R/XPSFitCompClass.r
In GSperanza/RxpsG_2.3-1: Processing Tool for X-ray Photoelectron Spectroscopy Data
###
### Classes and methods for describing fit components
###
#' @title Class "fitComponents"
#' @description a class that describes a fit component. The class has the
#' definition of all the necessary informations needed to use a fit component
#' algorithm store all the related infromation, enable specific plot functionalities
#' Objects from the Class: Objects can be created by calls of the form
#' \code{new("fitComponents", ...)}.
#' @slot funcName the name of the fitting function
#' @slot description the description of the fitting function
#' @slot label label of the fit component associated to the added fit component
#' @slot param the list of fitting parameters
#' @slot rsf the RSF associated to the fit component (the same as that of the Core-Line)
#' @slot ycoor the y values of the best fit
#' @slot link the list containing the series of links associated to this fit component
#' @examples
#' \dontrun{
#' showClass("fitComponents")
#' }
#' @export
#'
setClass("fitComponents",
representation(funcName = "character",
description = "character",
label = "character",
param = "data.frame",
rsf = "numeric",
ycoor = "numeric",
link = "list"
),
prototype(param = data.frame( start = NA, min = NA, max = NA)[0,] ),
validity = function(object) {
if (!identical(names(object@param),
c("start","min","max")))
return("The param slot does not have the correct column names")
return(TRUE)
}
)
## Accessor functions:
#setGeneric("label", function(object) standardGeneric("label"))
#setMethod("label", "fitComponents", function(object) object@label)
#setGeneric("funcName", function(object) standardGeneric("funcName"))
#setMethod("funcName", "fitComponents", function(object) object@funcName)
#' @title setParam
#' @description S4method 'setParam' method for setting fitting parameters.
#' @param object an object of class \code{XPSCoreLine}
#' @param parameter character is one of the "start", "max" or "min" parameter to be set
#' @param variable character as "mu", "sigma"... indicates the parameter to set
#' @param value numeric the value to set
#' @return 'setParam' returns the object withthe parameter set
setGeneric("setParam", function(object, parameter=NULL, variable=NULL, value= NULL) standardGeneric("setParam"))
#' @title setParam
#' @description method to set fitting parameters of a object@Component[[j]]
#' where object is of class 'XPSCoreLine' and j indicates the jth fit component
#' @param object a Core_Line object of class \code{XPSCoreLine}
#' @param parameter character is one of the "start", "max" or "min" parameter to be set
#' @param variable character as "mu", "sigma"... indicates the parameter to set
#' @param value numeric the value to set
#' @return 'setParam' returns the object withthe parameter set
#' @examples
#' \dontrun{
#' setParam(test[["C1s"]]@Component[[2]], parameter="start", variable="mu", value="285")
#' }
#' @export
setMethod("setParam", "fitComponents", function(object, parameter=NULL, variable=NULL, value=NULL)
{
if ( is.null(value) ) stop(" value is required.")
rownamesParam <- rownames(slot(object,"param"))
if ( ! is.null(parameter) ) {
parameter <- match.arg(parameter,c("start","min", "max")) #set the single value START, MIN, MAX
if ( ! is.null(variable) ) {
variable <- match.arg(variable, rownamesParam)
slot(object,"param")[variable,parameter] <- value
} else {
if (length(value) != length(rownamesParam) )
stop("wrong value length")
else
slot(object,"param")[,parameter] <- value
}
} else {
if ( is.null(variable) ) {
warning(" if 'parameter' = NULL then 'variable' must be != NULL.")
} else if (variable == "all"){
LL <- length(rownamesParam)
for(ii in 1:LL){
parma <- rownamesParam[ii]
slot(object,"param")[variable,] <- value
}
} else {
variable <- match.arg(variable, rownamesParam)
if (length(value) != 3 ) { stop("wrong value length") } #set all three values START, MIN, MAX
else { slot(object,"param")[variable,] <- value }
}
}
invisible(object)
}
)
#' @title getParam
#' @description S4method 'getParam' method for get information about a fitting parameters.
#' @param object an object of class \code{XPSCoreLine}
#' @param parameter character is one of the "start", "max" or "min" parameter to be set
#' @param variable character as "mu", "sigma"... indicates the parameter to set
#' @return 'getParam' returns the value of the requested parameter
setGeneric("getParam", function(object, parameter=NULL, variable=NULL) standardGeneric("getParam"))
#' @title getParam
#' @description method to get the value of the specified fitting parameter from an object@Component[[j]]
#' where object is of class 'XPSCoreLine' and j indicates the jth fit component
#' @param object a Core_Line object of class \code{XPSCoreLine}
#' @param parameter character is one of the "start", "max" or "min" parameter to be set
#' @param variable character as "mu", "sigma"... indicates the parameter to set
#' @return 'getParam' returns the value of the requested parameter
#' @examples
#' \dontrun{
#' getParam(test[["C1s"]]@Component[[2]], parameter="start", variable="mu")
#' }
#' @export
setMethod("getParam", "fitComponents", function(object, parameter=NULL, variable=NULL)
{
if ( ! is.null(parameter) ) {
parameter <- match.arg(parameter,c("start","min", "max"))
if ( is.null(variable) ) { value <- slot(object,"param")[,parameter] }
else {
variable <- match.arg(variable, rownames(object@param))
value <- slot(object,"param")[variable,parameter]
}
} else {
if ( is.null(variable) ) {
warning(" if 'parameter' = NULL then 'variable' must be != NULL.")
