inst/testHelpers/metadata/md2ap/ap_add_2.r

In bpollner/aquap2: Multivariate Data Analysis Tools for R including Aquaphotomics Methods

####################################################################
############### aquap2 analysis procedure file #####################
####################################################################

### do NOT change the names of the variables !!  ####

################################################################
##################### split dataset ############################
################################################################
spl.var <- NULL							## by which variables should the dataset be split? leave empty c() or set to NULL for *no* splitting by class variables, or provide one or more valid class variables to split along these variables; e.g. "C_Group", or c("C_Group", "C_Mode", ...)
spl.wl <- NULL							## which wavelengths to use? leave empty c() or set to NULL for using all available wavelengths. Provide a character vector in the format e.g. c("1300-to-1600"), or c("1000-to-2000", "1300-to-1600", ...) to split along these wavelengths.
#######
dpt.pre <- NULL							## Character vector, which of the available modules of data pre-treatments to apply. Leave at NULL for no additional data pre-treatment. For possible values see ?dpt_modules.
#######
spl.do.csAvg <- FALSE					## if all the consecutive scans of a single sample should be reduced, i.e. averaged into a single spectrum
spl.csAvg.raw <- TRUE					## if, should the consecutive scans of a single sample be reduced, an other dataset containing every single consecutive scan should be kept as well
#
spl.do.noise <- FALSE					## if artificial noise should be added to the dataset
spl.noise.raw <- TRUE					## if, should the noise-test be performed, the raw original data should be used as well. Recommended value = TRUE
#
spl.do.exOut <- FALSE					## if exclusion of outliers should be performed
spl.exOut.raw <- FALSE					## if, should exclusion of outliers be performed, the raw original data should be used as well. If set to TRUE, outliers will be flagged in the dataset in *ANY* case.
spl.exOut.var <- c("C_FooBar")			## A vector with valid class variable names (one or more) to be used for the grouping defining the scope for outlier detection.
#######
dpt.post <- NULL						## Character vector, which of the available modules of data pre-treatments to apply.  Leave at NULL for no additional data pre-treatment. For possible values see ?dpt_modules.
################################################################
		
		


################################################################
########## statistics & specific plotting options ##############
################################################################

#########################
### PCA 
do.pca <- FALSE							## if PCA of the given datasets should be performed

# plotting 
pca.colorBy <- NULL						## which variables to use for coloring the score plots. leave empty c() or set to NULL for using all available class-variables for coloring. Provide a character vector with valid class variable names to color along these variables; e.g. c("C_Group", "C_Temp", "C_RelHum", ...)
pca.elci <- "def"						## the confidence interval for the ellipse to draw around groups in score plots; leave at 'def' to read in the default from the settings.r file; provide a numeric length one (e.g. 0.95); or set to NULL for not drawing ellipses at all
pca.elcolorBy <- NULL					## which variables to use for plotting additional confidence intervall ellipses. Set to NULL for not drawing additional CI-ellipses. Provide one variable (gets recycled) or a vector with equal length as pca.colorBy to have the additional ci-ellipses along these variables; e.g. "C_RelHum"
pca.what <- "both"						## can be either 'both' for plotting both PCA scores and loadings, or 'scores' or 'loadings' for plotting only one of them.
pca.sc <- c(1, 2)						## Numeric length 2, the two PCs to be plotted against each other in the score plots.
pca.sc.pairs <- 1:6 					## Numeric sequence of length >=2, indicating what PC components to plot in the score pairs plot. Set to NULL for not plotting the pairs plot.
pca.lo <- 1:6							## Numeric sequence of length >=2, indicating what PC components to plot in the loadingplot.
#########################
 
 
#########################
### SIMCA
do.sim <- FALSE							## if SIMCA models of the given datasets should be calculated
sim.vars <- NULL						## which variables should be use to group the data? Leave empty c() or set to NULL for using all available class-variables, or provide a character vector with valid class variable names to group along these variables; e.g. "C_Group", or c("C_Group", "C_FooBar", ...)
sim.K <- 0								## The number of components. In mode "robust", leave at 0 for automatic detection. (it is a capital "K")

