Package: PressPurt 1.0.2

PressPurt: Indeterminacy of Networks via Press Perturbations

This is a computational package designed to identify the most sensitive interactions within a network which must be estimated most accurately in order to produce qualitatively robust predictions to a press perturbation. This is accomplished by enumerating the number of sign switches (and their magnitude) in the net effects matrix when an edge experiences uncertainty. The package produces data and visualizations when uncertainty is associated to one or more edges in the network and according to a variety of distributions. The software requires the network to be described by a system of differential equations but only requires as input a numerical Jacobian matrix evaluated at an equilibrium point. This package is based on Koslicki, D., & Novak, M. (2017) <doi:10.1007/s00285-017-1163-0>.

Authors:David Koslicki [aut, cre], Dana Gibbon [aut, trl], Mark Novak [aut]

PressPurt_1.0.2.tar.gz
PressPurt_1.0.2.zip(r-4.7-any)PressPurt_1.0.2.zip(r-4.6-any)PressPurt_1.0.2.zip(r-4.5-any)
PressPurt_1.0.2.tgz(r-4.6-any)PressPurt_1.0.2.tgz(r-4.5-any)
PressPurt_1.0.2.tar.gz(r-4.7-any)PressPurt_1.0.2.tar.gz(r-4.6-any)
PressPurt_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
PressPurt/json (API)

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

Bug tracker:https://github.com/dkoslicki/presspurt/issues

On CRAN:

Conda:

2.30 score 246 downloads 13 exports 29 dependencies

Last updated from:f549fef186. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK164
source / vignettesOK187
linux-releaseOK158
macos-releaseOK196
macos-oldrelOK228
windows-develOK91
windows-releaseOK109
windows-oldrelOK111
wasm-releaseOK134

Exports:ComputeEntryWisePerturbationExpectationComputeMultiEntryPerturbationExpectationcreate_conda_envcreate_virtual_envfind_pythonGenerateEntryWiseFiguresget_distributions_singlens_to_stepPreprocessMatrixprocess_datapy_dependset_python_condaset_python_virtual

Dependencies:clicpp11data.tablefarverggplot2gluegridExtragtablehereisobandjsonlitelabelinglatticelifecycleMatrixpngR6rappdirsRColorBrewerRcppRcppTOMLreticulaterlangrprojrootS7scalesvctrsviridisLitewithr

Basic Tutorial
Quick start | Load Python | Example: IGP.csv | R-object based | Save to disk

Last update: 2020-10-19
Started: 2020-10-19

Set up
Installing Dependencies | R | Python

Last update: 2020-10-19
Started: 2020-10-19