ds.clusterPlot: Draws a basic plot for clustering methods

In FlorianSchw/dsClusterAnalysisClient: DataSHIELD client side functions for the dsClusterAnalysisClient package

Draws a basic plot for clustering methods

Description

This function produces a plot for hclust clustering data

Usage

ds.clusterPlot(
  tree = NULL,
  k = NULL,
  h = NULL,
  k_colors = NULL,
  palette = NULL,
  show_labels = TRUE,
  color_labels_by_k = FALSE,
  datasources = NULL
)

Arguments

tree	is a string character of the data set
k	specifies the number of clusters in which the tree should be cut
h	specifies the height of a tree at which the tree should be cut
k_colors	is a vector containing colors to be used for groups
palette	a vector containing colors to be used for groups
show_labels	will always be set to false on the server-side for disclosure reasons
color_labels_by_k	is a logical value which colors the branches by group when k is not NULL
datasources	DSCOnnections

Details

The function calls the server-side function kmeansDS that computes the k-means clustering of a data set (type 'data.frame' or 'matrix'). The function creates a new object on the server-side, which is of class 'kmeans'. The new object is named by the user using the newobj argument, otherwise it is named kmeans.newobj by default.

The function computes the dendrogram without any labels to prevent any disclosures. The new object is named by the user using the newobj argument, otherwise it is named kmeans.newobj by default.

Value

the object specified by the newobj argument of ds.kmeans or default name kmeans.newobj

Author(s)

Florian Schwarz for the German Institute of Human Nutrition

FlorianSchw/dsClusterAnalysisClient documentation built on Feb. 8, 2025, 10:32 a.m.