test submission

[mpadge]

Submitting Author: Mark Padgham (@mpadge)
Repository: https://github.com/mpadge/fastadi-demo
Version submitted:
Editor: @mpadge
Reviewers: @adamhsparks

Due date for @adamhsparks: 2021-06-12

Archive: TBD
Version accepted: TBD

---

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

Implements the AdaptiveImpute matrix completion
algorithm of 'Intelligent Initialization and Adaptive Thresholding 
Iterative Matrix Completion',
<https://amstat.tandfonline.com/doi/abs/10.1080/10618600.2018.1518238>.
AdaptiveImpute is useful for embedding sparsely observed matrices,
often out performs competing matrix completion algorithms, and
self-tunes its hyperparameter, making usage easy.

General Information

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

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

  • The first implementation of a novel algorithm; or
  • The first implementation within R of an algorithm which has previously been implemented in other languages or contexts; or
  • An improvement on other implementations of similar algorithms in R.

  Please include hyperlinked references to all other relevant software.

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

Badging

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

• 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)

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.
• 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?

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.

[mpadge]

@ropensci-review-bot help

[ropensci-review-bot]

Hello @mpadge, here are the things you can ask me to do:

# List all available commands
@ropensci-review-bot help

# Show our Code of Conduct
@ropensci-review-bot code of conduct

# Switch to "seeking reviewers"
@ropensci-review-bot seeking reviewers

# Approve the package
@ropensci-review-bot approve

# Add a user to this issue's reviewers list
@ropensci-review-bot add xxxxx to reviewers

# Remove a user from the reviewers list
@ropensci-review-bot remove xxxxx from reviewers

# Assign a user as the editor of this submission
@ropensci-review-bot assign @username as editor

# Remove the editor assigned to this submission
@ropensci-review-bot remove editor

# Close the issue
@ropensci-review-bot approve

# Close the issue
@ropensci-review-bot out of scope

# Check whether a package is good to send out to review
@ropensci-review-bot goodtoreview

[mpadge]

@ropensci-review-bot check package

[mpadge]

Checks for fastadi (v0.0.0.9019)

git hash: c207f3b8

• ✔️ Package uses 'roxygen2'
• ✖️ Package does not have a 'contributing.md' file
• ✖️ These funtions do not have examples: [adaptive_imputation.Rd]
• ✔️ Package 'DESCRIPTION' has a URL field
• ✔️ Package 'DESCRIPTION' has a BugReports field
• ✔️ Package has continuous integration checks
• ✔️ Package coverage is 78.8%
• ✖️ R CMD check found one warning

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

Package License: MIT + file LICENSE

---

1. srr

This package is in the following category:
Dimensionality Reduction, Clustering and Unsupervised Learning

• ✔️ This package is ready to submit!

Click here to view output of 'srr_report', which can be re-generated locally by running the `srr_report() function from within a local clone of the repository.

---

2. Statistical Properties

The statistical properties of this package are all within normal ranges.

click to see

The package has:

• Code in R (69%, in 10 files) and C++ (31%, in 7 files)
• 4 Authors
• 3 Vignettes
• No internal data
• 6 imported packages
• 9 exported functions (median 25 lines of code)
• 63 non-exported functions in R (median 5 lines of code)
• 13 C++ functions (median 15 lines of code)
• No C++ class or struct objects

---

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	10	55.4
files_vignettes	4	94.3
files_tests	12	90.6
loc_R	597	50.2
loc_vignettes	617	89.2
loc_tests	396	67.3
loc_per_fn_r	6	22.7
loc_per_fn_r_exp	25	57.6
loc_per_fn_r_not_exp	5	17.3
loc_per_fn_src	15	57.2
num_params_per_fn	6	79.2
loc_per_fn_r	6	22.7
loc_per_fn_r_exp	25	57.6
loc_per_fn_r_not_exp	5	17.3
loc_per_fn_src	15	57.2
fn_call_network_size	30	49.9

---

2a. Network visualisation

Click here for interactive network visualisation of calls between objects in package.

