luispedro

Numpy arrays come with several reduce operations: sum(), std(), argmin(), min(), ....

The traditional implementation of these suffers from two big problems: It is slow and it often allocates intermediate memory. I have code that is failing with OOM (out of memory) exceptions in calls to ndarray.std(). I regularly handle arrays with 100 million entries (have a couple of million objects * 20 features per object = 100 million doubles), so this is a real problem for me.