Closed micha-silver closed 3 months ago
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@micha-silver thanks for your submission! We'll fix this glitch in our system next week.
Hi @maelle : It's good to hear from you. I'll look forward to getting the review underway next week.
Thanks @micha-silver for your submission. As Maëlle has noted our automatic package checker has a glitch, one that we think is a GitLab-related edge case. (We have fewer - totally fine! - submissions from GitLab so the system has had less stress-testing against it).
In the meantime, I've determined that your package is in-scope. From an initial manual check of the repository I note a few important things that that will be required before proceeding to assign an editor and reviewers. It may be worth moving ahead on these while we get the automatic checks going:
release
. (https://devguide.ropensci.org/ci.html)@ropensci-review-bot check package
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Editor check started
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git hash: dd810f2f
Important: All failing checks above must be addressed prior to proceeding
Package License: GPL (>= 3) + file LICENSE
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 | 125|
|internal |rOPTRAM | 20|
|internal |datasets | 1|
|imports |terra | 25|
|imports |utils | 7|
|imports |dplyr | 3|
|imports |sf | 1|
|imports |ggplot2 | NA|
|imports |tools | NA|
|suggests |xml2 | 17|
|suggests |stats | 8|
|suggests |sen2r | 1|
|suggests |geojsonio | NA|
|suggests |testthat | NA|
|suggests |knitr | NA|
|suggests |rmarkdown | 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(
file.path (16), lapply (15), c (13), basename (7), paste (7), strsplit (6), unlist (6), data.frame (5), list.files (5), as.data.frame (4), dir (4), nrow (4), grepl (3), sample (3), as.Date (2), do.call (2), length (2), rbind (2), split (2), t (2), as.character (1), dirname (1), gsub (1), log2 (1), max (1), min (1), package_version (1), paste0 (1), path.expand (1), row.names (1), suppressWarnings (1), Sys.which (1), system.file (1), T (1), try (1)
rast (10), as.data.frame (6), writeRaster (4), ext (3), crs (1), project (1)
calculate_str (6), calculate_vi (5), aoi_to_name (3), check_scihub_access (2), optram_wetdry_coefficients (2), check_aoi (1), optram_calculate_str (1)
read_xml (5), xml_find_first (5), xml_text (5), xml_contents (1), xml_find_all (1)
lm (3), quantile (3), offset (1), step (1)
data (3), vi (3), packageVersion (1)
full_join (3)
iris (1)
check_gcloud (1)
st_read (1)
base
terra
rOPTRAM
xml2
stats
utils
dplyr
datasets
sen2r
sf
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 13 files) and - 1 authors - 1 vignette - no internal data file - 6 imported packages - 15 exported functions (median 42 lines of code) - 21 non-exported functions in R (median 20 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 | 13| 68.2| | |files_vignettes | 2| 85.7| | |files_tests | 11| 91.7| | |loc_R | 759| 60.2| | |loc_vignettes | 142| 37.0| | |loc_tests | 206| 55.5| | |num_vignettes | 1| 64.8| | |n_fns_r | 36| 45.9| | |n_fns_r_exported | 15| 58.5| | |n_fns_r_not_exported | 21| 42.1| | |n_fns_per_file_r | 2| 32.7| | |num_params_per_fn | 4| 54.6| | |loc_per_fn_r | 30| 76.5| | |loc_per_fn_r_exp | 42| 74.5| | |loc_per_fn_r_not_exp | 20| 63.0| | |rel_whitespace_R | 15| 56.6| | |rel_whitespace_vignettes | 23| 25.0| | |rel_whitespace_tests | 16| 47.0| | |doclines_per_fn_exp | 26| 25.3| | |doclines_per_fn_not_exp | 0| 0.0|TRUE | |fn_call_network_size | 20| 46.4| | ---
Click to see the interactive network visualisation of calls between objects in package
goodpractice
