canaper: Categorical Analysis of Neo- And Paleo-Endemism in R

[joelnitta]

Date accepted: 2022-09-14
Submitting Author: @joelnitta
Other Package Authors: (delete if none) Shawn Laffan (@shawnlaffan)
Repository: https://github.com/joelnitta/canaper
Version submitted: 0.0.1
Submission type: Stats
Badge grade: silver
Editor: @tdhock
Reviewers: @KlausVigo, @luismurao

Due date for @KlausVigo: 2021-11-24

Due date for @luismurao: 2021-12-21
Archive: TBD
Version accepted: TBD

---

• Paste the full DESCRIPTION file inside a code block below:

Package: canaper
Title: Categorical Analysis of Neo- And Paleo-Endemism
Version: 0.0.1
Authors@R: 
    c(
    person(given = "Joel H.",
           family = "Nitta",
           role = c("aut", "cre"),
           email = "joelnitta@gmail.com",
           comment = c(ORCID = "0000-0003-4719-7472")),
    person(given = "Shawn W.",
           family = "Laffan",
           role = c("ctb", "dtc")),
    person(given = "Brent D.",
           family = "Mishler",
           role = c("ctb", "dtc")),
    person(given = "Wataru",
           family = "Iwasaki",
           role = c("ctb"),
           comment = c(ORCID = "0000-0002-9169-9245"))
           )
Description: Provides functions to conduct categorical analysis of neo- and paleo-endemism (CANAPE).
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE, roclets = c ("collate", "namespace", "rd", "roxyglobals::global_roclet", "srr::srr_stats_roclet"))
RoxygenNote: 7.1.2
URL: https://github.com/joelnitta/canaper
BugReports: https://github.com/joelnitta/canaper/issues
Imports: 
    ape,
    assertr,
    assertthat,
    dplyr,
    future.apply,
    phyloregion,
    progressr,
    purrr,
    stats,
    tibble,
    vegan
Suggests: 
    rmarkdown,
    knitr,
    future,
    tictoc,
    patchwork,
    tidyverse,
    testthat (>= 3.0.0),
    roxyglobals (>= 0.2.1),
    stringr,
    magrittr,
    covr,
    picante
Config/testthat/edition: 3
Depends: 
    R (>= 3.5.0)
VignetteBuilder: knitr
Remotes: 
    anthonynorth/roxyglobals

Pre-submission Inquiry

• A pre-submission inquiry has been approved in issue #469

General Information

• Who is the target audience and what are scientific applications of this package?

  • Target audience is evolutionary biologists. Scientific application is the analysis of phylogenetic endemism.

• Paste your responses to our General Standard G1.1 here, describing whether your software is:

  • The first implementation within R of an algorithm which has previously been implemented in other languages or contexts

  • Please include hyperlinked references to all other relevant software: https://github.com/shawnlaffan/biodiverse

• (If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?

  • (Not applicable)

Note also there is a package website available: https://joelnitta.github.io/canaper/

Badging

• What grade of badge are you aiming for? (bronze, silver, gold)

  • Silver, but open to suggestions from the reviewers and editors.

• If aiming for silver or gold, describe which of the four aspects listed in the Guide for Authors chapter the package fulfils (at least one aspect for silver; three for gold)

  • Demonstrates excellence in compliance with multiple standards from at least two broad sub-categories
  • Compliance with a good number of standards beyond those identified as minimally necessary. I am in compliance with most of the standards for "General" and "Dimensionality Reduction, Clustering, and Unsupervised Learning".

Technical checks

Confirm each of the following by checking the box.

• I/we have read the guide for authors and rOpenSci packaging guide.

• I/we have read the Statistical Software Peer Review Guide for Authors.

• I/we have run autotest checks on the package, and ensured no tests fail.

  • autotest hangs (doesn't produce any output after waiting ca. 20 minutes) on most functions. I was only able to use it on cpr_classify_endem().

• The srr_stats_pre_submit() function confirms this package may be submitted.

This package:

• does not violate the Terms of Service of any service it interacts with.
• has a CRAN and OSI accepted license.
• contains a README with instructions for installing the development version.

Publication options

• Do you intend for this package to go on CRAN?

• Do you intend for this package to go on Bioconductor?

  • Also, I intend to submit a paper about this package to Methods in Ecology and Evolution after ROpenSci review.

Code of conduct

• I agree to abide by rOpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.

[ropensci-review-bot]

Thanks for submitting to rOpenSci, our editors and @ropensci-review-bot will reply soon. Type @ropensci-review-bot help for help.

[ropensci-review-bot]

🚀

The following problem was found in your submission template:

• 'author1' variable must be GitHub hanle only ('@myhandle')
  Editors: Please ensure these problems with the submission template are rectified. Package checks have been started regardless.

