# HG changeset patch # User lecorguille # Date 1522238712 14400 # Node ID 5e64657b4fe5d040dd2ee6bf5ed912955ccd2c75 # Parent cbea5e9fd0b4601308c614ba07cb417282d1cdb5 planemo upload for repository https://github.com/workflow4metabolomics/nmr_preprocessing commit 22ca8782d7c4c0211e13c95b425d4f29f53f995e diff -r cbea5e9fd0b4 -r 5e64657b4fe5 DrawFunctions.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/DrawFunctions.R Wed Mar 28 08:05:12 2018 -0400 @@ -0,0 +1,268 @@ +require(ggplot2) +require(gridExtra) +require(reshape2) + + +Draw <- function(Signal_data, type.draw = c("signal", "pca"), output = c("default", + "window", "png", "pdf"), dirpath = ".", filename = "%003d", height = 480, + width = 640, pdf.onefile = TRUE, ...) { + + # Data initialisation and checks ---------------------------------------------- + type.draw <- match.arg(type.draw) + output <- match.arg(output) + fullpath <- paste(file.path(dirpath, filename), output, sep = ".") + createFile <- TRUE + createWindow <- FALSE + + # Drawing -------------------------------------------------------------------- + # output + switch(output, default = { + createFile <- FALSE + }, window = { + createWindow <- TRUE + createFile <- FALSE + }, png = { + grDevices::png(fullpath, width, height) + }, pdf = { + grDevices::pdf(fullpath, width = width/72, height = height/72, + onefile = pdf.onefile) + }, { + stop("Unknown output type.") + }) + + # Drawing type (signal/spectrum or PCA) + funs <- list(signal = DrawSignal, pca = DrawPCA) + if (type.draw %in% names(funs)) { + fun <- funs[[type.draw]] + } else { + stop(paste("Unknown type:", type.draw)) + } + + # Plot finalisation ---------------------------------------------- + if (is.vector(Signal_data)) { + Signal_data <- vec2mat(Signal_data) + } + fun(Signal_data, createWindow = createWindow, ...) + if (createFile) { + grDevices::dev.off() + } +} + + + +##### DrawSignal + +DrawSignal <- function(Signal_data, subtype = c("stacked", "together", + "separate", "diffmean", "diffmedian", "diffwith"), + ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, + xlab = "rowname", RowNames = NULL, row = 1, num.stacked = 4, + main = NULL, createWindow) { + # nticks + + # Data initialisation and checks ---------------------------------------------- + + subtype <- match.arg(subtype) + vec <- is.vector(Signal_data) + if (vec) { + Signal_data <- vec2mat(Signal_data) + } + + n <- nrow(Signal_data) + m <- ncol(Signal_data) + + if (n < num.stacked){ + num.stacked <- n + } + + scale <- colnames(Signal_data) + + num.plot <- sum(ReImModArg) + + Var <- rowname <- value <- NULL # only for R CMD check + + # Drawing array + if (num.plot <= 0) { + stop("Nothing selected in ReImModArg.") + } else if (num.plot <= 2) { + if (vertical) { + nrow <- num.plot + ncol <- 1 + } else { + nrow <- 1 + ncol <- num.plot + } + } else { + nrow <- 2 + ncol <- 2 + } + + # RowNames + if (is.null(RowNames)) { + RowNames <- rownames(Signal_data) + if (is.null(RowNames)) { + RowNames <- 1:n + } + } else { + if (!is.vector(RowNames)) { + stop("RowNames is not a vector") + } + if (length(RowNames) != n) { + stop(paste("RowNames has length", length(RowNames), "and there are", n, "FIDs.")) + } + } + + if (n == 1) { + RowNames <- deparse(substitute(Signal_data)) + } + + elements <- list() + if (ReImModArg[1]) { + elements[["Re"]] <- Re(Signal_data) + rownames(elements[["Re"]]) <- RowNames + } + if (ReImModArg[2]) { + elements[["Im"]] <- Im(Signal_data) + rownames(elements[["Im"]]) <- RowNames + } + if (ReImModArg[3]) { + elements[["Mod"]] <- Mod(Signal_data) + rownames(elements[["Mod"]]) <- RowNames + } + if (ReImModArg[4]) { + elements[["Arg"]] <- Arg(Signal_data) + rownames(elements[["Arg"]]) <- RowNames + } + + + + + # Drawing -------------------------------------------------------------------- + + y = x = NULL # only for R CMD check + + + # SEPARATE or STACKED =============== + if (subtype == "separate" | subtype == "stacked") { + + i <- 1 + while (i <= n) { + if (createWindow) { + grDevices::dev.new(noRStudioGD = TRUE) + } + if (subtype == "separate") { + # The other uses gridExtra to do that + graphics::par(mfrow = c(nrow, ncol)) + } + plots <- list() + if (subtype == "separate") { + last <- i + } else { + last <- min(i + num.stacked - 1, n) + } + for (name in names(elements)) { + if (subtype == "separate") { + if (n == 1) { + df <- data.frame(x = as.numeric(scale), y = elements[[name]]) + } else {df <- data.frame(x = as.numeric(scale), y = elements[[name]][i, ]) + } + + plots[[name]] <- ggplot2::ggplot(data = df, ggplot2::aes(x = x, y = y)) + + ggplot2::geom_line(size = 1) + + ggplot2::theme(legend.position = "none") + + ggplot2::labs(x = xlab, y = name) + + ggplot2::ggtitle(RowNames[i]) + + ggplot2::theme_bw() + + if ((df[1, "x"] - df[(dim(df)[1]), "x"]) > 0) { + plots[[name]] <- plots[[name]] + ggplot2::scale_x_reverse() + } + + } else { + + if (n == 1 ) { + melted <- data.frame(rowname = rep(name, m), + Var = as.numeric(scale), value = elements[[name]][i,]) + } else if (last==i){ + melted <- data.frame(rowname = rep(rownames(elements[[name]])[i], m), + Var = as.numeric(scale), value = elements[[name]][i,]) + } else {melted <- reshape2::melt(elements[[name]][i:last, ], + varnames = c("rowname", "Var")) + } + + + plots[[name]] <- ggplot2::ggplot(data = melted, ggplot2::aes(x = Var, y = value)) + + ggplot2::geom_line(size = 0.3) + + ggplot2::facet_grid(rowname ~ ., scales = "free_y") + + ggplot2::theme(legend.position = "none") + + ggplot2::labs(x = xlab, y = name) + + ggplot2::ggtitle(label = main) + + ggplot2::theme_bw() + + if ((melted[1, "Var"] - melted[(dim(melted)[1]), "Var"]) > 0) { + plots[[name]] <- plots[[name]] + ggplot2::scale_x_reverse() + } + } + } + + if (subtype == "stacked") { + do.call(gridExtra::grid.arrange, c(plots, list(nrow = nrow, ncol = ncol))) + } + + i <- last + 1 + } + } else if (subtype %in% c("together", "diffmean", "diffmedian", "diffwith")) { + + # TOGHETER or DIFFMEAN or DIFFMEDIAN or DIFFWITH =============== + + rainbow_colors <- grDevices::rainbow(n) + + if (createWindow) { + grDevices::dev.new(noRStudioGD = TRUE) + } + graphics::par(mfrow = c(nrow, ncol)) + + plots <- list() + + # Loop for Re, Im, Mod and Arg + for (name in names(elements)) { + # Get this part of the signal + element <- elements[[name]] + + # Express the signal according to a reference if asked by `subtype' + if (subtype == "diffmean") { + element <- sweep(element, MARGIN = 2, colMeans(element), `-`) + } else if (subtype == "diffmedian") { + element <- sweep(element, MARGIN = 2, matrixStats::colMedians(element), `-`) + } else if (subtype == "diffwith") { + element <- sweep(element, MARGIN = 2, element[row, ], `-`) + if (row == 1 & n > 1) { + # Since we use plot on the first row and lines on the following, the y + # scale is calculated at the first row so if the first row is all 0, it + # causes problems + tmp <- element[1, ] + element[1, ] <- element[2, ] + element[2, ] <- tmp + } + } + + + melted <- reshape2::melt(elements[[name]], varnames = c("rowname", "Var")) + + + plots[[name]] <- ggplot2::ggplot(melted, ggplot2::aes(x = Var, + y = value, group = rowname, colour = rowname)) + ggplot2::geom_line() + + ggplot2::labs(x = xlab, y = name) + ggplot2::scale_colour_discrete(name = NULL) + + ggplot2::ggtitle(main) + + if ((melted[1, "Var"] - melted[(dim(melted)[1]), "Var"]) > + 0) { + plots[[name]] <- plots[[name]] + ggplot2::scale_x_reverse() + } + + do.call(gridExtra::grid.arrange, c(plots, list(nrow = nrow, + ncol = ncol))) + } + } + + +} diff -r cbea5e9fd0b4 -r 5e64657b4fe5 NmrPreprocessing_script.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/NmrPreprocessing_script.R Wed Mar 28 08:05:12 2018 -0400 @@ -0,0 +1,1214 @@ +## ========================== +# Internal functions +## ========================== + +# beginTreatment +beginTreatment <- function(name, Signal_data = NULL, Signal_info = NULL, + force.real = FALSE) { + + cat("Begin", name, "\n") + + + # Formatting the Signal_data and Signal_info ----------------------- + + vec <- is.vector(Signal_data) + if (vec) { + Signal_data <- vec2mat(Signal_data) + } + if (is.vector(Signal_info)) { + Signal_info <- vec2mat(Signal_info) + } + if (!is.null(Signal_data)) { + if (!is.matrix(Signal_data)) { + stop("Signal_data is not a matrix.") + } + if (!is.complex(Signal_data) && !is.numeric(Signal_data)) { + stop("Signal_data contains non-numerical values.") + } + } + if (!is.null(Signal_info) && !is.matrix(Signal_info)) { + stop("Signal_info is not a matrix.") + } + + + Original_data <- Signal_data + + # Extract the real part of the spectrum --------------------------- + + if (force.real) { + if (is.complex(Signal_data)) { + Signal_data <- Re(Signal_data) + } else { + # The signal is numeric Im(Signal_data) is zero anyway so let's avoid + # using complex(real=...,imaginary=0) which would give a complex signal + # in endTreatment() + force.real <- FALSE + } + } + + + # Return the formatted data and metadata entries -------------------- + + return(list(start = proc.time(), vec = vec, force.real = force.real, + Original_data = Original_data, Signal_data = Signal_data, Signal_info = Signal_info)) +} + +# endTreatment +endTreatment <- function(name, begin_info, Signal_data) { + + # begin_info: object outputted from beginTreatment + + + # Formatting the entries and printing process time ----------------------- + end_time <- proc.time() # record it as soon as possible + start_time <- begin_info[["start"]] + delta_time <- end_time - start_time + delta <- delta_time[] + cat("End", name, "\n") + cat("It lasted", round(delta["user.self"], 3), "s user time,", round(delta["sys.self"],3), + "s system time and", round(delta["elapsed"], 3), "s elapsed time.