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? _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
