This repository was archived by the owner on Apr 11, 2023. It is now read-only.
Add vectorize option for Numpy arraywise evaluation of like/prior - #6
Open
lpsinger wants to merge 1 commit into
Open
Add vectorize option for Numpy arraywise evaluation of like/prior#6lpsinger wants to merge 1 commit into
lpsinger wants to merge 1 commit into
Conversation
This behaves exactly the same as the `vectorize` option from `emcee.EnsembleSampler`.
Owner
|
Thanks for the PR, and I apologise for how long it's taken me to respond. I'm currently refactoring ptemcee to make it a little more robust and maintainable, so I'll merge this once the dust has settled. |
Author
|
You're welcome. I was just working on getting the unit tests to pass, but if you are making a bunch of other changes at the moment, I'll wait. |
Author
|
Any update? |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
This behaves exactly the same as the
vectorizeoption fromemcee.EnsembleSampler.