On Wed, Oct 26, 2016 at 11:03 AM, Mathew S. Madhavacheril <
mathewsyr...@gmail.com> wrote:
> On Wed, Oct 26, 2016 at 1:46 PM, Stephan Hoyer <sho...@gmail.com> wrote:
>
>> 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.
>>
>
> That's a fair suggestion which I'm happy to switch to. This eliminates the
> need for two new functions.
> I'll add an optional `cov = False` argument to numpy.corrcoef that returns
> a tuple (corr, cov) instead.
>
>
>>
>> Either way, `covcorr` feels like a helper function that could exist in
>> user code rather than numpy proper.
>>
>
> The user would have to re-implement the part that converts the covariance
> matrix to a correlation
> coefficient. I made this PR to avoid that code duplication.
>
With the API I was envisioning (or even your proposed API, for that
matter), this function would only be a few lines, e.g.,
def covcorr(x):
cov = np.cov(x)
corr = np.corrcoef(x, cov=cov)
return (cov, corr)
Generally, functions this short should be provided as recipes (if at all)
rather than be added to numpy proper, unless the need for them is extremely
common.
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