R/GUI_utils.R

In phenomecentre/peakPantheR: Peak Picking and Annotation of High Resolution Experiments

#' UI data import helper - initialise new annotation from files
#'
#' Fully initialise a \code{peakPantheRAnnotation} using the target files path,
#' CSV parameter path and metadata.
#'
#' @param CSVParamPath (str) Path to a CSV file of fit parameters
#' @param spectraPaths (str) character vector of spectra file paths, to set
#' samples to process
#' @param cpdMetadataPath NULL or path to a csv of compound metadata, with
#' compounds as row and metadata as columns
#' @param spectraMetadata NULL or DataFrame of sample metadata, with
#' samples as row and metadata as columns
#' @param verbose (bool) If TRUE message progress
#'
#' @return (peakPantheRAnnotation) Object initialised with ROI, uROI and FIR
#' read from the CSV file
#'
#' @export
#'
#' @examples
#' ## Input data
#' input_CSV <- data.frame(matrix(nrow=2,ncol=21,dimnames=list(c(),
#'     c('cpdID', 'cpdName',
#'     'X','ROI_rt', 'ROI_mz', 'ROI_rtMin', 'ROI_rtMax','ROI_mzMin','ROI_mzMax',
#'     'X','uROI_rtMin', 'uROI_rtMax', 'uROI_mzMin', 'uROI_mzMax', 'uROI_rt',
#'     'uROI_mz', 'X', 'FIR_rtMin', 'FIR_rtMax', 'FIR_mzMin', 'FIR_mzMax'))))
#' input_CSV[1,]  <- c('ID-1', 'Cpd 1', '|', 1.,  2.,  3.,  4.,  5.,  6.,  '|',
#'                     7.,  8.,  9.,  10., 11., 12., '|', 13., 14., 15., 16.)
#' input_CSV[2,]  <- c('ID-2', 'Cpd 2', '|', 17., 18., 19., 20., 21., 22., '|',
#'                     23., 24., 25., 26., 27., 28., '|', 29., 30., 31., 32.)
#' input_CSV[,-c(1,2,3,10,17)]  <- vapply(input_CSV[,-c(1,2,3,10,17)],
#'                                             as.numeric, FUN.VALUE=numeric(2))
#'
#' input_spectraPaths    <- c('./path/file1', './path/file2', './path/file3')
#'
#' # temporary file location
#' savePath1      <- tempfile(pattern='file', tmpdir=tempdir(), fileext='.csv')
#' # save csv
#' utils::write.csv(input_CSV, file=savePath1, row.names=FALSE)
#'
#' # Load parameters from CSV
#' loadedAnnotation <- initialise_annotation_from_files_UI_helper(savePath1,
#'                                                         input_spectraPaths,
#'                                                         verbose=TRUE)
#' # An object of class peakPantheRAnnotation
#' #   2 compounds in 3 samples.
#' #   updated ROI exist (uROI)
#' #   does not use updated ROI (uROI)
#' #   does not use fallback integration regions (FIR)
#' #   is not annotated
initialise_annotation_from_files_UI_helper <- function(CSVParamPath,
                                                        spectraPaths,
                                                        cpdMetadataPath = NULL,
                                                        spectraMetadata = NULL,
                                                        verbose = TRUE) {
    # Initialise with parameters
    init_annotation <- peakPantheR_loadAnnotationParamsCSV(CSVParamPath,
                                                            verbose = FALSE)
    # Add spectraPaths
    init_annotation <- resetAnnotation(init_annotation,
                                        spectraPaths = spectraPaths,
                                        verbose = FALSE)
    # Load metadata
    cpdMetadata     <- NULL
    if (!is.null(cpdMetadataPath)) {
        if (!file.exists(cpdMetadataPath)) {
            stop('Err','or: cpdMetadata file does not exist') }
        tmp_cpdMeta <- read.csv(cpdMetadataPath, header=TRUE, sep=",",
                                quote="\"", stringsAsFactors=FALSE)
        # check nb rows match the nb of cpd
        if (dim(tmp_cpdMeta)[1] != nbCompounds(init_annotation)) {
            message('War','ning: cpdMetadata number of rows (',
                    dim(tmp_cpdMeta)[1],
                    ') does not match the number of compounds targeted (',
                    nbCompounds(init_annotation), ')')
        } else { cpdMetadata <- tmp_cpdMeta }
    }
    if (!is.null(spectraMetadata)) {
        if (!is.data.frame(spectraMetadata)) {
            stop('Err','or: spectraMetadata is not a DataFrame') }
        # check nb of rows match the nb of spectra
        if (dim(spectraMetadata)[1] != nbSamples(init_annotation)) {
            message('War','ning: spectraMetadata number of rows (',
                    dim(spectraMetadata)[1],
                    ') does not match the number of compounds targeted (',
                    nbSamples(init_annotation), ')')
            spectraMetadata <- NULL
        } # else keep the spectraMetadata value
    }