\n") + + + if (begin_info[["force.real"]]) { + # The imaginary part is left untouched + i <- complex(real = 0, imaginary = 1) + Signal_data <- Signal_data + i * Im(begin_info[["Original_data"]]) + } + + if (begin_info[["vec"]]) { + Signal_data <- Signal_data[1, ] + } + + # Return the formatted data and metadata entries -------------------- + return(Signal_data) +} + +# checkArg +checkArg <- function(arg, checks, can.be.null=FALSE) { + check.list <- list(bool=c(is.logical, "a boolean"), + int =c(function(x){x%%1==0}, "an integer"), + num =c(is.numeric, "a numeric"), + str =c(is.character, "a string"), + pos =c(function(x){x>0}, "positive"), + pos0=c(function(x){x>=0}, "positive or zero"), + l1 =c(function(x){length(x)==1}, "of length 1") + ) + if (is.null(arg)) { + if (!can.be.null) { + stop(deparse(substitute(arg)), " is null.") + } + } else { + if (is.matrix(arg)) { + stop(deparse(substitute(arg)), " is not scalar.") + } + for (c in checks) { + if (!check.list[[c]][[1]](arg)) { + stop(deparse(substitute(arg)), " is not ", check.list[[c]][[2]], ".") + } + } + } +} + +# getArg +getArg <- function(arg, info, argname, can.be.absent=FALSE) { + if (is.null(arg)) { + start <- paste("impossible to get argument", argname, "it was not given directly and"); + if (!is.matrix(info)) { + stop(paste(start, "the info matrix was not given")) + } + if (!(argname %in% colnames(info))) { + if (can.be.absent) { + return(NULL) + } else { + stop(paste(start, "is not in the info matrix")) + } + } + if (nrow(info) < 1) { + stop(paste(start, "the info matrix has no row")) + } + arg <- info[1,argname] + if (is.na(arg)) { + stop(paste(start, "it is NA in the info matrix")) + } + } + return(arg) +} + +# binarySearch +binarySearch <- function(a, target, lower = TRUE) { + # search the index i in a such that a[i] == target + # if it doesn't exists and lower, it searches the closer a[i] such that a[i] < target + # if !lower, it seraches the closer a[i] such that a[i] > target + # a should be monotone but can be increasing or decreasing + + # if a is increasing INVARIANT: a[amin] < target < a[amax] + N <- length(a) + if ((a[N] - target) * (a[N] - a[1]) <= 0) { + return(N) + } + if ((a[1] - target) * (a[N] - a[1]) >= 0) { + return(1) + } + amin <- 1 + amax <- N + while (amin + 1 < amax) { + amid <- floor((amin + amax)/2) + if ((a[amid] - target) * (a[amax] - a[amid]) < 0) { + amin <- amid + } else if ((a[amid] - target) * (a[amax] - a[amid]) > 0) { + amax <- amid + } else { + # a[amid] == a[amax] or a[amid] == target In both cases, a[amid] == + # target + return(amid) + } + } + if (xor(lower, a[amin] > a[amax])) { + # (lower && a[amin] < a[amax]) || (!lower && a[min] > a[max]) + # If increasing and we want the lower, we take amin + # If decreasing and we want the bigger, we take amin too + return(amin) + } else { + return(amax) + } +} + +# Interpol +Interpol <- function(t, y) { + # y: sample + # t : warping function + + m <- length(y) + # t <= m-1 + # because if t > m-1, y[ti+1] will be NA when we compute g + valid <- 1 <= t & t <= m-1 # FIXME it was '<' in Bubble v2 + s <- (1:m)[valid] + ti <- floor(t[s]) + tr <- t[s] - ti + g <- y[ti + 1] - y[ti] + f <- y[ti] + tr * g + list(f=f, s=s, g=g) +} + +# vec2mat +vec2mat <- function(vec) { + return(matrix(vec, nrow = 1, dimnames = list(c(1), names(vec)))) + +} + +# binarySearch +binarySearch <- function(a, target, lower = TRUE) { + # search the index i in a such that a[i] == target + # if it doesn't exists and lower, it searches the closer a[i] such that a[i] < target + # if !lower, it seraches the closer a[i] such that a[i] > target + # a should be monotone but can be increasing or decreasing + + # if a is increasing INVARIANT: a[amin] < target < a[amax] + N <- length(a) + if ((a[N] - target) * (a[N] - a[1]) <= 0) { + return(N) + } + if ((a[1] - target) * (a[N] - a[1]) >= 0) { + return(1) + } + amin <- 1 + amax <- N + while (amin + 1 < amax) { + amid <- floor((amin + amax)/2) + if ((a[amid] - target) * (a[amax] - a[amid]) < 0) { + amin <- amid + } else if ((a[amid] - target) * (a[amax] - a[amid]) > 0) { + amax <- amid + } else { + # a[amid] == a[amax] or a[amid] == target In both cases, a[amid] == + # target + return(amid) + } + } + if (xor(lower, a[amin] > a[amax])) { + # (lower && a[amin] < a[amax]) || (!lower && a[min] > a[max]) + # If increasing and we want the lower, we take amin + # If decreasing and we want the bigger, we take amin too + return(amin) + } else { + return(amax) + } +} + + +# indexInterval +indexInterval <- function (a, from, to, inclusive=TRUE) { + # If inclusive and from <= to, we need to take the lower + # If not inclusive and from > to, we need to take the lower too + lowerFrom <- xor(inclusive, from > to) + fromIndex <- binarySearch(a, from, lowerFrom) + toIndex <- binarySearch(a, to, !lowerFrom) + return(fromIndex:toIndex) +} + + + +## ========================== +# GroupDelayCorrection +## ========================== +GroupDelayCorrection <- function(Fid_data, Fid_info = NULL, group_delay = NULL) { + + + # Data initialisation and checks ---------------------------------------------- + + begin_info <- beginTreatment("GroupDelayCorrection", Fid_data, Fid_info) + Fid_data <- begin_info[["Signal_data"]] + dimension_names <- dimnames(Fid_data) + Fid_info <- begin_info[["Signal_info"]] + checkArg(group_delay, c("num", "pos0"), can.be.null = TRUE) + # if Fid_info and group_delay are NULL, getArg will generate an error + + group_delay <- getArg(group_delay, Fid_info, "GRPDLY", can.be.absent = TRUE) + + if (is.null(group_delay)) { + + # See DetermineBrukerDigitalFilter.m in matNMR MATLAB library + group_delay_matrix <- matrix(c(44.75, 46, 46.311, 33.5, 36.5, 36.53, 66.625, + 48, 47.87, 59.0833, 50.1667, 50.229, 68.5625, 53.25, 53.289, 60.375, + 69.5, 69.551, 69.5313, 72.25, 71.6, 61.0208, 70.1667, 70.184, 70.0156, + 72.75, 72.138, 61.3438, 70.5, 70.528, 70.2578, 73, 72.348, 61.5052, 70.6667, + 70.7, 70.3789, 72.5, 72.524, 61.5859, 71.3333, NA, 70.4395, 72.25, NA, + 61.6263, 71.6667, NA, 70.4697, 72.125, NA, 61.6465, 71.8333, NA, 70.4849, + 72.0625, NA, 61.6566, 71.9167, NA, 70.4924, 72.0313, NA), nrow = 21, + ncol = 3, byrow = TRUE, dimnames = list(c(2, 3, 4, 6, 8, 12, 16, 24, + 32, 48, 64, 96, 128, 192, 256, 384, 512, 768, 1024, 1536, 2048), + c(10, 11, 12))) + decim <- Fid_info[1, "DECIM"] + dspfvs <- Fid_info[1, "DSPFVS"] + if (!(toString(decim) %in% rownames(group_delay_matrix))) { + stop(paste("Invalid DECIM", decim, "it should be one of", rownames(group_delay_matrix))) + } + if (!(toString(dspfvs) %in% colnames(group_delay_matrix))) { + stop(paste("Invalid DSPFVS", dspfvs, "it should be one of", colnames(group_delay_matrix))) + } + group_delay <- group_delay_matrix[toString(decim), toString(dspfvs)] + if (is.na(group_delay)) { + stop(paste("Invalid DECIM", decim, "for DSPFVS", dspfvs)) + } + } + m <- ncol(Fid_data) + n <- nrow(Fid_data) + + # GroupDelayCorrection ---------------------------------------------- + + # We do the shifting in the Fourier domain because the shift can be non-integer. + # That way we automatically have the circular behaviour of the shift and the + # interpolation if it is non-integer. + + Spectrum <- t(stats::mvfft(t(Fid_data))) + + # Spectrum <- FourierTransform(Fid_data, Fid_info) + p <- ceiling(m/2) + new_index <- c((p + 1):m, 1:p) + Spectrum <- Spectrum[,new_index] + Spectrum <- matrix(data = Spectrum, ncol = m, nrow = n) + + Omega <- (0:(m - 1))/m + i <- complex(real = 0, imaginary = 1) + + if (n>1) { + Spectrum <- sweep(Spectrum, MARGIN = 2, exp(i * group_delay * 2 * pi * Omega), `*`) + Spectrum <- Spectrum[,new_index] + }else { + Spectrum <- Spectrum* exp(i * group_delay * 2 * pi * Omega) + Spectrum <- Spectrum[new_index] + Spectrum <- matrix(data = Spectrum, ncol = m, nrow = n) + } + + + Fid_data <- t(stats::mvfft(t(Spectrum), inverse = TRUE))/m + colnames(Fid_data) <- dimension_names[[2]] + rownames(Fid_data) <- dimension_names[[1]] + + # Data finalisation ---------------------------------------------- + + return(endTreatment("GroupDelayCorrection", begin_info, Fid_data)) + } + +## ========================== +# SolventSuppression +## ========================== +SolventSuppression <- function(Fid_data, lambda.ss = 1e+06, ptw.ss = TRUE, + plotSolvent = F, returnSolvent = F) { + + # Data initialisation and checks ---------------------------------------------- + + begin_info <- beginTreatment("SolventSuppression", Fid_data) + Fid_data <- begin_info[["Signal_data"]] + checkArg(ptw.ss, c("bool")) + checkArg(lambda.ss, c("num", "pos0")) + + + # difsm function definition for the smoother ----------------------------------- + + if (ptw.ss) { + # Use of the function in ptw that smoothes signals with a finite difference + # penalty of order 2 + difsm <- ptw::difsm + } else { + # Or manual implementation based on sparse matrices for large data series (cf. + # Eilers, 2003. 