shapes.blocks3d: Generation of data set containing two clusters with untypical...

In clusterSim: Searching for Optimal Clustering Procedure for a Data Set

Generation of data set containing two clusters with untypical shapes (cube divided into two parts by main diagonal plane)

Description

Generation of data set containing two clusters with untypical shapes (cube starting at point (0,0,0) divided into two parts by main diagonal plane)

Usage

shapes.blocks3d(numObjects=180,shapesUnitSize=0.5, shape2coordinateX=1.2,
shape2coordinateY=1.2,shape2coordinateZ=1.2, outputCsv="", outputCsv2="", 
outputColNames=TRUE, outputRowNames=TRUE)

Arguments

numObjects	number of objects in each cluster - positive integer value or vector with length=2
shapesUnitSize	length of one unit for shape (maximal heigth, width and depth of shape is 2*shapesUnitSize)
shape2coordinateX	maximal value for second shape in first (X) dimension
shape2coordinateY	maximal value for second shape in second (Y) dimension
shape2coordinateZ	maximal value for second shape in third (Z) dimension
outputCsv	optional, name of csv file with generated data (first column contains id, second - number of cluster and others - data)
outputCsv2	optional, name of csv (a comma as decimal point and a semicolon as field separator) file with generated data (first column contains id, second - number of cluster and others - data)
outputColNames	outputColNames=TRUE indicates that output file (given by outputCsv and outputCsv2 parameters) contains first row with column names
outputRowNames	outputRowNames=TRUE indicates that output file (given by outputCsv and outputCsv2 parameters) contains a vector of row names

Value

clusters	cluster number for each object
data	generated data - matrix with objects in rows and variables in columns

Author(s)

Marek Walesiak [e-mail], Andrzej Dudek [e-mail]

Department of Econometrics and Computer Science, University of Economics, Wroclaw, Poland

See Also

shapes.worms,shapes.circles2,shapes.circles3,shapes.bulls.eye,shapes.two.moon

Examples

library(clusterSim)
#library(rgl)
sb3d<-shapes.blocks3d(300,1,3,3,3)
#plot3d(sb3d$data,col=rainbow(2)[sb3d$clusters])

clusterSim documentation built on Sept. 30, 2024, 9:15 a.m.