On Sun, Jul 29, 2012 at 8:27 AM, Jeffrey <zfyuan@mail.ustc.edu.cn> wrote:
Thanks eat. I found the reason is that numpy.sqrt cannot deal with too large number. When calculating kendalltau, assume n=len(x),then the total pair number is 'tot' below:
tot=(n-1)*n//2
when calculating tau, the de-numerator is as below:
np.sqrt((tot-u)*(tot-v))
u and v stands for ties in x[] and y[perm[]], which is zero if the two array sample from continuous dist. Hence (tot-u)*(tot-v) may be out of range for the C written ufunc 'np.sqrt', and an Error is then raised.
What about using math.sqrt here, or multiply two np.sqrt in the de-numerator? Since big data sets are often seen these days.
It seems like the bug is that np.sqrt is raising an AttributeError on valid input... can you give an example of a value that np.sqrt fails on? Like
np.sqrt(<something>) AttributeError
-n