pgu.correlator: pgu.correlator
In pguIMP: Visually Guided Preprocessing of Bioanalytical Laboratory Data
pgu.correlator R Documentation
pgu.correlator
Description
An R6 class that performs pairwise correlation on the pguIMP data set.
Format
[R6::R6Class] object.
Construction
x <- pguIMP::pgu.correlator$new()
Active bindings
featureNamesReturns the instance variable featureNames.
(character)
setFeatureNamesSets the instance variable featureNames.
It further initializes the instance variables:
intercept, pIntercept, slope, pSlope.
(character)
methodReturns the instance variable method.
(character)
rReturns the instance variable r.
(matrix)
pPearsonReturns the instance variable pPearson.
(matrix)
tauReturns the instance variable tau.
(matrix)
pKendallReturns the instance variable pKendall.
(matrix)
rhoReturns the instance variable rho.
(matrix)
pSpearmanReturns the instance variable pSpearman.
(matrix)
abscissaReturns the instance variable abscissa.
(character)
setAbscissaSets the instance variable abscicca to value.
ordinateReturns the instance variable ordinate.
(character)
setOrdinateSets the instance variable ordinate to value.
testReturns the instance variable test.
(stats::cor.test)
Methods
Public methods
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Method new()
Creates and returns a new 'pgu.correlator' object.
Usage
pgu.correlator$new(data = "tbl_df")
Arguments
dataThe data to be modeled.
(tibble::tibble)
Returns
A new 'pgu.correlator' object.
(pguIMP::pgu.correlator)
Method finalize()
Clears the heap and
indicates if instance of 'pgu.correlator' is removed from heap.
Usage
pgu.correlator$finalize()
Method print()
Prints instance variables of a 'pgu.correlator' object.
Usage
pgu.correlator$print()
Returns
string
Method resetCorrelator()
Performes pair-wise correlation analysis on the attributes of the data frame.
Progresse is indicated by the progress object passed to the function.
Usage
pgu.correlator$resetCorrelator(data = "tbl_df", progress = "Progress")
Arguments
dataDataframe with at least two numeric attributes.
(tibble::tibble)
progressKeeps track of the analysis progress.
(shiny::Progress)
Method resetMatrix()
Creates a square matrix which dimension corresponds to the length
of the instance variable featureNames. The matrix entries are set to a distict 'value'.
Usage
pgu.correlator$resetMatrix(value = "numeric")
Arguments
valueThe value the matrix entries are set to.
(numeric)
Returns
A square matrix.
(matrix)
Method featureIdx()
Determines the numerical index of the column of an attribute based on the attribute name.
Usage
pgu.correlator$featureIdx(feature = "character")
Arguments
featureThe attribute's name.
(character)
Returns
The attributes column index.
(numeric)
Method calcCorrelationNumeric()
Creates a correlation test between two attributes of a dataframe.
The test is stored as instance variable.
Usage
pgu.correlator$calcCorrelationNumeric(
abscissa = "numeric",
ordinate = "numeric",
method = "character"
)
Arguments
abscissaThe abscissa values.
(numeric)
ordinateThe ordinate values.
(numeric)
methodThe cname of the correlation test.
Valid coiced are defined by the instance variable 'method'.
(chatacter)
Method createCorrelationMatrixPearson()
Performs the actual correlation test routine after Pearson.
Iteratively runs through the attributes known to the class
and calculates Pearson's correlation for each valid attribute pair.
The test results are stored in the instance variables:
r, pPearson.
Here, pX represents the p-value of the respective parameter X.
Displays the progress if shiny is loaded.
Usage
pgu.correlator$createCorrelationMatrixPearson(
data = "tbl_df",
progress = "Progress"
)
Arguments
dataThe data to be analysed.
(tibble::tibble)
progressIf shiny is loaded, the analysis' progress is stored within this instance of the shiny Progress class.
(shiny::Progress)
Method createCorrelationMatrixKendall()
Performs the actual correlation test routine after Kendall.
Iteratively runs through the attributes known to the class
and calculates Kendall's correlation for each valid attribute pair.
The test results are stored in the instance variables:
tau, pKendall.
Here, pX represents the p-value of the respective parameter X.
Displays the progress if shiny is loaded.
Usage
pgu.correlator$createCorrelationMatrixKendall(
data = "tbl_df",
progress = "Progress"
)
Arguments
dataThe data to be analysed.
(tibble::tibble)
progressIf shiny is loaded, the analysis' progress is stored within this instance of the shiny Progress class.
(shiny::Progress)
Method createCorrelationMatrixSpearman()
Performs the actual correlation test routine after Spearman.
Iteratively runs through the attributes known to the class
and calculates Spearman's correlation for each valid attribute pair.
The test results are stored in the instance variables:
rho, pSpearman.
Here, pX represents the p-value of the respective parameter X.
Displays the progress if shiny is loaded.
Usage
pgu.correlator$createCorrelationMatrixSpearman(
data = "tbl_df",
progress = "Progress"
)
Arguments
dataThe data to be analysed.
