Submission tsbox: Class-Agnostic Time Series

[christophsax]

Date accepted: 2023-02-23
Submitting Author Name: Christoph Sax
Submitting Author Github Handle: @christophsax
Repository: https://github.com/christophsax/tsbox
Version submitted: 3.1.9001
Submission type: Stats
Badge grade: silver
Editor: @rkillick
Reviewers: @chamberlinc, @brunaw, @nunesmatt

Due date for @chamberlinc: 2021-11-23

Due date for @brunaw: 2021-11-23
Due date for @nunesmatt: 2022-10-03
Archive: TBD
Version accepted: TBD

---

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

Package: tsbox
Type: Package
Title: Class-Agnostic Time Series
Version: 0.3.1.9001
Authors@R: person("Christoph", "Sax", email = "christoph.sax@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7192-7044"))
Description: Time series toolkit with identical behavior for all
  time series classes: 'ts','xts', 'data.frame', 'data.table', 'tibble', 'zoo',
  'timeSeries', 'tsibble', 'tis' or 'irts'. Also converts reliably between these classes.
Imports:
    data.table (>= 1.10.0),
    anytime
Suggests:
    testthat,
    dplyr,
    tibble,
    tidyr,
    forecast,
    seasonal,
    dygraphs,
    xts,
    ggplot2,
    scales,
    knitr,
    rmarkdown,
    tsibble (>= 0.8.2),
    tsibbledata,
    tibbletime,
    tseries,
    units,
    zoo,
    tis,
    timeSeries,
    nycflights13,
    imputeTS,
    spelling
License: GPL-3
Encoding: UTF-8
URL: https://www.tsbox.help, https://github.com/christophsax/tsbox
BugReports: https://github.com/christophsax/tsbox/issues
Roxygen: list(markdown = TRUE, roclets = c ("namespace", "rd", "srr::srr_stats_roclet"))
RoxygenNote: 7.1.2
VignetteBuilder: knitr
Depends:
    R (>= 2.10)
Config/testthat/parallel: true
Config/testthat/edition: 3
Language: en-US

Pre-submission Inquiry

• A pre-submission inquiry has been approved in issue#457

General Information

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

Anyone who works with time series. Many statistical packages require time series to be in a certain object (ts, xts, tsibble, data.frame). tsbox facilitates the conversion between these objects. It also provides a general toolkit that works the same way with all time series classes. {tsbox} is also mentioned in the rOpenSci Statistical Software Peer Review Section on Time Series.

• 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.

In the rOpenSci classification, this package is An improvement on other implementations of similar algorithms in R. Many time series packages, e.g., zoo or tsibble contain converter functions from one class to another. They often convert from their class to ts objects and back, but lack converters to other time series class.

In most cases, tsbox transforms an object into an augmented data.table. And uses the data.table infrastructure for efficient joining and reshaping. After computation, it restores the original input class. This restoring feature is
was also used in the xts::reclass() function of the xts package.

• Please include hyperlinked references to all other relevant software.

data.table: For efficient joining and reshaping
xts: Similar reclassing mechanism
tsibble: Tidy Temporal Data Frames and Tools

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

Not applicable.

Badging

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

I probably need some advice on this. I think that tsbox complies with most standards that are applicable. Generality of usage is a particular feature that should qualify the package for silver.

• 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)

The most outstanding point is probably the one on generality:

Have a demonstrated generality of usage beyond one single envisioned use case.

The package facilitates work with time series in general. It can also be used to ease the burden of object testing and time series conversion for other time series packages.

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?

  Already published 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.

[ropensci-review-bot]

Thanks for submitting to rOpenSci, our editors and @ropensci-review-bot will reply soon. Type @ropensci-review-bot help for help.

[ropensci-review-bot]

🚀

Editor check started

👋

[ropensci-review-bot]

Oops, something went wrong with our automatic package checks. Our developers have been notified and package checks will appear here as soon as we've resolved the issue. Sorry for any inconvenience.

[mpadge]

@christophsax Sorry about the mess up here - the checks server is currently running R4.0.3, so doesn't recognise native pipes which you use in some test code. Will upgrade asap and deliver your checks.

