Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Explore using numba and cython #116

Open
hlasimpk opened this issue Aug 15, 2019 · 4 comments
Open

Explore using numba and cython #116

hlasimpk opened this issue Aug 15, 2019 · 4 comments
Assignees

Comments

@hlasimpk
Copy link
Contributor

This should improve speed of code when iterating through lists

@hlasimpk hlasimpk self-assigned this Aug 15, 2019
@fsimkovic
Copy link
Contributor

numba is not really an option unless CCP4 started supporting it. not sure where you'd need cython except for reading files though cctbx is about as good as it gets whilst keeping the Python interface

@fsimkovic
Copy link
Contributor

I think you could gain some performance by

  • caching results. any calculation that is based on some input that might be identical to others could be stored in a cache (see functools.lru_cache). matthews/solvent/lattice scores/etc.

Apart from that you might struggle to keep the ability to distribute calculations both locally and across a cluster

@hlasimpk
Copy link
Contributor Author

Fair point about numba. I thought I might get some performance improvements when looping through results, but this was just something I wanted to explore when I get a little more time rather than a hard plan

@fsimkovic
Copy link
Contributor

had a stab in #117 to improve performance of the lattice search. I noticed that functools.lru_cache is not available until py3+ so you're stuck until CCP4 finally decide to upgrade their version.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

No branches or pull requests

2 participants