Fixed paste error in rarefy_even_dept & improved efficiency #1630
Conversation
This file contains 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
fixed the paste mistake in the message for removed samples (there were no space between the names) changed `unlist(data.frame())` for `rep.int()`; faster, uses less memory merge `message` functions added comment for the changes used `@` when possible replaced `badcolumns`with -(1:CN); more straightforward tested everything; all passed
had lots of warnings about `is_true` and `is_false` being deprecated so I changed the syntax for `expect_true` and `expect_false`
merge message to match other messages
|
I did not update the doc of the replace argument though. |
the way I modified it `FALSE wasn't allowed anymore, so fixed that
salix-d
changed the title
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Outdated suggestions cannot be applied.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.
Wanted to fix the message outputting the names of the samples pruned since there was no space between them.
Also made some changes to improve speed and memory usage, mainly :
unlist(data.frame())-->rep.int()andtable()-->tabulate().I added comment in the code for those changes.
Also, merged some
messagefunctions and used@when possible.I tested everything and it all passed; I updated the depricated functions in the tests as well.
With my data (33323 taxa and 384 samples), it's uses half the memory and runs ~28x faster with
replace = FALSEwhich makes it as fast and memory efficient as withreplace = TRUE.edit: I also changed the check for rngseed because it wouldn't let me use 0.