R/defaults.R

In mdatools: Multivariate Data Analysis for Chemometrics

#' Show plot with several figures of merit vs. number of components (generic function).
#'
#' @param obj
#' result object, e.g. \code{ddsimcares}
#' @param ...
#' other parameters relevant for the method
#'
#' @export
plotFoMs <- function(obj, ...) {
   UseMethod("plotFoMs")
}


#' Show plot with figure of merit vs. number of components (generic function).
#'
#' @param obj
#' result object, e.g. \code{ddsimcares}
#' @param ...
#' other parameters relevant for the method
#'
#' @export
plotFoM <- function(obj, ...) {
   UseMethod("plotFoM")
}


#' Set model parameters other than number of components (generic function)
#'
#' @param obj
#' model object, e.g. \code{ddsimca}
#' @param ...
#' other parameters relevant for the method
#'
#' @export
setParams <- function(obj, ...) {
   UseMethod("setParams")
}


#' Selectivity vs sensitivity plot for DD-SIMCA results (generic function)
#'
#' @param obj
#' result object, e.g. \code{ddsimcares}
#' @param ...
#' other parameters relevant for the plot
#'
#' @export
plotSelectivityArea <- function(obj, ...) {
   UseMethod("plotSelectivityArea")
}

#' Aliens plot for DD-SIMCA results (generic function)
#'
#' @param obj
#' result object, e.g. \code{ddsimcares}
#' @param ...
#' other parameters relevant for the plot
#'
#' @export
plotAliens <- function(obj, ...) {
   UseMethod("plotAliens")
}


#' Distance plot for model and results (generic function)
#'
#' @param obj
#' model or result object, e.g. \code{ddsimcares}
#' @param ...
#' other parameters relevant for the plot
#'
#' @export
plotDistances <- function(obj, ...) {
   UseMethod("plotDistances")
}


#' Acceptance plot for DDSIMCA model and results (generic function)
#'
#' @param obj
#' model or result object, e.g. \code{ddsimcares}
#' @param ...
#' other parameters relevant for the plot
#'
#' @export
plotAcceptance <- function(obj, ...) {
   UseMethod("plotAcceptance")
}


#' S3 implementation of asjson() method
#'
#' @param obj
#' object of any class, e.g. \code{pca}
#' @param ...
#' other parameters relevant for the method
#'
#' @export
asjson <- function(obj, ...) {
   UseMethod("asjson")
}


#' S3 implementation of as.vector() method
#'
#' @param obj
#' object of any class, e.g. \code{pca}
#'
#' @export
asvector <- function(obj) {
   UseMethod("asvector")
}


#' Save model as JSON file
#'
#' @param obj
#' model object, e.g. \code{pca}
#' @param fileName
#' name (or full path) to JSON file to be created.
#'
#' @export
writeJSON <- function(obj, fileName) {
   UseMethod("writeJSON")
}


#' Method to write outcomes of any result object to CSV file
#'
#' @param res
#' result object (\code{plsres}, \code{pcares}, etc.).
#' @param fileName
#' name (or full path) to CSV file to be created.
#' @param name
#' short name of the result object (e.g. \code{"cal"}, \code{"test"}. etc.).
#' @param sep
#' values separator (either \code{","} or \code{";"}).
#' @param dataFile
#' optional, name of the data file used to create the results.
#' @param ...
#' other optional parameters
#'
#' @export
writeCSV <- function(res, fileName, name, sep = ",", dataFile = "", ...) {
   UseMethod("writeCSV")
}



#' Plot for ratio RMSEC/RMSECV vs RMSECV
#' @param obj
#' object with any regression model
#' @param ...
#' other parameters
#'
#' @export
plotRMSERatio <- function(obj, ...) {
   UseMethod("plotRMSERatio")
}

#' Plot purity spectra
#' @param obj
#' object with mcr pure case
#' @param ...
#' other parameters
#'
#' @export
plotPuritySpectra <- function(obj, ...) {
   UseMethod("plotPuritySpectra")
}

#' Plot purity values
#' @param obj
#' object with mcr pure case
#' @param ...
#' other parameters
#'
#' @export
plotPurity <- function(obj, ...) {
   UseMethod("plotPurity")
}

