bdm.boxp: Clustering statistics box-plot.

In jgarriga65/bigMap: Big Data Mapping

Clustering statistics box-plot.

Description

Clustering statistics box-plot.

Usage

bdm.boxp(data, bdm, byVars = F, merged = T, clusters = NULL, layer = 1)

Arguments

data	A matrix of data to be plotted (either the input data matrix or any covariate matrix as well).
bdm	A bdm instance as generated by bdm.init().
byVars	A logical value. By default (byVars = FALSE) box-plots are grouped by cluster. With byVars = TRUE box-plots are grouped by input feature.
merged	A logical value. If TRUE (default value) and the !is.null(bdm$merge) the boxplots depict the clusters after merging. If merged = FALSE or is.null(bdm$merge) the boxplots correspond to the top-level clustering.
clusters	A vector with a subset of cluster ids. (Default value is clusters=NULL to plot all clusters, with a maximum of 25).
layer	The number of a layer (1 by default).

Details

If the number of clusters is large, only the first 25 clusters will be plotted. Note that the WTT algorithm numbers the clusters based on density value at the peak cell of the cluster. Thus, the numbering of the clusters is highly correlated with their relevance in terms of partial density. Therefore, in case of more than 25 clusters, the most relevant should always be included in the plot.

Value

None.

Examples

bdm.example()
bdm.boxp(ex$map, data = ex$data[, 1:4])
bdm.boxp(ex$map, data = ex$data[, 1:4], byVars = TRUE)

jgarriga65/bigMap documentation built on June 10, 2024, 7:05 a.m.