    # Update annotation with metadata
    init_annotation <- resetAnnotation(init_annotation,
                                        cpdMetadata = cpdMetadata,
                                        spectraMetadata = spectraMetadata,
                                        verbose = FALSE)
    # return success message
    if(verbose){ message(show(init_annotation)) }
    return(init_annotation)
}


#' UI data import helper - prepare file paths and metadata
#'
#' Return spectraPaths and spectraMetadata from a .csv file (if available).
#' If reading from the spectraMetadata file, the spectraPaths are taken from
#' the `filepath` column
#'
#' @param spectraPaths NULL or character vector of spectra file paths, to set
#' samples to process
#' @param spectraMetadataPath NULL or path to a csv of spectra metadata, with
#' spectra as row and metadata as columns. (spectraPaths in column `filepath`)
#'
#' @return spectraPaths (str) and spectraMetadata (DataFrame or NULL) read from
#' the CSV file
#'
#' @export
#'
#' @examples
#' ## Input data
#' # spectraPath
#' input_spectraPaths    <- c('./path/file1', './path/file2', './path/file3')
#'
#' # spectraMetadata
#' input_spectraMetadata <- data.frame(matrix(data=c(input_spectraPaths,
#'                          c('a','b','c')), nrow=3, ncol=2,
#'                          dimnames=list(c(),c('filepath', 'testcol')),
#'                          byrow=FALSE), stringsAsFactors=FALSE)
#'
#' # temporary file location
#' spectraMetaPath <- tempfile(pattern="file", tmpdir=tempdir(), fileext='.csv')
#' # save csv
#' utils::write.csv(input_spectraMetadata,
#'                  file=spectraMetaPath,
#'                  row.names=FALSE)
#'
#' # load data from CSV
#' spectraPaths_and_metadata_UI_helper(spectraPaths = NULL,
#'                                      spectraMetadataPath = spectraMetaPath)
spectraPaths_and_metadata_UI_helper <- function(spectraPaths = NULL,
                                                spectraMetadataPath = NULL) {
    # None are set
    if (is.null(spectraPaths) & is.null(spectraMetadataPath)) {
        stop('Err','or: spectraPaths and spectraMetadataPath are not set')
    }

    # Only spectraPaths are set
    if (!is.null(spectraPaths) & is.null(spectraMetadataPath)) {
        out_path <- spectraPaths
        out_meta <- NULL
    }

    # spectraMetadataPath is set
    if (!is.null(spectraMetadataPath)) {

        # load file
        if (!file.exists(spectraMetadataPath)) {
                stop('Err','or: spectraMetadata file does not exist') }
        tmp_spectraMeta <- read.csv(spectraMetadataPath, header=TRUE, sep=",",
                                    quote="\"", stringsAsFactors=FALSE)

        # check 'filepath' is in columns
        if (!('filepath' %in% colnames(tmp_spectraMeta))) {
            stop("Err","or: the column 'filepath' must be present in the ",
                "spectraMetadata")
        }

