Package: cardinalR 0.1.1

cardinalR: Collection of Data Structures

A collection of simple simulation datasets designed for generating Nonlinear Dimension Reduction representations techniques such as t-distributed Stochastic Neighbor Embedding, and Uniform Manifold Approximation and Projection. These datasets serve as a valuable resource for understanding the reliability of Nonlinear Dimension Reduction representations in various contexts.

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

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NEWS

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

Peer review:

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

Datasets:
  • mobius_clust_data - Mobius clust dataset with noise dimensions
  • mobius_clust_tsne_param1 - TSNE embedding for mobius_clust_data dataset which with noise dimensions tSNE parameters set to perplexity: 15.
  • mobius_clust_tsne_param2 - TSNE embedding for mobius_clust_data dataset which with noise dimensions tSNE parameters set to perplexity: 30.
  • mobius_clust_tsne_param3 - TSNE embedding for mobius_clust_data dataset which with noise dimensions tSNE parameters set to perplexity: 5.
  • mobius_clust_umap_param1 - UMAP embedding for mobius_clust_data dataset which with noise dimensions UMAP parameters set to n-neigbors: 15 and min-dist: 0.1.
  • mobius_clust_umap_param2 - UMAP embedding for mobius_clust_data dataset which with noise dimensions UMAP parameters set to n-neigbors: 30 and min-dist: 0.08.
  • mobius_clust_umap_param3 - UMAP embedding for mobius_clust_data dataset which with noise dimensions UMAP parameters set to n-neigbors: 5 and min-dist: 0.9.

On CRAN:

78 exports 1.18 score 7 dependencies 215 downloads

Last updated 3 months agofrom:67be1a41e5. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 15 2024
R-4.5-winOKSep 15 2024
R-4.5-linuxOKSep 15 2024
R-4.4-winOKSep 15 2024
R-4.4-macOKSep 15 2024
R-4.3-winOKSep 15 2024
R-4.3-macOKSep 15 2024

Exports:cell_cycleclust_diff_shapesclust_diff_shapes_ptsconic_spiral_3dconic_spiral_3d_rowcube_3dcurv_2dcurvy_branchcurvy_branch_clustcurvy_branch_clust_bkgcurvy_cyclecurvy_treediff_spheredini_surface_3ddini_surface_3d_roweight_branchfour_branchfour_long_clustfour_long_clust_bkggau_clustgau_clust_diffgau_curvy_clustgau_curvy_clust_bkggen_bkg_noisegen_noise_dimsmirror_scurvesmobius_5dmobius_5d_rowmobius_clustnonlinear_2dnonlinear_connectnonlinear_mirrorone_doubletone_doublet_bkgone_doublet_diff_patternsone_doublet_diff_var_clustone_doublet_four_clustsone_gridone_grid_bkgplaneplane_2d_holeroman_surface_3droman_surface_3d_rowscurvescurve_holeseven_branchsine_curvespherespiral_3dswiss_rollthree_circularsthree_clust_diff_distthree_clust_mirrorthree_diff_linearthree_doubletsthree_gridthree_long_clustthree_nonlineartorus_3dtorus_3d_rowtreetri_3dtri_plane_bkgtwo_circularstwo_curvilineartwo_curvytwo_curvy_diff_ptstwo_curvy_panckakestwo_doublets_bkgtwo_doublets_paralleltwo_gridtwo_grid_combtwo_grid_comb_bkgtwo_long_clusttwo_long_clust_difftwo_nonlineartwo_scurve_holetwo_scurves

Dependencies:cligluelifecyclemagrittrpurrrrlangvctrs

Example datasets

Rendered fromquollr1sample.Rmdusingknitr::rmarkdownon Sep 15 2024.

