R Observatory: Metrics for waves version 0.2.7

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

waves

0.2.7Package record

Vis-NIR Spectral Analysis Wrapper

0packages depend

3.5Kdownloads / year

0.0%test coverage

13/13flavors OK

Overview

About

Maintained by Jenna HershbergerCRAN page ↗GitHub ↗Website ↗Issues ↗Declared funder: NSF BREAD IOS-1543958

Originally designed application in the context of resource-limited plant research and breeding programs, 'waves' provides an open-source solution to spectral data processing and model development by bringing useful packages together into a streamlined pipeline. This package is wrapper for functions related to the analysis of point visible and near-infrared reflectance measurements. It includes visualization, filtering, aggregation, preprocessing, cross-validation set formation, model training, and prediction functions to enable open-source association of spectral and reference data. This package is documented in a peer-reviewed manuscript in the Plant Phenome Journal doi:10.1002/ppj2.20012. Specialized cross-validation schemes are described in detail in Jarquín et al. (2017) doi:10.3835/plantgenome2016.12.0130. Example data is from Ikeogu et al. (2017) doi:10.1371/journal.pone.0188918.

Changes in 0.2.7

Bug fix: Fixed namespace resolution error with lifecycle::deprecated() function calls that was causing "could not find function deprecated" errors for users. All function parameters now properly use lifecycle::deprecated() instead of deprecated().
Bug fix: train_spectra() now correctly populates RMSEcv and R2cv for rf, svmLinear, and svmRadial model methods. Previously these were always NA for non-PLS models.
Bug fix: Replaced deprecated tidyr and dplyr functions across plot_spectra(), aggregate_spectra(), train_spectra(), and the ikeogu.2017 example to resolve deprecation warnings.
Internal: Fixed trainControl() configuration in train_spectra() — changed method from "repeatedcv" (with no repeats set) to "cv" and removed a malformed seeds argument that was being silently ignored. Reproducibility is maintained via the existing set.seed() call.
Bug fix: The final RF model returned by train_spectra() is now trained with 500 trees (the randomForest default) instead of tune.length (≤5). The tuned mtry from training iterations is now correctly applied to the final model.
Bug fix: The final SVM model returned by train_spectra() no longer incorrectly uses the unique.id column as a predictor. Training data is now subset to reference and spectral columns only, consistent with iterative model training.
Bug fix: The final PLS model returned by train_spectra() is now fit using the modal best ncomp from training iterations rather than tune.length. predict_spectra() now reads ncomp directly from the model object instead of the stats file.
Bug fix: train_spectra() now correctly subsets partitioned data using column names rather than pre-computed indices, preventing an undefined columns selected crash when cv.scheme is used (the genotype column is removed by format_cv() before subsetting).
Bug fix: train_spectra() now correctly determines the training data for the final model when cv.scheme is used. It calls format_cv() one final time to obtain the training set defined by the chosen scheme: CV0/CV00 train on trial2 + trial3; CV1 trains on t1.b + t2.b; CV2 trains on t1.b + trial2. In all schemes the test set is t1.a (held-out genotypes from trial1).
Bug fix: test_spectra() now correctly forwards best.model.metric and seed to train_spectra(). Previously these arguments were accepted but silently ignored.
Bug fix: train_spectra() now calls set.seed() before createDataPartition(), ensuring that stratified train/test splits are fully reproducible. Previously, set.seed() was called after createDataPartition(), so the partition depended on whatever the random state happened to be at call time. **Note on reproducibility:** users who called test_spectra() with a non-default seed were previously receiving results generated with seed = 1 regardless of the value they set. To reproduce old results, set seed = 1 explicitly. This will restore previous iterative performance statistics (RMSEp, R2p, etc.), but the returned $model object will still differ due to the RF, SVM, and PLS final model fixes also introduced in this version.
Bug fix: Removed invalid ntree and mtry arguments from predict.randomForest() calls in train_individual_model() and predict_spectra(). These arguments are not accepted by predict.randomForest() and were silently ignored.