        # extract filepaths
        out_path <- tmp_spectraMeta[,'filepath']
        # remove filepaths from metadata
        out_meta <- tmp_spectraMeta[ , !(names(tmp_spectraMeta) %in%
                                        c('filepath')), drop=FALSE]
    }

    return(list(spectra=out_path, meta=out_meta))
}


#' UI data import helper - check loaded annotation
#'
#' Load a .RData file (check it exists) and that a peakPantheRAnnotation named
#' "annotationObject" is present. Returns the annotation if everything is valid
#'
#' @param annotationPath (str) Path to a RData file containing a
#' peakPantheRAnnotation names `annotationObject`
#'
#' @return (peakPantheRAnnotation) Object loaded from file
#'
#' @export
#'
#' @examples
#' ## Initialise a peakPantheRAnnotation object with 3 samples and 2 compounds
#'
#' ## Inputs
#' # spectraPaths
#' spectraPaths <- c('./path/file1', './path/file2', './path/file3')
#'
#' # targetFeatTable
#' targetFeatTable <- data.frame(matrix(vector(), 2, 8, dimnames=list(c(),
#'                     c('cpdID','cpdName','rtMin','rt','rtMax','mzMin','mz',
#'                     'mzMax'))), stringsAsFactors=FALSE)
#' targetFeatTable[1,] <- c('ID-1', 'Cpd 1', 3310., 3344.888, 3390., 522.194778,
#'                         522.2, 522.205222)
#' targetFeatTable[2,] <- c('ID-2', 'Cpd 2', 3280., 3385.577, 3440., 496.195038,
#'                         496.2, 496.204962)
#' targetFeatTable[,c(3:8)] <- vapply(targetFeatTable[,c(3:8)], as.numeric,
#'                                     FUN.VALUE=numeric(2))
#'
#' annotationObject <- peakPantheRAnnotation(spectraPaths=spectraPaths,
#'                                         targetFeatTable=targetFeatTable)
#'
#' # save annotation to disk
#' annotPath <- tempfile(pattern="file", tmpdir=tempdir(), fileext='.RData')
#' save(annotationObject, file=annotPath, compress=TRUE)
#'
#' # Load annotation
#' load_annotation_from_file_UI_helper(annotationPath = annotPath)
#' # An object of class peakPantheRAnnotation
#' #   2 compounds in 3 samples.
#' #   updated ROI do not exist (uROI)
#' #   does not use updated ROI (uROI)
#' #   does not use fallback integration regions (FIR)
#' #   is not annotated
load_annotation_from_file_UI_helper <- function(annotationPath) {
    # Check file exist
    if (!file.exists(annotationPath)) {
        stop('Err','or: annotation file does not exist') }

    # load file content
    load(annotationPath)

    # check it exist and is named correctly
    if (length(ls()[ls() == 'annotationObject']) !=1) {
        stop("Err","or: annotation file must contain a ",
            "`peakPantheRAnnotation` named 'annotationObject'") }
    # dummy initialisation to pass BiocCheck. In no case would the code reach
    # this section if `annotationObject` wasn't present in the environment
    if (0) {annotationObject <- NULL}

    # check it's a peakPantheRAnnotation
    if (!is(annotationObject, "peakPantheRAnnotation")) {
        stop("Err","or: the variable loaded is not a `peakPantheRAnnotation`") }

    return(annotationObject)
}


#' UI show annotation helper - list of properties
#'
#' show method specific to the UI, that returns each field in a named list to
#' ease display
#'
#' @param annotation (peakPantherAnnotation) Object to describe
#'
#' @return (list) Named list of annotation properties
#'
#' @export
#'
#' @examples
#' # Initialise an empty annotation, no uROI, no use of FIR
#' annotInit     <- peakPantheRAnnotation()
#'
#' # return properties
#' annotation_showMethod_UI_helper(annotInit)
#' # $nbCompounds
#' # [1] 0
#' #
#' # #$nbSamples
#' # [1] 0
#' #
#' # #$uROIExist
#' # [1] FALSE
#' #
#' # $useUROI
#' # [1] FALSE
#' #
#' # $useFIR
#' # [1] FALSE
#' #
#' # $isAnnotated
#' # [1] FALSE
annotation_showMethod_UI_helper <- function(annotation){
    properties <- list(nbCompounds = nbCompounds(annotation),
                        nbSamples = nbSamples(annotation),
                        uROIExist = uROIExist(annotation),
                        useUROI = useUROI(annotation),
                        useFIR = useFIR(annotation),
                        isAnnotated = isAnnotated(annotation)
    )

