ClusterApp: A Shiny Application in R

JohannaMz commented 8 months ago

Submitting Author Name: Johanna Märtz Submitting Author Github Handle: !--author1-->@JohannaMz<!--end-author1-- Repository: https://github.com/JohannaMz/ClusterApp Version submitted: 0.0.0.9000 Submission type: Standard Editor: TBD Reviewers: TBD

Archive: TBD Version accepted: TBD Language: en

Paste the full DESCRIPTION file inside a code block below:

Package: ClusterApp
Title: A Shiny R application to guide and streamline cluster studies based
    on GPS data
Version: 0.0.0.9000
Date: 2023-07-15
Authors@R: c(
    person("Johanna", "Märtz", , "johanna@maertz.eu", role = c("cre", "aut"),
           comment = c(ORCID = "0000-0001-9981-0430")),
    person("Aimee", "Tallian", role = c("aut", "ctb")),
    person("Camilla", "Wikenros", role = c("aut", "ctb")),
    person("Rick", "Heeres", role = c("aut", "ctb"))
  )
Description: The Cluster Analysis App is a Shiny App developed for the
    easy and straightforward analysis of GPS collared individuals to
    identify clusters of visits.
License: GPL (>= 3)
URL: https://github.com/JohannaMz/ClusterApp
BugReports: https://github.com/JohannaMz/ClusterApp/issues
Depends: 
    R (>= 2.10)
Imports: 
    bslib,
    config (>= 0.3.1),
    dplyr,
    DT,
    foreign,
    golem (>= 0.4.0),
    hms,
    leaflet,
    lubridate,
    magrittr,
    methods,
    openxlsx,
    readr,
    readxl,
    sf,
    sftrack,
    shiny (>= 1.7.3),
    shinyFiles,
    shinyWidgets,
    stats,
    stringr,
    tidyr,
    tmap,
    utils
Suggests: 
    knitr,
    rmarkdown,
    shinytest2,
    testthat
VignetteBuilder: 
    knitr
Config/testthat/edition: 3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3

Scope

Please indicate which category or categories from our package fit policies this package falls under: (Please check an appropriate box below. If you are unsure, we suggest you make a pre-submission inquiry.):
- [ ] data retrieval
- [ ] data extraction
- [ ] data munging
- [ ] data deposition
- [ ] data validation and testing
- [ x] workflow automation
- [ ] version control
- [ ] citation management and bibliometrics
- [ ] scientific software wrappers
- [ ] field and lab reproducibility tools
- [ ] database software bindings
- [ ] geospatial data
- [ ] text analysis
Explain how and why the package falls under these categories (briefly, 1-2 sentences): The 'ClusterApp' is developed to facilitate the cluster analysis of GPS data. Automated workflows, as implemented in this Shiny App, decreases the chance for error during field data collection, allows projects to maintain methods across personnel and seasons, and makes field methodology transparent and reproducible.
Who is the target audience and what are scientific applications of this package? Mainly fieldworkers, repeatedly executing cluster analysis of GPS data, to visit clusters of acitvity in the field. Researches will profit from having a transparent and reproducible method description of how GPS clusters were identified.
Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category? As far as we know, only the package "GPSeqClus" by Clapp et al. (2023) applies sequential clustering algorithm to GPS data. This method however differs from the method that we used for clustering GPS data. The strength of our package furthermore lies in the fact that it is packed as a ShinyApp which facilitates user implementation immensly.
(If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research? Yes
If you made a pre-submission inquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted.
Explain reasons for any pkgcheck items which your package is unable to pass. The function run_app does not include a return value or example as it is an inherent function to shiny apps. I still changed the documentation for it to be included, but do not understand why the checks still call an error on these two missing. Furthermore, I was struggling with implementing a testing structure with golem+shinytest2, since one of their latest updates. Therefore the package coverage tests fail and I have not found a way to fix this problem. I am happy for any help!

Technical checks

Confirm each of the following by checking the box.