---

3. goodpractice and other checks

Click to see

3a. Continuous Integration Badges

GitHub Workflow Results

name	conclusion	sha	date
Commands	skipped	694594	2021-01-04
pkgdown	failure	4fc3b6	2021-03-17
R-CMD-check	failure	4fc3b6	2021-03-17
test-coverage	failure	4fc3b6	2021-03-17

---

3b. goodpractice results

---

Test coverage (covr)

• ✔️ Package coverage is 78.8%
• ✖️ The following files have coverage < 75%:
  • R/fastadi-package.R (0.00%),
  • R/generative-model.R (0.00%)
  • R/object.R (30.00%)

---

Cyclomatic Complexity (cyclocomp)

• ✔️ Maximal cyclomatic complexity is 13 (adaptive_impute, citation_impute)

---

R CMD check (rcmdcheck)

R CMD check generated the following warning:

1. checking Rd cross-references ... WARNING
Missing link or links in documentation object 'adaptive_impute.Rd':
  ‘stat’

See section 'Cross-references' in the 'Writing R Extensions' manual.

In addition, the following tests failed:

• no_description_depends
• no_import_package_as_a_whole
• rcmdcheck_rd_cross_references

---

Code linting (lintr)

lintr observed potential issues with code style in 106 lines

---

Editor-in-Chief Instructions:

Processing may not proceed until the items in the top section marked with ✖️ have been resolved (other items in subsequent sub-sections may be ignored for moment at your discretion).

[mpadge]

@ropensci-review-bot goodtoreview

[ropensci-review-bot]

Thanks, about to check whether the package is review-ready

[ropensci-review-bot]

🚀

Handling Editor Instructions:

This package is a great shape! Please proceed to finding reviewers.

👋

[mpadge]

@ropensci-review-bot assign @mpadge as editor

[ropensci-review-bot]

Assigned! @mpadge is now editor. Please review the package check details, comment on any areas for reviewers to focus on, and assign reviewers when ready”

[mpadge]

@ropensci-review-bot add @noamross to reviewers

[ropensci-review-bot]

@noamross added to the reviewers list. Review due date is 2021-05-24. Thanks @noamross for accepting to review! Please refer to our reviewer guide.

[mpadge]

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

• Briefly describe any working relationship you may have (had) with the package authors (or otherwise remove this statement)

• As the reviewer I confirm that there are no conflicts of interest for me to review this work (If you are unsure whether you are in conflict, please speak to your editor before starting your review).

---

Compliance with Standards

• This package complies with a sufficient number of standards for a silver badge
• This grade of badge is the same as what the authors wanted to achieve

The following standards currently deemed non-applicable (through tags of @srrstatsNA) could potentially be applied to future versions of this software:

• UL1.1 because it should
• UL1.2 because it could

Please also comment on any standards which you consider either particularly well, or insufficiently, documented.

For packages aiming for silver or gold badges:

• This package extends beyond minimal compliance with standards in the following ways:

It complies with a lot of standards.

---

General Review

Documentation

The package includes all the following forms of documentation:

• A statement of need clearly stating problems the software is designed to solve and its target audience in README
• Installation instructions: for the development version of package and any non-standard dependencies in README
• Community guidelines including contribution guidelines in the README or CONTRIBUTING
• The documentation is sufficient to enable general use of the package beyond one specific use case

The following sections of this template include questions intended to be used as guides to provide general, descriptive responses. Please remove this, and any subsequent lines that are not relevant or necessary for your final review.

Algorithms

• How well are algorithms encoded?
• Is the choice of computer language appropriate for that algorithm, and/or envisioned use of package?
• Are aspects of algorithmic scaling sufficiently documented and tested?
• Are there any aspects of algorithmic implementation which could be improved?

Testing

• Regardless of actual coverage of tests, are there any fundamental software operations which are not sufficiently expressed in tests?
• Is there a need for extended tests, or if extended tests exists, have they been implemented in an appropriate way, and are they appropriately documented?

Visualisation (where appropriate)

• Do visualisations aid the primary purposes of statistical interpretation of results?
• Are there any aspects of visualisations which could risk statistical misinterpretation?

Package Design

• Is the package well designed for its intended purpose?
• In relation to External Design: Do exported functions and the relationships between them enable general usage of the package?
• In relation to External Design: Do exported functions best serve inter-operability with other packages?
• In relation to Internal Design: Are algorithms implemented appropriately in terms of aspects such as efficiency, flexibility, generality, and accuracy?
• In relation to Internal Design: Could ranges of admissible input structures, or form(s) of output structures, be expanded to enhance inter-operability with other packages?

