On Wed, Aug 12, 2009 at 7:24 AM, Keith Goodman<kwgood...@gmail.com> wrote: > On Wed, Aug 12, 2009 at 1:31 AM, Lars > Bittrich<lars.bittr...@googlemail.com> wrote: >> Hi, >> >> 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 [1]:import numpy >> >> In [2]:numpy.__version__ >> Out[2]:'1.4.0.dev7301' >> >> In [3]:numpy.identity?? >> [...] >> def identity(n, dtype=None): >> """ >> [...] >> """ >> a = array([1]+n*[0],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 >> identity? > > 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.
Here's the ticket: http://projects.scipy.org/numpy/ticket/1193 BTW, a fast eye function is already in svn. But identity, having fewer options, is a tiny bit faster. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