(tibble::tibble)
progressIf shiny is loaded, the analysis' progress is stored within this instance of the shiny Progress class.
(shiny::Progress)
Method correlate()
Performs the all three correlation test routines defined
within the instance variable 'method'.
Displays the progress if shiny is loaded.
Usage
pgu.correlator$correlate(data = "tbl_df", progress = "Progress")
Arguments
dataThe data to be analysed.
(tibble::tibble)
progressIf shiny is loaded, the analysis' progress is stored within this instance of the shiny Progress class.
(shiny::Progress)
Method printFeature()
Transforms the results of the correlation procedure for a valid pair of attributes to a dataframe
and returns it.
Usage
pgu.correlator$printFeature()
Returns
The analyis result as a dataframe.
(tibble::tibble)
Method printRTbl()
Transfroms instance variable 'r' to a dataframe and returns it.
Usage
pgu.correlator$printRTbl()
Returns
Dataframe of instance variable 'r'.
(tibble::tibble)
Method printPPearsonTbl()
Transfroms instance variable 'pPearson' to a dataframe and returns it.
Usage
pgu.correlator$printPPearsonTbl()
Returns
Dataframe of instance variable 'pPearson'.
(tibble::tibble)
Method printTauTbl()
Transfroms instance variable 'tau' to a dataframe and returns it.
Usage
pgu.correlator$printTauTbl()
Returns
Dataframe of instance variable 'tau'.
(tibble::tibble)
Method printPKendallTbl()
Transfroms instance variable 'pKendall' to a dataframe and returns it.
Usage
pgu.correlator$printPKendallTbl()
Returns
Dataframe of instance variable 'pKendall'.
(tibble::tibble)
Method printRhoTbl()
Transfroms instance variable 'rho' to a dataframe and returns it.
Usage
pgu.correlator$printRhoTbl()
Returns
Dataframe of instance variable 'rho'.
(tibble::tibble)
Method printPSpearmanTbl()
Transfroms instance variable 'pSpearman' to a dataframe and returns it.
Usage
pgu.correlator$printPSpearmanTbl()
Returns
Dataframe of instance variable 'pSpearman'.
(tibble::tibble)
Method clone()
The objects of this class are cloneable with this method.
Usage
pgu.correlator$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
Author(s)
Sebastian Malkusch
Examples
require(dplyr)
require(tibble)
data(iris)
data_df <- iris %>%
tibble::as_tibble() %>%
dplyr::select(-c("Species"))
correlator = pguIMP::pgu.correlator$new(data_df)
pguIMP documentation built on Feb. 20, 2026, 5:08 p.m.
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| pgu.correlator | R Documentation |
pgu.correlator
Description
An R6 class that performs pairwise correlation on the pguIMP data set.
Format
[R6::R6Class] object.
Construction
x <- pguIMP::pgu.correlator$new()
Active bindings
featureNamesReturns the instance variable featureNames. (character)
setFeatureNamesSets the instance variable featureNames. It further initializes the instance variables: intercept, pIntercept, slope, pSlope. (character)
methodReturns the instance variable method. (character)
rReturns the instance variable r. (matrix)
pPearsonReturns the instance variable pPearson. (matrix)
tauReturns the instance variable tau. (matrix)
pKendallReturns the instance variable pKendall. (matrix)
rhoReturns the instance variable rho. (matrix)
pSpearmanReturns the instance variable pSpearman. (matrix)
abscissaReturns the instance variable abscissa. (character)
setAbscissaSets the instance variable abscicca to value.
ordinateReturns the instance variable ordinate. (character)
setOrdinateSets the instance variable ordinate to value.
testReturns the instance variable test. (stats::cor.test)
Methods
Public methods
Method new()
Creates and returns a new 'pgu.correlator' object.
Usage
pgu.correlator$new(data = "tbl_df")
Arguments
dataThe data to be modeled. (tibble::tibble)
Returns
A new 'pgu.correlator' object. (pguIMP::pgu.correlator)
Method finalize()
Clears the heap and indicates if instance of 'pgu.correlator' is removed from heap.
Usage
pgu.correlator$finalize()
Method print()
Prints instance variables of a 'pgu.correlator' object.
Usage
pgu.correlator$print()
Returns
string
Method resetCorrelator()
Performes pair-wise correlation analysis on the attributes of the data frame. Progresse is indicated by the progress object passed to the function.
Usage
pgu.correlator$resetCorrelator(data = "tbl_df", progress = "Progress")
Arguments
dataDataframe with at least two numeric attributes. (tibble::tibble)
progressKeeps track of the analysis progress. (shiny::Progress)
Method resetMatrix()
Creates a square matrix which dimension corresponds to the length of the instance variable featureNames. The matrix entries are set to a distict 'value'.
