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Change m1 to a1, and mN (or mT) to aT, as per manuscript
Test if package installs okay and vignette can be seen
You should be able to install the package and run the vignette. See the README file here for instructions.....
https://github.com/andrew-edwards/eDNAcutoff
This repo is public but shouldn't make much sense to anyone without the manuscript (which is private) - having it public does make testing easier.
Okay, let me know if anything works! The structure is all set up nicely so it should be relatively easy to add new methods etc., in conjunction with updating the manuscript.
If the vignette doesn't work then you probably won't get too far - just let me know (here).
Making vignette automatically viewable
Maybe try this (and put a short example in the readme):
What about My Vignettes?
So how should you make your vignettes available to the public? What I’ve done is commit both the .rmd and generated .html file to my GitHub repository. GitHub won’t directly render the .html file, but you can use the GitHub HTML Preview service. Basically, you just give it the url of your html file from your GitHub and it will render it. For instance, here is the preview of my html vignette:
Generalise code (and write up) to allow more than one mock sample
Next steps to get package working
- Do simple example as a unit test
- Do complex example (anonymise the species) as a unit test
- Write a vignette
- Add test for change_alpha
- Change terminology (mock etc.) as per andrew-edwards/eDNA-filter#17
- Add README.Rmd to make README.md
- Get Travis running to check commits don't break anything
- Do a check() to check submittable to CRAN down the road
- Get someone to test a download
Vignette not working with install(build_vignettes = TRUE)
Clean R session, this works:
load_all()
build_vignettes()
but
install(build_vignettes = TRUE)
fails and can't find small_example
.
Once manuscript essentially finalised
- Add any table numbers to dataset descriptions in
R/data.R
Make big_example_result.csv in data-raw/
Verify that big_example_result matches Davon's manual calculation
A while back https://github.com/andrew-edwards/eDNA-filter/commit/733b7b7d0cf13fa51c351dd6bb29f6a2db7f4813 Davon confirmed that my result from the function matched hers. Need to double check that again (as it's not clear when or what I gave her), and then it will be automatic in the unit test.
Create a function to highlight which were set to zeros
Can't just do
> small_removed <- remove_false_pos(small_example)
> small_removed - small_example
because the first column contains characters:
> small_removed
# A tibble: 4 x 8
Sample m1 m2 m3 m4 `1` `2` `3`
<chr> <int> <int> <int> <int> <int> <int> <int>
1 mock 257329 169668 79560 47859 0 17 0
2 1 0 0 0 0 42 17 61802
3 2 0 0 0 0 43997 10 17
4 3 0 0 0 0 26 0 22621
So function just needs to remove first column, do the difference, then put the first column back in again. Presumably something like
res <- dplyr::select(input, -1) - dplyr::select(output, -1)
res <- cbind(dplyr::select(input, 1), res) # or dplyr version of cbind
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