Re: [Numpy-discussion] Maximum available dimensions in numpy

For reasons that were laid out when this topic came up a month or so ago (perhaps on another of our infinitude of email lists), I'm opposed to reducing the number of dimensions to even 10. A sizeable chunk of the community does use many dimensions. I routinely use more than 5 dimensions, and I'm pretty good at reducing the number for performance where it's practical. There's an atmospheric sciences tool called vis5d (x,y,z,t,field parameter vector), which shows just how commonly meteorologists use 5 dimensions. I don't think of the atmospheric sciences as being a particularly dimension-heavy group, but you can easily think of adding a few more dimensions that let you choose model runs with varied initial parameters. Try tracking the variables of a complex medical trial in just 5 dimensions. IDL's limit is 7 dimensions, and many don't use it as a result. Having more in our default binary installs is a selling point. This is a pretty limiting change to be suggesting, so if there's a change to be made, it should come only after implementing and benchmarking to see what the actual performance benefits are, and then polling the community. If there is a really big improvement in having 4 or 8 dimensions max, and if "malloc and unlimit everything" isn't fast, then it may be worth supporting low-dim and high-dim versions of the binary installs. But, let's wait until we have more volunteers before doing that. --jh--
participants (1)
-
Joe Harrington