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Refactor BHMM core into separate repo from spectroscopic analysis using BHMMs? #40
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Splitting the sklearn question off to #42 |
I'm finally back to working on this again. Did we want to proceed with keeping BHMM-only functionality in this repo and splitting out force spectroscopy stuff into, say, If so, I can do that today. |
Yes please! Thank you. Am 23/06/15 um 16:20 schrieb John Chodera:
Prof. Dr. Frank Noe Phone: (+49) (0)30 838 75354 Mail: Arnimallee 6, 14195 Berlin, Germany |
I'll start doing this separation, because we need it for pyemma. |
Sorry about the delay here. Are you doing this now? Otherwise, I can tackle it right now. My plan was to just peel out the force spectroscopy stuff into a separate repo |
Or did you mean that you needed some other components that aren't here already for |
OK, if you can do it please go ahead. I am not very familiar how to Apparently bhmm is currently so large (several hundreds of MB - there is Everything else can be split off into bhmm-force-spectroscopy (I have Thanks! Am 08/07/15 um 19:26 schrieb John Chodera:
Prof. Dr. Frank Noe Phone: (+49) (0)30 838 75354 Mail: Arnimallee 6, 14195 Berlin, Germany |
OK, I'll take care of this in a few min. |
Do you think the size of the commit history for |
yes, better! I think there's something like git subtree to do that (and Am 08/07/15 um 19:47 schrieb John Chodera:
Prof. Dr. Frank Noe Phone: (+49) (0)30 838 75354 Mail: Arnimallee 6, 14195 Berlin, Germany |
OK, stay tuned. |
First try didn't work. Trying a new approach based on this: |
OK, it finally worked, using this strategy: |
Great, thank you!!! The new repo bhmm-force-spectroscopy-manuscript still contains the bhmm Am 09/07/15 um 06:31 schrieb John Chodera:
Prof. Dr. Frank Noe Phone: (+49) (0)30 838 75354 Mail: Arnimallee 6, 14195 Berlin, Germany |
I think so. I think I can expunge the bhmm/ history from that repo so we
can keep them separate.
I agree that we should make a new bhmm release and the import the bhmm
package into the force spectroscopy code, but I would like to put the force
spectroscopy specific code into a module to make it easier for people to
perform their own analyses and avoid code duplication. I can do the
tinkering to make this work.
I struggled go try to get Travis working again for the bhmm repo, so there
may still be things we need to do to get everything working again.
|
Am 09/07/15 um 12:24 schrieb John Chodera:
Prof. Dr. Frank Noe Phone: (+49) (0)30 838 75354 Mail: Arnimallee 6, 14195 Berlin, Germany |
Conda release package builds occur when PRs are committed into the If we want to cut a new release, we first have to make a GitHub release, then update the conda recipe release information in a PR. Merging the PR (after travis tests to ensure we didn't break package resolution) will cause a package to be built and deployed to binstar. (Make sure not to delete the old packages! We need them for historical reproducibility!)
Still struggling. Not sure if travis is confused by the renaming of repos. |
Hm. It looks like we somehow lost the release history of bhmm in the split: I'm wondering if I should go back and try to re-do this to try to preserve the release history as well, or if it's OK if I just cut a new release? |
I don't think it matters at this point. No problem for me if you loose Am 09/07/15 um 13:08 schrieb John Chodera:
Prof. Dr. Frank Noe Phone: (+49) (0)30 838 75354 Mail: Arnimallee 6, 14195 Berlin, Germany |
Am 09/07/15 um 13:06 schrieb John Chodera:
Prof. Dr. Frank Noe Phone: (+49) (0)30 838 75354 Mail: Arnimallee 6, 14195 Berlin, Germany |
OK, travis build is working now (though we will have to see if it passes) and conda recipe for 0.4.0 created. Will update soon. We have to move issues over to the |
Yes, sure. Thanks a lot for your help. Am 09/07/15 um 14:17 schrieb John Chodera:
Prof. Dr. Frank Noe Phone: (+49) (0)30 838 75354 Mail: Arnimallee 6, 14195 Berlin, Germany |
It sounds like @franknoe would like to use the BHMM model estimation core in multiple projects that have nothing to do with spectroscopic analysis, but are instead pure machine learning projects.
The best way to do this is to separate out the BHMM model estimation core into a separate repository (or extract the single-molecule spectroscopy parts into another project).
This could optimally be made compatible with scikit-learn, which seems to be the modern way new machine learning codes are written.
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