and other checks--- #### 3b. `goodpractice` results #### `R CMD check` with [rcmdcheck](https://r-lib.github.io/rcmdcheck/) R CMD check generated the following error: 1. Error in proc$get_built_file() : Build process failed R CMD check generated the following check_fail: 1. no_import_package_as_a_whole #### Test coverage with [covr](https://covr.r-lib.org/) ERROR: Test Coverage Failed #### Cyclocomplexity with [cyclocomp](https://github.com/MangoTheCat/cyclocomp) Error : Build failed, unknown error, standard output: * checking for file ‘roptram/DESCRIPTION’ ... OK * preparing ‘rOPTRAM’: * checking DESCRIPTION meta-information ... OK * installing the package to build vignettes ----------------------------------- * installing *source* package ‘rOPTRAM’ ... ** using staged installation ** R ** inst ** byte-compile and prepare package for lazy loading Error in library(hexSticker) : there is no package called ‘hexSticker’ Error: unable to load R code in package ‘rOPTRAM’ Execution halted ERROR: lazy loading failed for package ‘rOPTRAM’ * removing ‘/tmp/RtmpcVV09j/Rinst1adf150625cf/rOPTRAM’ ----------------------------------- ERROR: package installation failed #### Static code analyses with [lintr](https://github.com/jimhester/lintr) [lintr](https://github.com/jimhester/lintr) found the following 67 potential issues: message | number of times --- | --- Avoid 1:length(...) expressions, use seq_len. | 2 Avoid library() and require() calls in packages | 4 Lines should not be more than 80 characters. | 59 Use <-, not =, for assignment. | 2
|package |version | |:--------|:--------| |pkgstats |0.1.3.9 | |pkgcheck |0.1.2.10 |
Processing may not proceed until the items marked with :heavy_multiplication_x: have been resolved.
Thanks:
* We require that all packages have at least on vignette (https://devguide.ropensci.org/building.html#documentation)
I've written and added an appropriate vignette.
* We also require a CONTRIBUTING.md or similar file to provide guidance to potential package reviewers (https://devguide.ropensci.org/collaboration.html?q=contributing.md#contributing-guide)
Added CONTRIBUTING.md (in
docs
subdir)* We require testing against the current (release), last (oldrel), and development (devel) versions of R, as well as across linux, macos, and windows platforms (usually just on release). We also require coverage reporting of testing. Based on your [.gitlab-ci.yml file](https://gitlab.com/rsl-bidr/roptram/-/blob/main/.gitlab-ci.yml), I think you are only testing on `release`. (https://devguide.ropensci.org/ci.html)
Yes, I have only one CI so far. I'll start preparing tests for additional releases and OS.
Thanks, @micha-silver. Now that we have automated checks, I also see that the repo doesn't show the test coverage (though you may be measuring this locally as I see you have a .covrignore file). Since reviewers may be less familiar with navigation in GitLab, please put badges in your readme to point us to the CI build logs and coverage outputs once those are set up.
Correct, I'm running covr
locally.
My coverage is not good, (about 48%) and I'd like some advice here: I have three main functions that pull down multiple Sentinel 2 or Landsat imagery tiles, over a time span.
optram()
optram_acquire_s2()
optram_landsat
Even if I do a test that limits the time span to one day, it would be > 1GB download for each of these functions. I think that such a big download should not be done in a test. How can I work around this?
This is a common challenge we see. There are several complementary strategies one can take:
ROPTRAM_ALL_TESTS=1
. This would normally be turned off on CI and thus lower coverage would be reported, but that's OK. The test-running procedure should be explained in CONTRIBUTING.md and reviewers will be able to consider it.@noamross : I'm considering migrating the rOPTRAM repo from gitlab to github. I think I'll be able to configure the CI tests more easily on github (lots more examples...). And since most ROpenSci projects are on github, the review process might also be smoother. Shall I go ahead with this? Anything I need to be aware of??
Regarding your explanation above about testing functions with large downloads, I'd like to go with the 4th option, setting a condition, and skipping those tests (with explanation in CONTRIBUTING).
