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Commit c016a605 authored by Florian de Boissieu's avatar Florian de Boissieu
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clean code and update imports/exports for package

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DESCRIPTION
View file @ c016a605
......@@ -26,5 +26,6 @@ Imports:
dissUtils,
labdsv,
raster,
rgdal
rgdal,
tools
RoxygenNote: 6.1.1
NAMESPACE
View file @ c016a605
......@@ -3,7 +3,24 @@
S3method(split,line)
export(Check.Data.Format)
export(Convert.Raster2BIL)
export(Get.Diversity.From.Plots)
export(Get.List.Shp)
export(Get.Projection)
export(Map.Alpha.Diversity)
export(Map.Beta.Diversity)
export(Map.Spectral.Species)
export(Perform.PCA.Image)
export(Perform.Radiometric.Filtering)
export(Select.Components)
import(future)
import(raster)
import(tools)
importFrom(dissUtils,diss)
importFrom(fields,rdist)
importFrom(future,plan)
importFrom(future.apply,future_lapply)
importFrom(labdsv,pco)
importFrom(matlab,padarray)
importFrom(matrixStats,rowSds)
importFrom(rgdal,readOGR)
importFrom(snow,splitRows)
R/Lib_CheckConvertData.R
View file @ c016a605
......@@ -12,138 +12,142 @@
#' converts a raster into BIL format as expected by DivMapping codes
#'
#' @param Raster.Path full path for the raster to be converted
#' @param Sensor name of the sensor
#' @param Convert.Integer should data be converted into integer ?
#' @param Multiplying.Factor multiplying factor (eg convert real reflectance values between 0 and 1 into integer between 0 and 10000)
#' @param Output.Directory
#' @param Multiplying.Factor.Last multiplying factor for last band
#' @param Raster.Path character. Full path for the raster to be converted
#' @param Sensor character. Name of the sensor
#' @param Convert.Integer boolean. Should data be converted into integer ?
#' @param Multiplying.Factor numeric. Multiplying factor (eg convert real reflectance values between 0 and 1 into integer between 0 and 10000).
#' @param Output.Directory character. Path to output directory.
#' @param Multiplying.Factor.Last numeric. Multiplying factor for last band.
#'
#' @return Output.Path path for the image converted into ENVI BIL format
#' @import raster
#' @export
Convert.Raster2BIL = function(Raster.Path,Sensor = 'unknown',Output.Directory = FALSE,Convert.Integer = TRUE,Multiplying.Factor = 1,Multiplying.Factor.Last = 1){
Convert.Raster2BIL <- function(Raster.Path, Sensor = "unknown", Output.Directory = FALSE, Convert.Integer = TRUE, Multiplying.Factor = 1, Multiplying.Factor.Last = 1) {
# get directory and file name of original image
Input.File = basename(Raster.Path)
Input.Dir = dirname(Raster.Path)
Input.File <- basename(Raster.Path)
Input.Dir <- dirname(Raster.Path)
# define path where data will be stored
if (Output.Directory == FALSE){
Output.Path = paste(Input.Dir,'/Converted_DivMAP/',file_path_sans_ext(Input.File),sep='')
if (Output.Directory == FALSE) {
Output.Path <- paste(Input.Dir, "/Converted_DivMAP/", file_path_sans_ext(Input.File), sep = "")
} else {
dir.create(Output.Directory, showWarnings = FALSE,recursive = TRUE)
Output.Path = paste(Output.Directory,'/',file_path_sans_ext(Input.File),sep='')
dir.create(Output.Directory, showWarnings = FALSE, recursive = TRUE)
Output.Path <- paste(Output.Directory, "/", file_path_sans_ext(Input.File), sep = "")
}
message('The converted file will be written in the following location:')
message("The converted file will be written in the following location:")
print(Output.Path)
Output.Dir = dirname(Output.Path)
dir.create(Output.Dir, showWarnings = FALSE,recursive = TRUE)
Output.Dir <- dirname(Output.Path)
dir.create(Output.Dir, showWarnings = FALSE, recursive = TRUE)
# apply multiplying factors
message('reading initial file')
Output.Img = Multiplying.Factor*brick(Raster.Path)
Last.Band.Name = Output.Img@data@names[length(Output.Img@data@names)]
Output.Img[[Last.Band.Name]] = Multiplying.Factor.Last*Output.Img[[Last.Band.Name]]
message("reading initial file")
Output.Img <- Multiplying.Factor * brick(Raster.Path)
Last.Band.Name <- Output.Img@data@names[length(Output.Img@data@names)]
Output.Img[[Last.Band.Name]] <- Multiplying.Factor.Last * Output.Img[[Last.Band.Name]]
# convert into integer
if (Convert.Integer==TRUE){
Output.Img = round(Output.Img)
if (Convert.Integer == TRUE) {
Output.Img <- round(Output.Img)
}
# write raster
message('writing converted file')
if (Convert.Integer ==TRUE){
r = writeRaster(Output.Img, filename = Output.Path, format="EHdr", overwrite=TRUE,datatype='INT2S')
message("writing converted file")
if (Convert.Integer == TRUE) {
r <- writeRaster(Output.Img, filename = Output.Path, format = "EHdr", overwrite = TRUE, datatype = "INT2S")
} else {
r = writeRaster(Output.Img, filename = Output.Path, format="EHdr", overwrite=TRUE)
r <- writeRaster(Output.Img, filename = Output.Path, format = "EHdr", overwrite = TRUE)
}
hdr(r, format="ENVI")
hdr(r, format = "ENVI")
# remove unnecessary files
File2Remove = paste(Output.Path,'.aux.xml',sep='')
File2Remove2 = paste(file_path_sans_ext(Output.Path),'.aux.xml',sep='')
File2Remove <- paste(Output.Path, ".aux.xml", sep = "")
File2Remove2 <- paste(file_path_sans_ext(Output.Path), ".aux.xml", sep = "")
file.remove(File2Remove)
File2Remove = paste(Output.Path,'.prj',sep='')
File2Remove2 = paste(file_path_sans_ext(Output.Path),'.prj',sep='')
if (file.exists(File2Remove)){
File2Remove <- paste(Output.Path, ".prj", sep = "")
File2Remove2 <- paste(file_path_sans_ext(Output.Path), ".prj", sep = "")
if (file.exists(File2Remove)) {
file.remove(File2Remove)
} else if (file.exists(File2Remove2)){
} else if (file.exists(File2Remove2)) {
file.remove(File2Remove2)
}
File2Remove = paste(Output.Path,'.sta',sep='')
File2Remove = paste(file_path_sans_ext(Output.Path),'.sta',sep='')
if (file.exists(File2Remove)){
File2Remove <- paste(Output.Path, ".sta", sep = "")
File2Remove <- paste(file_path_sans_ext(Output.Path), ".sta", sep = "")
if (file.exists(File2Remove)) {
file.remove(File2Remove)
} else if (file.exists(File2Remove2)){
} else if (file.exists(File2Remove2)) {
file.remove(File2Remove2)
}
File2Remove = paste(Output.Path,'.stx',sep='')
File2Remove2 = paste(file_path_sans_ext(Output.Path),'.stx',sep='')
if (file.exists(File2Remove)){
File2Remove <- paste(Output.Path, ".stx", sep = "")
File2Remove2 <- paste(file_path_sans_ext(Output.Path), ".stx", sep = "")
if (file.exists(File2Remove)) {
file.remove(File2Remove)
} else if (file.exists(File2Remove2)){
} else if (file.exists(File2Remove2)) {
file.remove(File2Remove2)
}
File2Rename = paste(file_path_sans_ext(Output.Path),'.hdr',sep='')
File2Rename2= paste(Output.Path,'.hdr',sep='')
if (file.exists(File2Rename)){
file.rename(from = File2Rename,to = File2Rename2)
File2Rename <- paste(file_path_sans_ext(Output.Path), ".hdr", sep = "")
File2Rename2 <- paste(Output.Path, ".hdr", sep = "")
if (file.exists(File2Rename)) {
file.rename(from = File2Rename, to = File2Rename2)
}
# change dot into underscore
Output.Path.US = gsub(Output.Path,pattern = '[.]',replacement = '_')
if (!Output.Path.US==Output.Path){
file.rename(from = Output.Path,to = Output.Path.US)
Output.Path.US <- file.path(
dirname(Output.Path),
gsub(basename(Output.Path), pattern = "[.]", replacement = "_")
)
if (!Output.Path.US == Output.Path) {
file.rename(from = Output.Path, to = Output.Path.US)
}
Output.Path.US.HDR = paste(gsub(Output.Path,pattern = '[.]',replacement = '_'),'.hdr',sep='')
if (!Output.Path.US.HDR==paste(Output.Path,'.hdr',sep='')){
file.rename(from = paste(Output.Path,'.hdr',sep=''),to = Output.Path.US.HDR)
file.rename(from = Output.Path.US.HDR,to = Output.Path.US.HDR)
Output.Path.US.HDR <- paste0(Output.Path.US, ".hdr")
if (!Output.Path.US.HDR == paste0(Output.Path, ".hdr")) {
file.rename(from = paste0(Output.Path, ".hdr"), to = Output.Path.US.HDR)
### UTILITY?? ###
file.rename(from = Output.Path.US.HDR, to = Output.Path.US.HDR)
}
if (!Sensor=='unknown'){
HDR.Temp.Path = system.file('extdata','HDR',paste0(Sensor,'.hdr'),package = 'DiversityMappR')
if (file.exists(HDR.Temp.Path)){
message('reading header template corresponding to the sensor located here:')
if (!Sensor == "unknown") {
HDR.Temp.Path <- system.file("extdata", "HDR", paste0(Sensor, ".hdr"), package = "DiversityMappR")
if (file.exists(HDR.Temp.Path)) {
message("reading header template corresponding to the sensor located here:")
print(HDR.Temp.Path)
# get raster template corresponding to the sensor
HDR.Template = read.ENVI.header(HDR.Temp.Path)
HDR.Template <- read.ENVI.header(HDR.Temp.Path)
# get info to update hdr file
# read hdr
HDR.input = read.ENVI.header(Get.HDR.Name(Output.Path))
if (!is.null(HDR.Template$wavelength)){
HDR.input$wavelength = HDR.Template$wavelength
HDR.input <- read.ENVI.header(Get.HDR.Name(Output.Path))
if (!is.null(HDR.Template$wavelength)) {
HDR.input$wavelength <- HDR.Template$wavelength
}
if (!is.null(HDR.Template$`sensor type`)){
HDR.input$`sensor type` = HDR.Template$`sensor type`
if (!is.null(HDR.Template$`sensor type`)) {
HDR.input$`sensor type` <- HDR.Template$`sensor type`
}
if (!is.null(HDR.Template$`band names`)){
HDR.input$`band names` = HDR.Template$`band names`
if (!is.null(HDR.Template$`band names`)) {
HDR.input$`band names` <- HDR.Template$`band names`
}
if (!is.null(HDR.Template$`wavelength units`)){
HDR.input$`wavelength units` = HDR.Template$`wavelength units`
if (!is.null(HDR.Template$`wavelength units`)) {
HDR.input$`wavelength units` <- HDR.Template$`wavelength units`
}
# define visual stretch in the VIS domain
HDR.input$`default stretch` = '0 1000 linear'
HDR.input$`default stretch` <- "0 1000 linear"
# write corresponding hdr file
write.ENVI.header(HDR.input, Get.HDR.Name(Output.Path))
} else if (!file.exists(HDR.Temp.Path)){
message('Header template corresponding to the sensor expected to be found here')
} else if (!file.exists(HDR.Temp.Path)) {
message("Header template corresponding to the sensor expected to be found here")
print(HDR.Temp.Path)
message('please provide this header template in order to write info in HDR file')
message("please provide this header template in order to write info in HDR file")
print(Get.HDR.Name(Output.Path))
message('or manually add wavelength location in HDR file, if relevant')
message("or manually add wavelength location in HDR file, if relevant")
}
} else if (Sensor=='unknown'){
message('please make sure that the follozing header file contains information required')
} else if (Sensor == "unknown") {
message("please make sure that the follozing header file contains information required")
print(Get.HDR.Name(Output.Path))
message('or manually add wavelength location in HDR file, if relevant')
message("or manually add wavelength location in HDR file, if relevant")
}
return(Output.Path)
}
......@@ -153,78 +157,76 @@ Convert.Raster2BIL = function(Raster.Path,Sensor = 'unknown',Output.Directory =
#' @param Raster.Path full path for the raster to be converted
#' @param Mask is the raster a mask?
#'
#' @return Output.Path path for the image converted into ENVI BIL format
#' @export
Check.Data.Format = function(Raster.Path,Mask = FALSE){
HDR.Path = Get.HDR.Name(Raster.Path)
Check.Data.Format <- function(Raster.Path, Mask = FALSE) {
HDR.Path <- Get.HDR.Name(Raster.Path)
# check if the hdr file exists
if (file.exists(HDR.Path)){
HDR = read.ENVI.header(HDR.Path)
if (Mask == FALSE & (!HDR$interleave=='bil') & (!HDR$interleave=='BIL')){
message('')
message('*********************************************************')
message('The image format may not compatible with the processing chain')
message('Image format expected:')
message('ENVI hdr file with band interleaved by line (BIL) file format')
message('')
message('Current Image format')
if (file.exists(HDR.Path)) {
HDR <- read.ENVI.header(HDR.Path)
if (Mask == FALSE & (!HDR$interleave == "bil") & (!HDR$interleave == "BIL")) {
message("")
message("*********************************************************")
message("The image format may not compatible with the processing chain")
message("Image format expected:")
message("ENVI hdr file with band interleaved by line (BIL) file format")
message("")
message("Current Image format")
print(HDR$interleave)
message('Please run the function named ')
print('Convert.Raster2BIL')
message('in order to convert your raster data')
message('or use appropriate software')
message('*********************************************************')
message('')
message("Please run the function named ")
print("Convert.Raster2BIL")
message("in order to convert your raster data")
message("or use appropriate software")
message("*********************************************************")
message("")
stop()
} else if (Mask == FALSE & ((HDR$interleave=='bil') | (HDR$interleave=='BIL'))){
if (HDR$`wavelength units`=='Unknown'){
message('')
message('*********************************************************')
message('Please make sure the wavelengths are in nanometers')
message('if not, stop processing and convert wavelengths in nanometers in HDR file')
message('*********************************************************')
message('')
} else if (Mask == FALSE & ((HDR$interleave == "bil") | (HDR$interleave == "BIL"))) {
if (HDR$`wavelength units` == "Unknown") {
message("")
message("*********************************************************")
message("Please make sure the wavelengths are in nanometers")
message("if not, stop processing and convert wavelengths in nanometers in HDR file")
message("*********************************************************")
message("")
}
if ((!HDR$`wavelength units`=='Nanometers') & (!HDR$`wavelength units`=='nanometers')){
message('')
message('*********************************************************')
message('Please make sure the wavelengths are in nanometers')
message('if not, stop processing and convert wavelengths in nanometers in HDR file')
message('*********************************************************')
message('')
if ((!HDR$`wavelength units` == "Nanometers") & (!HDR$`wavelength units` == "nanometers")) {
message("")
message("*********************************************************")
message("Please make sure the wavelengths are in nanometers")
message("if not, stop processing and convert wavelengths in nanometers in HDR file")
message("*********************************************************")
message("")
}
if (HDR$`wavelength units`=='micrometers'){
message('')
message('*********************************************************')
message('Please convert wavelengths in nanometers in HDR file')
message('*********************************************************')
message('')
if (HDR$`wavelength units` == "micrometers") {
message("")
message("*********************************************************")
message("Please convert wavelengths in nanometers in HDR file")
message("*********************************************************")
message("")
stop()
}
if ((HDR$`wavelength units`=='nanometers') | (HDR$`wavelength units`=='Nanometers')){
message('')
message('*********************************************************')
message(' All information seem OK for image processing ')
message('*********************************************************')
message('')
if ((HDR$`wavelength units` == "nanometers") | (HDR$`wavelength units` == "Nanometers")) {
message("")
message("*********************************************************")
message(" All information seem OK for image processing ")
message("*********************************************************")
message("")
}
}
} else {
message('')
message('*********************************************************')
message('The following HDR file was expected, but could not be found:')
message("")
message("*********************************************************")
message("The following HDR file was expected, but could not be found:")
print(HDR.Path)
message('The image format may not compatible with the processing chain')
message('Image format expected:')
message('ENVI hdr file with band interleaved by line (BIL) file format')
message('')
message('Please run the function named ')
print('Convert.Raster2BIL')
message('in order to convert your raster data')
message('*********************************************************')
message('')
message("The image format may not compatible with the processing chain")
message("Image format expected:")
message("ENVI hdr file with band interleaved by line (BIL) file format")
message("")
message("Please run the function named ")
print("Convert.Raster2BIL")
message("in order to convert your raster data")
message("*********************************************************")
message("")
stop()
}
return()
return(invisible())
}
R/Lib_ContinuumRemoval.R
View file @ c016a605
......@@ -9,187 +9,189 @@
# This Library is dedicated to the computation of the continuum removal
# ===============================================================================
#' prepares data to run multithreaded continuum removal
#'
#' @param Spectral.Data initial data matrix (nb samples x nb bands)
#' @param nbCPU
#' @param Spectral information about spectral bands
#'
#' @return samples from image and updated number of pixels to sampel if necessary
Apply.Continuum.Removal=function(Spectral.Data,Spectral,nbCPU=1){
if (!length(Spectral$WaterVapor)==0){
Spectral.Data=Spectral.Data[,-Spectral$WaterVapor]
# prepares data to run multithreaded continuum removal
#
# @param Spectral.Data initial data matrix (nb samples x nb bands)
# @param nbCPU
# @param Spectral information about spectral bands
#
# @return samples from image and updated number of pixels to sampel if necessary
#' @importFrom snow splitRows
#' @import future
#' @importFrom future.apply future_lapply
Apply.Continuum.Removal <- function(Spectral.Data, Spectral, nbCPU = 1) {
if (!length(Spectral$WaterVapor) == 0) {
Spectral.Data <- Spectral.Data[, -Spectral$WaterVapor]
}
# split data to perform continuum removal on into reasonable amount of data
nb.Values = size(Spectral.Data)[1]*size(Spectral.Data)[2]
if (nb.Values>0){
nb.Values <- dim(Spectral.Data)[1] * dim(Spectral.Data)[2]
if (nb.Values > 0) {
# corresponds to ~ 40 Mb data, but CR tends to requires ~ 10 times memory
# avoids memory crash
Max.nb.Values = 2e6
nb.CR = ceiling(nb.Values/Max.nb.Values)
Spectral.Data = splitRows(Spectral.Data,nb.CR)
Max.nb.Values <- 2e6
nb.CR <- ceiling(nb.Values / Max.nb.Values)
Spectral.Data <- splitRows(Spectral.Data, nb.CR)
# perform multithread continuum removal
plan(multiprocess, workers = nbCPU) ## Parallelize using four cores
Schedule.Per.Thread = ceiling(nb.CR/nbCPU)
Spectral.Data.tmp=future_lapply(Spectral.Data,FUN = ContinuumRemoval,Spectral.Bands=Spectral$Wavelength,future.scheduling = Schedule.Per.Thread)
Schedule.Per.Thread <- ceiling(nb.CR / nbCPU)
Spectral.Data.tmp <- future_lapply(Spectral.Data, FUN = ContinuumRemoval, Spectral.Bands = Spectral$Wavelength, future.scheduling = Schedule.Per.Thread)
plan(sequential)
Spectral.Data = do.call("rbind",Spectral.Data.tmp)
Spectral.Data <- do.call("rbind", Spectral.Data.tmp)
rm(Spectral.Data.tmp)
} else {
# edit 31-jan-2018
# resize to delete first and last band as in continuum removal
Spectral.Data=Spectral.Data[,-c(1,2)]
Spectral.Data <- Spectral.Data[, -c(1, 2)]
}
gc()
return(Spectral.Data)
}
#' Computes continuum removal for matrix shaped data: more efficient than
#' processing individual spectra
#' the convex hull is based on the computation of the derivative between R at a
#' given spectral band and R at the following bands
#'
#' @param Minit initial data matrix (nb samples x nb bands)
#' @param Spectral.Bands information about spectral bands
#'
#' @return samples from image and updated number of pixels to sampel if necessary
ContinuumRemoval=function(Minit,Spectral.Bands){
# Computes continuum removal for matrix shaped data: more efficient than
# processing individual spectra
# the convex hull is based on the computation of the derivative between R at a
# given spectral band and R at the following bands
#
# @param Minit initial data matrix (nb samples x nb bands)
# @param Spectral.Bands information about spectral bands
#
# @return samples from image and updated number of pixels to sampel if necessary
ContinuumRemoval <- function(Minit, Spectral.Bands) {
# Filter and prepare data prior to continuum removal
CR.data = Filter.Prior.CR(Minit,Spectral.Bands)
Minit = CR.data$Minit
nb.Bands = size(Minit)[2]
CR.data$Minit = c()
Spectral.Bands = CR.data$Spectral.Bands
nb.Samples = CR.data$nb.Samples
CR.data <- Filter.Prior.CR(Minit, Spectral.Bands)
Minit <- CR.data$Minit
nb.Bands <- dim(Minit)[2]
CR.data$Minit <- c()
Spectral.Bands <- CR.data$Spectral.Bands
nb.Samples <- CR.data$nb.Samples
# if samples to be considered
if (nb.Samples>0){
if (nb.Samples > 0) {
# initialization:
# spectral band corresponding to each element of the data matrix
Lambda = repmat(matrix(Spectral.Bands,nrow=1),nb.Samples,1)
Lambda <- repmat(matrix(Spectral.Bands, nrow = 1), nb.Samples, 1)
# prepare matrices used to check evolution of the CR process
# - elements still not processed through continuum removal: initialization to 1
Still.Need.CR = matrix(1,nrow=nb.Samples,ncol=nb.Bands)
Still.Need.CR <- matrix(1, nrow = nb.Samples, ncol = nb.Bands)
# - value of the convex hull: initially set to 0
Convex.Hull = matrix(0,nrow=nb.Samples,ncol=nb.Bands)
Convex.Hull <- matrix(0, nrow = nb.Samples, ncol = nb.Bands)
# - reflectance value for latest interception with convex hull:
# initialization to value of the first reflectance measurement
Intercept.Hull = repmat(matrix(Minit[,1],ncol=1),1,nb.Bands)
Intercept.Hull <- repmat(matrix(Minit[, 1], ncol = 1), 1, nb.Bands)
# - spectral band of latest interception
Latest.Intercept= repmat(matrix(Spectral.Bands[1],ncol=1),nb.Samples,nb.Bands)
Latest.Intercept <- repmat(matrix(Spectral.Bands[1], ncol = 1), nb.Samples, nb.Bands)
# number of spectral bands found as intercept
nb.Intercept = 0
nb.Intercept <- 0
# continues until arbitrary stopping criterion:
# stops when reach last spectral band (all values before last = 0)
while (max(Still.Need.CR[,1:(nb.Bands-2)])==1 & (nb.Intercept <=(nb.Bands/2))){
nb.Intercept = nb.Intercept+1
while (max(Still.Need.CR[, 1:(nb.Bands - 2)]) == 1 & (nb.Intercept <= (nb.Bands / 2))) {
nb.Intercept <- nb.Intercept + 1
# Mstep give the position of the values to be updated
Update.Data = matrix(1,nrow=nb.Samples,ncol=nb.Bands)
Update.Data[,nb.Bands]=0
Update.Data <- matrix(1, nrow = nb.Samples, ncol = nb.Bands)
Update.Data[, nb.Bands] <- 0
# initial step: first column set to 0; following steps: all bands below
# max of the convex hull are set to 0
Update.Data[which((Lambda-Latest.Intercept)<0)]=0
Update.Data[which((Lambda - Latest.Intercept) < 0)] <- 0
# compute slope for each coordinate
Slope = (Minit-Intercept.Hull)/(Lambda-Latest.Intercept)*Still.Need.CR
Slope <- (Minit - Intercept.Hull) / (Lambda - Latest.Intercept) * Still.Need.CR
# set current spectral band and previous bands to -9999
if (!length(which(Still.Need.CR==0))==0){
Slope[which(Still.Need.CR==0)]=-9999
if (!length(which(Still.Need.CR == 0)) == 0) {
Slope[which(Still.Need.CR == 0)] <- -9999
}
if (!length(which(is.na(Slope)))==0){
Slope[which(is.na(Slope))]=-9999
if (!length(which(is.na(Slope))) == 0) {
Slope[which(is.na(Slope))] <- -9999
}
# get max index for each row and convert into linear index
Index.Max.Slope = RowToLinear(max.col(Slope,ties.method="last"),nb.Samples,nb.Bands)
Index.Max.Slope <- RowToLinear(max.col(Slope, ties.method = "last"), nb.Samples, nb.Bands)
# !!!! OPTIM: replace repmat with column operation
# update coordinates of latest intercept
Latest.Intercept = repmat(matrix(Lambda[Index.Max.Slope],ncol=1),1,nb.Bands)
Latest.Intercept <- repmat(matrix(Lambda[Index.Max.Slope], ncol = 1), 1, nb.Bands)
# update latest intercept
Intercept.Hull = repmat(matrix(Minit[Index.Max.Slope],ncol=1),1,nb.Bands)
Intercept.Hull <- repmat(matrix(Minit[Index.Max.Slope], ncol = 1), 1, nb.Bands)
# values corresponding to the domain between the two continuum maxima
Update.Data[which((Lambda-Latest.Intercept)>=0 | Latest.Intercept==Spectral.Bands[nb.Bands])]=0
Update.Data[which((Lambda - Latest.Intercept) >= 0 | Latest.Intercept == Spectral.Bands[nb.Bands])] <- 0
# values to eliminate for the next analysis: all spectral bands before latest intercept
Still.Need.CR[which((Lambda-Latest.Intercept)<0)] = 0
Still.Need.CR[which((Lambda - Latest.Intercept) < 0)] <- 0
# the max slope is known, as well as the coordinates of the beginning and ending
# a matrix now has to be built