[christophsax]

But I did't intend to use native pipes, that was an accident. I will remove them right now.

[christophsax]

I did so now. Perhaps rerunning is sufficient.

[ropensci-review-bot]

Checks for tsbox (v0.3.1.9001)

git hash: aad57cea

• ✔️ Package uses 'roxygen2'.
• ✔️ Package has a 'contributing.md' file.
• ✔️ Package has a 'CITATION' file.
• ✔️ Package has a 'codemeta.json' file.
• ✔️ All functions have examples.
• ✔️ Package has at least one HTML vignette
• ✔️ Package 'DESCRIPTION' has a URL field.
• ✔️ Package 'DESCRIPTION' has a BugReports field.
• ✔️ Package is already on CRAN.
• ✔️ Package has continuous integration checks.
• ✖️ Package coverage failed
• ✖️ R CMD check found 1error.
• ✔️ R CMD check found no warnings.
• ✔️ All applicable standards [v0.0.1] have been documented in this package.

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

Package License: GPL-3

---

1. rOpenSci Statistical Standards (srr package)

This package is in the following category:

• Time Series

✔️ All applicable standards [v0.0.1] have been documented in this package

Click here to see the report of author-reported standards compliance of the package with links to associated lines of code, which can be re-generated locally by running the srr_report() function from within a local clone of the repository.

---

2. Statistical Properties

This package features some noteworthy statistical properties which may need to be clarified by a handling editor prior to progressing.

Details of statistical properties (click to open)

The package has:

• code in R (100% in 53 files) and
• 1 authors
• 3 vignettes
• no internal data file
• 2 imported packages
• 63 exported functions (median 7 lines of code)
• 277 non-exported functions in R (median 9 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

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	53	96.0
files_vignettes	3	90.8
files_tests	44	98.7
loc_R	2649	88.3
loc_vignettes	344	80.6
loc_tests	1951	92.1
num_vignettes	3	93.1
n_fns_r	340	93.4
n_fns_r_exported	63	90.4
n_fns_r_not_exported	277	93.8
n_fns_per_file_r	4	51.4
num_params_per_fn	1	1.1	TRUE
loc_per_fn_r	8	29.0
loc_per_fn_r_exp	7	14.2
loc_per_fn_r_not_exp	9	41.9
rel_whitespace_R	25	91.6
rel_whitespace_vignettes	32	87.8
rel_whitespace_tests	28	98.0	TRUE
doclines_per_fn_exp	41	51.1
doclines_per_fn_not_exp	0	0.0	TRUE
fn_call_network_size	475	94.6

---

2a. Network visualisation

Interactive network visualisation of calls between objects in package can be viewed by clicking here

---

3. goodpractice and other checks

Details of goodpractice and other checks (click to open)

3a. Continuous Integration Badges

GitHub Workflow Results

name	conclusion	sha	date
R-CMD-check	success	aad57c	2021-09-18

---

3b. goodpractice results

R CMD check with rcmdcheck

R CMD check generated the following error:

1. checking tests ...
   Running ‘spelling.R’
   Running ‘testthat.R’
   ERROR
   Running the tests in ‘tests/testthat.R’ failed.
   Last 13 lines of output:
   █
   1. ├─fl[i]
   2. │ └─tsbox::ts_apply(x, ff, ...)
   3. │ └─tsbox:::ts_apply_dts(ts_dts(x), fun, ...)
   4. │ ├─x[, fun(.SD, ...), by = eval(.by)]
   5. │ └─data.table:::[.data.table(x, , fun(.SD, ...), by = eval(.by))
   6. └─tsbox:::fun(.SD, ...)
   7. └─(function(x, ...) seasonal::final(seasonal::seas(x, ...)))(...)

   8. ├─seasonal::final(seasonal::seas(x, ...))
      

   9. └─seasonal::seas(x, ...)
      