Thanks, Micha
@micha-silver No problem for us if you move to GitHub, though we are happy to do the process either way. We might have to make a tweak so the bot knows that the repository is in a new location, so let us know when you switch.
Hi:
I've made progress with the rOPTRAM
package:
Added examples to all functions
CI tests are now integrated.
covr::package_coverage()
now shows:
r$> covr::package_coverage()
rOPTRAM Coverage: 75.49%
R/optram_acquire_s2.R: 17.86%
R/utilities.R: 85.29%
R/optram_wetdry_coefficients.R: 95.10%
R/optram_ndvi_str.R: 95.12%
R/optram_calculate_str.R: 95.45%
R/optram_soilmoisture.R: 100.00%
(TODO: Still needs to be improved. I've added one addition testthat function to test downloading in the optram_acquire_s2.R
function by limiting the timespan so that only one sentinel tile is downloaded. But that function still has low coverage. )
I run tests on 5 platforms: Windows release, Windows oldrel, Windows devel, MacOS, and Ubuntu. The gitlab-ci.yml
performs these tests by sending to rhub. Here's the summary currently:
platform errors warnings notes
ubuntu-gcc-devel 0 0 0
windows-x86_64-release 0 0 0
windows-x86_64-oldrel 0 0 0
windows-x86_64-devel 0 0 0
macos_release 0 0 11
[1] "2023-11-26 11:21:16.729992 - Check completed"
Here are links to the results: for Ubuntu: for Win release: release for Win devel: for Win oldrel: for Mac macbuilds:
Not sure how long these artifacts are kept on rhub. But the full artifact on gitlab is available: artifacts on gitlab
What's next? Best regards, Micha
Following up: On my local machine I get good coverage:
r$> cvr <- covr::package_coverage()
r$> cvr
rOPTRAM Coverage: 92.70%
R/utilities.R: 85.29%
R/optram_acquire_s2.R: 90.59%
R/optram_wetdry_coefficients.R: 95.10%
R/optram_ndvi_str.R: 95.12%
R/optram_calculate_str.R: 95.45%
R/optram_soilmoisture.R: 100.00%
The explanation: The optram_acquire_s2()
function relies on Google Cloud CLI to download Sentinel images. I have that SDK installed locally, but I have not seen any way to install non-interactively, on a rocker image. There seems to be no work around to get access authentication to Google services, and the gsutil
utility setup in a CI machine. I tried to copy my Google access token into a CI variable, and use that, but there is no way to get gsutil
setup automatically to recognize a username and token. So when I run covr
in gitlab-ci
it skips the whole download procedure, and shows lower coverage.
Hi @micha-silver, thanks for moving a ahead on this. It's good you got to 75% coverage without the gsutil
dependency! I note that https://cloud.google.com/sdk/docs/downloads-interactive#silent to have some guidance for installing on CI services. I'd make good-faith effort with that, but if it is not possible a full description in the install section of the README as well as CONTRIBUTING for those running tests will be sufficient. I note this is one thing that we might ask reviewers to comment on in the next stage - would another dependency be a simpler way to fetch the images?
@noamross I appreciate your encouraging words.
Two comments
It should be fine to present the package in its current state. Let me re-run checks.
@ropensci-review-bot check package
Thanks, about to send the query.