# plotting

#########################


#########################
### PLSR
do.pls <- FALSE							## if PLSR models of the given datasets should be calculated
pls.ncomp <- NULL						## number of components, leave at NULL for automatic detection of optimal number of components
pls.regOn <- NULL						## which variables should be used to regress on? Leave empty c() or set to NULL for using all numerical variables, or provide a character vector with valid numerical variable names to regress on these variables; e.g. "Y_Temp", or c("Y_Temp", "Y_FooBar", ...)
pls.valid <- "def"						## 'def' to get the default value from the settings file (parameter 'plsr_calc_typeOfCrossvalid'); a number to perform this n-fold crossvalidation, 'LOO' for a leave-one-out crossvalidation, or a valid name of a class variable for performing a crossvalidation based on the grouping defined by this variable. Can be of equal length as the vector in 'pls.regOn' to perform the corresponding type of CV for each element in 'pls.regOn'.
pls.exOut <- "def"						## 'def' to get the default value from the settings file (parameter 'plsr_calc_excludePlsrOutliers'); TRUE or FALSE for deciding whether to perform a plsr-specific outlier-detection algorithm or not.  Can be of equal length as the vector in 'pls.regOn' to perform the corresponding outlier-detection (or not) for each element in 'pls.regOn'.

# plotting
pls.colorBy <- NULL						## What class-variable should be used for coloring in the RMSEP and RMSECV plots? Leave empty c() or set to NULL for no coloring, or provide a character length one with a valid class variable name to color along this variable; e.g. "C_Group"
pls.what <- "both"						## what types of plots to plot. Possible values are "regression" for the regression vector, "errors" for the error plots, or "both" for both of them.
pls.rdp <- FALSE						## if errors should be given in RDP
#########################




#########################
### Aquagram
do.aqg <- FALSE							## if Aquagrams of the given datasets should be calculated
aqg.vars <- NULL						## which variables should be use to group the data? Provide a character vector with valid class variable names to group along these variables; e.g. "C_Group", or c("C_Group", "C_FooBar", ...)
aqg.nrCorr <- "def"						## please see the help for ?calc_aqg_args and ?plot_aqg_args for further information regarding these arguments.
aqg.spectra <- FALSE
aqg.minus <- NULL
aqg.mod <- "def"  
aqg.TCalib <- "def"
aqg.Texp <- "def"
aqg.bootCI <- "def"
aqg.R <- "def"
aqg.smoothN <- 21
aqg.selWls <- "def"
aqg.msc <- TRUE
aqg.reference <- NULL

# plotting
aqg.fsa <- 	"only"						## 'Fix scale for Aquagram'. Logical, numeric or character.
aqg.fss <- 	"only"						## 'Fix scale for spectra'. Logical, numeric or character.
aqg.ccol <- NULL						## custom color vector 
aqg.clt <- "def"						## custom line-type
aqg.pplot <- "def" 						## if peak plot should be added to the spectra
aqg.plines <- "def"						## if "lines" XXX should be added to the peak plot
aqg.discr <- "def"						## Logical or character 'def'. If set to TRUE, negative (resp. positive) peaks can be only found in peak-heights below (resp. above) zero.
#########################	





####################################################################
################## general plotting options ########################
####################################################################
pg.where <- "pdf"						## If left at the default 'def', the value from the settings.r file is read in (parameter gen_plot_pgWhereDefault). For plotting PDFs provide "pdf", for plotting to graphics device provide anything but "pdf".
pg.main <- ""							## the additional text on the title of each single plot
pg.sub <- ""							## the additional text on the subtitle of each single plot
pg.fns <- ""							## 'filename suffix', the additional text in the filename of the pdf.
####################################################################

### do NOT change the names of the variables !!  ####
####################################################################