Package: cardinalR 1.0.6

cardinalR: Collection of Data Structures

A collection of functions to generate a large variety of structures in high dimensions. These data structures are useful for testing, validating, and improving algorithms used in dimensionality reduction, clustering, machine learning, and visualization.

Authors:Jayani P. Gamage [aut, cre], Dianne Cook [aut], Paul Harrison [aut], Michael Lydeamore [aut], Thiyanga S. Talagala [aut]

cardinalR_1.0.6.tar.gz
cardinalR_1.0.6.zip(r-4.7)cardinalR_1.0.6.zip(r-4.6)cardinalR_1.0.6.zip(r-4.5)
cardinalR_1.0.6.tgz(r-4.6-any)cardinalR_1.0.6.tgz(r-4.5-any)
cardinalR_1.0.6.tar.gz(r-4.7-any)cardinalR_1.0.6.tar.gz(r-4.6-any)
cardinalR_1.0.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
cardinalR/json (API)
NEWS

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

Bug tracker:https://github.com/jayanilakshika/cardinalr/issues

Pkgdown/docs site:https://jayanilakshika.github.io

Datasets:
  • mobiusgau - Mobius clust dataset with a noise dimension
  • mobiusgau_tsne1 - TSNE embedding for mobiusgau dataset which with noise dimensions tSNE parameters set to perplexity: 15.
  • mobiusgau_tsne2 - TSNE embedding for mobiusgau dataset which with noise dimensions tSNE parameters set to perplexity: 30.
  • mobiusgau_tsne3 - TSNE embedding for mobiusgau dataset which with noise dimensions tSNE parameters set to perplexity: 5.
  • mobiusgau_umap1 - UMAP embedding for mobiusgau dataset which with noise dimensions UMAP parameters set to n-neigbors: 15 and min-dist: 0.1.
  • mobiusgau_umap2 - UMAP embedding for mobiusgau dataset which with noise dimensions UMAP parameters set to n-neigbors: 30 and min-dist: 0.08.
  • mobiusgau_umap3 - UMAP embedding for mobiusgau dataset which with noise dimensions UMAP parameters set to n-neigbors: 5 and min-dist: 0.9.
  • three_clust_01 - Three-Cluster Dataset in 4-D
  • three_clust_02 - Three-Cluster Dataset in 4-D
  • three_clust_03 - Three-Cluster Dataset in 4-D
  • three_clust_04 - Three-Cluster Dataset in 4-D
  • three_clust_05 - Three-Cluster Dataset in 4-D

On CRAN:

Conda:

5.89 score 2 stars 20 scripts 210 downloads 63 exports 25 dependencies

Last updated from:15342317fd. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK149
source / vignettesOK197
linux-release-x86_64OK171
macos-release-arm64OK151
macos-oldrel-arm64OK165
windows-develOK106
windows-releaseOK111
windows-oldrelOK104
wasm-releaseOK119

Exports:gen_bkgnoisegen_circlegen_clusteredspheresgen_clustlocgen_conegen_conicspiralgen_crescentgen_cubicgen_curvybranchesgen_curvycyclegen_curvycylindergen_expbranchesgen_gaussiangen_gridcubegen_gridedspheregen_helicalspiralgen_hemispheregen_holegen_hollowspheregen_linearbranchesgen_longlineargen_mobiusgen_multiclustergen_noisedimsgen_nonlineargen_nproductgen_nsumgen_orgcurvybranchesgen_orglinearbranchesgen_pyrfracgen_pyrrectgen_pyrstargen_pyrtrigen_quadraticgen_rotationgen_scurvegen_scurveholegen_sphericalspiralgen_swissrollgen_trefoil3dgen_trefoil4dgen_unifcubegen_unifcubeholegen_unifspheregen_wavydims1gen_wavydims2gen_wavydims3make_chain_circlesmake_chain_curvycyclemake_curvygaumake_gaucirclesmake_gaucurvycyclemake_klink_circlesmake_klink_curvycyclemake_mobiusgaumake_multigaumake_onegridmake_shape_paramake_twogrid_overlapmake_twogrid_shiftnormalize_datarandomize_rowsrelocate_clusters

Dependencies:bitopsclicpp11dplyrgenericsgeozoogluegtoolslifecyclemagrittrMASSmvtnormpillarpkgconfigpurrrR6rlangstringistringrtibbletidyrtidyselectutf8vctrswithr

Additional functions

Rendered fromcardinalR03additionalfun.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2025-11-17
Started: 2025-11-17

Example data structures

Rendered fromcardinalR02examples.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2025-11-17
Started: 2025-11-17

Quick start

Rendered fromcardinalR01main_function.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2025-11-17
Started: 2025-11-17

