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. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
