ohun: Optimizing Acoustic Signal Detection

Facilitates the automatic detection of acoustic signals, providing functions to diagnose and optimize the performance of detection routines. Detections from other software can also be explored and optimized. Araya-Salas et al. (2022) <doi:10.1101/2022.12.13.520253>.

Version: 1.0.1
Depends: R (≥ 3.2.1)
Imports: tuneR, warbleR (≥ 1.1.29), cli, methods, stats, utils, seewave (≥ 2.0.1), fftw, rlang, sf, igraph, checkmate, ggplot2
Suggests: knitr, rmarkdown, testthat, viridis, Sim.DiffProc, vdiffr
Published: 2023-11-17
DOI: 10.32614/CRAN.package.ohun
Author: Marcelo Araya-Salas ORCID iD [aut, cre], Alec L. Robitaille ORCID iD [rev], Sam Lapp ORCID iD [rev]
Maintainer: Marcelo Araya-Salas <marcelo.araya at ucr.ac.cr>
BugReports: https://github.com/ropensci/ohun/issues/
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://docs.ropensci.org/ohun/, https://github.com/ropensci/ohun/
NeedsCompilation: no
Language: en-US
Citation: ohun citation info
Materials: README NEWS
CRAN checks: ohun results


Reference manual: ohun.pdf
Vignettes: 3. Energy-based detection
1. Introduction to ohun
2. Template-based detection


Package source: ohun_1.0.1.tar.gz
Windows binaries: r-devel: ohun_1.0.1.zip, r-release: ohun_1.0.1.zip, r-oldrel: ohun_1.0.1.zip
macOS binaries: r-release (arm64): ohun_1.0.1.tgz, r-oldrel (arm64): ohun_1.0.1.tgz, r-release (x86_64): ohun_1.0.1.tgz, r-oldrel (x86_64): ohun_1.0.1.tgz
Old sources: ohun archive


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