#' Plot resolved spectra
#' @param obj
#' object with mcr case
#' @param ...
#' other parameters
#'
#' @export
plotSpectra <- function(obj, ...) {
   UseMethod("plotSpectra")
}

#' Plot resolved contributions
#' @param obj
#' object with mcr case
#' @param ...
#' other parameters
#'
#' @export
plotContributions <- function(obj, ...) {
   UseMethod("plotContributions")
}

#' Categorize PCA results
#' @param obj
#' object with PCA model
#' @param ...
#' other parameters
#'
#' @export
categorize <- function(obj, ...) {
   UseMethod("categorize")
}

#' Confusion matrix for classification results
#'
#' @details
#' Returns confusion matrix for classification results represented by the object.
#'
#' @param obj
#' classification results (object of class \code{simcares}, \code{simcamres}, etc)
#' @param ...
#' other parameters.
#'
#' @export
getConfusionMatrix <- function(obj, ...) {
   UseMethod("getConfusionMatrix")
}

#' Plot for class belonging probability
#'
#' @description
#' Makes a plot with class belonging probabilities for each object of the classification results.
#' Works only with classification methods, which compute this probability (e.g. SIMCA).
#'
#' @param obj
#' an object with classification results (e.g. SIMCA)
#' @param ...
#' other parameters
#'
#' @export
plotProbabilities <- function(obj, ...) {
   UseMethod("plotProbabilities")
}

#' Get class belonging probability
#'
#' @description
#' Compute class belonging probabilities for classification results.
#'
#' @param obj
#' an object with classification results (e.g. SIMCA)
#' @param ...
#' other parameters
#'
#' @export
getProbabilities <- function(obj, ...) {
   UseMethod("getProbabilities")
}

#' Set residual distance limits
#'
#' @description
#' Calculates and sets critical limits for residuals of PCA model
#'
#' @param obj
#' a model object
#' @param ...
#' other parameters
#'
#' @export
setDistanceLimits <- function(obj, ...) {
   UseMethod("setDistanceLimits")
}

#' Show residual distance limits
#'
#' @description
#' Shows critical limits for residuals of PCA model
#'
#' @param obj
#' a model object
#' @param ...
#' other parameters
#'
#' @export
showDistanceLimits <- function(obj, ...) {
   UseMethod("showDistanceLimits")
}

#' Shows extreme plot for PCA and DD-SIMCA models
#'
#' @description
#' Generic function for creating extreme plot for PCA and DD-SIMCA models
#'
#' @param obj
#' a PCA or DD-SIMCA model
#' @param ...
#' other parameters
#'
#' @export
plotExtreme <- function(obj, ...) {
   UseMethod("plotExtreme")
}

#' Shows extreme plot for PCA and DD-SIMCA models
#'
#' @description
#' Generic function for creating extreme plot for PCA and DD-SIMCA models
#'
#' @param obj
#' a PCA or DD-SIMCA model
#' @param ...
#' other parameters
#'
#' @export
plotExtremes <- function(obj, ...) {
   UseMethod("plotExtremes")
}

#' Get regression coefficients
#'
#' @description
#' Generic function for getting regression coefficients from PLS model
#'
#' @param obj
#' a PLS model
#' @param ...
#' other parameters
#'
#' @export
getRegcoeffs <- function(obj, ...) {
   UseMethod("getRegcoeffs")
}

#' VIP scores plot
#'
#' @description
#' Generic function for plotting VIP scores values for regression model (PCR, PLS, etc)
#'
#' @param obj
#' a regression model
#' @param ...
#' other parameters
#'
#' @export
plotVIPScores <- function(obj, ...) {
   UseMethod("plotVIPScores")
}

#' VIP scores
#'
#' @description
#' Generic function for returning VIP scores values for regression model (PCR, PLS, etc)
#'
#' @param obj
#' a regression model
#' @param ...
#' other parameters
#'
#' @export
getVIPScores <- function(obj, ...) {
   UseMethod("getVIPScores")
}