} else {
variable <- match.arg(variable, rownames(object@param))
value <- slot(object,"param")[variable,]
}
}
return(value)
}
)
##==============================================================================
# returns a list with the y values for the component n
##==============================================================================
#' @title Ycomponent
#' @description S4method 'Ycomponent' method for generate the Y values of the
#' fit component using the chosen fitting function and the associated fit parameters
#' @param object a fit component object of the type CL@Components[[j]] where
#' CL is of class 'XPSCoreLine', j indicates the jth fit component
#' @param x numeric vector of the type CL@RegionToFit$x where
#' CL is of class 'XPSCoreLine'
#' @param y numeric vector of the type CL@Baseline$y where
#' CL is of class 'XPSCoreLine'
#' @return 'Ycomponent' returns Baseline subtracted vales of the fit component
setGeneric("Ycomponent", function(object, x, y) standardGeneric("Ycomponent"))
#' @title Ycomponent
#' @description S4method 'Ycomponent' method for generate the Y values of the
#' fit component using the chosen fitting function and the associated fit parameters
#' @param object a fit component object of the type CL@Components[[j]] where
#' CL is of class 'XPSCoreLine', j indicates the jth fit component
#' @param x numeric vector of the type CL@RegionToFit$x where
#' CL is of class 'XPSCoreLine'
#' @param y numeric vector of the type CL@Baseline$y where
#' CL is of class 'XPSCoreLine'
#' @return 'Ycomponent' returns Baseline subtracted vales of the fit component
#' @examples
#' \dontrun{
#' Ycomponent(test[["C1s"]]@Component[[2]],test[["C1s"]]@RegionToFit$x, test[["C1s"]]@Baseline$y)
#' }
#' @export
setMethod("Ycomponent", signature(object="fitComponents"),
function(object, x, y)
{
# let's take the starting values
startPar <- getParam(object, parameter = "start")
# combine x with start values
parm <- list(x=x) # x = object@RegionToFit$x
parm <- c(parm,startPar)
# formula e parameters to do the call
fmla <- slot(object,"funcName")
names(parm) <- formalArgs(fmla)
# calculate y values using the fit lineshape=funcName for the given x values
ycomponent <- do.call(fmla, parm)
# exit with ycomp + Baseline$y
slot(object, "ycoor") <- ( ycomponent + y ) # y=object@Baseline$y
return(object)
}
)
## fitAlgorithms is a list containing the default data defining each of the fit functions
fitAlgorithms <- list(
Initialize = new("fitComponents",
funcName = "Initialize",
description = "Symmetric Function(h, mu, sigma)",
label = "",
param = data.frame(
row.names = c("h", "mu", "sigma"), # min and max values are set in XPSaddFitComponent()
start = c(NA, NA, NA),
min = c(NA, NA, NA),
max = c(NA, NA, NA) ),
ycoor = 0,
rsf = 0,
link = list()
),
Generic = new("fitComponents",
funcName = "Generic",
description = "Generic Function(x)",
label = "",
param = data.frame(
start = c(NA, NA, NA),
min = c(NA, NA, NA),
max = c(NA, NA, NA) ),
ycoor = 0,
rsf = 0,
link = list()
),
Gauss = new("fitComponents",
funcName = "Gauss",
description = "Symmetric Gaussian shape",
label = "Gauss",
param = data.frame(
row.names = c("h", "mu", "sigma"),
start = c(1, NA, 1),
min = c(0, 0, 0.1),
max = c(Inf, Inf, 10) ),
ycoor = 0,
rsf = 0,
link = list()
),
Lorentz = new("fitComponents",
funcName = "Lorentz",
description = "Symmetric Lorentz shape",
label = "Lorentz",
param = data.frame(
row.names = c("h", "mu", "sigma"),
start = c(1, NA, 0.7),
min = c(0, 0, 0.1),
max = c(Inf, Inf, 10) ),
ycoor = 0,
rsf = 0,
link = list()
),
Voigt = new("fitComponents",
funcName = "Voigt",
description = "Symmetric Voigt shape",
label = "Voigt",
param = data.frame(
row.names = c("h", "mu", "sigma", "lg"),
start = c(1, NA, 1, 0.2),
min = c(0, 0, 0.05, 0.01),
max = c(Inf, Inf, 10, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
Sech2 = new("fitComponents",
funcName = "Sech2",
description = "Symmetric Sech2 shape",
label = "Sech2",
param = data.frame(
row.names = c("h", "mu", "sigma"),
start = c(1, NA, 0.5),
min = c(0, 0, 0.1),
max = c(Inf, Inf, 10) ),
ycoor = 0,
rsf = 0,
link = list()
),
GaussLorentzProd = new("fitComponents",
funcName = "GaussLorentzProd",
description = "Symmetric Gaussian Lorentz cross product form",
label = "GaussLorentzProd",
param = data.frame(