   10.   └─seasonal::checkX13(fail = TRUE, fullcheck = FALSE, htmlcheck = FALSE)
       

[ FAIL 1 | WARN 8 | SKIP 17 | PASS 644 ]
Error: Test failures
Execution halted

R CMD check generated the following test_fail:

1. library(testthat)
   Warning message:
   package 'testthat' was built under R version 4.1.0

library(tsbox)

test_check("tsbox")
Starting 2 test processes
══ Skipped tests ═══════════════════════════════════════════════════════════════
• On CRAN (17)

══ Failed tests ════════════════════════════════════════════════════════════════
── Error (test-units.R:41:5): tsbox works with units ───────────────────────────
Error: Process terminated
Backtrace:
█

1. ├─fl[i]
2. │ └─tsbox::ts_apply(x, ff, ...)
3. │ └─tsbox:::ts_apply_dts(ts_dts(x), fun, ...)
4. │ ├─x[, fun(.SD, ...), by = eval(.by)]
5. │ └─data.table:::[.data.table(x, , fun(.SD, ...), by = eval(.by))
6. └─tsbox:::fun(.SD, ...)
7. └─(function(x, ...) seasonal::final(seasonal::seas(x, ...)))(...)

8. ├─seasonal::final(seasonal::seas(x, ...))
   

9. └─seasonal::seas(x, ...)
   

10.   └─seasonal::checkX13(fail = TRUE, fullcheck = FALSE, htmlcheck = FALSE)
    

[ FAIL 1 | WARN 8 | SKIP 17 | PASS 644 ]
Error: Test failures
Execution halted

R CMD check generated the following check_fail:

1. rcmdcheck_tests_pass

Test coverage with covr

ERROR: Test Coverage Failed

Cyclocomplexity with cyclocomp

The following functions have cyclocomplexity >= 15:

function	cyclocomplexity
ts_span	34
time_shift	21
ts_plot	21
copy_class	19

Static code analyses with lintr

lintr found the following 178 potential issues:

message	number of times
Lines should not be more than 80 characters.	178

✔️ Package has at least one HTML vignette

---

Package Versions

package	version
pkgstats	0.0.0.311
pkgcheck	0.0.1.486
srr	0.0.1.107

---

Editor-in-Chief Instructions:

Processing may not proceed until the items marked with ✖️ have been resolved.

[christophsax]

R CMD check

There seems to be an issue with the package seasonal on your system. The package is special since it uses x13binary which downloads pre-built binaries from CRAN. Usually this works fine and on most CRAN platforms.

Is there anything special about your system? There was an issue for Mac M1.

If you want to check, this should works:

library(seasonal)
seas(AirPassengers)
checkX13()

But I don't want you to drag into this. I can also remove the few tests that are using seasonal, which should then resolve the issue?

Coverage

Perhaps this is just because of the failing R CMD check? If not, is there a way to see what ist the measured coverage? I had 81.2% on my system, which passed the threshold (see below).

Report on my side

If I run pkgcheck::pkgcheck(".") on my side, I get:

#### Coverage

✔ Package uses 'roxygen2'.
✔ Package has a 'contributing.md' file.
✔ Package has a 'CITATION' file.
✔ Package has a 'codemeta.json' file.
✔ All functions have examples.
✔ Package has at least one HTML vignette
✔ Package 'DESCRIPTION' has a URL field.
✔ Package 'DESCRIPTION' has a BugReports field.
✔ Package is already on CRAN.
✔ Package has continuous integration checks.
✔ Package coverage is 81.2%.
✔ R CMD check found no errors.
✔ R CMD check found no warnings.
✔ All applicable standards [v0.0.1] have been documented in this package.

ℹ Current status:
✔ This package may be submitted.

[noamross]

@ropensci-review-bot assign @rkillick as editor

[ropensci-review-bot]

Assigned! @rkillick is now the editor

[rkillick]

The goodpractice() checks came back with:

• Use <- instead of =
  ts_frequency.R L120
• Lines longer than 80 characters:
  ts_bind.R L58, L62
  ts_first_of_period.R L12, L13, L18
  test-ts_frequency.R L33

I had problems running covr() but see that it is passing on the checks above. Please fix the above and I'll look to assign reviewers as these are small changes.