DataVisualizations (version 1.3.3)

ShepardDensityscatter: Shepard PDE scatter

Description

Draws ein Shepard Diagram (scatterplot of distances) with an two-dimensional PDE density estimation .

Usage

ShepardDensityScatter(InputDists, OutputDists, Plotter= "native", Type = "DDCAL",
DensityEstimation="SDH", Marginals = FALSE, xlab='Input Distances',
ylab='Output Distances',main='ProjectionMethod', sampleSize=500000)

Arguments

InputDists

[1:n,1:n] with n cases of data in d variables/features: Matrix containing the distances of the inputspace.

OutputDists

[1:n,1:n] with n cases of data in d dimensionalites of the projection method variables/features: Matrix containing the distances of the outputspace.

Plotter

Optional, either "native" or "plotly"

Type

Optional, either "DDCAL" which creates a special hard color transition sensitive to density-based structures or "Standard" which creates a standard continuous color transition which is proven to be not very sensitive for complex density-based structures.

DensityEstimation

Optional, use either "SDH" or "PDE" for data density estimation.

Marginals

Optional, either TRUE (draw Marginals) or FALSE (do not draw Marginals)

xlab

Label of the x axis in the resulting Plot.

ylab

Label of the y axis in the resulting Plot.

main

Title of the Shepard diagram

sampleSize

Optional, default(500000), reduces a.ount of data for density estimation, if too many distances given

Author

Michael Thrun

Details

Introduced and described in [Thrun, 2018, p. 63] with examples in [Thrun, 2018, p. 71-72]

References

[Thrun, 2018] Thrun, M. C.: Projection Based Clustering through Self-Organization and Swarm Intelligence, doctoral dissertation 2017, Springer, ISBN: 978-3-658-20540-9, Heidelberg, 2018.

Examples

data("Lsun3D")
Cls=Lsun3D$Cls
Data=Lsun3D$Data
InputDist=as.matrix(dist(Data))
res = stats::cmdscale(d = InputDist, k = 2, eig = TRUE, 
        add = FALSE, x.ret = FALSE)
# \donttest{
ProjectedPoints = as.matrix(res$points)
ShepardDensityScatter(InputDist,as.matrix(dist(ProjectedPoints)),main = 'MDS')
ShepardDensityScatter(InputDist[1:100,1:100],

as.matrix(dist(ProjectedPoints))[1:100,1:100],main = 'MDS')
# }