row.names = c("h", "mu", "sigma", "lg"),
start = c(1, NA, 1, 0.75),
min = c(0, 0, 0.1, 0.01),
max = c(Inf, Inf, 10, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
GaussLorentzSum = new("fitComponents",
funcName = "GaussLorentzSum",
description = "Symmetric Gaussian Lorentz Sum Form",
label = "GaussLorentzSum",
param = data.frame(
row.names = c("h", "mu", "sigma", "lg"),
start = c(1, NA, 1, 0.95),
min = c(0, 0, 0.1, 0),
max = c(Inf, Inf, 10, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
AsymmGauss = new("fitComponents",
funcName = "AsymmGauss",
description = "Simple Asymmetric Gaussian shape",
label = "AsymmGauss",
param = data.frame(
row.names = c("h", "mu", "sigma", "asym"), #min e max values are set in XPSaddFitComponent()
start = c(1, NA, 1, 0.3),
min = c(0, 0, 0.05, 0.01),
max = c(Inf, Inf, 10, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
AsymmLorentz = new("fitComponents",
funcName = "AsymmLorentz",
description = "Simple Asymmetric Lorentz shape",
label = "AsymmLorentz",
param = data.frame(
row.names = c("h", "mu", "sigma", "asym"), #min e max values are set in XPSaddFitComponent()
start = c(1, NA, 0.7, 0.3),
min = c(0, 0, 0.1, 0.01),
max = c(Inf, Inf, 10, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
AsymmVoigt = new("fitComponents",
funcName = "AsymmVoigt",
description = "Asymmetric Voigt shape",
label = "AsymmVoigt",
param = data.frame(
row.names = c("h", "mu", "sigma", "lg", "asym"), #min e max values are set in XPSaddFitComponent()
start = c(1, NA, 0.4, 0.1, 0.1),
min = c(0, 0, 0.1, 0.01, 0.01),
max = c(Inf, Inf, 10, 1, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
AsymmGaussLorentz = new("fitComponents",
funcName = "AsymmGaussLorentz",
description = "Asymmetric Gaussian Lorentz used in Genplot",
label = "AsymmGaussLorentz",
param = data.frame(
row.names = c("h", "mu", "sigma", "lg", "asym"),
start = c(1, NA, 1, 0.3, 0.45),
min = c(0, 0, 0.05, 0.4, 1e-5),
max = c(Inf, Inf, 5, 1, 0.4) ),
ycoor = 0,
rsf = 0,
link = list()
),
AsymmGaussVoigt = new("fitComponents",
funcName = "AsymmGaussVoigt",
description = "Asymmetric Line-Shape from CasaXPS",
label = "AsymmGaussVoigt",
param = data.frame(
row.names = c("h", "mu", "sigma", "lg", "asym", "gv"),
start = c(1, NA, 0.6, 0.1, 0.2, 0.4),
min = c(0, 0, 0.01, 0.01, 0.01, 0.01),
max = c(Inf, Inf, 5, 1, 1, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
AsymmGaussLorentzProd = new("fitComponents",
funcName = "AsymmGaussLorentzProd",
description = "Asym Gaussian Lorentz cross product from UNIFIT Publication",
label = "AsymmGaussLorentzProd",
param = data.frame(
row.names = c("h", "mu", "sigma", "asym", "lg"),
start = c(1, NA, 1, 0.2, 0.8),
min = c(0, 0, 0.05, 0.1, 1e-5),
max = c(Inf, Inf, 5, 1, 0.4) ),
ycoor = 0,
rsf = 0,
link = list()
),
DoniachSunjic = new("fitComponents",
funcName = "DoniachSunjic",
description = "Asymm. DoniachSunjic shape",
label = "DoniachSunjic",
param = data.frame(
row.names = c("h", "mu", "sigmaDS", "asym"),
start = c(1, NA, 1, 0.02),
min = c(0, 0, 0.01, 0.01),
max = c(Inf, Inf, 10, 1)),
ycoor = 0,
rsf = 0,
link = list()
),
DoniachSunjicTail = new("fitComponents",
funcName = "DoniachSunjicTail",
description = "Asymm. DoniachSunjic shape Tail corrected",
label = "DoniachSunjicTail",
param = data.frame(
row.names = c("h", "mu", "sigmaDS", "asym", "tail"),
start = c(1, NA, 1, 0.05, 0.2),
min = c(0, 0, 0.01, 0.01, 0.01),
max = c(Inf, Inf, 10, 1, 5) ),
ycoor = 0,
rsf = 0,
link = list()
),
DoniachSunjicGauss = new("fitComponents",
funcName = "DoniachSunjicGauss",
description = "Asymm. DoniachSunjic shape + GaussBroadening",
label = "DoniachSunjicGauss",
param = data.frame(
row.names = c("h", "mu", "sigmaDS", "sigmaG", "asym"),
start = c(1, NA, 1, 0.8, 0.02),
min = c(0, 0, 0.01, 0.01, 0.01),
max = c(Inf, Inf, 5, 5, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
DoniachSunjicGaussTail = new("fitComponents",
funcName = "DoniachSunjicGaussTail",
description = "Asymm. DoniachSunjic shape + GaussBroadening and Tail correction",
label = "DoniachSunjicGaussTail",
param = data.frame(
row.names = c("h", "mu", "sigmaDS", "sigmaG", "asym", "tail"),
start = c(1, NA, 1, 0.8, 0.02, 0.2),
min = c(0, 0, 0.01, 0.01, 0.01, 0.01),
max = c(Inf, Inf, 5, 5, 1, 5) ),
ycoor = 0,
rsf = 0,
link = list()
),
SimplifiedDoniachSunjic = new("fitComponents",
