Package: ScatterDensity 0.1.1

Michael Thrun

ScatterDensity: Density Estimation and Visualization of 2D Scatter Plots

The user has the option to utilize the two-dimensional density estimation techniques called smoothed density published by Eilers and Goeman (2004) <doi:10.1093/bioinformatics/btg454>, and pareto density which was evaluated for univariate data by Thrun, Gehlert and Ultsch, 2020 <doi:10.1371/journal.pone.0238835>. Moreover, it provides visualizations of the density estimation in the form of two-dimensional scatter plots in which the points are color-coded based on increasing density. Colors are defined by the one-dimensional clustering technique called 1D distribution cluster algorithm (DDCAL) published by Lux and Rinderle-Ma (2023) <doi:10.1007/s00357-022-09428-6>.

Authors:Michael Thrun [aut, cre, cph], Felix Pape [aut, rev], Luca Brinkman [aut], Quirin Stier [aut]

ScatterDensity_0.1.1.tar.gz
ScatterDensity_0.1.1.tar.gz(r-4.7-arm64)ScatterDensity_0.1.1.tar.gz(r-4.7-x86_64)ScatterDensity_0.1.1.tar.gz(r-4.6-arm64)ScatterDensity_0.1.1.tar.gz(r-4.6-x86_64)
ScatterDensity_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
ScatterDensity/json (API)

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

Bug tracker:https://github.com/mthrun/scatterdensity/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

1.00 score 1 scripts 283 downloads 8 exports 4 dependencies

Last updated from:ec7c64b2f8. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK172
linux-devel-x86_64OK187
source / vignettesOK318
linux-release-arm64OK223
linux-release-x86_64OK190
wasm-releaseOK175

Exports:DDCALDensityScatter.DDCALfast_table_numPDEscatterPointsInPolygonPolygonGateSampleScatterSmoothedDensitiesXY

Dependencies:pracmaRcppRcppArmadilloRcppParallel