[ezquerra]

I am one of the Arraymancer contributors. I believe that what mratsim (Arraymancer’s creator) has done is pretty amazing but I agree that the scope is a quite ambitious. There’s been some talk about separating the deep learning bits into its own library (which I expect would be done in a backwards compatible way). Recently we worked on adding FFT support but instead of adding it to Arraymancer it was added to “impulse” (https://github.com/SciNim/impulse) which is a separate, signal processing focused library. There is also Vindaar’s datamancer (a pandas like dataframe library) and ggplotnim (a plotting library inspired by R’s ggplot). The combination of all of these libraries makes nim a very compelling language for signal processing, data science and ML.

Personally I’d like Arraymancer to be a great tensor library (basically a very good and ideally faster alternative to numpy and base Matlab). Frankly I think that it’s nearly there already. I’ve been using Arraymancer to port a 5G physical layer simulator from Matlab to nim and it’s been a joy. It’s not perfect by any means but it’s already very good. And given how fast nim’s scientific ecosystem keeps improving it will only get much better.