Hi all,
I posted on the change in semantics of ndarray.base here:
https://github.com/numpy/numpy/commit/6c0ad59#commitcomment-2153047
And some folks asked me to post my question to the numpy mailing list. I've
implemented a tool for mapping processes in parallel applications to nodes in
cartesian networks. It uses hierarchies of numpy arrays to represent the
domain decomposition of the application, as well as corresponding groups of
processes on the network. You can "map" an application to the network using
assignment of through views. The tool is here if anyone is curious:
https://github.com/tgamblin/rubik. I used numpy to implement this because I
wanted to be able to do mappings for arbitrary-dimensional networks. Blue
Gene/Q, for example, has a 5-D network.
The reason I bring this up is because I rely on the ndarray.base pointer and
some of the semantics in __array_interface__ to translate indices within my
hierarchy of views. e.g., if a value is at (0,0) in a view I want to know that
it's actually at (4,4) in its immediate parent array.
After looking over the commit I linked to above, I realized I'm actually
relying on a lot of stuff that's not guaranteed by numpy. I rely on .base
pointing to its closest parent, and I rely on __array_interface__.data
containing the address of the array's memory and its strides. None of these is
guaranteed by the API docs:
http://docs.scipy.org/doc/numpy/reference/arrays.interface.html
So I guess I have a few questions:
1. Is translating indices between base arrays and views something that would be
useful to other people?
2. Is there some better way to do this than using ndarray.base and
__array_interface__?
3. What's the numpy philosophy on this? Should views know about their parents
or not? They obviously have to know a little bit about their memory, but
whether or not they know how they were derived from their owning array is a
different question. There was some discussion on the vagueness of .base here:
http://thread.gmane.org/gmane.comp.python.numeric.general/51688/focus=51703
But it doesn't look like you're deprecating .base in 1.7, only changing its
behavior, which I tend to agree is worse than deprecating it.
After thinking about all this, I'm not sure what I would like to happen. I can
see the value of not keeping extra references around within numpy, and my
domain is pretty different from the ways that I imagine people use numpy. I
wouldn't have to change my code much to make it work without .base, but I do
rely on __array_interface__. If that doesn't include the address and strides,
t think I'm screwed as far as translating indices go.
Any suggestions?
Thanks!
-Todd
______________________________________________________________________
Todd Gamblin, [email protected], http://people.llnl.gov/gamblin2
CASC @ Lawrence Livermore National Laboratory, Livermore, CA, USA
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