Hi,

depending on the needs you have you might be interested in my "minimal

implementation" of what I call a

mock-ndarray.

I needed somthing like this to analyze higher dimensional stacks of 2d

images and what I needed was mostly the indexing features of

nd-arrays.

A mockarray is initialized with a list of nd-arrays. The result is a

mock array having one additional dimention "in front".

>>> a = N.arange(9)

>>> b = N.arange(9)

>>> a.shape=3,3

>>> b.shape=3,3

>>> c = F.mockNDarray(a,b)

>>> c.shape

(2, 3, 3)

>>> c[2,2,2]

>>> c[1,2,2]

8

No memory copy is done.

I put the module file here

http://drop.io/kpu4bib/asset/mockndarray-pyOtherwise this is part of my (BSD) "Priithon" image analysis framework.

Regards

Sebastian Haase

On Wed, Sep 2, 2009 at 11:31 AM, "V. Armando Solé"<

[hidden email]> wrote:

> Citi, Luca wrote:

>> As Gaël pointed out you cannot create A, B and then C

>> as the concatenation of A and B without duplicating

>> the vectors.

>>

>> But you can still re-link A to the left elements

>> and B to the right ones afterwards by using views into C.

>>

>

> Thanks for the hint. In my case the A array is already present and the

> contents of the B array can be read from disk.

>

> At least I have two workarounds making use of your suggested solution of

> re-linking:

>

> - create the C array, copy the contents of A to it and read the contents

> of B directly into C with duplication of the memory of A during some time.

>

> - save the array A in disk, create the array C, read the contents of A

> and B into it and re-link A and B with no duplication but ugly.

>

> Thanks,

>

> Armando

>

>

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