-
Notifications
You must be signed in to change notification settings - Fork 0
Generalize functions to include Scikit fingerprints support #1
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
Merged
Conversation
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 join this conversation on GitHub.
Already have an account?
Sign in to comment
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Outdated suggestions cannot be applied.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.
Changed the fingerprint computation code quite a bit.
It now can run with
rdkitas well asscikit-fingerprintstype generators.Some inconsistency between both packages is the use of the term
sparse, which means unfolded fingerprints in rdkit, but scipy.csr formated versions of folded fingerpritns for scikit-fingerprints.Here, I now switched to a general distinction of three categories:
count: True / False --> either counting occurences or simple binary presence/absencereturn_csr: True / False --> when True will return the folded fingerprints in csr formatfolded: True / False --> when False, will not output fixed-sized fingerprints but arrays of integer bits