On Mon, Oct 28, 2013 at 6:25 AM, Pierre Haessig wrote:
> > a.base
>
> In this document, it is mentionned several time that slicing yields
> "views of the original data", but the .base attribute is not mentionned.
> Should it be or is it out-of-scope of the Indexing guide ?
>
Indeed, that is no
On Mon, Oct 28, 2013 at 1:25 PM, Pierre Haessig
wrote:
>
> Le 28/10/2013 13:40, Robert Kern a écrit :
> > > What I didn't find (by quick googling) is how to access the original
> > > array. Is it possible to access it (with Python code) ?
> >
> > a.base
> Thanks! Is there a specific paragraph I mi
Le 28/10/2013 13:40, Robert Kern a écrit :
> > What I didn't find (by quick googling) is how to access the original
> > array. Is it possible to access it (with Python code) ?
>
> a.base
Thanks! Is there a specific paragraph I missed in the user guide ?
I had googled "numpy access original array"
On Mon, Oct 28, 2013 at 12:37 PM, Pierre Haessig
wrote:
> What I didn't find (by quick googling) is how to access the original
> array. Is it possible to access it (with Python code) ?
a.base
--
Robert Kern
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Hi,
Along the line of what David said, I just looked at the flags :
a = np.arange(10)
a.flags
[...]
OWNDATA : True
a = a[:3]
a.flags
[...]
OWNDATA : False
Indeed, after a=a[:3], a is not the same Python object but still points
to the data of the first object.
What I didn't find (by q
On 28 October 2013 03:13, Georgios Exarchakis wrote:
> If yes then how do you release memorry by slicing away parts of an array?
An array is a single Python object. In your example, there is always one
reference pointing to the array (either the whole array or only a view), so
the memory cannot
Hi,
I am using numpy with ipython from anaconda and I observe the following
behavior:
Python 2.7.5 |Anaconda 1.7.0 (64-bit)| (default, Jun 28 2013, 22:10:09)
Type "copyright", "credits" or "license" for more information.
IPython 1.0.0 -- An enhanced Interactive Python.
? -