Show all changes in 0.2.7Hide the rest of the changes in 0.2.7

Bug fix: Fixed corrupted importance output when running test_spectra() with multiple pretreatments and an SVM model. Previously, cbind() on a NULL importance element produced a garbage 1×1 matrix instead of NULL.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("waves", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("GoreLab/waves")

Development version from GoreLab/waves. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-waves

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-waves

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-waves

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 6.8 min · r-release-macos-x86_64

Status changes

OK13 OK2026-08-04
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09
ERROR12 OK, 1 ERROR2026-06-08
NOTE12 OK, 1 NOTE2026-06-07

Show 3 earlier changesHide 3 earlier changes

OK13 OK2026-05-02
ERROR11 OK, 1 ERROR2026-04-25
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.2.7

READMEYes · 551 wordsVignettesYes · 1 · dynamicNEWSYes · 100% structured · mentions 0.2.7Citation fileYes · cites a publicationWebsiteYes · pkgdown

Help pages: 11 (1 internal)
Examples that run: 50%5 run in a plain check · 4 only when donttest examples are enabled (R CMD check --as-cran) · 1 never run
Exported functions with examples: 90%
Documented parameters: 90%
Return-value docs: 90%
Help pages citing references: 27%

Vignettes (1)

waves HTML

How these are measured

Downloads

3.5K

CRAN downloads in the past year

Rank #9,002 · ~9/day · ~289/mo

Releases R versions

Daily download trend is not available in this view yet.

36130 days

1.1K90 days

3.5K1 year

Compare downloads with other packages →

Also on124 r2u1 autocran

How downloads are counted

Repository

gorelab/waves ↗Organization: GoreLab

8Stars

6Forks

6Open issues

0Open PRs

10Releases

186Commits

3Commit identities

186 commits · Last activity 2026-07-28 · 0% stars, 30d · Default branch at 0.2.7.9000, ahead of CRAN 0.2.7 (checked 2026-10-18)

Responsiveness

How these are sampled

PRs merged (all time): 100%
Median days to close, 50 most recently updated closed issues: 43
Median days to close, 50 most recently updated closed PRs: 0

Stars over time

2025-10-09 · 72026-07-07 · 8

How these are measured

PracticesBeta

10 development-tooling and community-health practices detected across 6 families in the upstream repository

Checks run against github.com/gorelab/waves on 2026-10-18.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Governance and community (1)

Contributing guide

Docs source (3)

pkgdown

GitHub Pages site last deployed 2026-07-28 · The repository has a site deploy workflow

pkgdown site last built 2026-06-02

Reproducibility and dev environment (1)

data-raw/

Show all practicesHide 2 practices

CRAN release process (2)

cran-comments.mdrevdep/

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

19 external dependencies (excludes base and recommended)

Installing waves adds 127 packages (73 with compiled code, 118 MB of source tarballs). Heaviest: stringi 11 MB, sf 9.3 MB, prospectr 6.2 MB.

Depends (1)

R >= 4.1.0

Imports (16)

caret dplyr ggplot2 lifecycle magrittr pls prospectr randomForest readr rlang scales spectacles stringr tibble tidyr tidyselect

LinkingTo (0)

none

Suggests (3)

testthat knitr rmarkdown

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (3)

Jenna Hershberger

Author, Maintainer since 0.1.0 (2020)

NSF BREAD IOS-1543958

Funder

Michael Gore

Thesis advisor

Releases (10)

Pick two releases to compare their code metrics.

0.2.7Latest
record
2026-06-02 · current release · diff ↗
R
R 4.6.0 released · 2026-04-24
unarchivedReturned to CRAN
2025-10-31
0.2.6
record
2025-10-31 · diff ↗
archivedRemoved from CRAN
2025-06-02
requires archived package 'spectacles'
R
R 4.5.0 released · 2025-04-11
R
R 4.4.0 released · 2024-04-24
0.2.5
record
2023-12-12 · diff ↗
R
R 4.3.0 released · 2023-04-21
R
R 4.2.0 released · 2022-04-22
0.2.4
record
2022-03-29 · diff ↗
0.2.3
record
2022-03-07 · diff ↗
0.2.2
record
2022-02-18 · diff ↗
0.2.1
record
2022-02-03 · diff ↗
0.2.0
record
2022-01-21 · diff ↗ ·
added 9 exports
aggregate_spectra, filter_spectra, format_cv, plot_spectra, predict_spectra, pretreat_spectra, save_model, test_spectra, train_spectra
R
R 4.1.0 released · 2021-05-18

Show 3 earlier eventsHide 3 earlier events

0.1.1
record
2021-04-21 · diff ↗
0.1.0
record
2020-09-17
R
R 4.0.0 released · 2020-04-24

Package metadata

First published: 2020-09-17
Total releases: 10 / 6 yrs
License: MIT + file LICENSE OSI
Minimum R: ≥ 4.1.0
Bundled data: 1.9 MB / 1 file
Download size: 2.9 MB

Appears in task views

Agricultural Science

Cite

Cite this package

Run in R for the authors' entry:

citation("waves")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.1002/ppj2.20012.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for waves version 0.2.7 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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