Closed Rekyt closed 10 months ago
@Rekyt Thank you for the inquiry! Wanted to at least let you know that I have received this and that it is on my radar. I probably won't have a chance to dig into it until early next week, but hope to have a response to you early in the week.
@Rekyt the other editors and I are discussing your pre-submission and whether it is within rOpenSci scope. Hope to have an answer for you soon.
@Rekyt the other editors and I are discussing your pre-submission and whether it is within rOpenSci scope. Hope to have an answer for you soon.
Alright! Thanks for the update! That was precisely the goal of the pre-submission inquiry 😉
@ropensci-review-bot check package
Thanks, about to send the query.
:rocket:
The following problems were found in your submission template:
:wave:
git hash: 417c058b
Important: All failing checks above must be addressed prior to proceeding
Package License: GPL (>= 2)
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 | 250|
|internal |funbiogeo | 52|
|internal |grid | 1|
|imports |ggplot2 | 40|
|imports |utils | 14|
|imports |terra | 8|
|imports |rlang | 6|
|imports |tidyr | 6|
|imports |scales | 5|
|imports |sf | 3|
|imports |stats | 3|
|imports |tidyselect | 2|
|imports |xfun | NA|
|suggests |ggridges | 1|
|suggests |knitr | NA|
|suggests |mockery | NA|
|suggests |patchwork | NA|
|suggests |rmarkdown | NA|
|suggests |rstudioapi | 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(
drop (30), c (24), lapply (23), colnames (21), by (17), nrow (16), data.frame (10), mean (8), vapply (8), list (7), ncol (7), merge (6), paste0 (6), is.na (5), apply (4), rownames (4), seq (4), unlist (4), as.data.frame (3), ifelse (3), length (3), rowSums (3), character (2), choose (2), class (2), intersect (2), round (2), sapply (2), sum (2), tapply (2), typeof (2), unique (2), as.list (1), cbind (1), for (1), if (1), is.numeric (1), mapply (1), max (1), names (1), paste (1), rep_len (1), scale (1), seq_along (1), stop (1), vector (1)
labels (10), split_species_categories (5), fb_get_trait_coverage_by_site (4), fb_count_sites_by_species (3), fb_count_species_by_trait (3), fb_get_all_trait_coverages_by_site (3), fb_count_species_by_site (2), fb_count_traits_by_species (2), list_common_species (2), check_object_name (1), check_site_locations (1), check_site_species (1), check_species_categories (1), check_species_traits (1), check_threshold_proportion (1), fb_aggregate_site_data (1), fb_cwm (1), fb_filter_sites_by_species_coverage (1), fb_filter_sites_by_trait_coverage (1), fb_filter_species_by_site_coverage (1), fb_filter_species_by_trait_coverage (1), fb_filter_traits_by_species_coverage (1), fb_format_site_locations (1), fb_format_site_species (1), fb_format_species_categories (1), fb_format_species_traits (1), fb_get_environment (1)
aes (9), guide_axis (6), coord_cartesian (4), labs (4), element_blank (3), ggplot (3), sec_axis (3), geom_sf (2), theme (2), facet_wrap (1), geom_point (1), geom_tile (1), scale_y_discrete (1)
data (13), combn (1)
crs (2), values (2), vect (2), as.data.frame (1), extract (1)
sym (6)
pivot_longer (5), pivot_wider (1)
label_percent (5)
st_as_sf (2), st_drop_geometry (1)
proj (2), sd (1)
all_of (2)
stat_density_ridges (1)
unit (1)
base
funbiogeo
ggplot2
utils
terra
rlang
tidyr
scales
sf
stats
tidyselect
ggridges
grid
This package features some noteworthy statistical properties which may need to be clarified by a handling editor prior to progressing.
