraining.com>
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On 06/05/2015 06:11 AM, Paul Appleby 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.)
Nope.  It's odder than that.  a[1] is still a view into the inderlying 
numpy array, and your id is the id of that view. Each such index 
produces a new such view object.  Check this out:

 >>> import numpy
 >>> a = numpy.array([1,2,3])
 >>> id(a[1])
28392768
 >>> id(a[1])
28409872

This produces two different view of the same underlying object.

Gary Herron