funcName = "SimplifiedDoniachSunjic",
description = "Asymmetric DoniachSunjic shape",
label = "SimplifiedDoniachSunjic",
param = data.frame(
row.names = c("h", "mu", "sigma", "asym"),
start = c(1, NA, 0.6, 0.02),
min = c(0, 0, 0.01, 0.01),
max = c(Inf, Inf, 5, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
#----- Special Fit Components -----
Linear = new("fitComponents",
funcName = "Linear",
description = "Linear Fit",
label = "Linear",
param = data.frame(
row.names = c("m", "c", "mu"), #min e max values are set in XPSaddFitComponent()
start = c(NA, 0, NA),
min = c(-Inf, -Inf, NA),
max = c(Inf, Inf, NA) ),
ycoor = 0,
rsf = 0,
link = list()
),
ExpDecay = new("fitComponents",
funcName = "ExpDecay",
description = "Exponential Decay",
label = "ExpDecay",
param = data.frame(
row.names = c("h", "mu", "k", "c"), #min e max values are set in XPSaddFitComponent()
start = c(1, NA, 1, 0),
min = c(0, 0, 0, 0),
max = c(Inf, Inf, 5, Inf) ),
ycoor = 0,
rsf = 0,
link = list()
),
PowerDecay = new("fitComponents",
funcName = "PowerDecay",
description = "Power Law Decay",
label = "PowerDecay",
param = data.frame(
row.names = c("h", "mu", "pow", "c"), #min e max values are set in XPSaddFitComponent()
start = c(1, NA, 2, 0),
min = c(0, 0, 0.1, 0),
max = c(Inf, Inf, 5, Inf) ),
ycoor = 0,
rsf = 0,
link = list()
),
Sigmoid = new("fitComponents",
funcName = "Sigmoid",
description = "Sigmoid function",
label = "Sigmoid",
param = data.frame(
row.names = c("h", "mu", "k", "c"), #min e max values are set in XPSaddFitComponent()
start = c(1, NA, 1, 0),
min = c(0, 0, 0, 0),
max = c(Inf, Inf, 5, Inf) ),
ycoor = 0,
rsf = 0,
link = list()
),
HillSigmoid = new("fitComponents",
funcName = "HillSigmoid",
description = "Hill Sigmoid function",
label = "HS",
param = data.frame(
row.names = c("h", "mu", "pow", "A", "B"), #mu, A, B values are set by do.fit() in XPSVBTopGUI()
start = c(NA, NA, 8, NA, NA),
min = c(0, 0, 0, 0, 0),
max = c(Inf, Inf, 50, Inf, Inf) ),
ycoor = 0,
rsf = 0,
link = list()
),
HillSigmoid.KE = new("fitComponents",
funcName = "HillSigmoid.KE",
description = "Hill Sigmoid function",
label = "HS",
param = data.frame(
row.names = c("h", "mu", "pow", "A", "B"), #mu, A, B values are set by do.fit() in XPSVBTopGUI()
start = c(NA, NA, 8, NA, NA),
min = c(0, 0, 0, 0, 0),
max = c(Inf, Inf, 50, Inf, Inf) ),
ycoor = 0,
rsf = 0,
link = list()
),
VBFermi = new("fitComponents",
funcName = "VBFermi",
description = "Fermi Distribution function",
label = "Ef",
param = data.frame(
row.names = c("h", "mu", "k"),
start = c(1, 0, 1),
min = c(0, 0, 0),
max = c(10, 2, 5) ),
ycoor = 0,
rsf = 0,
link = list()
),
VBtop = new("fitComponents", #Together with FitAlgorithms this is needeed to create a slot
funcName = "VBtop", #in the ...@Components[[ii]]@param location of the XPSSample
description = "VBtop fit", #where to save the VBtop position.
label = "VBtop", #This slot is sensitive to the EnergyShift function
param = data.frame(
row.names = c("mu"),
start = c(NA),
min = c(NA),
max = c(NA) ),
ycoor = 0,
rsf = 0,
link = list()
),
Derivative = new("fitComponents", #Together with FitAlgorithms this is needeed to create a slot
funcName = "Derivative", #in the ...@Components[[ii]]@param location of the XPSSample
description = "First Derivative", #where to save the core line first derivative.
label = "D1", #This slot is sensitive to the EnergyShift function
param = data.frame(
row.names = c("mu"),
start = c(NA),
min = c(NA),
max = c(NA) ),
ycoor = 0,
rsf = 0,
link = list()
),
FitProfile = new("fitComponents",
funcName = "FitProfile",
description = "Depth Profile",
label = "DepthP.",
param = data.frame(
row.names = c("R.I", "d", "La", "Lb"), #min e max values are set in XPSaddFitComponent()
start = c(NA, 10, NA, NA),
min = c(NA, 0, NA, NA),
max = c(NA, 50, NA, NA) ),
ycoor = 0,
rsf = 0,
link = list()
)
)
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###
### Classes and methods for describing fit components
###
#' @title Class "fitComponents"
#' @description a class that describes a fit component. The class has the
#' definition of all the necessary informations needed to use a fit component
#' algorithm store all the related infromation, enable specific plot functionalities
#' Objects from the Class: Objects can be created by calls of the form
#' \code{new("fitComponents", ...)}.