---

• Packaging guidelines: The package conforms to the rOpenSci packaging guidelines

Estimated hours spent reviewing:

• Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer ("rev" role) in the package DESCRIPTION file.

[mpadge]

@ropensci-review-bot approve silver

[mpadge]

Approved! Thanks @{{issue_author}} for submitting and {{reviewers-list}} for your reviews! 😁

To-dos:

• Transfer the repo to rOpenSci's "ropensci" GitHub organization under "Settings" in your repo. I have invited you to a team that should allow you to do so. You'll be made admin once you do.
• Fix all links to the GitHub repo to point to the repo under the ropensci organization.
• Delete your current code of conduct file if you had one since rOpenSci's default one will apply, see https://devguide.ropensci.org/collaboration.html#coc-file
• If you already had a pkgdown website and are ok relying only on rOpenSci central docs building and branding,
  • deactivate the automatic deployment you might have set up
  • remove styling tweaks from your pkgdown config but keep that config file
  • replace the whole current pkgdown website with a redirecting page
  • replace your package docs URL with https://docs.ropensci.org/package_name
  • In addition, in your DESCRIPTION file, include the docs link in the URL field alongside the link to the GitHub repository, e.g.: URL: https://docs.ropensci.org/foobar (website) https://github.com/ropensci/foobar
• Fix any links in badges for CI and coverage to point to the ropensci URL. We no longer transfer Appveyor projects to ropensci Appveyor account so after transfer of your repo to rOpenSci's "ropensci" GitHub organization the badge should be [![AppVeyor Build Status](https://ci.appveyor.com/api/projects/status/github/ropensci/pkgname?branch=master&svg=true)](https://ci.appveyor.com/project/individualaccount/pkgname). If Appveyor does not pick up new commits after transfer, you might need to delete and re-create the Appveyor project. (Repo transfers are smoother with GitHub Actions)
• Please check you updated the package version post-review version updated and that you documented all changes in NEWS.md
• We're starting to roll out software metadata files to all ropensci packages via the Codemeta initiative, see https://github.com/ropensci/codemetar/#codemetar for how to include it in your package, after installing the package - should be easy as running codemetar::write_codemeta() in the root of your package.

Should you want to acknowledge your reviewers in your package DESCRIPTION, you can do so by making them "rev"-type contributors in the Authors@R field (with their consent). More info on this here.

Welcome aboard! We'd love to host a post about your package - either a short introduction to it with an example for a technical audience or a longer post with some narrative about its development or something you learned, and an example of its use for a broader readership. If you are interested, consult the blog guide, and tag @stefaniebutland in your reply. She will get in touch about timing and can answer any questions.

We've put together an online book with our best practice and tips, this chapter starts the 3d section that's about guidance for after onboarding. Please tell us what could be improved, the corresponding repo is here.

Last but not least, you can volunteer as a reviewer via filling a short form.

[mpadge]

@ropensci-review-bot remove @noamross from reviewers

[ropensci-review-bot]

@noamross removed from the reviewers list!

[mpadge]

@ropensci-review-bot add @adamhsparks to reviewers

[ropensci-review-bot]

@adamhsparks added to the reviewers list. Review due date is 2021-06-12. Thanks @adamhsparks for accepting to review! Please refer to our reviewer guide.

[mpadge]

@ropensci-review-bot help

[ropensci-review-bot]

Hello @mpadge, here are the things you can ask me to do:

# List all available commands
@ropensci-review-bot help

# Show our Code of Conduct
@ropensci-review-bot code of conduct

# Switch to "seeking reviewers"
@ropensci-review-bot seeking reviewers

# Approve the package
@ropensci-review-bot approve

# Add a user to this issue's reviewers list
@ropensci-review-bot add xxxxx to reviewers

# Remove a user from the reviewers list
@ropensci-review-bot remove xxxxx from reviewers

# Assign a user as the editor of this submission
@ropensci-review-bot assign @username as editor

# Remove the editor assigned to this submission
@ropensci-review-bot remove editor

# Close the issue
@ropensci-review-bot approve

# Close the issue
@ropensci-review-bot out of scope

# Various package checks
@ropensci-review-bot check package