[x ] I have read the rOpenSci packaging guide.
[ x] I have read the author guide and I expect to maintain this package for at least 2 years or to find a replacement.

This package:

[ x] does not violate the Terms of Service of any service it interacts with.
[ ] has a CRAN and OSI accepted license.
[x ] contains a README with instructions for installing the development version.
[ x] includes documentation with examples for all functions, created with roxygen2.
[ x] contains a vignette with examples of its essential functions and uses.
[x ] has a test suite.
[ ] has continuous integration, including reporting of test coverage.

Publication options

[x ] Do you intend for this package to go on CRAN?
[ ] Do you intend for this package to go on Bioconductor?
[ x] Do you wish to submit an Applications Article about your package to Methods in Ecology and Evolution? If so:

MEE Options

- [x ] The package is novel and will be of interest to the broad readership of the journal. - [x ] The manuscript describing the package is no longer than 3000 words. - [ x] You intend to archive the code for the package in a long-term repository which meets the requirements of the journal (see [MEE's Policy on Publishing Code](http://besjournals.onlinelibrary.wiley.com/hub/journal/10.1111/(ISSN)2041-210X/journal-resources/policy-on-publishing-code.html)) - (*Scope: Do consider MEE's [Aims and Scope](http://besjournals.onlinelibrary.wiley.com/hub/journal/10.1111/(ISSN)2041-210X/aims-and-scope/read-full-aims-and-scope.html) for your manuscript. We make no guarantee that your manuscript will be within MEE scope.*) - (*Although not required, we strongly recommend having a full manuscript prepared when you submit here.*) - (*Please do not submit your package separately to Methods in Ecology and Evolution*)

Code of conduct

[ x] 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 commented 8 months ago

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

ropensci-review-bot commented 8 months ago

:rocket:

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.

:wave:

ropensci-review-bot commented 8 months ago

Checks for ClusterApp (v0.0.0.9000)

git hash: 3d80ab75

:heavy_check_mark: Package name is available
:heavy_check_mark: has a 'codemeta.json' file.
:heavy_check_mark: has a 'contributing' file.
:heavy_check_mark: uses 'roxygen2'.
:heavy_check_mark: 'DESCRIPTION' has a URL field.
:heavy_check_mark: 'DESCRIPTION' has a BugReports field.
:heavy_check_mark: Package has at least one HTML vignette
:heavy_multiplication_x: These functions do not have examples: [run_app].
:heavy_check_mark: Package has continuous integration checks.
:heavy_multiplication_x: Package coverage failed
:heavy_check_mark: R CMD check found no errors.
:heavy_check_mark: R CMD check found no warnings.
:eyes: Function names are duplicated in other packages

Important: All failing checks above must be addressed prior to proceeding

(Checks marked with :eyes: may be optionally addressed.)

Package License: GPL (>= 3)

1. Package Dependencies

Details of Package Dependency Usage (click to open)

The table below tallies all function calls to all packages ('ncalls'), both internal (r-base + recommended, along with the package itself), and external (imported and suggested packages). 'NA' values indicate packages to which no identified calls to R functions could be found. Note that these results are generated by an automated code-tagging system which may not be entirely accurate. |type |package | ncalls| |:----------|:------------|------:| |internal |base | 224| |internal |ClusterApp | 25| |internal |graphics | 3| |imports |magrittr | 67| |imports |stats | 55| |imports |dplyr | 42| |imports |shiny | 40| |imports |sf | 18| |imports |tmap | 9| |imports |DT | 7| |imports |golem | 4| |imports |leaflet | 4| |imports |readr | 4| |imports |sftrack | 4| |imports |openxlsx | 3| |imports |tidyr | 3| |imports |readxl | 2| |imports |utils | 2| |imports |bslib | 1| |imports |hms | 1| |imports |lubridate | 1| |imports |methods | 1| |imports |config | NA| |imports |foreign | NA| |imports |shinyFiles | NA| |imports |shinyWidgets | NA| |imports |stringr | NA| |suggests |knitr | NA| |suggests |rmarkdown | NA| |suggests |shinytest2 | NA| |suggests |testthat | NA| |linking_to |NA | NA| Click below for tallies of functions used in each package. Locations of each call within this package may be generated locally by running 's <- pkgstats::pkgstats()', and examining the 'external_calls' table.

