# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
#' ParseBrukerXML.
#'
#' Reads a Bruker's xml file exported using fleximaging.
#' A list is returned where each element in the list is named according the ROI name.
#' Each element in the list consists in a data.frame with the pixels XY coordinates inside each ROI.
#'
#' @param xml_path the full path where XML file is stored.
#'
#' @return ROI pixel coordinates arranged in a named list.
#'
CparseBrukerXML <- function(xml_path) {
.Call('_rMSI_CparseBrukerXML', PACKAGE = 'rMSI', xml_path)
}
CimzMLParse <- function(xml_path) {
.Call('_rMSI_CimzMLParse', PACKAGE = 'rMSI', xml_path)
}
CimzMLStore <- function(fname, imgInfo) {
.Call('_rMSI_CimzMLStore', PACKAGE = 'rMSI', fname, imgInfo)
}
#' CalcMassAxisBinSize.
#'
#' Calc the bin size of a mass axis at each mass channels using simple peak-picking information.
#'
#' @param mass the mass axis.
#' @param intensity the intensity of a given spectrum.
#'
#' @return the bin size of each m/z channel.
#' @export
#'
CalcMassAxisBinSize <- function(mass, intensity) {
.Call('_rMSI_CalcMassAxisBinSize', PACKAGE = 'rMSI', mass, intensity)
}
#' MergeMassAxis.
#'
#' Merges two mass axis in a single one using an apropiate bin size.
#' The resulting mass axis will display a bin size equal to the minimum of two supplied vectors.
#' The bin size must be supplied along each input mass axis.
#' The first mass axis (mz1) can be a zero-length vector.
#'
#' @param mz1 the first mass axis to merge.
#' @param bins1 the bins size for the first mass axis.
#' @param mz2 the second mass axis to merge.
#' @param intensity2 the spectral intensities corresponding to the second mass axis.
#'
#' @return a list containing the common mass axis that represents mz1 and mz1 accurately and a boolean indicating if and error was raised.
#' @export
#'
MergeMassAxis <- function(mz1, bins1, mz2, bins2) {
.Call('_rMSI_MergeMassAxis', PACKAGE = 'rMSI', mz1, bins1, mz2, bins2)
}
ReduceDataPointsC <- function(mass, intensity, massMin, massMax, npoints) {
.Call('_rMSI_ReduceDataPointsC', PACKAGE = 'rMSI', mass, intensity, massMin, massMax, npoints)
}
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