I wonder if the goals of this addition could be achieved by simply adding an optional `cov` argument to np.corr, which would provide a pre-computed covariance.
Either way, `covcorr` feels like a helper function that could exist in user code rather than numpy proper. On Wed, Oct 26, 2016 at 10:27 AM, Mathew S. Madhavacheril < mathewsyr...@gmail.com> wrote: > Hi all, > > I posted a pull request: > https://github.com/numpy/numpy/pull/8211 > > which adds a function `numpy.covcorr` that calculates both > the covariance matrix and correlation coefficient with a single > call to `numpy.cov` (which is often an expensive call for large > data-sets). A function `numpy.covtocorr` has also been added > that converts a covariance matrix to a correlation coefficent, > and `numpy.corrcoef` has been modified to call this. The > motivation here is that one often needs the covariance for > subsequent analysis and the correlation coefficient for > visualization, so instead of forcing the user to write their own > code to convert one to the other, we want to allow both to > be obtained from `numpy` as efficiently as possible. > > Best, > Mathew > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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