Hello,
Just thinking. If the parameters are limited, you may be able to use the
histogram feature? Doing one histogram with Y as weights, then one
without weights and calculating the mean from this yourself should be
pretty speedy I imagine. Other then that maybe sorting the whole thing
and then d
Yeah, I memory wise it doesn't matter to sum to a double, but just
trying around it seems that the mixing of float and double is very slow
(at least on my comp) while if the starting array is already double
there is almost no difference for summing. Generally double precision
calculations should be
Hi,
just guessing here. But numarray seems to calculate the result in a
bigger dataype, while numpy uses float32 which is the input arrays size
(at least I thought so, trying it confused me right now ...). In any
case, maybe the difference will be gone if you
use .mean(dtype='float64') (or whateve
