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 > >
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