👋

[ropensci-review-bot]

Checks for canaper (v0.0.1)

git hash: 43a9f0a2

• ✔️ Package name is available
• ✔️ has a 'CITATION' file.
• ✔️ has a 'codemeta.json' file.
• ✔️ has a 'contributing' file.
• ✔️ uses 'roxygen2'.
• ✔️ 'DESCRIPTION' has a URL field.
• ✔️ 'DESCRIPTION' has a BugReports field.
• ✔️ Package has at least one HTML vignette
• ✔️ All functions have examples.
• ✔️ Package has continuous integration checks.
• ✔️ Package coverage is 100%.
• ✔️ R CMD check found no errors.
• ✔️ R CMD check found no warnings.

Package License: MIT + file LICENSE

---

1. rOpenSci Statistical Standards (srr package)

This package is in the following category:

• Dimensionality Reduction, Clustering and Unsupervised Learning

✔️ All applicable standards [v0.1.0] have been documented in this package

Click here to see the report of author-reported standards compliance of the package with links to associated lines of code, which can be re-generated locally by running the srr_report() function from within a local clone of the repository.

---

2. Statistical Properties

This package features some noteworthy statistical properties which may need to be clarified by a handling editor prior to progressing.

Details of statistical properties (click to open)

The package has:

• code in R (100% in 11 files) and
• 1 authors
• 3 vignettes
• 8 internal data files
• 11 imported packages
• 4 exported functions (median 41 lines of code)
• 30 non-exported functions in R (median 7 lines of code)

---

Statistical properties of package structure as distributional percentiles in relation to all current CRAN packages
The following terminology is used:

• loc = "Lines of Code"
• fn = "function"
• exp/not_exp = exported / not exported

The final measure (fn_call_network_size) is the total number of calls between functions (in R), or more abstract relationships between code objects in other languages. Values are flagged as "noteworthy" when they lie in the upper or lower 5th percentile.

measure	value	percentile	noteworthy
files_R	11	59.3
files_vignettes	2	83.0
files_tests	8	85.7
loc_R	650	52.9
loc_vignettes	162	64.9
loc_tests	939	83.5
num_vignettes	3	93.1
data_size_total	66301	81.2
data_size_median	509	59.9
n_fns_r	34	35.6
n_fns_r_exported	4	15.6
n_fns_r_not_exported	30	42.6
n_fns_per_file_r	3	42.7
num_params_per_fn	4	67.6
loc_per_fn_r	10	40.0
loc_per_fn_r_exp	41	75.3
loc_per_fn_r_not_exp	7	29.9
rel_whitespace_R	13	43.9
rel_whitespace_vignettes	0	0.0	TRUE
rel_whitespace_tests	7	84.7
doclines_per_fn_exp	55	68.2
doclines_per_fn_not_exp	0	0.0	TRUE
fn_call_network_size	9	22.0

---

2a. Network visualisation

Interactive network visualisation of calls between objects in package can be viewed by clicking here

---

3. goodpractice and other checks

Details of goodpractice and other checks (click to open)

3a. Continuous Integration Badges

GitHub Workflow Results

name	conclusion	sha	date
pkgdown	success	43a9f0	2021-10-26
R-CMD-check	success	43a9f0	2021-10-26
Render codemeta	failure	43a9f0	2021-10-26
test-coverage	success	43a9f0	2021-10-26

---

3b. goodpractice results

R CMD check with rcmdcheck

rcmdcheck found no errors, warnings, or notes

Test coverage with covr

Package coverage: 100

Cyclocomplexity with cyclocomp

The following functions have cyclocomplexity >= 15:

function	cyclocomplexity
cpr_rand_test	29
calc_biodiv_random	16

Static code analyses with lintr

lintr found the following 353 potential issues:

message	number of times
Lines should not be more than 80 characters.	353

---

Package Versions

package	version
pkgstats	0.0.2.16
pkgcheck	0.0.2.86
srr	0.0.1.120

---

Editor-in-Chief Instructions:

This package is in top shape and may be passed on to a handling editor

[tdhock]

@ropensci-review-bot seeking reviewers

[ropensci-review-bot]

I'm sorry @tdhock, I'm afraid I can't do that. That's something only editors are allowed to do.

[noamross]

@ropensci-review-bot assign @tdhock as editor

[ropensci-review-bot]

Assigned! @tdhock is now the editor

[joelnitta]

I forgot to mention, I plan to submit this as a paper to Methods in Ecology and Evolution after ROpenSci review (have also added this to the original description)

[tdhock]

@ropensci-review-bot assign @KlausVigo as reviewer

[mpadge]

@tdhock Only just realised the command there has the wrong syntax - should be add <@name> to reviewers, like this example. Could you please try again? Nevertheless good that you got this one wrong, because it made us realise we need the bot to tell you it didn't understand. Thanks!