On 1/21/2009 1:27 PM, Neal Becker wrote: > It might if I had used this for all of my c++ code, but I have a big library > of c++ wrapped code that doesn't use pyublas. Pyublas takes numpy objects > from python and allows the use of c++ ublas on it (without conversion).
If you can get a pointer (as integer) to your C++ data, and the shape and dtype is known, you may use this (rather unsafe) 'fromaddress' hack: http://www.mail-archive.com/numpy-discussion@scipy.org/msg04974.html import numpy def fromaddress(address, dtype, shape, strides=None): """ Create a numpy array from an integer address, a dtype or dtype string, a shape tuple, and possibly strides. Make sure dtype is a dtype, not just "f" or whatever. """ dtype = numpy.dtype(dtype) class Dummy(object): pass d = Dummy() d.__array_interface__ = dict( data = (address, False), typestr = dtype.str, descr = dtype.descr, shape = shape, strides = strides, version = 3, ) return numpy.asarray(d) Example: >>> a = numpy.zeros(10) >>> a array([ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]) >>> a.__array_interface__ {'descr': [('', '<f8')], 'strides': None, 'shape': (10,), 'version': 3, 'typestr': '<f8', 'data': (20388752, False)} >>> b = fromaddress(20388752, numpy.float64, (10,)) >>> b array([ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]) >>> b[0] = 1.0 >>> a array([ 1., 0., 0., 0., 0., 0., 0., 0., 0., 0.]) Sturla Molden _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
