BoxPlotDistance: Box plots of one distance matrix categorized against another...

In IntClust: Integration of Multiple Data Sets with Clustering Techniques

Description

Given two distance matrices, the function categorizes one distance matrix and produces a box plot from the other distance matrix against the created categories. The option is available to choose one of the plots or to have both plots. The function also works on outputs from ADEC and CEC functions which do not have distance matrices but incidence matrices.

Usage

BoxPlotDistance(Data1, Data2, type = c("data", "dist", "clusters"),
  distmeasure = c("tanimoto", "tanimoto"), normalize = c(FALSE, FALSE),
  method = c(NULL, NULL), lab1, lab2, limits1 = NULL, limits2 = NULL,
  plot = 1, StopRange = FALSE, plottype = "new", location = NULL)

Arguments

Data1	The first data matrix, cluster outcome or distance matrix to be plotted.
Data2	The second data matrix, cluster outcome or distance matrix to be plotted.
type	indicates whether the provided matrices in "List" are either data matrices, distance matrices or clustering results obtained from the data. If type="dist" the calculation of the distance matrices is skipped and if type="clusters" the single source clustering is skipped. Type should be one of "data", "dist" or "clusters".
distmeasure	A vector of the distance measures to be used on each data matrix. Should be one of "tanimoto", "euclidean", "jaccard", "hamming". Defaults to c("tanimoto","tanimoto").
normalize	Logical. Indicates whether to normalize the distance matrices or not, defaults to c(FALSE, FALSE) for two data sets. This is recommended if different distance types are used. More details on normalization in Normalization.
method	A method of normalization. Should be one of "Quantile","Fisher-Yates", "standardize","Range" or any of the first letters of these names. Default is c(NULL,NULL) for two data sets.
lab1	The label to plot for Data1.
lab2	The label to plot for Data2.
limits1	The limits for the categories of Data1.
limits2	The limits for the categories of Data2.
plot	The type of plots: 1 - Plot the values of Data1 versus the categories of Data2. 2 - Plot the values of Data2 versus the categories of Data1. 3 - Plot both types 1 and 2.
StopRange	Logical. Indicates whether the distance matrices with values not between zero and one should be standardized to have so. If FALSE the range normalization is performed. See Normalization. If TRUE, the distance matrices are not changed. This is recommended if different types of data are used such that these are comparable. Default is FALSE.
plottype	Should be one of "pdf","new" or "sweave". If "pdf", a location should be provided in "location" and the figure is saved there. If "new" a new graphic device is opened and if "sweave", the figure is made compatible to appear in a sweave or knitr document, i.e. no new device is opened and the plot appears in the current device or document. Default is "new".
location	If plottype is "pdf", a location should be provided in "location" and the figure is saved there. Default is NULL.

Value

One/multiple box plots.

Examples

## Not run: 
data(fingerprintMat)
data(targetMat)

MCF7_F = Cluster(fingerprintMat,type="data",distmeasure="tanimoto",normalize=FALSE,
method=NULL,clust="agnes",linkage="flexible",gap=FALSE,maxK=55,StopRange=FALSE)
MCF7_T = Cluster(targetMat,type="data",distmeasure="tanimoto",normalize=FALSE,
method=NULL,clust="agnes",linkage="flexible",gap=FALSE,maxK=55,StopRange=FALSE)


BoxPlotDistance(MCF7_F,MCF7_T,type="cluster",lab1="FP",lab2="TP",limits1=c(0.3,0.7),
limits2=c(0.3,0.7),plot=1,StopRange=FALSE,plottype="new", location=NULL)

## End(Not run)

IntClust documentation built on May 2, 2019, 5:51 a.m.