RE: [Numpy-discussion] Introduction

[Scott G. <xs...@ya...>]

Hi Perry.

Well, I don't think I've made any progress convincing you that
standardizing what it means to be an interoperable "NDArray"
would be good for me or others in the community, but I do
appreciate you letting me try.


I'll take your suggestion and make my C-API understand a superset
of array types.  I'll wait to see how the tonumarray() thing pans
out.  That might meet all of my practical concerns even if I don't
think it is as elegant of a solution as defining a strong interface.


I'll just respond to the one point below.  If I had to sum up my
argument for why I think separate array implementations could 
(should) be compatible, it is buried in the answer to this question.


>
> >
> > Important Question:  If an NDArray had a typecode (and it was a known
> > string), is it possible to promote it to one of the standard NumArray
> > types?
> >
>
> I think we want to avoid NDArray having any type attribute (Some types
> have subtypes and then the issue gets really messy). We leave it
> to the subclass to address how types will be handled.
> 

Ok that's what you're currently doing, but let me rephrase the question.

  :-)


Given a "leaf type" -- something that is really well specified and very
similar on all modern platforms:

    "Int32"    - not just an arbitrary "Int"
    "Float64"  - not just an arbitrary "Float")


Do you think you could write a general purpose _function_ that converted an
"NDArray" to a full featured "NumArray"?  I know this would be in Python,
but let's pretend it's a C++ prototype to make the types clear:


NumArray NDArray_to_NumArray(NDArray nda, String typecode, Endian end) {
    if (WellKnownLeafTypecodeString(typecode)) {

        /* fill in the blanks here */

        return NumArray(result)
    }

    throw "conversion really is impossible";
}



Cheers and thanks again for your time,
    -Scott Gilbert




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