    return(properties)
}


#' UI show annotation helper - UI sidebar string
#'
#' Return a text description of an annotation for UI presentation
#'
#' @param annotProp (list) Named list of annotation properties as
#' created by \code{annotation_showMethod_UI_helper()}
#'
#' @return (str) Textual description of the annotation to show on UI
#'
#' @export
#'
#' @examples
#' # Input
#' properties_default <- list(nbCompounds = 0,
#'                            nbSamples = 0,
#'                            uROIExist = FALSE,
#'                            useUROI = FALSE,
#'                            useFIR = FALSE,
#'                            isAnnotated = FALSE)
#'
#' # Generate description
#' annotation_showText_UI_helper(properties_default)
#' # [[1]]
#' # [1] "Not annotated"
#' #
#' # [[2]]
#' # [1] "0 compounds"
#' #
#' # [[3]]
#' # [1] "0 samples"
#' #
#' # [[4]]
#' # [1] "updated ROI do not exist (uROI)"
#' #
#' # [[5]]
#' # [1] "does not use updated ROI (uROI)"
#' #
#' # [[6]]
#' # [1] "does not use fallback integration regions (FIR)"
annotation_showText_UI_helper <- function(annotProp){
    UI_string <- list(
        if (annotProp$isAnnotated) {'Is annotated'} else {'Not annotated'},
        paste0(annotProp$nbCompounds, ' compounds'),
        paste0(annotProp$nbSamples, ' samples'),
        if (annotProp$uROIExist) {'updated ROI exist (uROI)'
        } else {'updated ROI do not exist (uROI)'},
        if (annotProp$useUROI) {'uses updated ROI (uROI)'
        } else {'does not use updated ROI (uROI)'},
        if (annotProp$useFIR) {'uses fallback integration regions (FIR)'
        } else {'does not use fallback integration regions (FIR)'}
    )

    return(UI_string)
}

#' UI diagnostic plot helper - single feature multiplot
#'
#' Return a ggplot object of a feature diagnostic multiplot
#'
#' @param cpdNb (int) position of the feature to extract (1 to nbCpd)
#' @param annotation (peakPantheRAnnotation) Annotation object
#' @param splNum (int) NULL or number of spectra to plot, chosen randomly
#' from all spectra. If NULL or equal to the total number of spectra, plot all
#' spectra
#' @param splColrColumn (str) NULL, None or a spectraMetadata column for
#' colouring each sample
#' @param ... Additional parameters for plotting
#'
#' @return (ggplotObject) Diagnostic multiplot for a feature
#'
#' @export
#'
#' @examples
#' ## Initialise a peakPantheRAnnotation object with 3 samples and 2 targeted
#' ## compounds
#'
#' # Paths to spectra files
#' spectraPaths <- c('./path/file1', './path/file2', './path/file3')
#'
#' # targetFeatTable
#' targetFeatTable <- data.frame(matrix(vector(), 2, 8, dimnames=list(c(),
#'                     c('cpdID','cpdName','rtMin','rt','rtMax','mzMin','mz',
#'                     'mzMax'))), stringsAsFactors=FALSE)
#' targetFeatTable[1,] <- c('ID-1', 'Cpd 1', 3310., 3344.888, 3390., 522.194778,
#'                         522.2, 522.205222)
#' targetFeatTable[2,] <- c('ID-2', 'Cpd 2', 3280., 3385.577, 3440., 496.195038,
#'                         496.2, 496.204962)
#' targetFeatTable[,c(3:8)] <- vapply(targetFeatTable[,c(3:8)], as.numeric,
#'                                     FUN.VALUE=numeric(2))
#'
#' emptyAnnotation <- peakPantheRAnnotation(spectraPaths=spectraPaths,
#'                                         targetFeatTable=targetFeatTable)
#'
#' # Plot of an empty annotation
#' annotation_diagnostic_multiplot_UI_helper(cpdNb = 2,
#'                                          annotation = emptyAnnotation,
#'                                          splNum = NULL,
#'                                          splColrColumn = NULL)
#' # Warning: the object has not been annotated, return an empty diagnostic
#' # plot list
annotation_diagnostic_multiplot_UI_helper <- function(cpdNb, annotation,
                                        splNum=NULL, splColrColumn=NULL, ...) {
    # subset the compound and sample according to inputs
    tmp_annotat <- subset_annot_diag_plot_UI_helper(cpdNb, annotation, splNum)

