On Tue, Jan 29, 2013 at 6:16 AM, denis <denis-bz...@t-online.de> wrote:
> Folks, > the doc for `where` says "x and y need to have the same shape as > condition" > http://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.where.html > But surely > "where is equivalent to: > [xv if c else yv for (c,xv,yv) in zip(condition,x,y)]" > holds as long as len(condition) == len(x) == len(y) ? > And `condition` can be broadcast ? > n = 3 > all01 = np.array([ t for t in np.ndindex( n * (2,) )]) # 000 001 ... > x = np.zeros(n) > y = np.ones(n) > w = np.where( all01, y, x ) # 2^n x n > > Can anyone please help me understand `where` > / extend "where is equivalent to ..." ? > Thanks, > cheers > -- denis > > Do keep in mind the difference between len() and shape (they aren't the same for 2 and greater dimension arrays). But, ultimately, yes, the arrays have to have the same shape, or use scalars. I haven't checked broadcast-ability though. Perhaps a note should be added into the documentation to explicitly say whether the arrays can be broadcastable. Ben Root
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