test submission

[mpadge]

Submitting Author: Mark Padgham (@mpadge) Repository: https://github.com/mpadge/fastadi-demo Version submitted: Editor: !--editor-->@mpadge<!--end-editor-- Reviewers: !--reviewers-list-->@adamhsparks<!--end-reviewers-list--

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.

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Technical checks

Confirm each of the following by checking the box.

• [ ] I/we have read the guide for authors and rOpenSci packaging guide.
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• [ ] I/we have run autotest checks on the package, and ensured no tests fail.
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This package:

• [ ] does not violate the Terms of Service of any service it interacts with.
• [ ] has a CRAN and OSI accepted license.
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• [ ] Do you intend for this package to go on CRAN?
• [ ] Do you intend for this package to go on Bioconductor?

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• [ ] I agree to abide by rOpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.

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[mpadge]

Checks for fastadi (v0.0.0.9019)

git hash: c207f3b8

• :heavy_check_mark: Package uses 'roxygen2'
• :heavy_multiplication_x: Package does not have a 'contributing.md' file
• :heavy_multiplication_x: These funtions do not have examples: [adaptive_imputation.Rd]
• :heavy_check_mark: Package 'DESCRIPTION' has a URL field
• :heavy_check_mark: Package 'DESCRIPTION' has a BugReports field
• :heavy_check_mark: Package has continuous integration checks
• :heavy_check_mark: Package coverage is 78.8%
• :heavy_multiplication_x: 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

• :heavy_check_mark: 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 [](https://github.com/mpadge/fastadi-demo/actions) **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`](https://github.com/jimhester/covr)) - :heavy_check_mark: Package coverage is 78.8% - :heavy_multiplication_x: 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`](https://github.com/MangoTheCat/cyclocomp)) - :heavy_check_mark: Maximal cyclomatic complexity is 13 (`adaptive_impute`, `citation_impute`) --- ### R CMD check ([`rcmdcheck`](https://github.com/r-lib/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`](https://github.com/jimhester/lintr)) [`lintr`](https://github.com/jimhester/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 :heavy_multiplication_x: have been resolved (other items in subsequent sub-sections may be ignored for moment at your discretion).

[mpadge]

@ropensci-review-bot goodtoreview

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

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:rocket:

Handling Editor Instructions:

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

:wave:

[mpadge]

@ropensci-review-bot assign @mpadge as editor

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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

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@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

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---

Compliance with Standards

• [x] This package complies with a sufficient number of standards for a silver badge
• [x] 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.

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

It complies with a lot of standards.

---

General Review

Documentation

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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

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Testing

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Visualisation (where appropriate)

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Package Design

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---

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[mpadge]

@ropensci-review-bot approve silver

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

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@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.

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