    # convert sampleColourColumn to a colour scale to use
    sampleColour <- spectra_metadata_colourScheme_UI_helper(tmp_annotat,
                                                            splColrColumn)

    # diagnostic plots
    tmp_diagPlotList <- annotationDiagnosticPlots(tmp_annotat,
        sampleColour = sampleColour, verbose = FALSE, ...)

    # multiplot
    suppressMessages(suppressWarnings(
        tmp_multiPlot <- annotationDiagnosticMultiplot(
            tmp_diagPlotList)))

    # something to plot
    if (length(tmp_multiPlot) != 0) {
        return(tmp_multiPlot)
    # nothing to plot
    } else { return(ggplot2::ggplot() + ggplot2::theme_void()) }
}

subset_annot_diag_plot_UI_helper <- function(cpdNb, annotation, splNum=NULL) {
    # subset the compound and sample according to inputs

    nSpl <- nbSamples(annotation)
    if (is.null(splNum)) { splNum <- nSpl }

    # fix extrem values allowed by UI
    if (splNum < 1) {
        splNum <- 1
        warning("Negative number of samples to show, 1 spectra will be shown!")
    }
    if (splNum > nSpl) {
        splNum <- nSpl
        warning("More samples to show than available,",
                " all spectra will be shown!")
    }

    # appoximately equally spaced
    currentSplChoice  <- round(seq(1, nSpl, length.out=splNum))

    # subset annotation to only 1 cpd and subset of samples
    subsetAnnotation <- annotation[currentSplChoice, cpdNb]

    return(subsetAnnotation)
}

#' UI diagnostic table - fit summary
#'
#' Return a table of fit statistic (ratio of peaks found, ratio of peaks filled,
#' ppm error, RT deviation)
#'
#' @param annot (peakPantheRAnnotation) Annotation object
#'
#' @return (data.frame) Fit statistics
#'
#' @export
#'
#' @examples
#' ## Initialise a peakPantheRAnnotation object with 3 samples and 2 targeted
#' ## compounds
#'
#' # Paths to spectra files
#' spectraPaths <- c('./path/file1', './path/file2', './path/file3')
#'
#' # targetFeatTable
#' targetFeatTable <- data.frame(matrix(vector(), 2, 8, dimnames=list(c(),
#'                     c('cpdID','cpdName','rtMin','rt','rtMax','mzMin','mz',
#'                     'mzMax'))), stringsAsFactors=FALSE)
#' targetFeatTable[1,] <- c('ID-1', 'Cpd 1', 3310., 3344.888, 3390., 522.194778,
#'                         522.2, 522.205222)
#' targetFeatTable[2,] <- c('ID-2', 'Cpd 2', 3280., 3385.577, 3440., 496.195038,
#'                         496.2, 496.204962)
#' targetFeatTable[,c(3:8)] <- vapply(targetFeatTable[,c(3:8)], as.numeric,
#'                                     FUN.VALUE=numeric(2))
#'
#' emptyAnnotation <- peakPantheRAnnotation(spectraPaths=spectraPaths,
#'                                         targetFeatTable=targetFeatTable)
#'
#' # statistics of an empty annotation
#' annotation_fit_summary_UI_helper(emptyAnnotation)
#' #              Ratio peaks found (%) Ratio peaks filled (%) ppm error
#' # ID-1 - Cpd 1                    NA                      0       NaN
#' # ID-2 - Cpd 2                    NA                      0       NaN
#' #               RT deviation (s)
#' # ID-1 - Cpd 1               NaN
#' # ID-2 - Cpd 2               NaN
annotation_fit_summary_UI_helper <- function(annot) {
    summary <- data.frame(matrix(ncol = 0, nrow = nbCompounds(annot)),
                                    stringsAsFactors = FALSE)
    rownames(summary) <- paste(cpdID(annot), "-", cpdName(annot))