:rocket:
Editor check started
:wave:
git hash: b54b2c5f
Important: All failing checks above must be addressed prior to proceeding
Package License: GPL (>= 3) + file LICENSE
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 | 120|
|internal |rOPTRAM | 19|
|imports |terra | 38|
|imports |sf | 5|
|imports |utils | 4|
|imports |dplyr | 3|
|imports |ggplot2 | NA|
|imports |tools | NA|
|suggests |xml2 | 13|
|suggests |stats | 9|
|suggests |sen2r | 1|
|suggests |geojsonio | NA|
|suggests |lwgeom | NA|
|suggests |knitr | NA|
|suggests |rmarkdown | 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(
lapply (15), c (14), file.path (14), basename (7), paste (7), strsplit (6), unlist (6), data.frame (5), list.files (5), nrow (4), dir (3), sample (3), as.Date (2), do.call (2), drop (2), grepl (2), length (2), rbind (2), split (2), t (2), as.character (1), dirname (1), gsub (1), log (1), log2 (1), max (1), min (1), package_version (1), paste0 (1), row.names (1), suppressWarnings (1), Sys.getenv (1), T (1), try (1), tryCatch (1)
as.data.frame (16), rast (12), writeRaster (4), ext (3), crs (1), mean (1), project (1)
calculate_str (6), calculate_vi (5), aoi_to_name (3), optram_wetdry_coefficients (2), check_aoi (1), check_scihub_access (1), optram_calculate_str (1)
read_xml (5), xml_text (5), xml_contents (1), xml_find_all (1), xml_find_first (1)
lm (3), quantile (3), offset (1), proj (1), step (1)
st_read (3), st_zm (2)
data (3), packageVersion (1)
full_join (3)
check_gcloud (1)
base
terra
rOPTRAM
xml2
stats
sf
utils
dplyr
sen2r
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 11 files) and - 1 authors - 1 vignette - no internal data file - 6 imported packages - 15 exported functions (median 32 lines of code) - 15 non-exported functions in R (median 40 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 | 11| 62.6| | |files_vignettes | 2| 85.7| | |files_tests | 10| 90.7| | |loc_R | 761| 60.3| | |loc_vignettes | 157| 40.5| | |loc_tests | 253| 60.4| | |num_vignettes | 1| 64.8| | |n_fns_r | 30| 40.1| | |n_fns_r_exported | 15| 58.5| | |n_fns_r_not_exported | 15| 32.7| | |n_fns_per_file_r | 2| 25.6| | |num_params_per_fn | 5| 69.6| | |loc_per_fn_r | 37| 83.0| | |loc_per_fn_r_exp | 32| 65.2| | |loc_per_fn_r_not_exp | 40| 86.1| | |rel_whitespace_R | 14| 55.1| | |rel_whitespace_vignettes | 30| 36.6| | |rel_whitespace_tests | 16| 52.0| | |doclines_per_fn_exp | 33| 38.5| | |doclines_per_fn_not_exp | 0| 0.0|TRUE | |fn_call_network_size | 18| 44.2| | ---
Click to see the interactive network visualisation of calls between objects in package
goodpractice
and other checks--- #### 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: 74.44 #### Cyclocomplexity with [cyclocomp](https://github.com/MangoTheCat/cyclocomp) The following functions have cyclocomplexity >= 15: function | cyclocomplexity --- | --- optram_safe | 29 optram_landsat | 20 #### Static code analyses with [lintr](https://github.com/jimhester/lintr) [lintr](https://github.com/jimhester/lintr) found the following 17 potential issues: message | number of times --- | --- Avoid changing the working directory, or restore it in on.exit | 1 Lines should not be more than 80 characters. | 15 Use <-, not =, for assignment. | 1
|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.
I have improved the coverage of optram_acquire_s2()
by moving the actual download code to a separate file, and entering that new file into .covrignore.
CI tests are, if I understand correctly, implemented in the .gitlab-ci.yml
file. In that file I put a rule to run the pipeline manually (to avoid firing off a check at every minor commit). Is that sufficient to fill the requirement for "✖️ Package has no continuous integration checks."?
I also fixed the lintr
comments.
Thanks, for the CI the reason for failure is that we don't yet have a standard way to detect it on GitLab. We'll work on that in the future, both detection and some guidance on how to signal it for non-GitHub users. In the meantime, I'm assigning an editor to get this going!
@ropensci-review-bot assign @adamhsparks as editor
Assigned! @adamhsparks is now the editor
Hi @micha-silver, I'll start looking for reviewers, but in the meantime I've found a few issues that should be corrected before they start their reviews.
