Description Usage Arguments Value Examples
View source: R/linkspotterOnFile.R
This function imports an external dataset, computes its correlation matrices, variable clustering and the customizable user interface to visualize them using a graph.
1 2 3 4 5 6 7 8 9 10 11 12 13 | linkspotterOnFile(
file,
corMethods = c("pearson", "spearman", "kendall", "mic", "MaxNMI"),
defaultMinCor = 0.3,
defaultCorMethod = corMethods[length(corMethods)],
clusteringCorMethod = corMethods[length(corMethods)],
nbCluster = 1:9,
printInfo = T,
appTitle = "Linkspotter",
htmlTop = "",
htmlBottom = "",
...
)
|
file |
the file containing a structured dataset which the bivariate correlations are to be analyzed. |
corMethods |
a vector of correlation coefficients to compute. The available coefficients
are the following : |
defaultMinCor |
a double between 0 and 1. It is the minimal correlation absolute value to consider for the first graph plot. |
defaultCorMethod |
a string. One of "pearson","spearman","kendall","mic", "distCor" or "MaxNMI". It is the correlation coefficient to consider for the first graph plot. |
clusteringCorMethod |
a string. One of "pearson","spearman","kendall","mic", "distCor" or "MaxNMI". It is the correlation coefficient to consider for the variables clustering. |
nbCluster |
an integer. It is the number of clusters to compute. |
printInfo |
a boolean indicating whether to print on the console some information about the dataset and the estimated computation time. |
appTitle |
a string taken as the title of the user interface. |
htmlTop |
a character string that enable to customize your shiny app by adding an HTML code in the HEAD tag. |
htmlBottom |
a character string that enable to customize your shiny app by adding an HTML code at the end of the BODY tag. |
... |
Further arguments to be passed to the used read.csv function. |
a list containing all the material enabling to analyze correlations:
computationTime
: a string
run_it
: a shiny.appobj object enable to deploy instantly the user interface
for a customizable visualization.
dataset
: the initial dataset
corDF
: a the correlation data.frame including values for all coefficients
corMatrices
: a list of correlation matrices
corGroups
: data.frame a data.frame list
clusteringCorMethod
: a character
defaultMinCor
: a numeric
defaultCorMethod
: a string
corMethods
: vector of strings
1 2 3 4 5 6 7 8 9 10 11 | # run linkspotter on iris example data
data(iris)
tmpCSV<-tempfile(fileext = '.csv')
write.csv(iris, tmpCSV, row.names = FALSE)
lsOutputIrisFromFile<-linkspotterOnFile(file=tmpCSV)
summary(lsOutputIrisFromFile)
## Not run:
# launch the UI
lsOutputIrisFromFile$launchShiny(options=list(port=8000))
## End(Not run)
|
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