    # used FIR (found = not filled, filled from is_filled)
    if (annot@useFIR) {
        summary$ratio_peaks_found  <- 1 - (colSums(
            annotationTable(annot, column = "is_filled"))/nbSamples(annot))
        summary$ratio_peaks_filled <- (colSums(
            annotationTable(annot, column = "is_filled"))/nbSamples(annot))

    # didn't use FIR (found from found, None are filled)
    } else {
        summary$ratio_peaks_found  <- colSums(
            annotationTable(annot, column = "found"))/nbSamples(annot)
        summary$ratio_peaks_filled <- 0
    }

    summary$ppm_error <-
        colMeans(annotationTable(annot, column = "ppm_error"), na.rm = TRUE)
    summary$rt_dev_sec <-
        colMeans(annotationTable(annot, column = "rt_dev_sec"), na.rm = TRUE)

    # nicer format for output
    summary$ratio_peaks_found  <- round(summary$ratio_peaks_found*100,1)
    summary$ratio_peaks_filled <- round(summary$ratio_peaks_filled*100,1)
    colnames(summary) <- c('Ratio peaks found (%)','Ratio peaks filled (%)',
                            'ppm error', 'RT deviation (s)')

    return(summary)
}


#' UI export helper - spectra path and metadata
#'
#' Return a table with spectra as rows and filepath and all spectra metadata
#' columns
#'
#' @param annot (peakPantheRAnnotation) Annotation object
#'
#' @return (data.frame) Spectra paths and metadata
#'
#' @export
#'
#' @examples
#' ## Initialise a peakPantheRAnnotation object with 3 samples and 2 targeted
#' ## compounds
#'
#' # Paths to spectra files
#' spectraPaths <- c('./path/file1', './path/file2', './path/file3')
#'
#' # targetFeatTable
#' targetFeatTable <- data.frame(matrix(vector(), 2, 8, dimnames=list(c(),
#'                     c('cpdID','cpdName','rtMin','rt','rtMax','mzMin','mz',
#'                     'mzMax'))), stringsAsFactors=FALSE)
#' targetFeatTable[1,] <- c('ID-1', 'Cpd 1', 3310., 3344.888, 3390., 522.194778,
#'                         522.2, 522.205222)
#' targetFeatTable[2,] <- c('ID-2', 'Cpd 2', 3280., 3385.577, 3440., 496.195038,
#'                         496.2, 496.204962)
#' targetFeatTable[,c(3:8)] <- vapply(targetFeatTable[,c(3:8)], as.numeric,
#'                                     FUN.VALUE=numeric(2))
#'
#' emptyAnnotation <- peakPantheRAnnotation(spectraPaths=spectraPaths,
#'                                         targetFeatTable=targetFeatTable)
#'
#' # spectraMetada of an empty annotation
#' outputAnnotationSpectraMetadata_UI_helper(emptyAnnotation)
#' #       filepath
#' # 1 ./path/file1
#' # 2 ./path/file2
#' # 3 ./path/file3
outputAnnotationSpectraMetadata_UI_helper <- function(annot) {
    # collect the data
    tmp_filepath        <- filepath(annot)
    tmp_spectraMetadata <- spectraMetadata(annot)

    # generate table
    outSpecMeta <- data.frame(filepath = tmp_filepath)
    outSpecMeta <- cbind(outSpecMeta, tmp_spectraMetadata)

