Leginon

I found the following bug report that explains the problem:
http://projects.scipy.org/numpy/ticket/465
Probably float32 will not hold the sum of a very large array.
Unfortunately, the status is "wontfix".

We will have to find a different way to calculate the mean in all of our code. Luckily, we use our own arraystats module in many places, so one change there will fix many instances. A quick grep found about 300 or more calls to mean() in myami that do not use arraystats, so those need to be changed to use arraystats. And std() will need similar fix.
The quick fix is to convert all arrays to float64 before calculating mean/std. This is not optimized for time/memory, so we could also write a mean/std function in numextension that uses a float64 accumulator but can operate on an float32 array. Maybe someone has already done this and we can just use their code.