#' @slot funcName the name of the fitting function
#' @slot description the description of the fitting function
#' @slot label label of the fit component associated to the added fit component
#' @slot param the list of fitting parameters
#' @slot rsf the RSF associated to the fit component (the same as that of the Core-Line)
#' @slot ycoor the y values of the best fit
#' @slot link the list containing the series of links associated to this fit component
#' @examples
#' \dontrun{
#' showClass("fitComponents")
#' }
#' @export
#'
setClass("fitComponents",
representation(funcName = "character",
description = "character",
label = "character",
param = "data.frame",
rsf = "numeric",
ycoor = "numeric",
link = "list"
),
prototype(param = data.frame( start = NA, min = NA, max = NA)[0,] ),
validity = function(object) {
if (!identical(names(object@param),
c("start","min","max")))
return("The param slot does not have the correct column names")
return(TRUE)
}
)
## Accessor functions:
#setGeneric("label", function(object) standardGeneric("label"))
#setMethod("label", "fitComponents", function(object) object@label)
#setGeneric("funcName", function(object) standardGeneric("funcName"))
#setMethod("funcName", "fitComponents", function(object) object@funcName)
#' @title setParam
#' @description S4method 'setParam' method for setting fitting parameters.
#' @param object an object of class \code{XPSCoreLine}
#' @param parameter character is one of the "start", "max" or "min" parameter to be set
#' @param variable character as "mu", "sigma"... indicates the parameter to set
#' @param value numeric the value to set
#' @return 'setParam' returns the object withthe parameter set
setGeneric("setParam", function(object, parameter=NULL, variable=NULL, value= NULL) standardGeneric("setParam"))
#' @title setParam
#' @description method to set fitting parameters of a object@Component[[j]]
#' where object is of class 'XPSCoreLine' and j indicates the jth fit component
#' @param object a Core_Line object of class \code{XPSCoreLine}
#' @param parameter character is one of the "start", "max" or "min" parameter to be set
#' @param variable character as "mu", "sigma"... indicates the parameter to set
#' @param value numeric the value to set
#' @return 'setParam' returns the object withthe parameter set
#' @examples
#' \dontrun{
#' setParam(test[["C1s"]]@Component[[2]], parameter="start", variable="mu", value="285")
#' }
#' @export
setMethod("setParam", "fitComponents", function(object, parameter=NULL, variable=NULL, value=NULL)
{
if ( is.null(value) ) stop(" value is required.")
rownamesParam <- rownames(slot(object,"param"))
if ( ! is.null(parameter) ) {
parameter <- match.arg(parameter,c("start","min", "max")) #set the single value START, MIN, MAX
if ( ! is.null(variable) ) {
variable <- match.arg(variable, rownamesParam)
slot(object,"param")[variable,parameter] <- value
} else {
if (length(value) != length(rownamesParam) )
stop("wrong value length")
else
slot(object,"param")[,parameter] <- value
}
} else {
if ( is.null(variable) ) {
warning(" if 'parameter' = NULL then 'variable' must be != NULL.")
} else if (variable == "all"){
LL <- length(rownamesParam)
for(ii in 1:LL){
parma <- rownamesParam[ii]
slot(object,"param")[variable,] <- value
}
} else {
variable <- match.arg(variable, rownamesParam)
if (length(value) != 3 ) { stop("wrong value length") } #set all three values START, MIN, MAX
else { slot(object,"param")[variable,] <- value }
}
}
invisible(object)
}
)
#' @title getParam
#' @description S4method 'getParam' method for get information about a fitting parameters.
#' @param object an object of class \code{XPSCoreLine}
#' @param parameter character is one of the "start", "max" or "min" parameter to be set
#' @param variable character as "mu", "sigma"... indicates the parameter to set
#' @return 'getParam' returns the value of the requested parameter
setGeneric("getParam", function(object, parameter=NULL, variable=NULL) standardGeneric("getParam"))
#' @title getParam
#' @description method to get the value of the specified fitting parameter from an object@Component[[j]]
#' where object is of class 'XPSCoreLine' and j indicates the jth fit component
#' @param object a Core_Line object of class \code{XPSCoreLine}
#' @param parameter character is one of the "start", "max" or "min" parameter to be set
#' @param variable character as "mu", "sigma"... indicates the parameter to set
#' @return 'getParam' returns the value of the requested parameter
#' @examples
#' \dontrun{
#' getParam(test[["C1s"]]@Component[[2]], parameter="start", variable="mu")
#' }
#' @export
setMethod("getParam", "fitComponents", function(object, parameter=NULL, variable=NULL)
{
if ( ! is.null(parameter) ) {
parameter <- match.arg(parameter,c("start","min", "max"))
if ( is.null(variable) ) { value <- slot(object,"param")[,parameter] }
else {
variable <- match.arg(variable, rownames(object@param))
value <- slot(object,"param")[variable,parameter]
}
} else {
if ( is.null(variable) ) {
warning(" if 'parameter' = NULL then 'variable' must be != NULL.")