'A perfect smoother') + difsm <- function(y, d = 2, lambda) { + + m <- length(y) + # Sparse identity matrix m x m + E <- Matrix::Diagonal(m) + D <- Matrix::diff(E, differences = d) + A <- E + lambda.ss * Matrix::t(D) %*% D + # base::chol does not take into account that A is sparse and is extremely slow + C <- Matrix::chol(A) + x <- Matrix::solve(C, Matrix::solve(Matrix::t(C), y)) + return(as.numeric(x)) + } + } + + # Solvent Suppression ---------------------------------------------- + + n <- dim(Fid_data)[1] + if (returnSolvent) { + SolventRe <- Fid_data + SolventIm <- Fid_data + } + for (i in 1:n) { + FidRe <- Re(Fid_data[i, ]) + FidIm <- Im(Fid_data[i, ]) + solventRe <- difsm(y = FidRe, lambda = lambda.ss) + solventIm <- difsm(y = FidIm, lambda = lambda.ss) + + if (plotSolvent) { + m <- length(FidRe) + graphics::plot(1:m, FidRe, type = "l", col = "red") + graphics::lines(1:m, solventRe, type = "l", col = "blue") + graphics::plot(1:m, FidIm, type = "l", col = "red") + graphics::lines(1:m, solventIm, type = "l", col = "blue") + } + FidRe <- FidRe - solventRe + FidIm <- FidIm - solventIm + Fid_data[i, ] <- complex(real = FidRe, imaginary = FidIm) + if (returnSolvent) { + SolventRe[i, ] <- solventRe + SolventIm[i, ] <- solventIm + } + } + + + # Data finalisation ---------------------------------------------- + + Fid_data <- endTreatment("SolventSuppression", begin_info, Fid_data) + if (returnSolvent) { + return(list(Fid_data = Fid_data, SolventRe = SolventRe, SolventIm = SolventIm)) + } else { + return(Fid_data) + } +} + + +## ========================== +# Apodization +# ============================= +Apodization <- function(Fid_data, Fid_info = NULL, DT = NULL, + type.apod = c("exp","cos2", "blockexp", "blockcos2", + "gauss", "hanning", "hamming"), phase = 0, rectRatio = 1/2, + gaussLB = 1, expLB = 1, plotWindow = F, returnFactor = F) { + + # Data initialisation and checks ---------------------------------------------- + begin_info <- beginTreatment("Apodization", Fid_data, Fid_info) + Fid_data <- begin_info[["Signal_data"]] + Fid_info <- begin_info[["Signal_info"]] + # Data check + type.apod <- match.arg(type.apod) + checkArg(DT, c("num", "pos"), can.be.null = TRUE) + checkArg(phase, c("num")) + + # Apodization ---------------------------------------------- + DT <- getArg(DT, Fid_info, "DT") # Dwell Time + m <- ncol(Fid_data) + t <- (1:m) * DT # Time + rectSize <- ceiling(rectRatio * m) + gaussLB <- (gaussLB/(sqrt(8 * log(2)))) + # Define the types of apodization: + switch(type.apod, exp = { + # exponential + Factor <- exp(-expLB * t) + }, cos2 = { + # cos^2 + c <- cos((1:m) * pi/(2 * m) - phase * pi/2) + Factor <- c * c + }, blockexp = { + # block and exponential + Factor <- c(rep.int(1, rectSize), rep.int(0, m - rectSize)) + # | rectSize | 1 ___________ | \ 0 \____ + Factor[(rectSize + 1):m] <- exp(-expLB * t[1:(m - rectSize)]) + }, blockcos2 = { + # block and cos^2 + Factor <- c(rep.int(1, rectSize), rep.int(0, m - rectSize)) + c <- cos((1:(m - rectSize)) * pi/(2 * (m - rectSize))) + Factor[(rectSize + 1):m] <- c * c + }, gauss = { + # gaussian + Factor <- exp(-(gaussLB * t)^2/2) + Factor <- Factor/max(Factor) + }, hanning = { + # Hanning + Factor <- 0.5 + 0.5 * cos((1:m) * pi/m - phase * pi) + }, hamming = { + # Hamming + Factor <- 0.54 + 0.46 * cos((1:m) * pi/m - phase * pi) + }) + if (plotWindow) { + graphics::plot(1:m, Factor, "l") + # dev.off() # device independent, it is the responsability of the + # caller to do it + } + # Apply the apodization factor on the spectra + Fid_data <- sweep(Fid_data, MARGIN = 2, Factor, `*`) + + # Data finalisation ---------------------------------------------- + Fid_data <- endTreatment("Apodization", begin_info, Fid_data) + if (returnFactor) { + return(list(Fid_data = Fid_data, Factor = Factor)) + } else { + return(Fid_data) + } +} + + +## ==================================================== +# FourierTransform +## ==================================================== + + +# fftshift1D2D +fftshift1D2D <- function(x) { + vec <- F + if (is.vector(x)) { + x <- vec2mat(x) + vec <- T + } + m <- dim(x)[2] + p <- ceiling(m/2) + new_index <- c((p + 1):m, 1:p) + y <- x[, new_index, drop = vec] +} + +# FourierTransform +FourierTransform <- function(Fid_data, Fid_info = NULL, SW_h = NULL, SW = NULL, O1 = NULL, reverse.axis = TRUE) { + + # Data initialisation and checks ---------------------------------------------- + begin_info <- beginTreatment("FourierTransform", Fid_data, Fid_info) + Fid_data <- begin_info[["Signal_data"]] + Fid_info <- begin_info[["Signal_info"]] + + m <- ncol(Fid_data) + n <- nrow(Fid_data) + + if (is.null(SW_h)) { + SW_h <- getArg(SW_h, Fid_info, "SW_h") + } + + if (is.null(SW)) { + SW <- getArg(SW, Fid_info, "SW") # Sweep Width in ppm (semi frequency scale in ppm) + } + + + if (is.null(O1)) { + O1 <- getArg(O1, Fid_info, "O1") + } + + + checkArg(reverse.axis, c("bool")) + + # Fourier Transformation ---------------------------------------------- + # mvfft does the unnormalized fourier transform (see ?mvfft), so we need divide + # by m. It does not matter a lot in our case since the spectrum will be + # normalized. + + # FT + RawSpect_data <- fftshift1D2D(t(stats::mvfft(t(Fid_data)))) + # recover the frequencies values + f <- ((0:(m - 1)) - floor(m/2)) * Fid_info[1, "SW_h"]/(m-1) + + if(reverse.axis == TRUE) { + revind <- rev(1:m) + RawSpect_data <- RawSpect_data[,revind] # reverse the spectrum + } + + RawSpect_data <- matrix(RawSpect_data, nrow = n, ncol = m) + colnames(RawSpect_data) <- f + rownames(RawSpect_data) <- rownames(Fid_data) + + # PPM conversion ---------------------------------------------- + + # The Sweep Width has to be the same since the column names are the same + + ppmInterval <- SW/(m-1) + + O1index = round((m+1)/2+O1*(m - 1) / SW_h) + + end <- O1index - m + start <- O1index -1 + ppmScale <- (start:end) * ppmInterval + RawSpect_data <- matrix(RawSpect_data, nrow = n, ncol = -(end - start) + 1, dimnames = + list(rownames(RawSpect_data), ppmScale)) + + + # Data finalisation ---------------------------------------------- + return(endTreatment("FourierTransform", begin_info, RawSpect_data)) +} + +## ==================================================== +# InternalReferencing +## ==================================================== + +InternalReferencing <- function(Spectrum_data, Fid_info, method = c("max", "thres"), + range = c("nearvalue", "all", "window"), ppm.value = 0, + direction = "left", shiftHandling = c("zerofilling", "cut", + "NAfilling", "circular"), c = 2, pc = 0.02, fromto.RC = NULL, + ppm.ir = TRUE, rowindex_graph = NULL) { + + + + # Data initialisation and checks ---------------------------------------------- + + begin_info <- beginTreatment("InternalReferencing", Spectrum_data, Fid_info) + Spectrum_data <- begin_info[["Signal_data"]] + Fid_info <- begin_info[["Signal_info"]] + + + # Check input arguments + range <- match.arg(range) + shiftHandling <- match.arg(shiftHandling) + method <- match.arg(method) + plots <- NULL + + + checkArg(ppm.ir, c("bool")) + checkArg(unlist(fromto.RC), c("num"), can.be.null = TRUE) + checkArg(pc, c("num")) + checkArg(ppm.value, c("num")) + checkArg(rowindex_graph, "num", can.be.null = TRUE) + + # fromto.RC + if (!is.null(fromto.RC)) { + diff <- diff(unlist(fromto.RC))[1:length(diff(unlist(fromto.RC)))%%2 !=0] + for (i in 1:length(diff)) { + if (diff[i] >= 0) { + fromto <- c(fromto.RC[[i]][2], fromto.RC[[i]][1]) + fromto.RC[[i]] <- fromto + } + } + } + + + # findTMSPpeak function ---------------------------------------------- + findTMSPpeak <- function(ft, c = 2, direction = "left") { + ft <- Re(ft) # extraction de la partie réelle + N <- length(ft) + if (direction == "left") { + newindex <- rev(1:N) + ft <- rev(ft) + } + thres <- 99999 + i <- 1000 # Start at point 1000 to find the peak + vect <- ft[1:i] + + while (vect[i] <= (c * thres)) { + cumsd <- stats::sd(vect) + cummean <- mean(vect) + thres <- cummean + 3 * cumsd + i <- i + 1 + vect <- ft[1:i] + } + if (direction == "left") { + v <- newindex[i] + } else {v <- i} + + if (is.na(v)) { + warning("No peak found, need to lower the threshold.") + return(NA) + } else { + # recherche dans les 1% de points suivants du max trouve pour etre au sommet du + # pic + d <- which.max(ft[v:(v + N * 0.01)]) + new.peak <- v + d - 1 # nouveau pic du TMSP si d > 0 + + if (names(which.max(ft[v:(v + N * 0.01)])) != names(which.max(ft[v:(v + N * 0.03)]))) { + # recherche dans les 3% de points suivants du max trouve pour eviter un faux + # positif + warning("the TMSP peak might be located further away, increase the threshold to check.") + } + return(new.peak) + } + } + + + # Apply the method ('thres' or 'max') on spectra + # ---------------------------------------------- + + n <- nrow(Spectrum_data) + m <- ncol(Spectrum_data) + + # The Sweep Width has to be the same since the column names are the same + SW <- Fid_info[1, "SW"] # Sweep Width in ppm (semi frequency scale in ppm) + ppmInterval <- SW/(m-1) + + if (range == "all") { + Data <- Spectrum_data + } else { # range = "nearvalue" or "window" + + if (range == "nearvalue") { + fromto.RC <- list(c(-(SW * pc)/2 + ppm.value, (SW * pc)/2 + ppm.value)) # automatic fromto values in ppm + colindex <- as.numeric(colnames(Spectrum_data)) + } else { + if (ppm.ir == TRUE) { + colindex <- as.numeric(colnames(Spectrum_data)) + } else { + colindex <- 1:m + } + } + + + Int <- vector("list", length(fromto.RC)) + for (i in 1:length(fromto.RC)) { + Int[[i]] <- indexInterval(colindex, from = fromto.RC[[i]][1], + to = fromto.RC[[i]][2], inclusive = TRUE) + } + + vector <- rep(0, m) + vector[unlist(Int)] <- 1 + if (n > 1) { + Data <- sweep(Spectrum_data, MARGIN = 2, FUN = "*", vector) # Cropped_Spectrum + } else { + Data <- Spectrum_data * vector + } # Cropped_Spectrum + } + + + if (method == "thres") { + TMSPpeaks <- apply(Data, 1, findTMSPpeak, c = c, direction = direction) + } else { + TMSPpeaks <- apply(abs(Re(Data)), 1, which.max) + } + + # TMSPpeaks is an column index + maxpeak <- max(TMSPpeaks) + minpeak <- min(TMSPpeaks) + + + + # Shift spectra according to the TMSPpeaks found -------------------------------- + # Depends on the shiftHandling + + if (shiftHandling %in% c("zerofilling", "NAfilling", "cut")) { + fill <- NA + if (shiftHandling == "zerofilling") { + fill <- 0 + } + + start <- maxpeak - 1 + end <- minpeak - m + + ppmScale <- (start:end) * ppmInterval + + # check if ppm.value is in the ppmScale interval + if(ppm.value < min(ppmScale) | ppm.value > max(ppmScale)) { + warning("ppm.value = ", ppm.value, " is not in the ppm interval [", + round(min(ppmScale),2), ",", round(max(ppmScale),2), "], and is set to its default ppm.value 0") + ppm.value = 0 + } + + ppmScale <- ppmScale + ppm.value + + Spectrum_data_calib <- matrix(fill, nrow = n, ncol = -(end - start) + 1, + dimnames = list(rownames(Spectrum_data), ppmScale)) + for (i in 1:n) { + shift <- (1 - TMSPpeaks[i]) + start + Spectrum_data_calib[i, (1 + shift):(m + shift)] <- Spectrum_data[i, ] + } + + if (shiftHandling == "cut") { + Spectrum_data_calib = as.matrix(stats::na.omit(t(Spectrum_data_calib))) + Spectrum_data_calib = t(Spectrum_data_calib) + base::attr(Spectrum_data_calib, "na.action") <- NULL + } + + + } else { + # circular + start <- 1 - maxpeak + end <- m - maxpeak + + ppmScale <- (start:end) * ppmInterval + + # check if ppm.value in is the ppmScale interval + if(ppm.value < min(ppmScale) | ppm.value > max(ppmScale)) { + warning("ppm.value = ", ppm.value, " is not in the ppm interval [", + round(min(ppmScale),2), ",", round(max(ppmScale),2), "], and is set to its default ppm.value 0") + ppm.value = 0 + } + ppmScale <- ppmScale + ppm.value + + Spectrum_data_calib <- matrix(nrow=n, ncol=end-start+1, + dimnames=list(rownames(Spectrum_data), ppmScale)) + for (i in 1:n) { + shift <- (maxpeak-TMSPpeaks[i]) + Spectrum_data_calib[i,(1+shift):m] <- Spectrum_data[i,1:(m-shift)] + if (shift > 0) { + Spectrum_data_calib[i,1:shift] <- Spectrum_data[i,(m-shift+1):m] + } + } + } + + + + + # Plot of the spectra --------------------------------------------------- + + ppm = xstart = value = xend = Legend = NULL # only for R CMD check + + + # with the search zone for TMSP and the location of the peaks just found + if (!is.null(rowindex_graph)) { + + if (range == "window") { + if (ppm.ir == TRUE) { + fromto <- fromto.RC + } else { + fromto <- list() + idcol <- as.numeric(colnames(Spectrum_data)) + for (i in 1:length(fromto.RC)) { + fromto[[i]] <- as.numeric(colnames(Spectrum_data))[fromto.RC[[i]]] + } + } + } else { + fromto <- fromto.RC + } + + # TMSPloc in ppm + TMSPloc <- as.numeric(colnames(Spectrum_data))[TMSPpeaks[rowindex_graph]] + + # num plot per window + num.stacked <- 6 + + # rectanglar bands of color for the search zone + rects <- data.frame(xstart = sapply(fromto, function(x) x[[1]]), + xend = sapply(fromto, function(x) x[[2]]), + Legend = "TMSP search zone and location") + + # vlines for TMSP peak + addlines <- data.frame(rowname = rownames(Spectrum_data)[rowindex_graph],TMSPloc) + + nn <- length(rowindex_graph) + i <- 1 + j <- 1 + plots <- vector(mode = "list", length = ceiling(nn/num.stacked)) + + while (i <= nn) { + + last <- min(i + num.stacked - 1, nn) + + melted <- reshape2::melt(Re(Spectrum_data[i:last, ]), + varnames = c("rowname", "ppm")) + + plots[[j]] <- ggplot2::ggplot() + ggplot2::theme_bw() + + ggplot2::geom_line(data = melted, + ggplot2::aes(x = ppm, y = value)) + + ggplot2::geom_rect(data = rects, ggplot2::aes(xmin = xstart, xmax = xend, + ymin = -Inf, ymax = Inf, fill = Legend), alpha = 0.4) + + ggplot2::facet_grid(rowname ~ ., scales = "free_y") + + ggplot2::theme(legend.position = "none") + + ggplot2::geom_vline(data = addlines, ggplot2::aes(xintercept = TMSPloc), + color = "red", show.legend = TRUE) + + ggplot2::ggtitle("TMSP peak search zone and location") + + ggplot2::theme(legend.position = "top", legend.text = ggplot2::element_text()) + + + + if ((melted[1, "ppm"] - melted[(dim(melted)[1]), "ppm"]) > 0) { + plots[[j]] <- plots[[j]] + ggplot2::scale_x_reverse() + } + + i <- last + 1 + j <- j + 1 + } + + plots + } + + + # Return the results ---------------------------------------------- + Spectrum_data <- endTreatment("InternalReferencing", begin_info, Spectrum_data_calib) + + if (is.null(plots)) { + return(Spectrum_data) + } else { + return(list(Spectrum_data = Spectrum_data, plots = plots)) + } + +} + +## ==================================================== +# ZeroOrderPhaseCorrection +## ==================================================== + +ZeroOrderPhaseCorrection <- function(Spectrum_data, type.zopc = c("rms", "manual", "max"), + plot_rms = NULL, returnAngle = FALSE, createWindow = TRUE, + angle = NULL, plot_spectra = FALSE, + ppm.zopc = TRUE, exclude.zopc = list(c(5.1,4.5))) { + + + # Data initialisation and checks ---------------------------------------------- + + # Entry arguments definition: + # plot_rms : graph of rms criterion returnAngle : if TRUE, returns avector of + # optimal angles createWindow : for plot_rms plots angle : If angle is not NULL, + # spectra are rotated according to the angle vector values + # plot_spectra : if TRUE, plot rotated spectra + + + + begin_info <- beginTreatment("ZeroOrderPhaseCorrection", Spectrum_data) + Spectrum_data <- begin_info[["Signal_data"]] + n <- nrow(Spectrum_data) + m <- ncol(Spectrum_data) + + rnames <- rownames(Spectrum_data) + + # Check input arguments + type.zopc <- match.arg(type.zopc) + checkArg(ppm.zopc, c("bool")) + checkArg(unlist(exclude.zopc), c("num"), can.be.null = TRUE) + + + # type.zopc in c("max", "rms") ----------------------------------------- + if (type.zopc %in% c("max", "rms")) { + # angle is found by optimization + + # rms function to be optimised + rms <- function(ang, y, meth = c("max", "rms")) { + # if (debug_plot) { graphics::abline(v=ang, col='gray60') } + roty <- y * exp(complex(real = 0, imaginary = ang)) # spectrum rotation + Rey <- Re(roty) + + if (meth == "rms") { + ReyPos <- Rey[Rey >= 0] # select positive intensities + POSss <- sum((ReyPos)^2, na.rm = TRUE) # SS for positive intensities + ss <- sum((Rey)^2, na.rm = TRUE) # SS for all intensities + return(POSss/ss) # criterion : SS for positive values / SS for all intensities + } else { + maxi <- max(Rey, na.rm = TRUE) + return(maxi) + } + } + + + # Define the interval where to search for (by defining Data) + if (is.null(exclude.zopc)) { + Data <- Spectrum_data + } else { + + # if ppm.zopc == TRUE, then exclude.zopc is in the colnames values, else, in the column + # index + if (ppm.zopc == TRUE) { + colindex <- as.numeric(colnames(Spectrum_data)) + } else { + colindex <- 1:m + } + + # Second check for the argument exclude.zopc + diff <- diff(unlist(exclude.zopc))[1:length(diff(unlist(exclude.zopc)))%%2 !=0] + for (i in 1:length(diff)) { + if (ppm.zopc == TRUE & diff[i] >= 0) { + stop(paste("Invalid region removal because from <= to in ppm.zopc")) + } else if (ppm.zopc == FALSE & diff[i] <= 0) {stop(paste("Invalid region removal because from >= to in column index"))} + } + + + Int <- vector("list", length(exclude.zopc)) + for (i in 1:length(exclude.zopc)) { + Int[[i]] <- indexInterval(colindex, from = exclude.zopc[[i]][1], + to = exclude.zopc[[i]][2], inclusive = TRUE) + } + + vector <- rep(1, m) + vector[unlist(Int)] <- 0 + if (n > 1) { + Data <- sweep(Spectrum_data, MARGIN = 2, FUN = "*", vector) # Cropped_Spectrum + } else { + Data <- Spectrum_data * vector + } # Cropped_Spectrum + } + + + # angles computation + Angle <- c() + for (k in 1:n) + { + # The function is rms is periodic (period 2pi) and it seems that there is a phase + # x such that rms is unimodal (i.e. decreasing then increasing) on the interval + # [x; x+2pi]. However, if we do the optimization for example on [x-pi; x+pi], + # instead of being decreasing then increasing, it might be increasing then + # decreasing in which case optimize, thinking it is a valley will have to choose + # between the left or the right of this hill and if it chooses wrong, it will end + # up at like x-pi while the minimum is close to x+pi. + + # Supposing that rms is unimodal, the classical 1D unimodal optimization will + # work in either [-pi;pi] or [0;2pi] (this is not easy to be convinced by that I + # agree) and we can check which one it is simply by the following trick + + f0 <- rms(0, Data[k, ],meth = type.zopc) + fpi <- rms(pi, Data[k, ], meth = type.zopc) + if (f0 < fpi) { + interval <- c(-pi, pi) + } else { + interval <- c(0, 2 * pi) + } + + # graphs of rms criteria + debug_plot <- F # rms should not plot anything now, only when called by optimize + if (!is.null(plot_rms) && rnames[k] %in% plot_rms) { + x <- seq(min(interval), max(interval), length.out = 100) + y <- rep(1, 100) + for (K in (1:100)) { + y[K] <- rms(x[K], Data[k, ], meth = type.zopc) + } + if (createWindow == TRUE) { + grDevices::dev.new(noRStudioGD = FALSE) + } + graphics::plot(x, y, main = paste("Criterion maximization \n", + rownames(Data)[k]), ylim = c(0, 1.1), + ylab = "positiveness criterion", xlab = "angle ") + debug_plot <- T + } + + # Best angle + best <- stats::optimize(rms, interval = interval, maximum = TRUE, + y = Data[k,], meth = type.zopc) + ang <- best[["maximum"]] + + + if (debug_plot) { + graphics::abline(v = ang, col = "black") + graphics::text(x = (ang+0.1*ang), y = (y[ang]-0.1*y[ang]), labels = round(ang, 3)) + } + + # Spectrum rotation + Spectrum_data[k, ] <- Spectrum_data[k, ] * exp(complex(real = 0, imaginary = ang)) + Angle <- c(Angle, ang) + } + + + + + } else { + # type.zopc is "manual" ------------------------------------------------------- + # if Angle is already specified and no optimisation is needed + Angle <- angle + + if (!is.vector(angle)) { + stop("angle is not a vector") + } + + if (!is.numeric(angle)) { + stop("angle is not a numeric") + } + + if (length(angle) != n) { + stop(paste("angle has length", length(angle), "and there are", n, "spectra to rotate.")) + } + for (k in 1:n) { + Spectrum_data[k, ] <- Spectrum_data[k, ] * exp(complex(real = 0, imaginary = - angle[k])) + } + } + + + # Draw spectra + if (plot_spectra == TRUE) { + nn <- ceiling(n/4) + i <- 1 + for (k in 1:nn) { + if (createWindow == TRUE) { + grDevices::dev.new(noRStudioGD = FALSE) + } + graphics::par(mfrow = c(4, 2)) + while (i <= n) { + last <- min(i + 4 - 1, n) + graphics::plot(Re(Spectrum_data[i, ]), type = "l", ylab = "intensity", + xlab = "Index", main = paste0(rownames(Spectrum_data)[i], " - Real part")) + graphics::plot(Im(Spectrum_data[i, ]), type = "l", ylab = "intensity", + xlab = "Index", main = paste0(rownames(Spectrum_data)[i], " - Imaginary part")) + i <- i + 1 + } + i <- last + 1 + } + } + + + # Data finalisation ---------------------------------------------- + + Spectrum_data <- endTreatment("ZeroOrderPhaseCorrection", begin_info, Spectrum_data) + if (returnAngle) { + return(list(Spectrum_data = Spectrum_data, Angle = Angle)) + } else { + return(Spectrum_data) + } +} + + +## ==================================================== +# Baseline