coincidentally, spark mlib just posted a pull request intended to add support for dense and sparse vectors, looks quite similar. https://github.com/mesos/spark/pull/736. They seem to choose JBlas backing for dense stuff (although at a vector level there's probably not much reason to) and as-is Colt for sparse stuff.
On Fri, Jul 26, 2013 at 5:20 PM, Dmitriy Lyubimov <[email protected]> wrote: > > > > On Fri, Jul 26, 2013 at 5:07 AM, Ted Dunning <[email protected]>wrote: > >> This sounds great in principle. I haven't seen any details yet (haven't >> had time to look). >> >> Is there a strong reason to go with the R syntax for multiplication >> instead >> of the matlab convention that a*b means a.times(b)? >> > > As discussed, but also because matlab style elementwise operators are > impossible to keep at proper precedence level in scala. It kind of has to > start with either '*' or '%' to keep proper precedence, '.*' will not work > unfortunately. And mix along the lines "some of Matlab, some of perhaps > completely something else' does not seem appealing at all. > >