} else {
variable <- match.arg(variable, rownames(object@param))
value <- slot(object,"param")[variable,]
}
}
return(value)
}
)
##==============================================================================
# returns a list with the y values for the component n
##==============================================================================
#' @title Ycomponent
#' @description S4method 'Ycomponent' method for generate the Y values of the
#' fit component using the chosen fitting function and the associated fit parameters
#' @param object a fit component object of the type CL@Components[[j]] where
#' CL is of class 'XPSCoreLine', j indicates the jth fit component
#' @param x numeric vector of the type CL@RegionToFit$x where
#' CL is of class 'XPSCoreLine'
#' @param y numeric vector of the type CL@Baseline$y where
#' CL is of class 'XPSCoreLine'
#' @return 'Ycomponent' returns Baseline subtracted vales of the fit component
setGeneric("Ycomponent", function(object, x, y) standardGeneric("Ycomponent"))
#' @title Ycomponent
#' @description S4method 'Ycomponent' method for generate the Y values of the
#' fit component using the chosen fitting function and the associated fit parameters
#' @param object a fit component object of the type CL@Components[[j]] where
#' CL is of class 'XPSCoreLine', j indicates the jth fit component
#' @param x numeric vector of the type CL@RegionToFit$x where
#' CL is of class 'XPSCoreLine'
#' @param y numeric vector of the type CL@Baseline$y where
#' CL is of class 'XPSCoreLine'
#' @return 'Ycomponent' returns Baseline subtracted vales of the fit component
#' @examples
#' \dontrun{
#' Ycomponent(test[["C1s"]]@Component[[2]],test[["C1s"]]@RegionToFit$x, test[["C1s"]]@Baseline$y)
#' }
#' @export
setMethod("Ycomponent", signature(object="fitComponents"),
function(object, x, y)
{
# let's take the starting values
startPar <- getParam(object, parameter = "start")
# combine x with start values
parm <- list(x=x) # x = object@RegionToFit$x
parm <- c(parm,startPar)
# formula e parameters to do the call
fmla <- slot(object,"funcName")
names(parm) <- formalArgs(fmla)
# calculate y values using the fit lineshape=funcName for the given x values
ycomponent <- do.call(fmla, parm)
# exit with ycomp + Baseline$y
slot(object, "ycoor") <- ( ycomponent + y ) # y=object@Baseline$y
return(object)
}
)
## fitAlgorithms is a list containing the default data defining each of the fit functions
fitAlgorithms <- list(
Initialize = new("fitComponents",
funcName = "Initialize",
description = "Symmetric Function(h, mu, sigma)",
label = "",
param = data.frame(
row.names = c("h", "mu", "sigma"), # min and max values are set in XPSaddFitComponent()
start = c(NA, NA, NA),
min = c(NA, NA, NA),
max = c(NA, NA, NA) ),
ycoor = 0,
rsf = 0,
link = list()
),
Generic = new("fitComponents",
funcName = "Generic",
description = "Generic Function(x)",
label = "",
param = data.frame(
start = c(NA, NA, NA),
min = c(NA, NA, NA),
max = c(NA, NA, NA) ),
ycoor = 0,
rsf = 0,
link = list()
),
Gauss = new("fitComponents",
funcName = "Gauss",
description = "Symmetric Gaussian shape",
label = "Gauss",
param = data.frame(
row.names = c("h", "mu", "sigma"),
start = c(1, NA, 1),
min = c(0, 0, 0.1),
max = c(Inf, Inf, 10) ),
ycoor = 0,
rsf = 0,
link = list()
),
Lorentz = new("fitComponents",
funcName = "Lorentz",
description = "Symmetric Lorentz shape",
label = "Lorentz",
param = data.frame(
row.names = c("h", "mu", "sigma"),
start = c(1, NA, 0.7),
min = c(0, 0, 0.1),
max = c(Inf, Inf, 10) ),
ycoor = 0,
rsf = 0,
link = list()
),
Voigt = new("fitComponents",
funcName = "Voigt",
description = "Symmetric Voigt shape",
label = "Voigt",
param = data.frame(
row.names = c("h", "mu", "sigma", "lg"),
start = c(1, NA, 1, 0.2),
min = c(0, 0, 0.05, 0.01),
max = c(Inf, Inf, 10, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
Sech2 = new("fitComponents",
funcName = "Sech2",
description = "Symmetric Sech2 shape",
label = "Sech2",
param = data.frame(
row.names = c("h", "mu", "sigma"),
start = c(1, NA, 0.5),
min = c(0, 0, 0.1),
max = c(Inf, Inf, 10) ),
ycoor = 0,
rsf = 0,
link = list()
),
GaussLorentzProd = new("fitComponents",
