3 comments

[ 4.0 ms ] story [ 14.4 ms ] thread
Theres a good (if slightly out of date) comparison between the features for ODE solving, putting DifferentialEquations.jl against the suites commonly used in other langauges: http://www.stochasticlifestyle.com/comparison-differential-e... (linked in the blog as well)

Worth checking out.

________________________________________________

Edit: Nevermind, its not out of date

Interesting write up! Hope this can incentivize python/r users to give Julia a try.

I'd be curious to see if there is any progress on the matlab interoperability as well (my field is mostly matlab).

The problem is that mexjulia is the established package for those bindings, but it needs an update for newer versions of MATLAB (https://github.com/twadleigh/mexjulia/issues/58) which won't happen because the author moved on (https://github.com/twadleigh/mexjulia#mexjulia-embedding-jul...). If anyone is willing to put time into building/maintaining the binding libraries I'd be willing to use them. The issue is that, for any non-OSS language, the essential tooling (CI, benchmarking, accessibility) are absent, making it hard to maintain bindings for.