    return(outSpecMeta)
}


#' UI export helper - feature metadata
#'
#' Return a table with features as rows and all feature metadata as columns
#'
#' @param annot (peakPantheRAnnotation) Annotation object
#'
#' @return (data.frame) Features metadata
#'
#' @export
#'
#' @examples
#' ## Initialise a peakPantheRAnnotation object with 3 samples and 2 targeted
#' ## compounds
#'
#' # Paths to spectra files
#' spectraPaths <- c('./path/file1', './path/file2', './path/file3')
#'
#' # targetFeatTable
#' targetFeatTable <- data.frame(matrix(vector(), 2, 8, dimnames=list(c(),
#'                     c('cpdID','cpdName','rtMin','rt','rtMax','mzMin','mz',
#'                     'mzMax'))), stringsAsFactors=FALSE)
#' targetFeatTable[1,] <- c('ID-1', 'Cpd 1', 3310., 3344.888, 3390., 522.194778,
#'                         522.2, 522.205222)
#' targetFeatTable[2,] <- c('ID-2', 'Cpd 2', 3280., 3385.577, 3440., 496.195038,
#'                         496.2, 496.204962)
#' targetFeatTable[,c(3:8)] <- vapply(targetFeatTable[,c(3:8)], as.numeric,
#'                                     FUN.VALUE=numeric(2))
#'
#' emptyAnnotation <- peakPantheRAnnotation(spectraPaths=spectraPaths,
#'                                         targetFeatTable=targetFeatTable)
#'
#' # featureMetadata of an empty annotation
#' outputAnnotationFeatureMetadata_UI_helper(emptyAnnotation)
#' # data frame with 0 columns and 2 rows
outputAnnotationFeatureMetadata_UI_helper <- function(annot) {
    # collect the data
    outCpdMetadata <- cpdMetadata(annot)

    return(outCpdMetadata)
}


#' UI export plot helper - sample colour
#'
#' Return a vector of spectra colours based on a metadata column
#'
#' @param annot (peakPantheRAnnotation) Annotation object
#' @param splColrColumn (str) NULL, None or a spectraMetadata column for
#' colouring each sample
#'
#' @return (character) Vector of colours
#'
#' @export
#'
#' @examples
#' ## Initialise a peakPantheRAnnotation object with 3 samples and 2 targeted
#' ## compounds
#'
#' # Paths to spectra files
#' spectraPaths <- c('./path/file1', './path/file2', './path/file3')
#'
#' # targetFeatTable
#' targetFeatTable <- data.frame(matrix(vector(), 2, 8, dimnames=list(c(),
#'                     c('cpdID','cpdName','rtMin','rt','rtMax','mzMin','mz',
#'                     'mzMax'))), stringsAsFactors=FALSE)
#' targetFeatTable[1,] <- c('ID-1', 'Cpd 1', 3310., 3344.888, 3390., 522.194778,
#'                         522.2, 522.205222)
#' targetFeatTable[2,] <- c('ID-2', 'Cpd 2', 3280., 3385.577, 3440., 496.195038,
#'                         496.2, 496.204962)
#' targetFeatTable[,c(3:8)] <- vapply(targetFeatTable[,c(3:8)], as.numeric,
#'                                     FUN.VALUE=numeric(2))
#'
#' emptyAnnotation <- peakPantheRAnnotation(spectraPaths=spectraPaths,
#'                                         targetFeatTable=targetFeatTable)
#'
#' # colour scheme with no spectraMetadata
#' outputAnnotationFeatureMetadata_UI_helper(emptyAnnotation)
#' # NULL
spectra_metadata_colourScheme_UI_helper <- function(annot,splColrColumn=NULL) {
    # convert sampleColourColumn to a colour scale to use
    if (is.null(splColrColumn)) {
        sampleColour <- NULL
    } else if (splColrColumn=='None') { # separate for case not set yet
        sampleColour <- NULL
    } else if (!(splColrColumn %in% colnames(
        peakPantheR::spectraMetadata(annot)))) {
        sampleColour <- NULL
    } else {
        # extract metadata column of interest and unique colours needed
        tmp_meta <- peakPantheR::spectraMetadata(annot)[[splColrColumn]]
        uniq_val <- unique(tmp_meta)
        n_colr   <- length(uniq_val)

        # known colors (repeat if more groups than colours available)
        colorVect <- c("blue", "red", "green", "orange", "purple", "seagreen",
                        "darkturquoise", "violetred", "saddlebrown", "black")
        if (length(colorVect) < n_colr) {
            colorVect <- rep(colorVect, ceiling(n_colr/length(colorVect)))
        }
        # iteratively replace values by colours
        for (i in seq_len(n_colr)) {
            tmp_meta <- replace(tmp_meta, tmp_meta==uniq_val[i], colorVect[i])
        }
        sampleColour <- tmp_meta
    }

    return(sampleColour)
} # TODO: unittest