It should never do some black magic without telling you. People are concerned by memory consumption, so if you use more memory than what you think, you can encounter bugs. Least surprise is always better ;)
Matthieu 2008/9/3, Hanni Ali <[EMAIL PROTECTED]>: > Sebastian you legend, that seems to be it. > > Thank you very much. > > >>> matrix.mean(dtype='float64') > 0.41582015156745911 > > What seems odd is that numpy doesn't do this on it's own... > > > > 2008/9/3 Sebastian Stephan Berg <[EMAIL PROTECTED]> > > > Hi, > > > > just guessing here. But numarray seems to calculate the result in a > > bigger dataype, while numpy uses float32 which is the input arrays size > > (at least I thought so, trying it confused me right now ...). In any > > case, maybe the difference will be gone if you > > use .mean(dtype='float64') (or whatever dtype numarray actually uses, > > which seems to be "numarray.MaximumType(a.type())" where > a is the array > > to take the mean). > > > > Sebastian > > > > > > > > > > _______________________________________________ > > Numpy-discussion mailing list > > Numpy-discussion@scipy.org > > > http://projects.scipy.org/mailman/listinfo/numpy-discussion > > > > > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > > -- French PhD student Information System Engineer Website: http://matthieu-brucher.developpez.com/ Blogs: http://matt.eifelle.com and http://blog.developpez.com/?blog=92 LinkedIn: http://www.linkedin.com/in/matthieubrucher _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
