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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