Repository navigation
IMP: Refactor tabulate-seqs visualization - #369
Conversation
|
Code looks good to me, @gregcaporaso would you like to take this for a spin? |
|
Yep, I'll try it out in the next day or two. |
|
This is looking great @Macabe222, thanks for the work on it! Just one request: could you make it so that the Here's my updated test visualization. You can see what I'm referring to with the Aside from that, it's nice and responsive now so this is a great upgrade for large tables. |
|
@gregcaporaso That should be fixed now |
|
Re-tested, and all good. Ready for merge, thanks again @Macabe222! |
…s merge_method (#371) # Description <!-- REQUIRED: Briefly describe this PR, or link the issue it closes. --> Since the refactor in #369, tabulate-seqs rendered only the first member of the --i-taxonomy collection, and it built rows from every sequence regardless of --p-merge-method (only the length statistics used the merged set). Each taxonomy now gets its own Taxon/Confidence columns, prefixed with its collection key when keys are given ('gtdb Taxon', 'silva Taxon'); unkeyed collections keep plain headers for one taxonomy and are numbered ('Taxonomy 1 Taxon', ...) for several. Rows are limited to the features selected by merge_method. Found by @gregcaporaso while comparing GTDB and SILVA taxonomies of the gut-to-soil ASVs; he asked for the fix on a branch. Claude wrote the change and the six new tests, which read the table JSON embedded in index.html (the existing tests check page text and did not catch either regression). This also led to the finding and fixing (by @Oddant1) of rachis-org/rachis#974. # AI Disclosure <!-- REQUIRED: Check exactly one option. --> - [ ] NO AI USED. - [X] AI USED. # AI Usage Details AI detected this issue through some work that I was doing that utilized this. Code, commit message, and tests initially written by Claude. --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com> Co-authored-by: Anthony Simard <als872@nau.edu> Co-authored-by: Oddant1 <oddant1@hotmail.com>
4 participants
Description
Addresses #368
AI Disclosure