Package index • cardinalR

Data

The example data sets.

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.

Branching

Branching data structure.

gen_expbranches(): Generate data with exponential shaped branches

gen_orglinearbranches(): Generate data with linear shaped branches in a initial point

gen_orgcurvybranches(): Generate data with curvy shaped branches in a initial point

gen_linearbranches(): Generate data with linear shaped branches

gen_curvybranches(): Generate data with curvy shaped branches

Cone

Cone data structure.

gen_cone(): Generate Blunted Cone

Cube

Cube data structure.

gen_gridcube(): Generate Cube with grid points

gen_unifcube(): Generate Cube with uniform points

gen_unifcubehole(): Generate Cube with Hole

Gaussian

Gaussian data structure.

gen_gaussian(): Generate Gaussian

Linear

Linear data structure.

gen_longlinear(): Generate Long Linear Data

Mobius

Mobius data structure.

gen_mobius(): Generate a 3-D Mobius

Multiple clusters

Main function.

gen_multicluster(): Generate Multiple Clusters

Odd shapes

Odd shaped clusters.

make_mobiusgau(): Generate Gaussian cluster with the Mobius Cluster

make_multigau(): Generate Multiple Gaussian Clusters

make_curvygau(): Generate Curvy Quadratic and Gaussian Clusters

make_klink_circles(): Generate Multiple Interlocked Circles in High-Dimensional Space

make_chain_circles(): Generate a Chain of Interlocked Circles in High-Dimensional Space

make_klink_curvycycle(): Generate Multiple Interlocked curvycycle in High-Dimensional Space

make_chain_curvycycle(): Generate a Chain of Interlocked curvycycle in High-Dimensional Space

make_gaucircles(): Generate Concentric Circles with a Gaussian Cluster in High Dimensions

make_gaucurvycycle(): Generate Concentric Curvycycles with a Gaussian Cluster in High Dimensions

make_onegrid(): Generate a Single Grid Cluster in High Dimensions

make_twogrid_overlap(): Generate Two Overlapping Grid Clusters in High Dimensions

make_twogrid_shift(): Generate Two Shifted Grid Clusters in High Dimensions

make_shape_para(): Generate Parallel Multi-Shape Clusters

Three clusters

Three different shaped clusters.

make_three_clust_01(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_02(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_03(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_04(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_05(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_06(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_07(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_08(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_09(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_10(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_11(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_12(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_13(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_14(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_15(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_16(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_17(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_18(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_19(): Generate a Three-Cluster Dataset in High Dimensions

make_three_clust_20(): Generate a Three-Cluster Dataset in High Dimensions

Polynomial

Polynomial data structures.

gen_quadratic(): Generate Quadratic

gen_cubic(): Generate Cubic

Pyramid

Pyramid data structures.

gen_pyrrect(): Generate Rectangular Based Pyramid

gen_pyrtri(): Generate Triangular Based Pyramid

gen_pyrstar(): Generate Star Based Pyramid

gen_pyrfrac(): Generate p-D Triangular Pyramid With Triangular Pyramid shaped holes

S-curve

S-curve data structures.

gen_scurve(): Generate S-curve Data

gen_scurvehole(): Generate S-curve Data with a Hole

Sphere

Sphere data structures.

gen_circle(): Generate Circle in p-d

gen_curvycycle(): Generate Curvy Cell Cycle in p-d

gen_unifsphere(): Generate Uniform Sphere

gen_gridedsphere(): Generate Grided Sphere

gen_clusteredspheres(): Generate Small Spheres Within a Big Sphere

gen_hemisphere(): Generate Hemisphere

gen_hollowsphere(): Generate Hollow Sphere

Swiss roll

Swiss roll data structures.

gen_swissroll(): Generate Swiss Roll Data

trigonometric

Trigonometric data structures.

gen_crescent(): Generate Crescent

gen_curvycylinder(): Generate Curvy Cylinder

gen_sphericalspiral(): Generate Spherical Spiral

gen_helicalspiral(): Generate Helical Hyper Spiral

gen_conicspiral(): Generate Conical Spiral

gen_nonlinear(): Generate Nonlinear Hyperbola

trefoil

trefoil data structures.

gen_trefoil3d(): Generate 3-D Trefoil Knot Coordinates (Stereographic Projection)

gen_trefoil4d(): Generate 4-D Trefoil Knot Coordinates

Additional functions

These are additional functionalities.

gen_noisedims(): Generate Random Noise Dimensions

gen_bkgnoise(): Generate Background Noise Data

randomize_rows(): Randomize Rows of a Data Frame

relocate_clusters(): Relocate Clusters in High-Dimensional Space

gen_nproduct(): Generates a vector of positive integers whose product is approximately equal to a target value.

gen_nsum(): Generates a vector of positive integers whose summation is approximately equal to a target value.

gen_wavydims1(): Generate Random Noise Dimensions With Wavy Pattern

gen_wavydims2(): Generate Random Noise Dimensions With Wavy Pattern

gen_wavydims3(): Generate Random Noise Dimensions With Wavy Pattern

gen_rotation(): Generate Rotations

normalize_data(): Generate Normalized data

gen_clustloc(): Generate Cluster Locations

gen_hole(): Remove points within a spherical hole in the middle