Usage
pgu.correlator$resetMatrix(value = "numeric")
Arguments
valueThe value the matrix entries are set to. (numeric)
Returns
A square matrix. (matrix)
Method featureIdx()
Determines the numerical index of the column of an attribute based on the attribute name.
Usage
pgu.correlator$featureIdx(feature = "character")
Arguments
featureThe attribute's name. (character)
Returns
The attributes column index. (numeric)
Method calcCorrelationNumeric()
Creates a correlation test between two attributes of a dataframe. The test is stored as instance variable.
Usage
pgu.correlator$calcCorrelationNumeric( abscissa = "numeric", ordinate = "numeric", method = "character" )
Arguments
abscissaThe abscissa values. (numeric)
ordinateThe ordinate values. (numeric)
methodThe cname of the correlation test. Valid coiced are defined by the instance variable 'method'. (chatacter)
Method createCorrelationMatrixPearson()
Performs the actual correlation test routine after Pearson. Iteratively runs through the attributes known to the class and calculates Pearson's correlation for each valid attribute pair. The test results are stored in the instance variables: r, pPearson. Here, pX represents the p-value of the respective parameter X. Displays the progress if shiny is loaded.
Usage
pgu.correlator$createCorrelationMatrixPearson( data = "tbl_df", progress = "Progress" )
Arguments
dataThe data to be analysed. (tibble::tibble)
progressIf shiny is loaded, the analysis' progress is stored within this instance of the shiny Progress class. (shiny::Progress)
Method createCorrelationMatrixKendall()
Performs the actual correlation test routine after Kendall. Iteratively runs through the attributes known to the class and calculates Kendall's correlation for each valid attribute pair. The test results are stored in the instance variables: tau, pKendall. Here, pX represents the p-value of the respective parameter X. Displays the progress if shiny is loaded.
Usage
pgu.correlator$createCorrelationMatrixKendall( data = "tbl_df", progress = "Progress" )
Arguments
dataThe data to be analysed. (tibble::tibble)
progressIf shiny is loaded, the analysis' progress is stored within this instance of the shiny Progress class. (shiny::Progress)
Method createCorrelationMatrixSpearman()
Performs the actual correlation test routine after Spearman. Iteratively runs through the attributes known to the class and calculates Spearman's correlation for each valid attribute pair. The test results are stored in the instance variables: rho, pSpearman. Here, pX represents the p-value of the respective parameter X. Displays the progress if shiny is loaded.
Usage
pgu.correlator$createCorrelationMatrixSpearman( data = "tbl_df", progress = "Progress" )
Arguments
dataThe data to be analysed. (tibble::tibble)
progressIf shiny is loaded, the analysis' progress is stored within this instance of the shiny Progress class. (shiny::Progress)
Method correlate()
Performs the all three correlation test routines defined within the instance variable 'method'. Displays the progress if shiny is loaded.
Usage
pgu.correlator$correlate(data = "tbl_df", progress = "Progress")
Arguments
dataThe data to be analysed. (tibble::tibble)
progressIf shiny is loaded, the analysis' progress is stored within this instance of the shiny Progress class. (shiny::Progress)
Method printFeature()
Transforms the results of the correlation procedure for a valid pair of attributes to a dataframe and returns it.
Usage
pgu.correlator$printFeature()
Returns
The analyis result as a dataframe. (tibble::tibble)
Method printRTbl()
Transfroms instance variable 'r' to a dataframe and returns it.
Usage
pgu.correlator$printRTbl()
Returns
Dataframe of instance variable 'r'. (tibble::tibble)
Method printPPearsonTbl()
Transfroms instance variable 'pPearson' to a dataframe and returns it.
Usage
pgu.correlator$printPPearsonTbl()
Returns
Dataframe of instance variable 'pPearson'. (tibble::tibble)
Method printTauTbl()
Transfroms instance variable 'tau' to a dataframe and returns it.
Usage
pgu.correlator$printTauTbl()
Returns
Dataframe of instance variable 'tau'. (tibble::tibble)
Method printPKendallTbl()
Transfroms instance variable 'pKendall' to a dataframe and returns it.
Usage
pgu.correlator$printPKendallTbl()
Returns
Dataframe of instance variable 'pKendall'. (tibble::tibble)
Method printRhoTbl()
Transfroms instance variable 'rho' to a dataframe and returns it.
Usage
pgu.correlator$printRhoTbl()
Returns
Dataframe of instance variable 'rho'. (tibble::tibble)
Method printPSpearmanTbl()
Transfroms instance variable 'pSpearman' to a dataframe and returns it.
Usage
pgu.correlator$printPSpearmanTbl()
Returns
Dataframe of instance variable 'pSpearman'. (tibble::tibble)
Method clone()
The objects of this class are cloneable with this method.
Usage
pgu.correlator$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
Author(s)
Sebastian Malkusch
Examples
require(dplyr)
require(tibble)
data(iris)
data_df <- iris %>%
tibble::as_tibble() %>%
dplyr::select(-c("Species"))
correlator = pguIMP::pgu.correlator$new(data_df)
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