base

list (116), c (42), as.character (5), as.numeric (5), colnames (5), paste (5), dirname (4), class (3), for (3), Negate (3), nrow (3), as.factor (2), data.frame (2), drop (2), lapply (2), options (2), unique (2), url (2), as.POSIXct (1), basename (1), date (1), Find (1), format (1), if (1), is.na (1), is.null (1), mapply (1), message (1), paste0 (1), seq_along (1), strftime (1), strsplit (1), sum (1), Sys.Date (1)

magrittr

%>% (67)

stats

ts (44), filter (10), aggregate (1)

dplyr

n (41), mutate (1)

shiny

reactive (16), checkboxGroupInput (7), column (7), radioButtons (4), reactiveValues (3), eventReactive (2), dateRangeInput (1)

ClusterApp

app_server (1), app_sys (1), app_ui (1), cluster_analysis (1), col_1 (1), col_10 (1), col_12 (1), col_2 (1), col_3 (1), col_4 (1), col_6 (1), col_8 (1), display (1), drop_nulls (1), enurl (1), get_golem_config (1), golem_add_external_resources (1), jq_hide (1), list_to_li (1), list_to_p (1), make_action_button (1), named_to_li (1), rep_br (1), run_app (1), rv (1)

sf

st_as_sf (13), st_as_text (1), st_buffer (1), st_crs (1), st_join (1), st_union (1)

tmap

tm_fill (4), tm_dots (2), tm_markers (2), tm_shape (1)

DT

datatable (3), dataTableOutput (2), renderDataTable (2)

golem

add_resource_path (1), bundle_resources (1), favicon (1), with_golem_options (1)

leaflet

hideGroup (2), leafletOutput (1), renderLeaflet (1)

readr

parse_number (2), read_delim (2)

sftrack

as_sftraj (4)

graphics

text (2), title (1)

openxlsx

write.xlsx (3)

tidyr

separate (2), unite (1)

readxl

read_excel (2)

utils

str (1), write.table (1)

bslib

bs_theme (1)

hms

as_hms (1)

lubridate

ymd_hms (1)

methods

is (1)

**NOTE:** Some imported packages appear to have no associated function calls; please ensure with author that these 'Imports' are listed appropriately.

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 12 files) and - 4 authors - 1 vignette - 2 internal data files - 24 imported packages - 1 exported function (median 6 lines of code) - 63 non-exported functions in R (median 3 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 All parameters are explained as tooltips in the locally-rendered HTML version of this report generated by [the `checks_to_markdown()` function](https://docs.ropensci.org/pkgcheck/reference/checks_to_markdown.html) 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 | 12| 65.5| | |files_vignettes | 1| 68.4| | |files_tests | 3| 75.2| | |loc_R | 1237| 73.5| | |loc_vignettes | 142| 37.0| | |loc_tests | 78| 34.2| | |num_vignettes | 1| 64.8| | |data_size_total | 70928| 81.5| | |data_size_median | 35464| 86.5| | |n_fns_r | 64| 64.2| | |n_fns_r_exported | 1| 0.0|TRUE | |n_fns_r_not_exported | 63| 73.5| | |n_fns_per_file_r | 5| 67.5| | |num_params_per_fn | 5| 69.6| | |loc_per_fn_r | 3| 1.1|TRUE | |loc_per_fn_r_exp | 6| 10.5| | |loc_per_fn_r_not_exp | 3| 1.5|TRUE | |rel_whitespace_R | 39| 88.1| | |rel_whitespace_vignettes | 87| 71.2| | |rel_whitespace_tests | 24| 34.2| | |doclines_per_fn_exp | 37| 45.3| | |doclines_per_fn_not_exp | 0| 0.0|TRUE | |fn_call_network_size | 6| 24.8| | ---

