Package: spathial 0.1.2

Erika Gardini

spathial: Evolutionary Analysis

A generic tool for manifold analysis. It allows to infer a relevant transition or evolutionary path which can highlights the features involved in a specific process. 'spathial' can be useful in all the scenarios where the temporal (or pseudo-temporal) evolution is the main problem (e.g. tumor progression). The algorithm for finding the principal path is described in: Ferrarotti et al., (2019) <doi:10.1109/TNNLS.2018.2884792>."

Authors:Erika Gardini [aut, cre], Federico M. Giorgi [aut], Sergio Decherchi [aut], Andrea Cavalli [aut]

spathial_0.1.2.tar.gz
spathial_0.1.2.tar.gz(r-4.5-noble)spathial_0.1.2.tar.gz(r-4.4-noble)
spathial_0.1.2.tgz(r-4.4-emscripten)spathial_0.1.2.tgz(r-4.3-emscripten)
spathial.pdf |spathial.html
spathial/json (API)

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

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

6 exports 0.23 score 40 dependencies 1 mentions 1 scripts 195 downloads

Last updated 4 years agofrom:6848d8e206. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 27 2024
R-4.5-linuxNOTEAug 27 2024

Exports:spathialBoundaryIdsspathialLabelsspathialPlotspathialPrefilteringspathialStatisticsspathialWay

Dependencies:base64encbslibcachemclassclicpp11digestevaluatefastmapfontawesomefsgluehighrhtmltoolsigraphirlbajquerylibjsonliteknitrlatticelifecyclemagrittrMASSMatrixmatrixStatsmemoisemimepkgconfigpracmaR6rappdirsRcpprlangrmarkdownRtsnesasstinytexvctrsxfunyaml

A short introduction to the spathial Package

Rendered fromvignette.rmdusingknitr::rmarkdownon Aug 27 2024.

Last update: 2020-04-10
Started: 2020-04-10

Readme and manuals

Help Manual

Help pageTopics
Select starting and ending pointsspathialBoundaryIds
Find labelsspathialLabels
2D spathialspathialPlot
Prefilter dataspathialPrefiltering
CorrelationspathialStatistics
Compute Principal PathspathialWay