Last update: 2024-04-15
Started: 2024-04-13

Readme and manuals

Help Manual

Help pageTopics
Generate Cell Cycle Data with Noisecell_cycle
Generate Clusters with Different Shapesclust_diff_shapes
Generate Clusters with Different Shapes and Different Number of Pointsclust_diff_shapes_pts
Generate data points along a conic spiral curve with optional noise.conic_spiral_3d
Generate points on a conic spiral in 3D space.conic_spiral_3d_row
Generate a 3D cube with optional noise.cube_3d
Generate points on a curvilinear 2D manifoldcurv_2d
Generate Curvy Branching Clusters with Noisecurvy_branch
Generate Curvy Branching Cluster Datacurvy_branch_clust
Generate Curvy Branching Cluster Data with Background Noisecurvy_branch_clust_bkg
Generate Curvy Cell Cycle Data with Noisecurvy_cycle
Generate Curvy Tree Data with Noisecurvy_tree
Generate data representing small spheres within a larger encompassing sphere with added noise.diff_sphere
Generate points sampled from the Dini surface with optional noise.dini_surface_3d
Generate points on a Dini's surface.dini_surface_3d_row
Generate Eight Branching Data with Noiseeight_branch
Generate Four-Branching Data with Noisefour_branch
Generate Four Different Long Clusters with Noisefour_long_clust
Generate Four Long Clusters with Background Noisefour_long_clust_bkg
Generate synthetic data with Gaussian clustersgau_clust
Generate Gaussian Clusters with Different Pointsgau_clust_diff
Generate Cluster and Curvilinear Data with Noisegau_curvy_clust
Generate Clusters and Curvilinear Data with Noisegau_curvy_clust_bkg
Generate Background Noise Datagen_bkg_noise
Generate Random Noise Dimensionsgen_noise_dims
Generate Mirror S-curve Datasets with Noisemirror_scurves
Generate a 5-D Mobius Stripmobius_5d
Generate a Single Row for a 5-D Mobius Stripmobius_5d_row
Generate Mobius Cluster with Noisemobius_clust
Mobius clust dataset with noise dimensionsmobius_clust_data
tSNE embedding for mobius_clust_data dataset which with noise dimensions tSNE parameters set to perplexity: 15.mobius_clust_tsne_param1
tSNE embedding for mobius_clust_data dataset which with noise dimensions tSNE parameters set to perplexity: 30.mobius_clust_tsne_param2
tSNE embedding for mobius_clust_data dataset which with noise dimensions tSNE parameters set to perplexity: 5.mobius_clust_tsne_param3
UMAP embedding for mobius_clust_data dataset which with noise dimensions UMAP parameters set to n-neigbors: 15 and min-dist: 0.1.mobius_clust_umap_param1
UMAP embedding for mobius_clust_data dataset which with noise dimensions UMAP parameters set to n-neigbors: 30 and min-dist: 0.08.mobius_clust_umap_param2
UMAP embedding for mobius_clust_data dataset which with noise dimensions UMAP parameters set to n-neigbors: 5 and min-dist: 0.9.mobius_clust_umap_param3
Generate points on a nonlinear 2D manifoldnonlinear_2d
Generate Nonlinear Connected Data with Noisenonlinear_connect
Generate Nonlinear Mirror Data with Noisenonlinear_mirror
Generate Doublets with Noiseone_doublet
Generate Doublets with Background Noiseone_doublet_bkg
Generate Doublets with Different Pattern Clusters and Noiseone_doublet_diff_patterns
Generate Doublets with Different Variance Clusters and Noiseone_doublet_diff_var_clust
Generate Doublets with Four Clusters and Noiseone_doublet_four_clusts
Generate Grid Data with Noiseone_grid
Generate One Grid with Different Values and Background Noiseone_grid_bkg
Generate points on a plane in 2D spaceplane
Generate 2D Plane with Hole and Noiseplane_2d_hole
Generate data points on a Roman surface with optional noise.roman_surface_3d
Generate points on a Roman surface in 3D space.roman_surface_3d_row
Generate S-curve Datascurve
Generate S-curve Data with a Holescurve_hole
Generate Seven-Branching Data with Noiseseven_branch
Generate Sine Curve Data with Noisesine_curve
Generate Coordinates for a Spheresphere
Generate a spiral dataset with optional noise.spiral_3d
Generate Swiss Roll Dataswiss_roll
Generate Three Circular Clusters with Noisethree_circulars
Generate three clusters of data points with optional noise.three_clust_diff_dist
Generate Three Cluster Mirror with Noisethree_clust_mirror
Generate Three Different Linear Data with Noisethree_diff_linear
Generate Doublets with Three Clusters and Noisethree_doublets
Generate Three Grids with Noisethree_grid
Generate Three Linear Clusters with Noisethree_long_clust
Generate Three Nonlinear Clusters with Noisethree_nonlinear
Generate a torus-shaped dataset with optional noise.torus_3d
Generate a row of data points for a 3D torus.torus_3d_row
Generate Tree-like Data with Noisetree
Generate Triangular 3D Datasets with Noisetri_3d
Generate Triangular Plane with Background Noisetri_plane_bkg
Generate Linked Datatwo_circulars
Generate Two Curvilinear Data with Noisetwo_curvilinear
Generate Two Curvilinear Clusters with Noisetwo_curvy
Generate Two Curvilinear Differentiated Clusters with Noisetwo_curvy_diff_pts
Generate Two Curvy Pancakes with Noisetwo_curvy_panckakes
Generate Two Doublets with Background Noisetwo_doublets_bkg
Generate Doublets in Parallel with Noisetwo_doublets_parallel
Generate Two Grids with Noisetwo_grid
Generate One Grid with Different Offsettwo_grid_comb
Generate Two Grids with Background Noisetwo_grid_comb_bkg
Generate Long Cluster Datatwo_long_clust
Generate Two Linear Differentiated Clusters with Noisetwo_long_clust_diff
Generate Two Nonlinear Clusters with Noisetwo_nonlinear
Generate Two S-Curve Data with Noisetwo_scurve_hole
Generate Two S-curve Datasets with Noisetwo_scurves