`", the proper way to refer to other packages in documentation is either,
\pkg{}or if it's on CRAN,
\CRANpkg{}`. The latter will link to the package docs.spelling::update_wordlist()
to generate a list that will be used to check against but first I check carefully against the list of words it thinks are misspelled and correct any first and then rerun it. To do this you should also set the spelling in your DESCRIPTION file, Spelling: en-US
.
T
and F
, spell out the whole word, please.@noRd
and @keywords Internal
so that they aren't exported and documented. Glancing over them, I'm unsure why a user would call them, but I may just not be familiar enough with the workflow yet.Hello @adamhsparks Thanks for your helpful comments. I've addressed most:
browseVignettes(package = "rOPTRAM")
works as expected. Am I missing something?Hi @micha-silver,
I'll try to answer your queries, if I'm still not providing enough information, please do not hesitate to ask for further clarification.
Traditionally these would be in "inst", e.g., https://github.com/ropensci/nasapower/tree/main/inst/paper. Not in the top level directory of the package.
You have a file, _rOPTRAM.Rmd.orig_, therefore I assumed you were pre-compiling, which given that this package uses Internet resources, is a good idea. However, I do not see the script that you are using to actually compile the .Rmd file of the vignette itself, e.g., https://github.com/ropensci/nasapower/blob/main/vignettes/precompile.R
@adamhsparks :
OK, that's clear now. I've moved the paper into /inst, and added the precompile script as you suggested.
One glitch, maybe you have some idea: I want a tmap image in the vignette (the final code chunk). However when I knit the rOPTRAM.Rmd.orig, I get this error at the end, inside the final compiled rOPTRAM.Rmd:
#> Error in path.expand(path): invalid 'path' argument
and there's no image in the output HTML, just the same error message.
Any ideas?
Thanks, Micha
Hi @micha-silver,
I'm trying to troubleshoot this for you but I'm having difficulties getting everything set up. I think one thing that will be necessary for users of this package will be to have very clear instructions on how to set up the computing environment to use this package as the normal install.packages("rOPTRAM")
won't work here. I've tried to set up the Google tools that are required and have created a new roptram
project but I still get this error in R:
Searching for a valid Google Cloud SDK installation...
No access to Google cloud
Exiting
Warning message:
In normalizePath(path, ...) : path[1]="": No such file or directory
I can get the vignette to properly knit using this code, which avoids using setwd()
so it is portable. This also fixes the output directory, since I don't have a "/home/micha/EO_Data/Israel/Migda_full"
directory to knit into, again, portability.
This assumes that you're using an RStudio Project. If not, I'd suggest using {here} for your directory structure handling rather than using setwd()
.
# vignette that depends on Internet access need to be pre-compiled and takes a
# while to run
library("knitr")
knit("vignettes/rOPTRAM.Rmd.orig", "vignettes/rOPTRAM.Rmd")
# remove file path such that vignettes will build with figures
replace <- readLines("vignettes/rOPTRAM.Rmd")
replace <- gsub("<img src=\"vignettes/", "<img src=\"", replace)
fileConn <- file("vignettes/rOPTRAM.Rmd")
writeLines(replace, fileConn)
close(fileConn)
# build vignette
library("devtools")
build_vignettes()
# move resource files to /docs
resources <-
list.files("vignettes/", pattern = ".png$", full.names = TRUE)
file.copy(from = resources,
to = "docs",
overwrite = TRUE)
It knits, but when I tried to step through the examples, the examples in the vignette don't work for me due to the use of hardcoded directories, once again. Here I used, tempdir()
to fix that and I'm unable to configure my "Google Cloud" environment properly for some reason, so I cannot generate the whole vignette as it should appear.
Maybe this helps you get it to knit properly and will be useful for the reviewers to suggest ways that the documentation can be improved on how to set up the computing environment.
Also, I noted that,
%\VignetteDepends{tmap}
,%\VignetteEngine{knitr::rmarkdown}
not %\VignetteEngine{knitr::rmarkdown_notangle}
, andEverything checks out with the normal editor checks. I'll start looking for reviewers now.