Readme and manuals

Help Manual

Help pageTopics
Generate Background Noise Datagen_bkgnoise
Generate Circle in p-dgen_circle
Generate Small Spheres Within a Big Spheregen_clusteredspheres
Generate Cluster Locationsgen_clustloc
Generate Blunted Conegen_cone
Generate Conical Spiralgen_conicspiral
Generate Crescentgen_crescent
Generate Cubicgen_cubic
Generate data with curvy shaped branchesgen_curvybranches
Generate Curvy Cell Cycle in p-dgen_curvycycle
Generate Curvy Cylindergen_curvycylinder
Generate data with exponential shaped branchesgen_expbranches
Generate Multivariate Gaussian Cloudgen_gaussian
Generate Cube with grid pointsgen_gridcube
Generate Grided Spheregen_gridedsphere
Generate Helical Hyper Spiralgen_helicalspiral
Generate Hemispheregen_hemisphere
Remove points within a spherical hole in the middlegen_hole
Generate Hollow Spheregen_hollowsphere
Generate data with linear shaped branchesgen_linearbranches
Generate Long Linear Datagen_longlinear
Generate a 3-D Mobiusgen_mobius
Generate Multiple Clustersgen_multicluster
Generate Random Noise Dimensionsgen_noisedims
Generate Nonlinear Hyperbolagen_nonlinear
Generates a vector of positive integers whose product is approximately equal to a target value.gen_nproduct
Generates a vector of positive integers whose summation is approximately equal to a target value.gen_nsum
Generate data with curvy shaped branches in a initial pointgen_orgcurvybranches
Generate data with linear shaped branches in a initial pointgen_orglinearbranches
Generate p-D Triangular Pyramid With Triangular Pyramid shaped holesgen_pyrfrac
Generate Rectangular-based Pyramidgen_pyrrect
Generate Star Based Pyramidgen_pyrstar
Generate Triangular Based Pyramidgen_pyrtri
Generate Quadraticgen_quadratic
Generate Rotationsgen_rotation
Generate S-curve Datagen_scurve
Generate S-curve Data with a Holegen_scurvehole
Generate Spherical Spiralgen_sphericalspiral
Generate Swiss Roll Datagen_swissroll
Generate 3-D Trefoil Knot Coordinates (Stereographic Projection)gen_trefoil3d
Generate 4-D Trefoil Knot Coordinatesgen_trefoil4d
Generate Cube with uniform pointsgen_unifcube
Generate Cube with Holegen_unifcubehole
Generate Uniform Spheregen_unifsphere
Generate Random Noise Dimensions With Wavy Patterngen_wavydims1
Generate Random Noise Dimensions With Wavy Patterngen_wavydims2
Generate Random Noise Dimensions With Wavy Patterngen_wavydims3
Generate a Chain of Interlocked Circles in High-Dimensional Spacemake_chain_circles
Generate a Chain of Interlocked curvycycle in High-Dimensional Spacemake_chain_curvycycle
Generate Curvy Quadratic and Gaussian Clustersmake_curvygau
Generate Concentric Circles with a Gaussian Cluster in High Dimensionsmake_gaucircles
Generate Concentric Curvycycles with a Gaussian Cluster in High Dimensionsmake_gaucurvycycle
Generate Multiple Interlocked Circles in High-Dimensional Spacemake_klink_circles
Generate Multiple Interlocked curvycycle in High-Dimensional Spacemake_klink_curvycycle
Generate Gaussian cluster with the Mobius Clustermake_mobiusgau
Generate Multiple Gaussian Clustersmake_multigau
Generate a Single Grid Cluster in High Dimensionsmake_onegrid
Generate Parallel Multi-Shape Clustersmake_shape_para
Generate Two Overlapping Grid Clusters in High Dimensionsmake_twogrid_overlap
Generate Two Shifted Grid Clusters in High Dimensionsmake_twogrid_shift
Mobius clust dataset with a noise dimensionmobiusgau
tSNE embedding for mobiusgau dataset which with noise dimensions tSNE parameters set to perplexity: 15.mobiusgau_tsne1
tSNE embedding for mobiusgau dataset which with noise dimensions tSNE parameters set to perplexity: 30.mobiusgau_tsne2
tSNE embedding for mobiusgau dataset which with noise dimensions tSNE parameters set to perplexity: 5.mobiusgau_tsne3
UMAP embedding for mobiusgau dataset which with noise dimensions UMAP parameters set to n-neigbors: 15 and min-dist: 0.1.mobiusgau_umap1
UMAP embedding for mobiusgau dataset which with noise dimensions UMAP parameters set to n-neigbors: 30 and min-dist: 0.08.mobiusgau_umap2
UMAP embedding for mobiusgau dataset which with noise dimensions UMAP parameters set to n-neigbors: 5 and min-dist: 0.9.mobiusgau_umap3
Generate Normalized datanormalize_data
Randomize Rows of a Data Framerandomize_rows
Relocate Clusters in High-Dimensional Spacerelocate_clusters
Three-Cluster Dataset in 4-Dthree_clust_01
Three-Cluster Dataset in 4-Dthree_clust_02
Three-Cluster Dataset in 4-Dthree_clust_03
Three-Cluster Dataset in 4-Dthree_clust_04
Three-Cluster Dataset in 4-Dthree_clust_05