[Numpy-discussion] minimal numpy ?

[Robert]

for use in binary distribution where I need only basics and fast 
startup/low memory footprint, I try to isolate the minimal ndarray 
type and what I need..

with "import numpy" or "import numpy.core.multiarray" almost the 
whole numpy package tree is imported, _dotblas  etc.
cxFreeze produces some 10MB numpy baggage (4MB zipped)

yet when copying and using the multiarray DLL only, I can create 
arrays, but he most things fail:

 >>> import multiarray
 >>> x=multiarray.array([5,6])
 >>> x+x
Traceback (most recent call last):
   File "<interactive input>", line 1, in <module>
TypeError: unsupported operand type(s) for +: 'numpy.ndarray' and 
'numpy.ndarray'


while this works:

 >>> b=numpy.core.multiarray.array([3,9])
 >>> b+b
array([ 6, 18])


I added some things from core.__init__.py  like this:

import umath
import _internal # for freeze programs
import numerictypes as nt
multiarray.set_typeDict(nt.sctypeDict)
..


but the problem of failed type self-recognition remains.
What is this? What to do?