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There is also the xtensor initiative which aims to provide a unified backend for array / statistical computations in C++ and then makes it pretty easy to create
by droelf 8y ago
There is also the xtensor initiative which aims to provide a unified backend for array / statistical computations in C++ and then makes it pretty easy to create bindings to all the data science languages (R, Julia and of course Python). Usually, going to C++ provides a pretty sizeable speedup.
https://github.com/QuantStack/xtensor-r https://github.com/QuantStack/xtensor-r
https://github.com/QuantStack/xtensor https://github.com/QuantStack/xtensor
Disclaimer: I'm one of the core devs.
- claytonjy 8y agoThis is very interesting! Have you gotten any buy-in from the wider R community, is anyone rewriting their packages atop xtensor? Does R 3.5 and ALTREP make such a transition any easier?
- droelf 8y agoI actually can't tell, but it has not yet been significant. It takes quite a bit of time to really get a library like this started. So far we've mostly dealt with people who are using xtensor from C++ or bind it to Python. We've mainly gone through RCpp for the R language, and that has been working great. I don't know about changes in R 3.5 or ALTREP. Is there something we should know/change for it?