[SciPy-User] stats.pearsonr divide by zero warning
Mon Aug 9 16:48:07 CDT 2010
On Aug 9, 2010, at 3:46 PM, firstname.lastname@example.org wrote:
> On Mon, Aug 9, 2010 at 3:19 PM, Zachary Pincus <email@example.com
> > wrote:
>> I just svn-up'd scipy, and now find that stats.pearsonr is causing
>> divide-by-zero warnings foolishly.
>> the function contains the following stanzas:
>> rs = np.corrcoef(ar,br,rowvar=axisout)
>> t = rs * np.sqrt((n-2) / ((rs+1.0)*(1.0-rs)))
>> prob = distributions.t.sf(np.abs(t),n-2)*2
>> if rs.shape == (2,2):
>> return rs[1,0], prob[1,0]
>> return rs, prob
>> Given that the diagonal of the correlation matrix returned by
>> will *always* be 1s, the t matrix will have divide-by-zero issues on
>> the diagonal, and give inf values -- which get zero values for the t-
>> distribution's survival function, so everything's fine, output-wise.
>> Presumably, though, the t-calculating line should be flanked by err =
>> np.seterr(divide='ignore') / np.seterr(**err), right?
>> Should I add a bug in the tracker? Someone want to just commit this
> I guess you mean spearmanr, pearsonr hasn't been rewritten as far
> as I can see.
Ugh, yes. Fingers typed a different thing than I was thinking!
> The old trick (still used in pearsonr) was to add TINY in the
> calculation of the test statistic.
> Maybe we should add TINY to the diagonal, which would keep a zero
> division warning if any of the series are perfectly correlated.
> seterr is also fine with me.
> a ticket is always good, at least for the record so we know what to
> watch out for. I have warnings turned off globally, so no zero
> division problems for me.
> np.corrcoef might throw a warning if there is zero variance, but I'm
> not sure this applies in this case
>> SciPy-User mailing list
> SciPy-User mailing list
More information about the SciPy-User