funcName = "GaussLorentzProd",
description = "Symmetric Gaussian Lorentz cross product form",
label = "GaussLorentzProd",
param = data.frame(
row.names = c("h", "mu", "sigma", "lg"),
start = c(1, NA, 1, 0.75),
min = c(0, 0, 0.1, 0.01),
max = c(Inf, Inf, 10, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
GaussLorentzSum = new("fitComponents",
funcName = "GaussLorentzSum",
description = "Symmetric Gaussian Lorentz Sum Form",
label = "GaussLorentzSum",
param = data.frame(
row.names = c("h", "mu", "sigma", "lg"),
start = c(1, NA, 1, 0.95),
min = c(0, 0, 0.1, 0),
max = c(Inf, Inf, 10, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
AsymmGauss = new("fitComponents",
funcName = "AsymmGauss",
description = "Simple Asymmetric Gaussian shape",
label = "AsymmGauss",
param = data.frame(
row.names = c("h", "mu", "sigma", "asym"), #min e max values are set in XPSaddFitComponent()
start = c(1, NA, 1, 0.3),
min = c(0, 0, 0.05, 0.01),
max = c(Inf, Inf, 10, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
AsymmLorentz = new("fitComponents",
funcName = "AsymmLorentz",
description = "Simple Asymmetric Lorentz shape",
label = "AsymmLorentz",
param = data.frame(
row.names = c("h", "mu", "sigma", "asym"), #min e max values are set in XPSaddFitComponent()
start = c(1, NA, 0.7, 0.3),
min = c(0, 0, 0.1, 0.01),
max = c(Inf, Inf, 10, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
AsymmVoigt = new("fitComponents",
funcName = "AsymmVoigt",
description = "Asymmetric Voigt shape",
label = "AsymmVoigt",
param = data.frame(
row.names = c("h", "mu", "sigma", "lg", "asym"), #min e max values are set in XPSaddFitComponent()
start = c(1, NA, 0.4, 0.1, 0.1),
min = c(0, 0, 0.1, 0.01, 0.01),
max = c(Inf, Inf, 10, 1, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
AsymmGaussLorentz = new("fitComponents",
funcName = "AsymmGaussLorentz",
description = "Asymmetric Gaussian Lorentz used in Genplot",
label = "AsymmGaussLorentz",
param = data.frame(
row.names = c("h", "mu", "sigma", "lg", "asym"),
start = c(1, NA, 1, 0.3, 0.45),
min = c(0, 0, 0.05, 0.4, 1e-5),
max = c(Inf, Inf, 5, 1, 0.4) ),
ycoor = 0,
rsf = 0,
link = list()
),
AsymmGaussVoigt = new("fitComponents",
funcName = "AsymmGaussVoigt",
description = "Asymmetric Line-Shape from CasaXPS",
label = "AsymmGaussVoigt",
param = data.frame(
row.names = c("h", "mu", "sigma", "lg", "asym", "gv"),
start = c(1, NA, 0.6, 0.1, 0.2, 0.4),
min = c(0, 0, 0.01, 0.01, 0.01, 0.01),
max = c(Inf, Inf, 5, 1, 1, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
AsymmGaussLorentzProd = new("fitComponents",
funcName = "AsymmGaussLorentzProd",
description = "Asym Gaussian Lorentz cross product from UNIFIT Publication",
label = "AsymmGaussLorentzProd",
param = data.frame(
row.names = c("h", "mu", "sigma", "asym", "lg"),
start = c(1, NA, 1, 0.2, 0.8),
min = c(0, 0, 0.05, 0.1, 1e-5),
max = c(Inf, Inf, 5, 1, 0.4) ),
ycoor = 0,
rsf = 0,
link = list()
),
DoniachSunjic = new("fitComponents",
funcName = "DoniachSunjic",
description = "Asymm. DoniachSunjic shape",
label = "DoniachSunjic",
param = data.frame(
row.names = c("h", "mu", "sigmaDS", "asym"),
start = c(1, NA, 1, 0.02),
min = c(0, 0, 0.01, 0.01),
max = c(Inf, Inf, 10, 1)),
ycoor = 0,
rsf = 0,
link = list()
),
DoniachSunjicTail = new("fitComponents",
funcName = "DoniachSunjicTail",
description = "Asymm. DoniachSunjic shape Tail corrected",
label = "DoniachSunjicTail",
param = data.frame(
row.names = c("h", "mu", "sigmaDS", "asym", "tail"),
start = c(1, NA, 1, 0.05, 0.2),
min = c(0, 0, 0.01, 0.01, 0.01),
max = c(Inf, Inf, 10, 1, 5) ),
ycoor = 0,
rsf = 0,
link = list()
),
DoniachSunjicGauss = new("fitComponents",
funcName = "DoniachSunjicGauss",
description = "Asymm. DoniachSunjic shape + GaussBroadening",
label = "DoniachSunjicGauss",
param = data.frame(
row.names = c("h", "mu", "sigmaDS", "sigmaG", "asym"),
start = c(1, NA, 1, 0.8, 0.02),
min = c(0, 0, 0.01, 0.01, 0.01),
max = c(Inf, Inf, 5, 5, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
DoniachSunjicGaussTail = new("fitComponents",
funcName = "DoniachSunjicGaussTail",
description = "Asymm. DoniachSunjic shape + GaussBroadening and Tail correction",
label = "DoniachSunjicGaussTail",
