linkspotter (version 1.3.0)

linkspotterGraph: Linkspotter graph runner

Description

plot the Linkspotter graph

Usage

linkspotterGraph(
  corDF,
  variablesClustering = NULL,
  minCor = 0.3,
  corMethod = colnames(corDF)[-c(1:3, ncol(corDF))][length(colnames(corDF)[-c(1:3,
    ncol(corDF))])],
  smoothEdges = T,
  dynamicNodes = F,
  colorEdgesByCorDirection = F
)

Arguments

corDF

a specific dataframe containing correlations values resulting from the function multiBivariateCorrelation()

variablesClustering

a specific dataframe containing the output of the variable clustering resulting from the function clusterVariables()

minCor

a double between 0 and 1. It is the minimal correlation absolute value to consider for the first graph plot.

corMethod

a string. One of "pearson","spearman","kendall","mic", "distCor" or "MaxNMI". It is the correlation coefficient to consider for the first graph plot.

smoothEdges

a boolean. TRUE to let the edges be smooth.

dynamicNodes

a boolean. TRUE to let the graph re-organize itself after any movement.

colorEdgesByCorDirection

a boolean. TRUE to get the edges colored according to the correlation direction (positive-> blue, negative->red or NA->grey).

Value

a visNetwork object corresponding to a dynamic graph for the correlation matrix visualization.

Examples

# NOT RUN {
# calculate a correlation dataframe
data(iris)
corDF=multiBivariateCorrelation(dataset = iris)
corMatrix=corCouplesToMatrix(x1_x2_val = corDF[,c('X1','X2',"spearman")])
corGroups=clusterVariables(corMatrix = corMatrix, nbCluster = 3)
# launch the graph
linkspotterGraph(corDF=corDF, variablesClustering=corGroups, minCor=0.3,
corMethod='spearman', colorEdgesByCorDirection=TRUE)

# }