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Showing content from https://github.com/ropensci/software-review/issues/267 below:

lightr · Issue #267 · ropensci/software-review · GitHub

• What does this package do? (explain in 50 words or less):

lightr imports UV-VIS reflectance/transmission/absorbance proprietary file formats in R. It also allows the import of related metadata that are critical to ensure reproducibility but that are often discarded by other tools.

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

Package: lightr
Title: Read Spectrometric Data in R
Version: 0.0.0.9000
Authors@R: c(
    person("Hugo", "Gruson", role = c("cre", "aut"),
    email = REDACTED,
    comment = c(ORCID = "0000-0002-4094-1476")),
    person("Rafael", "Maia", role = "aut",
    email = "REDACTED",
    comment = c(ORCID = "0000-0002-7563-9795")),
    person("Thomas", "White", role = "aut",
    email = "REDACTED",
    comment = c(ORCID = "0000-0001-8493-9450"))
    )
Description: Parse various UV-VIS reflectance/transmittance/absorbance spectra
    file formats to extract spectral data and metadata.
Imports:
    pbmcapply,
    xml2
Suggests:
    covr,
    knitr,
    rmarkdown,
    spelling,
    testthat
URL: https://bisaloo.github.io/lightr, https://github.com/Bisaloo/lightr
BugReports: https://github.com/Bisaloo/lightr/issues
License: GPL (>=2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Roxygen: list(markdown = TRUE)
Language: en-GB
VignetteBuilder: knitr

• URL for the package (the development repository, not a stylized html page):

https://github.com/Bisaloo/lightr

• Please indicate which category or categories from our package fit policies this package falls under and why? (e.g., data retrieval, reproducibility. If you are unsure, we suggest you make a pre-submission inquiry.):

  • data extraction, because the package parses multiple scientific data file formats
  • (reproducibility) because it also extracts metadata saved during the recording

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

People working with UV-VIS reflectance/transmittance/absorbance spectra, colour science (#colsci). People developing package to analyse spectral data with vision models (lightr has few dependencies). Even non-R users who do not own the proprietary software to convert the proprietary formats to csv files.

• Are there other R packages that accomplish the same thing? If so, how does
  yours differ or meet our criteria for best-in-category?

There is partial overlap with some other packages, as described in the README but to my knowledge, none of them have the same aims as lightr.

•   If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted.

Confirm each of the following by checking the box. 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.
• includes documentation with examples for all functions.
• contains a vignette with examples of its essential functions and uses. [in progress]
• has a test suite.
• has continuous integration, including reporting of test coverage, using services such as Travis CI, Coveralls and/or CodeCov.
• I agree to abide by ROpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.

• Do you intend for this package to go on CRAN?
• Do you wish to automatically submit to the Journal of Open Source Software? If so:
  • The package has an obvious research application according to JOSS's definition.
  • The package contains a paper.md matching JOSS's requirements with a high-level description in the package root or in inst/.
  • The package is deposited in a long-term repository with the DOI:
  • (Do not submit your package separately to JOSS)
• Do you wish to submit an Applications Article about your package to Methods in Ecology and Evolution? If so:
  • The package is novel and will be of interest to the broad readership of the journal.
  • The manuscript describing the package is no longer than 3000 words.
  • 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)
  • (Scope: Do consider MEE's Aims and Scope 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)

• Does R CMD check (or devtools::check()) succeed? Paste and describe any errors or warnings:

• Does the package conform to rOpenSci packaging guidelines? Please describe any exceptions:

Some function names do not meet rOpenSci criteria (e.g. getspec() and getmetadata()) but this is kept for backwards compatibility with the package pavo, from which lightr originated. Synonyms have been added (get_spec() and get_metadata()) but it is at the moment unlikely that the old names will be deprecated.

• If this is a resubmission following rejection, please explain the change in circumstances:

• If possible, please provide recommendations of reviewers - those with experience with similar packages and/or likely users of your package - and their GitHub user names:

As mentioned in the template, some pieces still need polishing, mainly the vignettes but before going for one last push, I'd like to know if you would be interested.

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