Wed Aug 12 09:24:36 CDT 2009
On Wed, Aug 12, 2009 at 1:31 AM, Lars
> a colleague made me aware of a speed issue with numpy.identity. Since he was
> using numpy.diag(numpy.ones(N)) before, he expected identity to be at least as
> fast as diag. But that is not the case.
> We found that there was a discussion on the list (July, 20th; "My identity" by
> Keith Goodman). The presented solution was much faster. Someone wondered if
> the change was already made in the svn.
> But I got something different:
> In :import numpy
> In :numpy.__version__
> In :numpy.identity??
> def identity(n, dtype=None):
> a = array(+n*,dtype=dtype)
> b = empty((n,n),dtype=dtype)
> # Note that this assignment depends on the convention that since the a
> # array is shorter than the flattened b array, then the a array will
> # be repeated until it is the appropriate size. Given a's construction,
> # this nicely sets the diagonal to all ones.
> b.flat = a
> return b
> instead of (mail by Keith Goodman):
> def myidentity(n, dtype=None):
> a = zeros((n,n), dtype=dtype)
> a.flat[::n+1] = 1
> return a
> Did I look at the wrong place or is there a reason to keep the slow version of
Things tend to get lost on the mailing list. The next step would be to
file a ticket on the numpy trac. (I've never done that) That would
increase the chance of someone important taking a look at it.
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