Correction +## ==================================================== +BaselineCorrection <- function(Spectrum_data, ptw.bc = TRUE, maxIter = 42, + lambda.bc = 1e+07, p.bc = 0.05, eps = 1e-08, + ppm.bc = TRUE, exclude.bc = list(c(5.1,4.5)), + returnBaseline = F) { + + # Data initialisation ---------------------------------------------- + begin_info <- beginTreatment("BaselineCorrection", Spectrum_data, force.real = T) + Spectrum_data <- begin_info[["Signal_data"]] + p <- p.bc + lambda <- lambda.bc + n <- dim(Spectrum_data)[1] + m <- dim(Spectrum_data)[2] + + + # Data check + checkArg(ptw.bc, c("bool")) + checkArg(maxIter, c("int", "pos")) + checkArg(lambda, c("num", "pos0")) + checkArg(p.bc, c("num", "pos0")) + checkArg(eps, c("num", "pos0")) + checkArg(returnBaseline, c("bool")) + checkArg(ppm.bc, c("bool")) + checkArg(unlist(exclude.bc), c("num"), can.be.null = TRUE) + + # Define the interval where to search for (by defining Data) + if (is.null(exclude.bc)) { + exclude_index <- NULL + } else { + # if ppm.bc == TRUE, then exclude.bc is in the colnames values, else, in the column + # index + if (ppm.bc == TRUE) { + colindex <- as.numeric(colnames(Spectrum_data)) + } else { + colindex <- 1:m + } + + Int <- vector("list", length(exclude.bc)) + for (i in 1:length(exclude.bc)) { + Int[[i]] <- indexInterval(colindex, from = exclude.bc[[i]][1], + to = exclude.bc[[i]][2], inclusive = TRUE) + } + exclude_index <- unlist(Int) + } + + # Baseline Correction implementation definition ---------------------- + + # 2 Ways: either use the function asysm from the ptw package or by + # built-in functions + if (ptw.bc) { + asysm <- ptw::asysm + } else { + difsmw <- function(y, lambda, w, d) { + # Weighted smoothing with a finite difference penalty cf Eilers, 2003. + # (A perfect smoother) + # y: signal to be smoothed + # lambda: smoothing parameter + # w: weights (use0 zeros for missing values) + # d: order of differences in penalty (generally 2) + m <- length(y) + W <- Matrix::Diagonal(x=w) + E <- Matrix::Diagonal(m) + D <- Matrix::diff(E, differences = d) + C <- Matrix::chol(W + lambda * t(D) %*% D) + x <- Matrix::solve(C, Matrix::solve(t(C), w * y)) + return(as.numeric(x)) + + } + asysm <- function(y, lambda, p, eps, exclude_index) { + # Baseline estimation with asymmetric least squares + # y: signal + # lambda: smoothing parameter (generally 1e5 to 1e8) + # p: asymmetry parameter (generally 0.001) + # d: order of differences in penalty (generally 2) + # eps: 1e-8 in ptw package + m <- length(y) + w <- rep(1, m) + i <- 1 + repeat { + z <- difsmw(y, lambda, w, d = 2) + w0 <- w + p_vect <- rep((1-p), m) # if y <= z + eps + p_vect[y > z + eps | y < 0] <- p # if y > z + eps | y < 0 + if(!is.null(exclude_index)){ + p_vect[exclude_index] <- 0 # if exclude area + } + + w <- p_vect + # w <- p * (y > z + eps | y < 0) + (1 - p) * (y <= z + eps) + + if (sum(abs(w - w0)) == 0) { + break + } + i <- i + 1 + if (i > maxIter) { + warning("cannot find Baseline estimation in asysm") + break + } + } + return(z) + } + } + + # Baseline estimation ---------------------------------------------- + Baseline <- matrix(NA, nrow = nrow(Spectrum_data), ncol = ncol(Spectrum_data)) + + # for (k in 1:n) { + # Baseline[k, ] <- asysm(y = Spectrum_data[k, ], lambda = lambda, p = p, eps = eps) + + if (ptw.bc ){ + Baseline <- apply(Spectrum_data,1, asysm, lambda = lambda, p = p, + eps = eps) + }else { + Baseline <- apply(Spectrum_data,1, asysm, lambda = lambda, p = p, + eps = eps, exclude_index = exclude_index) + } + + + Spectrum_data <- Spectrum_data - t(Baseline) + # } + + # Data finalisation ---------------------------------------------- + Spectrum_data <- endTreatment("BaselineCorrection", begin_info, Spectrum_data) # FIXME create removeImaginary filter ?? + + if (returnBaseline) { + return(list(Spectrum_data = Spectrum_data, Baseline = Baseline)) + } else { + return(Spectrum_data) + } +} + + + +## ==================================================== +# NegativeValuesZeroing +## ==================================================== + +NegativeValuesZeroing <- function(Spectrum_data) { + # Data initialisation and checks ---------------------------------------------- + begin_info <- beginTreatment("NegativeValuesZeroing", Spectrum_data, force.real = T) + Spectrum_data <- begin_info[["Signal_data"]] + + # NegativeValuesZeroing ---------------------------------------------- + Spectrum_data[Spectrum_data < 0] <- 0 + + # Data finalisation ---------------------------------------------- + return(endTreatment("NegativeValuesZeroing", begin_info, Spectrum_data)) +} + + diff -r cbea5e9fd0b4 -r 5e64657b4fe5 NmrPreprocessing_wrapper.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/NmrPreprocessing_wrapper.R Wed Mar 28 08:05:12 2018 -0400 @@ -0,0 +1,411 @@ +#!/usr/local/public/bin/Rscript --vanilla --slave --no-site-file + +## 170116_NmrPreprocessing.R +## Manon Martin and Marie Tremblay-Franco + +##====================================================== +##====================================================== +# Preamble +##====================================================== +##====================================================== + +runExampleL <- FALSE + + +##------------------------------ +## Options +##------------------------------ +strAsFacL <- options()$stringsAsFactors +options(stringsAsFactors = FALSE) + +##------------------------------ +## Libraries laoding +##------------------------------ +library(batch) +library(ptw) +library(Matrix) +library(ggplot2) +library(gridExtra) +library(reshape2) + + +# R script call +source_local <- function(fname) +{ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + source(paste(base_dir, fname, sep="/")) +} +#Import the different functions +source_local("NmrPreprocessing_script.R") +source_local("DrawFunctions.R") + +##------------------------------ +## Script +##------------------------------ +runExampleL <- FALSE + + +if(!runExampleL) + argLs <- parseCommandArgs(evaluate=FALSE) + +sink(argLs$logOut) + + +##------------------------------ +## Errors ????????????????????? +##------------------------------ + + +##------------------------------ +## Constants +##------------------------------ +topEnvC <- environment() +flagC <- "\n" + + + + +# log file +# print(argLs[["logOut"]]) + +## Starting +cat("\nStart of 'Preprocessing' Galaxy module call: ", as.character(Sys.time()), "\n", sep = "") + + +##====================================================== +##====================================================== +## Parameters Loading +##====================================================== +##====================================================== + +# graphical inputs +FirstOPCGraph <- argLs[["FirstOPCGraph"]] +SSGraph <- argLs[["SSGraph"]] +ApodGraph <- argLs[["ApodGraph"]] +FTGraph <- argLs[["FTGraph"]] +SRGraph <- argLs[["SRGraph"]] +ZeroOPCGraph <- argLs[["ZeroOPCGraph"]] +BCGraph <- argLs[["BCGraph"]] +FinalGraph <- argLs[["FinalGraph"]] + + +# 1rst order phase correction ------------------------ + # Inputs + ## Data matrix +Fid_data0 <- read.table(argLs[["dataMatrixFid"]],header=TRUE, check.names=FALSE, sep='\t') +# Fid_data0 <- Fid_data0[,-1] +Fid_data0 <- as.matrix(Fid_data0) + + ## Samplemetadata +samplemetadataFid <- read.table(argLs[["sampleMetadataFid"]],check.names=FALSE,header=TRUE,sep="\t") +samplemetadataFid <- as.matrix(samplemetadataFid) + + +# water and solvent(s) correction ------------------------ + # Inputs +lambda <- argLs[["lambda"]] + + + +# apodization ----------------------------------------- + # Inputs +phase=0 +rectRatio=1/2 +gaussLB=1 +expLB=1 +apodization <- argLs[["apodizationMethod"]] + +if (apodization=='exp'){ + expLB <- argLs[["expLB"]] + } else if (apodization=='cos2'){ + phase <- argLs[["phase"]] + } else if (apodization=='hanning'){ + phase <- argLs[["phase"]] + } else if (apodization=='hamming'){ + phase <- argLs[["phase"]] + } else if (apodization=='blockexp'){ + rectRatio <- argLs[["rectRatio"]] + expLB <- argLs[["expLB"]] + } else if (apodization=='blockcos2'){ + rectRatio <- argLs[["rectRatio"]] + } else if (apodization=='gauss'){ + rectRatio <- argLs[["rectRatio"]] + gaussLB <- argLs[["gaussLB"]] + } + + +# Fourier transform ---------------------------------- + # Inputs + + +# Internal referencering ---------------------------------- + # Inputs +shiftTreshold = 2 # c +ppm = TRUE +shiftReferencingRangeList = NULL # fromto.RC +pctNearValue = 0.02 # pc +rowindex_graph = NULL +ppm_ref = 0 # ppm.ref + +# +# shiftReferencing <- argLs[["shiftReferencing"]] +# print(shiftReferencing) +# +# if (shiftReferencing=="YES") +# { +# + # shiftReferencingMethod <- argLs[["shiftReferencingMethod"]] + # + # if (shiftReferencingMethod == "thres") { + # shiftTreshold <- argLs[["shiftTreshold"]] + # } + + shiftReferencingRange <- argLs[["shiftReferencingRange"]] + + if (shiftReferencingRange == "near0"){ + pctNearValue <- argLs[["pctNearValue"]] + } + + if (shiftReferencingRange == "window"){ + shiftReferencingRangeList <- list() + for(i in which(names(argLs)=="shiftReferencingRangeLeft")) + { + shiftReferencingRangeLeft <- argLs[[i]] + shiftReferencingRangeRight <- argLs[[i+1]] + shiftReferencingRangeList <- c(shiftReferencingRangeList,list(c(shiftReferencingRangeLeft,shiftReferencingRangeRight))) + } + } + + shiftHandling <- argLs[["shiftHandling"]] + + ppmvalue <- argLs[["ppmvalue"]] + + + +# } + + +# Zero Order Phase Correction ------------------------------- + # Inputs + +angle = NULL +excludeZOPC = NULL + + +zeroOrderPhaseMethod <- argLs[["zeroOrderPhaseMethod"]] + +if (zeroOrderPhaseMethod=='manual'){ + angle <- argLs[["angle"]] +} + +excludeZoneZeroPhase <- argLs[["excludeZoneZeroPhase.choice"]] +if (excludeZoneZeroPhase == 'YES') { + excludeZoneZeroPhaseList <- list() + for(i in which(names(argLs)=="excludeZoneZeroPhase_left")) { + excludeZoneZeroPhaseLeft <- argLs[[i]] + excludeZoneZeroPhaseRight <- argLs[[i+1]] + excludeZoneZeroPhaseList <- c(excludeZoneZeroPhaseList,list(c(excludeZoneZeroPhaseLeft,excludeZoneZeroPhaseRight))) + } + excludeZOPC <- excludeZoneZeroPhaseList +} + + +# Baseline Correction ------------------------------- + # Inputs +lambdaBc <- argLs[["lambdaBc"]] +pBc <- argLs[["pBc"]] +epsilon <- argLs[["epsilon"]] + +excludeBC = NULL + +excludeZoneBC <- argLs[["excludeZoneBC.choice"]] +if (excludeZoneBC == 'YES') { + excludeZoneBCList <- list() + for(i in which(names(argLs)=="excludeZoneBC_left")) { + excludeZoneBCLeft <- argLs[[i]] + excludeZoneBCRight <- argLs[[i+1]] + excludeZoneBCList <- c(excludeZoneBCList,list(c(excludeZoneBCLeft,excludeZoneBCRight))) + } + excludeBC <- excludeZoneBCList +} + +# transformation of negative values ------------------------------- + # Inputs +NegativetoZero <- argLs[["NegativetoZero"]] + + + # Outputs +nomGraphe <- argLs[["graphOut"]] +# dataMatrixOut <- argLs[["dataMatrixOut"]] +log <- argLs[["logOut"]] + + + +## Checking arguments +##------------------- +error.stock <- "\n" + +if(length(error.stock) > 1) + stop(error.stock) + + +##====================================================== +##====================================================== +## Computation +##====================================================== +##====================================================== + +pdf(nomGraphe, onefile = TRUE, width = 13, height = 13) + +# FirstOrderPhaseCorrection --------------------------------- +Fid_data <- GroupDelayCorrection(Fid_data0, Fid_info = samplemetadataFid, group_delay = NULL) + +if (FirstOPCGraph == "YES") { + title = "FIDs after Group Delay Correction" + DrawSignal(Fid_data, subtype = "stacked", + ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, + xlab = "Frequency", num.stacked = 4, + main = title, createWindow=FALSE) +} + +# SolventSuppression --------------------------------- +Fid_data <- SolventSuppression(Fid_data, lambda.ss = lambda, ptw.ss = TRUE, plotSolvent = F, returnSolvent = F) + +if (SSGraph == "YES") { + title = "FIDs after Solvent Suppression " + DrawSignal(Fid_data, subtype = "stacked", + ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, + xlab = "Frequency", num.stacked = 4, + main = title, createWindow=FALSE) +} + + +# Apodization --------------------------------- +Fid_data <- Apodization(Fid_data, Fid_info = samplemetadataFid, DT = NULL, + type.apod = apodization, phase = phase, rectRatio = rectRatio, gaussLB = gaussLB, expLB = expLB, plotWindow = F, returnFactor = F) + +if (ApodGraph == "YES") { + title = "FIDs after Apodization" + DrawSignal(Fid_data, subtype = "stacked", + ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, + xlab = "Frequency", num.stacked = 4, + main = title, createWindow=FALSE) +} + + +# FourierTransform --------------------------------- +Spectrum_data <- FourierTransform(Fid_data, Fid_info = samplemetadataFid, reverse.axis = TRUE) + + +if (FTGraph == "YES") { + title = "Fourier transformed spectra" + DrawSignal(Spectrum_data, subtype = "stacked", + ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, + xlab = "Frequency", num.stacked = 4, + main = title, createWindow=FALSE) +} + + + +# ZeroOrderPhaseCorrection --------------------------------- +Spectrum_data <- ZeroOrderPhaseCorrection(Spectrum_data, type.zopc = zeroOrderPhaseMethod, + plot_rms = NULL, returnAngle = FALSE, + createWindow = TRUE,angle = angle, + plot_spectra = FALSE, + ppm.zopc = TRUE, exclude.zopc = excludeZOPC) + + +# InternalReferencing --------------------------------- +# if (shiftReferencing=="YES") { +Spectrum_data <- InternalReferencing(Spectrum_data, samplemetadataFid, method = "max", range = shiftReferencingRange, + ppm.value = ppmvalue, shiftHandling = shiftHandling, ppm.ir = TRUE, + fromto.RC = shiftReferencingRangeList, pc = pctNearValue) + +if (SRGraph == "YES") { + title = "Spectra after Shift Referencing" + DrawSignal(Spectrum_data, subtype = "stacked", + ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, + xlab = "Frequency", num.stacked = 4, + main = title, createWindow=FALSE) +} + +# } + +if (ZeroOPCGraph == "YES") { +title = "Spectra after Zero Order Phase Correction" +DrawSignal(Spectrum_data, subtype = "stacked", + ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, + xlab = "Frequency", num.stacked = 4, + main = title, createWindow=FALSE) +} + + +# BaselineCorrection --------------------------------- +Spectrum_data <- BaselineCorrection(Spectrum_data, ptw.bc = TRUE, lambda.bc = lambdaBc, + p.bc = pBc, eps = epsilon, ppm.bc = TRUE, + exclude.bc = excludeBC, + returnBaseline = F) + + + +if (BCGraph == "YES") { +title = "Spectra after Baseline Correction" +DrawSignal(Spectrum_data, subtype = "stacked", + ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, + xlab = "Frequency", num.stacked = 4, + main = title, createWindow=FALSE) +} + + +# NegativeValuesZeroing --------------------------------- +if (NegativetoZero=="YES") { + Spectrum_data <- NegativeValuesZeroing(Spectrum_data) +} + +if (FinalGraph == "YES") { + title = "Final preprocessed spectra" + DrawSignal(Spectrum_data, subtype = "stacked", + ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, + xlab = "Frequency", num.stacked = 4, + main = title, createWindow=FALSE) +} + +invisible(dev.off()) + + +data_variable <- matrix(NA, nrow = 1, ncol = dim(Spectrum_data)[2], dimnames = list("ID", NULL)) +colnames(data_variable) <- colnames(Spectrum_data) +data_variable[1,] <- colnames(data_variable) + + +##====================================================== +##====================================================== +## Saving +##====================================================== +##====================================================== + +# Data Matrix +write.table(round(t(Re(Spectrum_data)),6), file=argLs$dataMatrix, quote=FALSE, row.names=TRUE, sep="\t", col.names=TRUE) + +# Variable metadata +write.table(data_variable,file=argLs$variableMetadata, quote=FALSE, row.names=TRUE, sep="\t", col.names=TRUE) + +# log file +# write.table(t(data.frame(argLs)), file = argLs$logOut, col.names = FALSE, quote=FALSE) + +# input arguments +cat("\n INPUT and OUTPUT ARGUMENTS :\n") + +argLs + + +## Ending + +cat("\nEnd of 'Preprocessing' Galaxy module call: ", as.character(Sys.time()), sep = "") + +sink() + +options(stringsAsFactors = strAsFacL) + +rm(list = ls()) diff -r cbea5e9fd0b4 -r 5e64657b4fe5 NmrPreprocessing_xml.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/NmrPreprocessing_xml.xml Wed Mar 28 08:05:12 2018 -0400 @@ -0,0 +1,575 @@ + + Preprocessing of 1D NMR spectra + + + macros.xml + + + + r-ptw + r-matrix + + + + + + ## Wrapper + Rscript $__tool_directory__/NmrPreprocessing_wrapper.R + + ## Data matrix of FID spectra + dataMatrixFid $dataMatrixFid + ## Sample metadata matrix + sampleMetadataFid $sampleMetadataFid + + ## First order phase correction + ## Graphical display + FirstOPCGraph $GDC.FirstOPCGraph + + ## Water and / or solvents suppression + ## Smoothing parameter + lambda $SS.lambda + + ## Graphical display + SSGraph $SS.SSGraph + + + ## Apodization + ## Graphical display + ApodGraph $Apod.ApodGraph + + apodizationMethod $Apod.apodizationMethod.method + #if $Apod.apodizationMethod.method == "exp": + ## Line broadening for the exponential window + expLB $Apod.apodizationMethod.expLB + #end if + #if $Apod.apodizationMethod.method == "cos2": + ## Phase + phase $Apod.apodizationMethod.phase + #end if + #if $Apod.apodizationMethod.method == "hanning": + ## Phase + phase $Apod.apodizationMethod.phase + #end if + #if $Apod.apodizationMethod.method == "hamming": + ## Phase + phase $Apod.apodizationMethod.phase + #end if + #if $Apod.apodizationMethod.method == "blockexp": + ## Proportion of signal in the window + rectRatio $Apod.apodizationMethod.rectRatio + expLB $Apod.apodizationMethod.expLB + #end if + #if $Apod.apodizationMethod.method == "blockcos2": + ## Proportion of signal in the window + rectRatio $Apod.apodizationMethod.rectRatio + #end if + #if $Apod.apodizationMethod.method == "gauss": + ## Line broadening for the gaussian window + gaussLB $Apod.apodizationMethod.gaussLB + #end if + + ## Fourier transform + ## Graphical display + FTGraph $FT.FTGraph + + ## Zero order phase correction + ## Graphical display + ZeroOPCGraph $ZOPC.ZeroOPCGraph + + zeroOrderPhaseMethod $ZOPC.zeroOrderPhaseMethod + + excludeZoneZeroPhase.choice ${ZOPC.excludeZoneZeroPhase.choice} + #if str($ZOPC.excludeZoneZeroPhase.choice) == "YES": + #for $i in $ZOPC.excludeZoneZeroPhase.conditions: + excludeZoneZeroPhase_left ${i.excludeZoneZeroPhase_left} + excludeZoneZeroPhase_right ${i.excludeZoneZeroPhase_right} + #end for + #end if + + ## Shift referencing + ## Graphical display + SRGraph $SR.SRGraph + + ## Definition of the search zone + shiftReferencingRange $SR.shiftReferencingRange.method + #if $SR.shiftReferencingRange.method == "nearvalue": + pctNearValue $SR.shiftReferencingRange.pctNearValue + #end if + #if $SR.shiftReferencingRange.method == "window": + #for $i in $SR.shiftReferencingRange.conditions: + shiftReferencingRangeLeft ${i.shiftReferencingRangeLeft} + shiftReferencingRangeRight ${i.shiftReferencingRangeRight} + #end for + #end if + shiftHandling $SR.shiftHandling + ppmvalue $SR.ppmvalue + + ## Baseline correction + ## Graphical display + BCGraph $BC.BCGraph + + lambdaBc $BC.lambdaBc + pBc $BC.pBc + epsilon $BC.epsilon + + excludeZoneBC.choice ${BC.excludeZoneBC.choice} + #if str($BC.excludeZoneBC.choice) == "YES": + #for $i in $BC.excludeZoneBC.conditions: + excludeZoneBC_left ${i.excludeZoneBC_left} + excludeZoneBC_right ${i.excludeZoneBC_right} + #end for + #end if + + + ## sets negative intensities to zero + NegativetoZero $NZ.NegativetoZero + + ## final spectra + ## Graphical display + FinalGraph $FinalGraph + + + ## Outputs + dataMatrix $dataMatrix + variableMetadata $variableMetadata + graphOut $graphOut + logOut $logOut + + + + + + + +