My last commit:
here()
function. (Thanks for saving my computer from being set on fire :-)) by Jenny )gcloud init
to get Google's token installed on their computer. knit
on the rOPTRAM.Rmd.orig file directly to HTML output does produce the inline map image). Best regards,
@micha-silver, I'll have a look tomorrow if I have some time. Thanks for all the effort thus far!
Hi @micha-silver, I would advise against your examples writing to "./inst" in the vignette as you do when saving the data. There is also no need to use {here} in your package (aside from the pre-compile function, which isn't really part of the R package so {here} won't need to be in the DESCRIPTION file anywhere) for these examples, just use tempdir()
for your vignette examples as I previously suggested. You're vignette also indicates in the text that the downloads are saved to tempdir()
whereas you're putting them in "./inst".
Also, there is no need to install {rOPTRAM} in the vignette example. One could assume that the user browsing the documents locally has installed it locally so that they can view the docs locally.
Unfortunately I can't really troubleshoot the map for you since I can't run the functions in the vignette due to difficulties with the Google tools that you require, sorry. Perhaps the reviewers will be able to assist with that.
@adamhsparks Thanks for your patience with this question.
I'm hesitating to use tempdir()
only because the download for each compile of the vignette is around 50GB, and takes around 1.5 hrs. (necessary to get a reasonable/realistic trapezoid from the model). If I define a local, permanent directory for my precompile script, then the package "sees" the files already downloaded from a previous compile, and completes the vignette in a few minutes. If I use tempdir()
then obviously each minor change to the vignette will require a long wait to see the results.
In any case, let's wait for reviewers, and then I'll revisit this issue.
Ah, well, since you’re precompiling and it’s an Rmd, you could use a hidden code chunk to download and knit but display another for the user rather than using tempdir()
for everything. That would be my suggestion. But putting it in “./inst” for the example is poor form, IMO. Use something like “~/Downloads” or the current working directory for the example code shown to the user while you put the real file somewhere else in your local system.
On 6 Dec 2023, at 17:44, Micha Silver @.***> wrote:
@adamhsparks https://github.com/adamhsparks Thanks for your patience with this question.
I'm hesitating to use tempdir() only because the download for each compile of the vignette is around 50GB, and takes around 1.5 hrs. (necessary to get a reasonable/realistic trapezoid from the model). If I define a local, permanent directory for my precompile script, then the package "sees" the files already downloaded from a previous compile, and completes the vignette in a few minutes. If I use tempdir() then obviously each minor change to the vignette will require a long wait to see the results.
In any case, let's wait for reviewers, and then I'll revisit this issue.
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@ropensci-review-bot assign @harryeslick as reviewer
@harryeslick added to the reviewers list. Review due date is 2023-12-29. Thanks @harryeslick for accepting to review! Please refer to our reviewer guide.
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@harryeslick, as discussed, take the time that you need given the holidays coming up
@adamhsparks Thanks for your help in enlisting reviewers. Looking forward to working with @harryeslick
@ropensci-review-bot add @obrl-soil as reviewer
@obrl-soil added to the reviewers list. Review due date is 2023-12-29. Thanks @obrl-soil for accepting to review! Please refer to our reviewer guide.
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Date accepted: 2024-06-05
Submitting Author Name: Micha Silver Submitting Author Github Handle: !--author1-->@micha-silver<!--end-author1-- Other Package Authors Github handles: (comma separated, delete if none) @github_handle1, @github_handle2 Repository: https://gitlab.com/rsl-bidr/roptram Version submitted: 0.0.1.000 Submission type: Standard Editor: !--editor-->@adamhsparks<!--end-editor-- Reviewers: @harryeslick, @obrl-soil
Archive: TBD Version accepted: TBD Language: en
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.):
Explain how and why the package falls under these categories (briefly, 1-2 sentences): This package includes acquiring satellite imagery, and preparing spatially explicit soil moisture raster grids.
Who is the target audience and what are scientific applications of this package? Researchers in ecology, agriculture, sustainability. Agricultural management of grazing lands, reforestration.
Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category? No
(If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research? Yes
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