Defines the underlying pipeline structure for reproducible
neuroscience, adopted by 'RAVE' (reproducible analysis and visualization
of intracranial electroencephalography); provides high-level class
definition to build, compile, set, execute, and share analysis pipelines.
Both R and 'Python' are supported, with 'Markdown' and 'shiny' dashboard
templates for extending and building customized pipelines. See the full
documentations at <https://rave.wiki>; to cite us,
check out our paper by Magnotti, Wang, and Beauchamp (2020,
<doi:10.1016/j.neuroimage.2020.117341>), or run
citation("ravepipeline") for details.
| Version: |
0.0.1 |
| Imports: |
utils, stats, base64url, callr, cli, digest, fastmap, future, fst (≥ 0.9.8), glue, jsonlite, knitr, promises, R6, remotes, rlang, targets, uuid, yaml |
| Suggests: |
filearray, future.apply, globals, ieegio, rpymat, rmarkdown, rstudioapi, shidashi, threeBrain, testthat (≥ 3.0.0), visNetwork |
| Published: |
2025-03-13 |
| Author: |
Zhengjia Wang [aut, cre, cph],
John Magnotti [ctb, res],
Xiang Zhang [ctb, res],
Michael Beauchamp [ctb, res],
Trustees of University of Pennsylvania [cph] (Copyright Holder) |
| Maintainer: |
Zhengjia Wang <dipterix.wang at gmail.com> |
| BugReports: |
https://github.com/dipterix/ravepipeline/issues |
| License: |
MIT + file LICENSE |
| Copyright: |
Trustees of University of Pennsylvania owns the copyright of
the package unless otherwise stated. Zhengjia Wang owns the
copyright of all the low-level functions included in
'R/common.R', 'R/fastmap2', 'R/fastqueue2.R', 'R/filesys.R',
'R/fst.R', 'R/json.R', 'R/os_info.R', 'R/parallel.R',
'R/progress.R', 'R/simplelocker.R', 'R/yaml.R', and all the
template files under 'inst/rave-pipelines' and
'inst/rave-modules', these files are licensed under 'MIT'. |
| URL: |
https://dipterix.org/ravepipeline/,
https://github.com/dipterix/ravepipeline |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Citation: |
ravepipeline citation info |
| Materials: |
README NEWS |
| CRAN checks: |
ravepipeline results |