Hi, On Sun, Sep 9, 2012 at 12:56 AM, nicky van foreest <vanforeest@gmail.com>wrote:

Hi,

I ran the following code:

args = np.array([4,8]) print np.sum( (arg > 0) for arg in args) print np.sum([(arg > 0) for arg in args]) print np.prod( (arg > 0) for arg in args) print np.prod([(arg > 0) for arg in args])

Can't see why someone would write code like above, but anyway: In []: args = np.array([4,8]) In []: print np.sum( (arg > 0) for arg in args) 2 In []: print np.sum([(arg > 0) for arg in args]) 2 In []: print np.prod( (arg > 0) for arg in args) <generator object <genexpr> at 0x062BDA08> In []: print np.prod([(arg > 0) for arg in args]) 1 In []: print np.prod( (arg > 0) for arg in args).next() True In []: sys.version Out[]: '2.7.2 (default, Jun 12 2011, 15:08:59) [MSC v.1500 32 bit (Intel)]' In []: np.version.version Out[]: '1.6.0' My 2 cents, -eat

with this result:

2 1 <generator object <genexpr> at 0x1c70410> 1

Is the difference between prod and sum intentional? I would expect that numpy.prod would also work on a generator, just like numpy.sum.

BTW: the last line does what I need: the product over the truth values of all elements of args. Is there perhaps a nicer (conciser) way to achieve this? Thanks.

Nicky _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion