R/chondro.R

In GegznaV/hyperSpec2: Work with Hyperspectral Data, i.e. Spectra + Meta Information (Spatial, Time, Concentration, ...)

# .make.chondro <- function() {
#     new("hyperSpec",
#         spc =  (
#             tcrossprod(.chondro.scores, .chondro.loadings) +
#                 rep(.chondro.center, each = nrow(.chondro.scores))
#         ),
#         wavelength = .chondro.wl,
#         data = .chondro.extra,
#         labels = .chondro.labels
#     )
# }

##' Raman spectra of 2 Chondrocytes in Cartilage
##' A Raman-map (laterally resolved Raman spectra) of chondrocytes in
##' cartilage.
##' 
##' See the vignette \code{vignette ("chondro", package = "hyperSpec")}.
##' 
##' @name chondro
##' @docType data
##' @format The data set has 875 Raman spectra measured on a 25 \eqn{\times}{x}
##'   35 grid with 1 micron step size. Spatial information is in
##'   \code{chondro$x} and \code{chondro$y}. Each spectrum has 300 data points
##'   in the range of ca. 600 - 1800 cm\eqn{^{-1}}{^-1}.
##' @author A. Bonifacio and C. Beleites
##' @keywords datasets
##' @references The raw data is available at
##'             \url{http://hyperspec.r-forge.r-project.org/blob/chondro.zip}
##' 
##' @examples
##' chondro
##' 
##' ## do baseline correction
##' baselines <- spc.fit.poly.below (chondro)
##' chondro <- chondro - baselines
##' 
##' ## area normalization
##' chondro <- chondro / colMeans(chondro)
##' 
##' ## substact common composition
##' chondro <- chondro - quantile(chondro, 0.05)
##' 
##' cols <- c("dark blue", "orange", "#C02020")
##' plotmap(chondro, clusters ~ x * y, col.regions = cols)
##' 
##' cluster.means <- aggregate(chondro, chondro$clusters, mean_pm_sd)
##' plot(cluster.means, stacked = ".aggregate", fill = ".aggregate", col = cols)
##' 
##' ## plot nucleic acid bands
##' plotmap(chondro[, , c(728, 782, 1098, 1240, 1482, 1577)],
##'        col.regions = colorRampPalette(c("white", "gold", "dark green"),
##'        space = "Lab")(20))

# @export chondro

NULL

# delayedAssign("chondro", .make.chondro())