#' Selectivity ratio plot
#'
#' @description
#' Generic function for plotting selectivity ratio values for regression model (PCR, PLS, etc)
#'
#' @param obj
#' a regression model
#' @param ...
#' other parameters
#'
#' @export
plotSelectivityRatio <- function(obj, ...) {
   UseMethod("plotSelectivityRatio")
}

#' Selectivity ratio
#'
#' @description
#' Generic function for returning selectivity ratio values for regression model (PCR, PLS, etc)
#'
#' @param obj
#' a regression model
#' @param ...
#' other parameters
#'
#' @export
getSelectivityRatio <- function(obj, ...) {
   UseMethod("getSelectivityRatio")
}

#' Select optimal number of components for a model
#'
#' @description
#' Generic function for selecting number of components for multivariate models (e.g. PCA, PLS, ...)
#'
#' @param obj
#' a model object
#' @param ncomp
#' number of components to select
#' @param ...
#' other arguments
#'
#' @export
selectCompNum <- function(obj, ncomp = NULL, ...) {
   UseMethod("selectCompNum")
}

#' Cooman's plot
#'
#' @details
#' Generic function for Cooman's plot
#'
#' @param obj
#' classification model or result object
#' @param ...
#' other arguments
#'
#' @export
plotCooman <- function(obj, ...) {
   UseMethod("plotCooman")
}

#' Model distance plot
#'
#' @details
#' Generic function for plotting distance from object to a multivariate model
#'
#' @param obj
#' a model object
#' @param ...
#' other arguments
#'
#' @export
plotModelDistance <- function(obj, ...) {
   UseMethod("plotModelDistance")
}

#' Discrimination power plot
#'
#' @details
#' Generic function for plotting discrimination power values for classification model
#'
#' @param obj
#' a model object
#' @param ...
#' other arguments
#'
#' @export
plotDiscriminationPower <- function(obj, ...) {
   UseMethod("plotDiscriminationPower")
}

#' Calibration data
#'
#' @details
#' Generic function getting calibration data from a linear decomposition model (e.g. PCA)
#'
#' @param obj
#' a model object
#'
#' @export
getCalibrationData <- function(obj) {
   UseMethod("getCalibrationData")
}

#' Modelling power plot
#'
#' @details
#' Generic function for plotting modelling power values for classification model
#'
#' @param obj
#' a model object
#' @param ...
#' other arguments
#'
#' @export
plotModellingPower <- function(obj, ...) {
   UseMethod("plotModellingPower")
}

#' Misclassification ratio plot
#'
#' @details
#' Generic function for plotting misclassification values for classification model or results
#'
#' @param obj
#' a model or a result object
#' @param ...
#' other arguments
#'
#' @export
plotMisclassified <- function(obj, ...) {
   UseMethod("plotMisclassified")
}

#' Specificity plot
#'
#' @details
#' Generic function for plotting specificity values for classification model or results
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotSpecificity <- function(obj, ...) {
   UseMethod("plotSpecificity")
}

#' Sensitivity plot
#'
#' @details
#' Generic function for plotting sensitivity values for classification model or results
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotSensitivity <- function(obj, ...) {
   UseMethod("plotSensitivity")
}

#' Classification performance plot
#'
#' @details
#' Generic function for plotting classification performance for model or results
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotPerformance <- function(obj, ...) {
   UseMethod("plotPerformance")
}

#' Predictions
#'
#' @details
#' Generic function for showing predicted values for classification or regression model or results
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
showPredictions <- function(obj, ...) {
   UseMethod("showPredictions")
}

#' X residuals plot
#'
#' @details
#' Generic function for plotting x residuals for classification or regression model or results
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotXResiduals <- function(obj, ...) {
   UseMethod("plotXResiduals")
}

#' Y residuals plot
#'
#' @details
#' Generic function for plotting y residuals for classification or regression model or results
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotYResiduals <- function(obj, ...) {
   UseMethod("plotYResiduals")
}

#' X variance plot
#'
#' @details
#' Generic function for plotting explained variance for decomposition of x data
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotXVariance <- function(obj, ...) {
   UseMethod("plotXVariance")
}

#' Y variance plot
#'
#' @details
#' Generic function for plotting explained variance for decomposition of y data
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotYVariance <- function(obj, ...) {
   UseMethod("plotYVariance")
}

#' Biplot
#'
#' @details
#' Generic function for biplot
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotBiplot <- function(obj, ...) {
   UseMethod("plotBiplot")
}

#' Scores plot
#'
#' @details
#' Generic function for scores values for data decomposition
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotScores <- function(obj, ...) {
   UseMethod("plotScores")
}

#' X scores plot
#'
#' @details
#' Generic function for plotting scores values for decomposition of x data
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotXScores <- function(obj, ...) {
   UseMethod("plotXScores")
}

#' XY scores plot
#'
#' @details
#' Generic function for plotting scores values for decomposition of x and y data
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotXYScores <- function(obj, ...) {
   UseMethod("plotXYScores")
}

#' Selected intervals plot
#'
#' @details
#' Generic function for plotting selected intervals or variables
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotSelection <- function(obj, ...) {
   UseMethod("plotSelection")
}

#' RMSE plot
#'
#' @details
#' Generic function for plotting RMSE values vs. complexity of a regression model
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotRMSE <- function(obj, ...) {
   UseMethod("plotRMSE")
}

#' Variance plot
#'
#' @details
#' Generic function for plotting explained variance for data decomposition
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotCumVariance <- function(obj, ...) {
   UseMethod("plotCumVariance")
}

#' X cumulative variance plot
#'
#' @details
#' Generic function for plotting cumulative explained variance for decomposition of x data
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotXCumVariance <- function(obj, ...) {
   UseMethod("plotXCumVariance")
}

#' Y cumulative variance plot
#'
#' @details
#' Generic function for plotting cumulative explained variance for decomposition of y data
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotYCumVariance <- function(obj, ...) {
   UseMethod("plotYCumVariance")
}

#' Loadings plot
#'
#' @details
#' Generic function for plotting loadings values for data decomposition
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotLoadings <- function(obj, ...) {
   UseMethod("plotLoadings")
}

#' Predictions plot
#'
#' @details
#' Generic function for plotting predicted values for classification or regression model or results
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotPredictions <- function(obj, ...) {
   UseMethod("plotPredictions")
}

#' Regression coefficients plot
#'
#' @details
#' Generic function for plotting regression coefficients values for a regression model
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotRegcoeffs <- function(obj, ...) {
   UseMethod("plotRegcoeffs")
}

#' Residuals plot
#'
#' @details
#' Generic function for plotting residual values for data decomposition
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotResiduals <- function(obj, ...) {
   UseMethod("plotResiduals")
}

#' Variance plot
#'
#' @details
#' Generic function for plotting explained variance for data decomposition
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotVariance <- function(obj, ...) {
   UseMethod("plotVariance")
}

#' Eigenvalues plot
#'
#' @details
#' Generic function for plotting eigenvalues vs. number of components
#'
#' @param obj
#' a model object
#' @param ...
#' other arguments
#'
#' @export
plotEigenvalues <- function(obj, ...) {
   UseMethod("plotEigenvalues")
}

#' X loadings plot
#'
#' @details
#' Generic function for plotting loadings values for decomposition of x data
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotXLoadings <- function(obj, ...) {
   UseMethod("plotXLoadings")
}

#' XY loadings plot
#'
#' @details
#' Generic function for plotting loadings values for decomposition of x and y data
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotXYLoadings <- function(obj, ...) {
   UseMethod("plotXYLoadings")
}

#' Statistic histogram
#'
#' @details
#' Generic function for plotting statistic histogram plot
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotHist <- function(obj, ...) {
   UseMethod("plotHist")
}

#' Correlation plot
#'
#' @details
#' Generic function for correlation plot
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotCorr <- function(obj, ...) {
   UseMethod("plotCorr")
}

#' Plot for PLS weights
#'
#' @details
#' Generic function for weight plot
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotWeights <- function(obj, ...) {
   UseMethod("plotWeights")
}

#' Plot for XY-residuals
#'
#' @details
#' Generic function for XY-residuals plot
#'
#' @param obj
#' a model or result object
#' @param ...
#' other arguments
#'
#' @export
plotXYResiduals <- function(obj, ...) {
   UseMethod("plotXYResiduals")
}