On Sat, Jan 21, 2012 at 6:26 PM, John Salvatier <jsalv...@u.washington.edu> wrote: > I ran into this a while ago and was confused why cov did not behave the way > pierre suggested.
same here, When I rewrote scipy.stats.spearmanr, I matched the numpy behavior for two arrays, while R only returns the cross-correlation part. Josef > > On Jan 21, 2012 12:48 PM, "Elliot Saba" <staticfl...@gmail.com> wrote: >> >> Thank you Sturla, that's exactly what I want. >> >> I'm sorry that I was not able to reply for so long, but Pierre's code is >> similar to what I have already implemented, and I am in support of changing >> the functionality of cov(). I am unaware of any arguments for a covariance >> function that works in this way, except for the fact that the MATLAB cov() >> function behaves in the same way. [1] >> >> MATLAB, however, has an xcov() function, which is similar to what we have >> been discussing. [2] >> >> Unless you all wish to retain compatibility with MATLAB, I feel that the >> behaviour of cov() suggested by Pierre is the most straightforward method, >> and that if users wish to calculate the covariance of X concatenated with Y, >> then they may simply concatenate the matrices explicitly before passing into >> cov(), as this way the default method does not use 75% more CPU time. >> >> Again, if there is an argument for this functionality, I would love to >> learn of it! >> -E >> >> [1] http://www.mathworks.com/help//techdoc/ref/cov.html >> [2] http://www.mathworks.com/help/toolbox/signal/ref/xcov.html >> >> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
