Package: sindyr 0.2.4

sindyr: Sparse Identification of Nonlinear Dynamics

This implements the Brunton et al (2016; PNAS <doi:10.1073/pnas.1517384113>) sparse identification algorithm for finding ordinary differential equations for a measured system from raw data (SINDy). The package includes a set of additional tools for working with raw data, with an emphasis on cognitive science applications (Dale and Bhat, 2018 <doi:10.1016/j.cogsys.2018.06.020>). See <https://github.com/racdale/sindyr> for examples and updates.

Authors:Rick Dale and Harish S. Bhat

sindyr_0.2.4.tar.gz
sindyr_0.2.4.zip(r-4.7-any)sindyr_0.2.4.zip(r-4.6-any)sindyr_0.2.4.zip(r-4.5-any)
sindyr_0.2.4.tgz(r-4.6-any)sindyr_0.2.4.tgz(r-4.5-any)
sindyr_0.2.4.tar.gz(r-4.7-any)sindyr_0.2.4.tar.gz(r-4.6-any)
sindyr_0.2.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
sindyr/json (API)

# Install 'sindyr' in R:
install.packages('sindyr', repos = c('https://racdale.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/racdale/sindyr/issues

On CRAN:

Conda:

3.98 score 16 stars 12 scripts 228 downloads 6 exports 16 dependencies

Last updated from:ff9c7029cf. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK102
source / vignettesOK192
linux-releaseOK105
macos-releaseOK74
macos-oldrelOK69
windows-develOK67
windows-releaseOK67
windows-oldrelOK75
wasm-releaseOK85

Exports:featuresfinite_differencefinite_differenceslorenzattractorsindywindowed_sindy

Dependencies:arrangementsclicpp11gluegmpigraphlatticelifecyclemagrittrMatrixmatrixStatspkgconfigpracmaR6rlangvctrs