Hi Olivier, No that does not seem to do anything am I missing another step whereever b is greater than a replace b with a? thanks
On Wed, Dec 7, 2011 at 11:55 AM, Olivier Delalleau <sh...@keba.be> wrote: > It may not be the most efficient way to do this, but you can do: > mask = b > a > a[mask] = b[mask] > > -=- Olivier > > 2011/12/6 questions anon <questions.a...@gmail.com> > >> I would like to produce an array with the maximum values out of many >> (10000s) of arrays. >> I need to loop through many multidimentional arrays and if a value is >> larger (in the same place as the previous array) then I would like that >> value to replace it. >> >> e.g. >> a=[1,1,2,2 >> 11,2,2 >> 1,1,2,2] >> b=[1,1,3,2 >> 2,1,0,0 >> 1,1,2,0] >> >> where b>a replace with value in b, so the new a should be : >> >> a=[1,1,3,2] >> 2,1,2,2 >> 1,1,2,2] >> >> and then keep looping through many arrays and replace whenever value is >> larger. >> >> I have tried numpy.putmask but that results in >> TypeError: putmask() argument 1 must be numpy.ndarray, not list >> Any other ideas? Thanks >> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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