[Numpy-discussion] numpy.mean still broken for large float32 arrays

[Alan G Isaac]

On 7/24/2014 5:59 AM, Eelco Hoogendoorn wrote to Thomas:
> np.mean isn't broken; your understanding of floating point number is.


This comment seems to conflate separate issues:
the desirable return type, and the computational algorithm.
It is certainly possible to compute a mean of float32
doing reduction in float64 and still return a float32.
There is nothing implicit in the name `mean` that says
we have to just add everything up and divide by the count.

My own view is that `mean` would behave enough better
if computed as a running mean to justify the speed loss.
Naturally similar issues arise for `var` and `std`, etc.
See http://www.johndcook.com/standard_deviation.html
for some discussion and references.

Alan Isaac