The package has: - code in R (100% in 39 files) and - 2 authors - 4 vignettes - 4 internal data files - 10 imported packages - 33 exported functions (median 36 lines of code) - 57 non-exported functions in R (median 35 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 | 39| 93.0| | |files_vignettes | 5| 96.9| | |files_tests | 36| 98.6| | |loc_R | 1985| 84.1| | |loc_vignettes | 1025| 91.0| | |loc_tests | 3143| 96.7|TRUE | |num_vignettes | 4| 96.6|TRUE | |data_size_total | 23324| 75.6| | |data_size_median | 3773| 72.7| | |n_fns_r | 90| 73.7| | |n_fns_r_exported | 33| 80.4| | |n_fns_r_not_exported | 57| 71.1| | |n_fns_per_file_r | 1| 19.2| | |num_params_per_fn | 3| 33.6| | |loc_per_fn_r | 35| 81.5| | |loc_per_fn_r_exp | 36| 69.4| | |loc_per_fn_r_not_exp | 35| 82.8| | |rel_whitespace_R | 43| 94.6| | |rel_whitespace_vignettes | 39| 95.4|TRUE | |rel_whitespace_tests | 35| 98.5|TRUE | |doclines_per_fn_exp | 35| 41.9| | |doclines_per_fn_not_exp | 0| 0.0|TRUE | |fn_call_network_size | 73| 73.8| | ---
Click to see the interactive network visualisation of calls between objects in package
goodpractice
and other checks#### 3a. Continuous Integration Badges [![R-CMD-check](https://github.com/FRBCesab/funbiogeo/workflows/R-CMD-check/badge.svg)](https://github.com/frbcesab/funbiogeo/actions) **GitHub Workflow Results** | id|name |conclusion |sha | run_number|date | |----------:|:----------------------------------------------|:----------|:------|----------:|:----------| | 7547814070|pages build and deployment |success |ee68c2 | 99|2024-01-16 | | 7571910781|pages build and deployment with artifacts-next |success |d141a9 | 103|2024-01-18 | | 7571854283|pkgdown |success |629de0 | 309|2024-01-18 | | 7571854275|R-CMD-check |success |629de0 | 349|2024-01-18 | | 7556614575|render-rmarkdown |failure |efa579 | 14|2024-01-17 | | 7571854278|test-coverage |success |629de0 | 337|2024-01-18 | | 7571854280|Update CITATION.cff |success |629de0 | 6|2024-01-18 | --- #### 3b. `goodpractice` results #### `R CMD check` with [rcmdcheck](https://r-lib.github.io/rcmdcheck/) R CMD check generated the following check_fail: 1. no_import_package_as_a_whole #### Test coverage with [covr](https://covr.r-lib.org/) Package coverage: 99.58 #### Cyclocomplexity with [cyclocomp](https://github.com/MangoTheCat/cyclocomp) The following functions have cyclocomplexity >= 15: function | cyclocomplexity --- | --- fb_format_site_locations | 23 fb_format_site_species | 20 fb_format_species_traits | 16 fb_make_report | 16 #### Static code analyses with [lintr](https://github.com/jimhester/lintr) [lintr](https://github.com/jimhester/lintr) found the following 43 potential issues: message | number of times --- | --- Avoid library() and require() calls in packages | 10 Avoid using sapply, consider vapply instead, that's type safe | 2 Lines should not be more than 80 characters. | 12 Use <-, not =, for assignment. | 19
|package |version | |:--------|:--------| |pkgstats |0.1.3.9 | |pkgcheck |0.1.2.11 |
Processing may not proceed until the items marked with :heavy_multiplication_x: have been resolved.
@Rekyt Sorry for the delay in getting back to you!
We have had a chance to take a look and discuss this. I do think funbiogeo is out of scope for geospatial data and mostly out of scope for data munging. However, we do think it is a pretty good fit for the Exploratory Data Analysis (EDA) and Summary Statistics category for statistical software packages.
Given this, I would encourage a statistical software submission in the EDA category.
Most of our checks look good. Only thing you'll need to add if you do move ahead with a full submission is the codemeta.json file. Details on this are on https://devguide.ropensci.org/building.html?q=codemeta#creating-metadata-for-your-package.
Thanks!
@jhollist thanks for your help.
Thanks for the clarification of categories! I didn't realize it could be submitted as a statistical package. In order to proceed to a full submission, should I edit this issue or close this one and open a new one?
Close and open a new one. I'll take care of the first step!
Submitting Author Name: Matthias Grenié Submitting Author Github Handle: !--author1-->@Rekyt<!--end-author1-- Other Package Authors Github handles: (comma separated, delete if none) !--author-others-->@ahasverus<!--end-author-others-- Repository: https://github.com/FRBCesab/funbiogeo Submission type: Pre-submission Language: en
Scope
Please indicate which category or categories from our package fit policies or statistical package categories this package falls under. (Please check an appropriate box below):
Data Lifecycle Packages
[ ] data retrieval
[ ] data extraction
[x] data munging
[ ] data deposition
[ ] workflow automation
[ ] version control
[ ] citation management and bibliometrics
[ ] scientific software wrappers
[ ] field and lab reproducibility tools
[ ] database software bindings
[x] geospatial data
[ ] text analysis
Statistical Packages
[ ] Bayesian and Monte Carlo Routines
[ ] Dimensionality Reduction, Clustering, and Unsupervised Learning
[ ] Machine Learning
[ ] Regression and Supervised Learning
[ ] Exploratory Data Analysis (EDA) and Summary Statistics
[ ] Spatial Analyses
[ ] Time Series Analyses
Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:
The package aims to provide tools to easily visualize, filter, and analyze data in functional ecology and functional biogeography: species-traits matrices, site-species matrices. It can be used both as a pre- and post-processing tool in functional ecology.
If submitting a statistical package, have you already incorporated documentation of standards into your code via the srr package?
Who is the target audience and what are scientific applications of this package?
There are three main targets for the package:
Newcomers to the field of functional ecology (= trait ecology), most packages focus on computing functional diversity indices, but there exists no tool to help provide a standard workflow to guide your analyses. These can be students, researchers, etc.
Experts in functional ecology who are looking for quick and easy visualizations and data exploration tools.
Applied scientists who would like to use the functional approach but are unsure how to proceed and would like some advanced feature like data upscaling.
Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?
To our knowledge, all other packages focus on computing functional diversity indices and creating functional spaces, but none are focused on the steps prior and after these.
N/A
Any other questions or issues we should be aware of?:
N/A