param = data.frame(
row.names = c("h", "mu", "sigmaDS", "sigmaG", "asym", "tail"),
start = c(1, NA, 1, 0.8, 0.02, 0.2),
min = c(0, 0, 0.01, 0.01, 0.01, 0.01),
max = c(Inf, Inf, 5, 5, 1, 5) ),
ycoor = 0,
rsf = 0,
link = list()
),
SimplifiedDoniachSunjic = new("fitComponents",
funcName = "SimplifiedDoniachSunjic",
description = "Asymmetric DoniachSunjic shape",
label = "SimplifiedDoniachSunjic",
param = data.frame(
row.names = c("h", "mu", "sigma", "asym"),
start = c(1, NA, 0.6, 0.02),
min = c(0, 0, 0.01, 0.01),
max = c(Inf, Inf, 5, 1) ),
ycoor = 0,
rsf = 0,
link = list()
),
#----- Special Fit Components -----
Linear = new("fitComponents",
funcName = "Linear",
description = "Linear Fit",
label = "Linear",
param = data.frame(
row.names = c("m", "c", "mu"), #min e max values are set in XPSaddFitComponent()
start = c(NA, 0, NA),
min = c(-Inf, -Inf, NA),
max = c(Inf, Inf, NA) ),
ycoor = 0,
rsf = 0,
link = list()
),
ExpDecay = new("fitComponents",
funcName = "ExpDecay",
description = "Exponential Decay",
label = "ExpDecay",
param = data.frame(
row.names = c("h", "mu", "k", "c"), #min e max values are set in XPSaddFitComponent()
start = c(1, NA, 1, 0),
min = c(0, 0, 0, 0),
max = c(Inf, Inf, 5, Inf) ),
ycoor = 0,
rsf = 0,
link = list()
),
PowerDecay = new("fitComponents",
funcName = "PowerDecay",
description = "Power Law Decay",
label = "PowerDecay",
param = data.frame(
row.names = c("h", "mu", "pow", "c"), #min e max values are set in XPSaddFitComponent()
start = c(1, NA, 2, 0),
min = c(0, 0, 0.1, 0),
max = c(Inf, Inf, 5, Inf) ),
ycoor = 0,
rsf = 0,
link = list()
),
Sigmoid = new("fitComponents",
funcName = "Sigmoid",
description = "Sigmoid function",
label = "Sigmoid",
param = data.frame(
row.names = c("h", "mu", "k", "c"), #min e max values are set in XPSaddFitComponent()
start = c(1, NA, 1, 0),
min = c(0, 0, 0, 0),
max = c(Inf, Inf, 5, Inf) ),
ycoor = 0,
rsf = 0,
link = list()
),
HillSigmoid = new("fitComponents",
funcName = "HillSigmoid",
description = "Hill Sigmoid function",
label = "HS",
param = data.frame(
row.names = c("h", "mu", "pow", "A", "B"), #mu, A, B values are set by do.fit() in XPSVBTopGUI()
start = c(NA, NA, 8, NA, NA),
min = c(0, 0, 0, 0, 0),
max = c(Inf, Inf, 50, Inf, Inf) ),
ycoor = 0,
rsf = 0,
link = list()
),
HillSigmoid.KE = new("fitComponents",
funcName = "HillSigmoid.KE",
description = "Hill Sigmoid function",
label = "HS",
param = data.frame(
row.names = c("h", "mu", "pow", "A", "B"), #mu, A, B values are set by do.fit() in XPSVBTopGUI()
start = c(NA, NA, 8, NA, NA),
min = c(0, 0, 0, 0, 0),
max = c(Inf, Inf, 50, Inf, Inf) ),
ycoor = 0,
rsf = 0,
link = list()
),
VBFermi = new("fitComponents",
funcName = "VBFermi",
description = "Fermi Distribution function",
label = "Ef",
param = data.frame(
row.names = c("h", "mu", "k"),
start = c(1, 0, 1),
min = c(0, 0, 0),
max = c(10, 2, 5) ),
ycoor = 0,
rsf = 0,
link = list()
),
VBtop = new("fitComponents", #Together with FitAlgorithms this is needeed to create a slot
funcName = "VBtop", #in the ...@Components[[ii]]@param location of the XPSSample
description = "VBtop fit", #where to save the VBtop position.
label = "VBtop", #This slot is sensitive to the EnergyShift function
param = data.frame(
row.names = c("mu"),
start = c(NA),
min = c(NA),
max = c(NA) ),
ycoor = 0,
rsf = 0,
link = list()
),
Derivative = new("fitComponents", #Together with FitAlgorithms this is needeed to create a slot
funcName = "Derivative", #in the ...@Components[[ii]]@param location of the XPSSample
description = "First Derivative", #where to save the core line first derivative.
label = "D1", #This slot is sensitive to the EnergyShift function
param = data.frame(
row.names = c("mu"),
start = c(NA),
min = c(NA),
max = c(NA) ),
ycoor = 0,
rsf = 0,
link = list()
),
FitProfile = new("fitComponents",
funcName = "FitProfile",
description = "Depth Profile",
label = "DepthP.",
param = data.frame(
row.names = c("R.I", "d", "La", "Lb"), #min e max values are set in XPSaddFitComponent()
start = c(NA, 10, NA, NA),
min = c(NA, 0, NA, NA),
max = c(NA, 50, NA, NA) ),
ycoor = 0,
rsf = 0,
link = list()
)
)
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