2a. Network visualisation

Click to see the interactive network visualisation of calls between objects in package

3. `goodpractice` and other checks

Details of goodpractice checks (click to open)

#### 3a. Continuous Integration Badges [![R-CMD-check.yaml](https://github.com/JohannaMz/ClusterApp/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/JohannaMz/ClusterApp/actions) [![pkgcheck](https://github.com/JohannaMz/ClusterApp/workflows/pkgcheck/badge.svg)](https://github.com/JohannaMz/ClusterApp/actions) **GitHub Workflow Results** | id|name |conclusion |sha | run_number|date | |----------:|:-------------|:----------|:------|----------:|:----------| | 6749397034|pkgcheck |failure |3d80ab | 7|2023-11-03 | | 6749397038|R-CMD-check |success |3d80ab | 54|2023-11-03 | | 6693418645|test-coverage |failure |c89fdf | 37|2023-10-30 | --- #### 3b. `goodpractice` results #### `R CMD check` with [rcmdcheck](https://r-lib.github.io/rcmdcheck/) R CMD check generated the following notes: 1. checking installed package size ... NOTE installed size is 15.1Mb sub-directories of 1Mb or more: doc 8.4Mb help 6.3Mb 2. checking data for non-ASCII characters ... NOTE Note: found 2599 marked UTF-8 strings R CMD check generated the following check_fails: 1. no_import_package_as_a_whole 2. rcmdcheck_non_ascii_characters_in_data 3. rcmdcheck_reasonable_installed_size #### Test coverage with [covr](https://covr.r-lib.org/) ERROR: Test Coverage Failed #### Cyclocomplexity with [cyclocomp](https://github.com/MangoTheCat/cyclocomp) The following functions have cyclocomplexity >= 15: function | cyclocomplexity --- | --- cluster_analysis | 41 app_server | 38 #### Static code analyses with [lintr](https://github.com/jimhester/lintr) [lintr](https://github.com/jimhester/lintr) found the following 366 potential issues: message | number of times --- | --- Avoid 1:nrow(...) expressions, use seq_len. | 3 Avoid library() and require() calls in packages | 1 Avoid using sapply, consider vapply instead, that's type safe | 1 Lines should not be more than 80 characters. | 326 unexpected input | 1 Use <-, not =, for assignment. | 34

4. Other Checks

Details of other checks (click to open)

:heavy_multiplication_x: The following function name is duplicated in other packages: - - `run_app` from apisensr, biodosetools, bSims, cheem, dash, dccvalidator, discoveR, dmdScheme, dragon, estudy2, fdapaceShiny, FielDHub, forecasteR, gravitas, gwpcormapper, INSPECTumours, kesernetwork, neo4r, OpenSpecy, phecodemap, predictoR, regressoR, ReviewR, ShinyItemAnalysis, spinifex, vici, viewpoly, visxhclust

Package Versions

|package |version | |:--------|:--------| |pkgstats |0.1.3.9 | |pkgcheck |0.1.2.10 |

Editor-in-Chief Instructions:

Processing may not proceed until the items marked with :heavy_multiplication_x: have been resolved.

jhollist commented 7 months ago

@JohannaMz Thank you for the submission of ClusterApp. It looks to be a nice application that will help GPS intensive field workflows.

Unfortunately, ClusterApp is out of scope for rOpenSci. In particular, packages that include apps need to provide the means to reproduce interactive workflows (https://devguide.ropensci.org/policies.html#other-scope-considerations). As it stands now, this does not seem to be a option with ClusterApp. If you are able to make changes to the app that 1.) generates reproducible code from the Shiny app and 2) facilitates running the analysis outside of the Shiny App (e.g. within the R Console via functions), a follow up submission could be reconsidered.

Thank you for considering rOpenSci for your application.

jhollist commented 7 months ago

@ropensci-review-bot out of scope

ropensci / software-review