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+ + + + + + + +@HELP_AUTHORS@ + + +===================== +Spectra preprocessing +===================== + +----------- +Description +----------- + +These steps correspond to the following steps in the PEPS-NMR R library (https://github.com/ManonMartin/PEPSNMR): + +* Group Delay suppression (First order phase correction) +* Removal of solvent residuals signal from the FID +* Apodization to increase the Signal-to-Noise ratio of the FID +* Fourier transformation +* Zero order phase correction +* Shift referencing to calibrate the spectra with internal compound referencing +* Baseline correction +* Setting of negatives values to 0 + + +----------------- +Workflow position +----------------- + +**Upstream tools** + ++---------------------------+-------------------------+--------+ +| Name | Output file | Format | ++===========================+=========================+========+ +|NMR_Read | NMR_Read_dataMatrix | Tabular| ++---------------------------+-------------------------+--------+ +|NMR_Read | NMR_Read_sampleMetadata | Tabular| ++---------------------------+-------------------------+--------+ + + + +**Downstream tools** + ++---------------------------+----------------------+--------+ +| Name | Output file | Format | ++===========================+======================+========+ +|NMR_Alignement | dataMatrix | Tabular| ++---------------------------+----------------------+--------+ +|NMR_Bucketing | dataMatrix | Tabular| ++---------------------------+----------------------+--------+ +|Normalization | dataMatrix | Tabular| ++---------------------------+----------------------+--------+ +|Univariate | variableMetadata | Tabular| ++---------------------------+----------------------+--------+ +|Multivariate | sampleMetadata | Tabular| ++---------------------------+----------------------+--------+ +| | variableMetadata | Tabular| ++---------------------------+----------------------+--------+ + + +----------- +Input files +----------- + ++--------------------------------+-----------------+ +| File | Format | ++================================+=================+ +|1 : dataMatrix | tabular | ++--------------------------------+-----------------+ +|2 : sampleMetadata | tabular | ++--------------------------------+-----------------+ + +**dataMatrix file** + +sample x variable matrix with tabular separations and "." as decimal; the table must not contain metadata apart from row and column names; the row names must be identical to the rownames of the sample metadata. + + +**sampleMetadata file** + +sample x metadata matrix with tabular separations and "." as decimal for numeric metadata and NA for missing values. + + +---------------------- + Steps parameters +---------------------- + +**Solvent Suppression** +----------------------------------- + +**Smoothing parameter** lambda: The higher lambda is, the smoother the estimated solvent signal will be + + +**Apodization** +---------------------- + +The **types of apodization** are: + +* exp: The signal is multiplied by a decreasing exponential exp(-t/LineBroadening). + +* cos2: The signal is multiplied by the value of a cosinus squared from 0 (where its value is 1) until pi/2 (where its value is 0). + +* blockexp: The first part of the signal (described by the proportion of signal in the window) is left unchanged and the second is multiplied by exp(-t/LineBroadening) starting at value 1. + +* blockcos2: The first part is left unchanged as with blockexp and the second part is multiplied by a cosinus squared where its value starts at 1 at the end of the block and ends at 0 at the end of the signal. + +* gauss: The signal is multiplied by a gaussian window centered at the beginning of the FID and with sigma=1/LineBroadening. + +* hanning: The signal is multiplied by a hanning window : 0.5 + 0.5 cos. + +* hamming: The signal is multiplied by a hamming window : 0.54 + 0.46 cos. + + + + +**Zero Order Phase Correction** +----------------------------------- + +**Zero Order Phase correction method**: + +* rms: A positiveness criterion is applied on the spectrum with a quantile probability parameter to trim the values. + +* max: Optimization of the maximal spectral intensity. + + +**Exclusion area(s) for the Zero Order Phase Correction**: enables to optimize the criterion with excluded spectral window(s), by default the water region is excluded. + + +**Shift Referencing** +---------------------- + +The **searching window** can be adapted: + +* nearvalue: the search concentrates around the value of the reference peak in ppm. + +* all: search accross the whole ppm axis. + +* window: the search is operated in the windows defined by the Search_zone bounds. + + +**shiftHandling**: spectra can be shifted differently, we can handle misalignment of the left and right of the spectrum by different ways: + +* zerofilling: The extremities at which a spectrum is not defined are replaced by 0. It makes sense since in practice the spectrum is close to zero at the extremities. + +* NAfilling: The extremities at which a spectrum is not defined are replaced by NA. + +* circular: The spectra are shifted circularly which means that the end of a spectrum is reproduced at the beginning. + +* cut: The ppm values for which some spectra are not defined are removed. + + +**value of the reference peak**: the value in ppm of the reference peak. By default the value is 0 ppm. + + + +**Baseline Correction** +---------------------------- + +**Smoothing parameter**: the larger it is, the smoother the estimated baseline will be. + +**Asymmetry parameter**: the smaller it is, the less the estimated baseline will try to follow peaks when it is under the spectrum and the more it will try to be under the spectrum. + +**numerical precision**: numerical precision for convergence when estimating the baseline. + +**Exclusion area(s) for the Baseline Correction**: enables to optimize the criterion with excluded spectral window(s), by default the water region is excluded. + + + +**Negative intensities to Zero** +------------------------------------ + +**Set negative intensities to zero**: the set of negative intensities to zero is optional. + + +------------ +Output files +------------ + +NMR_Preprocessing_dataMatrix + | tabular output + | Data matrix with n rows (descriptors) and p columns (samples) containing the preprocessed spectra. + | + +NMR_Preprocessing_variableMetadata + | tabular output + | Data matrix with 1 row (ppm value) and p columns (descriptors). + | + +NMR_Preprocessing_log + | text output + | Contains warnings and the input parameters + | + +NMR_Preprocessing_graph.pdf + | pdf output + | line plots of preprocessed spectra + | + + +@HELP_CHANGELOG@ + + + + + + diff -r cbea5e9fd0b4 -r 5e64657b4fe5 README.rst --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/README.rst Wed Mar 28 08:05:12 2018 -0400 @@ -0,0 +1,19 @@ + +Changelog/News +-------------- +**Version 3.2.0** + +* Updated R scripts and the help section of NMR_ReadFids and NMR_preprocessing +* Added sections +* Created a variableMetadata file in output of the NMR_preprocessing module +* Homogenised the input-output file names with the other modules +* Suppressed the option ptw for the baseline correction, set to TRUE all the time now +* Shift referencing: other values than 0 are admitted +* The log file recovers the input/output parameters +* Added an exclusion zone for the computation of the Baseline Correction criterion +* Switched Internal Referencing (goes second) and Zero Order Phase Correction (goes first) + + +**Version 3.1.0** + +* Implementation of NMR_ReadFids and NMR_preprocessing diff -r cbea5e9fd0b4 -r 5e64657b4fe5 ReadFids_script.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/ReadFids_script.R Wed Mar 28 08:05:12 2018 -0400 @@ -0,0 +1,404 @@ +################################################################################################ +# +# Read FIDs in Bruker format +# +# +################################################################################################ + + +# vec2mat ============================================================================== +vec2mat <- function(vec) { + return(matrix(vec, nrow = 1, dimnames = list(c(1), names(vec)))) +} + + +# ReadFid ============================================================================== +ReadFid <- function(path) { + + # Read 1D FID using Bruker XWinNMR and TopSpin format. It is inspired of the + # matNMR matlab library which deals with 2D FID and also other formats + # Read also the parameters in the acqus file + + paramFile <- file.path(path, "acqus") + # BYTEORDA: 0 -> Little Endian 1 -> Big Endian + params <- readParams(paramFile, c("TD", "BYTORDA", "DIGMOD", "DECIM", "DSPFVS", + "SW_h", "SW", "O1")) + + if (params[["DSPFVS"]] >= 20) { + # The group delay first order phase correction is given directly from version 20 + grpdly <- readParams(paramFile, c("GRPDLY")) + params[["GRPDLY"]] <- grpdly[["GRPDLY"]] + } + TD <- params[["TD"]] + endianness <- if (params$BYTORDA) + "big" else "little" + if (TD%%2 != 0) { + stop(paste("Only even numbers are allowed for size in TD because it is complex + data with the real and imaginary part for each element.", + "The TD value is in the", paramFile, "file")) + } + + # Interpret params Dwell Time, time between 2 data points in the FID + params[["DT"]] <- 1/(2 * params[["SW_h"]]) + + # Read fid + fidFile <- file.path(path, "fid") + fidOnDisk <- readBin(fidFile, what = "int", n = TD, size = 4L, endian = endianness) + + # Real size that is on disk (it should be equal to TD2, except for TopSpin/Bruker + # (which is our case) according to matNMR as just discussed + TDOnDisk <- length(fidOnDisk) + if (TDOnDisk < TD) { + warning("Size is smaller than expected, the rest is filled with zero so the size is the same for every fid") + fidGoodSize <- sapply(vector("list", length = TD), function(x) 0) + fidGoodSize[1:TDOnDisk] <- fidOnDisk + + } else if (TDOnDisk > TD) { + warning("Size is bigger than expected, the rest ignored so the size is the same for every fid") + fidGoodSize <- fidOnDisk(1:TD) + + } else { + fidGoodSize <- fidOnDisk + } + + fidRePart <- fidGoodSize[seq(from = 1, to = TD, by = 2)] + fidImPart <- fidGoodSize[seq(from = 2, to = TD, by = 2)] + fid <- complex(real = fidRePart, imaginary = fidImPart) + + return(list(fid = fid, params = params)) +} + + + + +# getDirsContainingFid ============================================================================== +getDirsContainingFid <- function(path) { + subdirs <- dir(path, full.names = TRUE) + if (length(subdirs) > 0) { + cond <- sapply(subdirs, function(x) { + content <- dir(x) + # subdirs must contain fid, acqu and acqus files + return("fid" %in% content && "acqu" %in% content && "acqus" %in% content) + }) + subdirs <- subdirs[cond] + } + return(subdirs) +} + + + + + + +# beginTreatment ============================================================================== + +beginTreatment <- function(name, Signal_data = NULL, Signal_info = NULL, + force.real = FALSE) { + + cat("Begin", name, "\n") + + + # Formatting the Signal_data and Signal_info ----------------------- + + vec <- is.vector(Signal_data) + if (vec) { + Signal_data <- vec2mat(Signal_data) + } + if (is.vector(Signal_info)) { + Signal_info <- vec2mat(Signal_info) + } + if (!is.null(Signal_data)) { + if (!is.matrix(Signal_data)) { + stop("Signal_data is not a matrix.") + } + if (!is.complex(Signal_data) && !is.numeric(Signal_data)) { + stop("Signal_data contains non-numerical values.") + } + } + if (!is.null(Signal_info) && !is.matrix(Signal_info)) { + stop("Signal_info is not a matrix.") + } + + + Original_data <- Signal_data + + # Extract the real part of the spectrum --------------------------- + + if (force.real) { + if (is.complex(Signal_data)) { + Signal_data <- Re(Signal_data) + } else { + # The signal is numeric Im(Signal_data) is zero anyway so let's avoid + # using complex(real=...,imaginary=0) which would give a complex signal + # in endTreatment() + force.real <- FALSE + } + } + + + # Return the formatted data and metadata entries -------------------- + + return(list(start = proc.time(), vec = vec, force.real = force.real, + Original_data = Original_data, Signal_data = Signal_data, Signal_info = Signal_info)) +} + + +# endTreatment ============================================================================== + +endTreatment <- function(name, begin_info, Signal_data) { + end_time = proc.time() # record it as soon as possible + start_time = begin_info[["start"]] + delta_time = end_time - start_time + delta = delta_time[] + cat("End", name, "\n") + cat("It lasted", + round(delta["user.self"], 3), "s user time,", + round(delta["sys.self"] , 3), "s system time and", + round(delta["elapsed"] , 3), "s elapsed time.\n") + if (begin_info[["force.real"]]) { + # The imaginary part is left untouched + i <- complex(real=0, imaginary=1) + Signal_data = Signal_data + i * Im(begin_info[["Original_data"]]) + } + if (begin_info[["vec"]]) { + Signal_data = Signal_data[1,] + } + return(Signal_data) +} + + +# checkArg ============================================================================== + +checkArg <- function(arg, checks, can.be.null=FALSE) { + check.list <- list(bool=c(is.logical, "a boolean"), + int =c(function(x){x%%1==0}, "an integer"), + num =c(is.numeric, "a numeric"), + str =c(is.character, "a string"), + pos =c(function(x){x>0}, "positive"), + pos0=c(function(x){x>=0}, "positive or zero"), + l1 =c(function(x){length(x)==1}, "of length 1") + ) + if (is.null(arg)) { + if (!can.be.null) { + stop(deparse(substitute(arg)), " is null.") + } + } else { + if (is.matrix(arg)) { + stop(deparse(substitute(arg)), " is not scalar.") + } + for (c in checks) { + if (!check.list[[c]][[1]](arg)) { + stop(deparse(substitute(arg)), " is not ", check.list[[c]][[2]], ".") + } + } + } +} + + +# getArg ============================================================================== + +getArg <- function(arg, info, argname, can.be.absent=FALSE) { + if (is.null(arg)) { + start <- paste("impossible to get argument", argname, "it was not given directly and"); + if (!is.matrix(info)) { + stop(paste(start, "the info matrix was not given")) + } + if (!(argname %in% colnames(info))) { + if (can.be.absent) { + return(NULL) + } else { + stop(paste(start, "is not in the info matrix")) + } + } + if (nrow(info) < 1) { + stop(paste(start, "the info matrix has no row")) + } + arg <- info[1,argname] + if (is.na(arg)) { + stop(paste(start, "it is NA in the info matrix")) + } + } + return(arg) +} + + + +# getTitle ============================================================================== + +# Get the name of the signal from the title file or fromt the name of the subdirectory +# Get the name of the signal from the title file or fromt the name of the subdirectory + +getTitle <- function(path, l, subdirs) { + title <- NULL + title_file <- file.path(file.path(file.path(path, "pdata"), "1"), "title") + if (file.exists(title_file)) { + lines <- readLines(title_file, warn = FALSE) + if (length(lines) >= 1) { + first_line <- gsub("^\\s+|\\s+$", "", lines[l]) + if (nchar(first_line) >= 1) { + title <- first_line + } else { + warning(paste("The", l ,"line of the title file is blank for directory ", + path, "and the (sub)dirs names are used instead")) + } + } else { + warning(paste("The title file is empty for directory ", path, "and the (sub)dirs names are used instead")) + } + } else { + warning(paste("Title file doesn't exists for directory ", path, "\n the (sub)dirs names are used instead")) + } + if (is.null(title)) { + if(subdirs) { + separator <- .Platform$file.sep + path_elem <- strsplit(path,separator)[[1]] + title <- paste(path_elem[length(path_elem)-1], path_elem[length(path_elem)], sep = "_") + } else{title <- basename(path)} + } + return(title) +} + + + + +# readParams ============================================================================== +# Read parameter values for Fid_info in the ReadFids function + +readParams <- function(file, paramsName) { + + isDigit <- function(c) { + return(suppressWarnings(!is.na(as.numeric(c)))) + } + lines <- readLines(file) + params <- sapply(paramsName, function(x) NULL) + + for (paramName in paramsName) { + # Find the line with the parameter I add a '$' '=' in the pattern so that for + # example 'TD0' is not found where I look for 'TD' and LOCSW and WBSW when I look + # for 'SW' + pattern <- paste("\\$", paramName, "=", sep = "") + occurences <- grep(pattern, lines) + if (length(occurences) == 0L) { + stop(paste(file, "has no field", pattern)) + } + if (length(occurences) > 1L) { + warning(paste(file, "has more that one field", pattern, " I take the first one")) + } + line <- lines[occurences[1]] + + # Cut beginning and end of the line '##$TD= 65536' -> '65536' + igual = as.numeric(regexpr("=", line)) + + first <- igual + while (first <= nchar(line) & !isDigit(substr(line, first, first))) { + first <- first + 1 + } + last <- nchar(line) + while (last > 0 & !isDigit(substr(line, last, last))) { + last <- last - 1 + } + params[paramName] <- as.numeric(substr(line, first, last)) + } + return(params) +} + + + +# ReadFids ============================================================================== + +ReadFids <- function(path, l = 1, subdirs = FALSE, dirs.names = FALSE) { + + # Data initialisation and checks ---------------------------------------------- + begin_info <- beginTreatment("ReadFids") + checkArg(path, c("str")) + checkArg(l, c("pos")) + if (file.exists(path) == FALSE) { + stop(paste("Invalid path:", path)) + } + + + # Extract the FIDs and their info ---------------------------------------------- + + if (subdirs == FALSE) { + fidDirs <- getDirsContainingFid(path) + n <- length(fidDirs) + if (n == 0L) { + stop(paste("No valid fid in", path)) + } + if (dirs.names) { + separator <- .Platform$file.sep + path_elem <- strsplit(fidDirs,separator) + fidNames <- sapply(path_elem, function(x) x[[length(path_elem[[1]])]]) + }else {fidNames <- sapply(X = fidDirs, FUN = getTitle, l = l, subdirs = subdirs, USE.NAMES = F)} + + for (i in 1:n) { + fidList <- ReadFid(fidDirs[i]) + fid <- fidList[["fid"]] + info <- fidList[["params"]] + m <- length(fid) + if (i == 1) { + Fid_data <- matrix(nrow = n, ncol = m, dimnames = list(fidNames, + info[["DT"]] * (0:(m - 1)))) + Fid_info <- matrix(nrow = n, ncol = length(info), dimnames = list(fidNames, + names(info))) + } + Fid_data[i, ] <- fid + Fid_info[i, ] <- unlist(info) + } + + } else { + maindirs <- dir(path, full.names = TRUE) # subdirectories + Fid_data <- numeric() + Fid_info <- numeric() + + fidDirs <- c() + for (j in maindirs) { + fd <- getDirsContainingFid(j) # recoved FIDs from subdirectories + n <- length(fd) + if (n > 0L) { + fidDirs <- c(fidDirs, fd) + } else {warning(paste("No valid fid in",j ))} + } + + if (dirs.names==TRUE) { + if (length(fidDirs)!= length(dir(path))) { # at least one subdir contains more than 1 FID + separator <- .Platform$file.sep + path_elem <- strsplit(fidDirs,separator) + fidNames <- sapply(path_elem, function(x) paste(x[[length(path_elem[[1]])-1]], + x[[length(path_elem[[1]])]], sep = "_")) + }else {fidNames <- dir(path)} + + } else {fidNames <- sapply(X = fidDirs, FUN = getTitle, l = l, subdirs = subdirs, USE.NAMES = F)} + + for (i in 1:length(fidNames)) { + fidList <- ReadFid(fidDirs[i]) + fid <- fidList[["fid"]] + info <- fidList[["params"]] + m <- length(fid) + if (i == 1) { + Fid_data <- matrix(nrow = length(fidNames), ncol = m, dimnames = list(fidNames, + info[["DT"]] * (0:(m - 1)))) + Fid_info <- matrix(nrow = length(fidNames), ncol = length(info), dimnames = list(fidNames, + names(info))) + } + Fid_data[i, ] <- fid + Fid_info[i, ] <- unlist(info) + } + + + } + + # Check for non-unique IDs ---------------------------------------------- + NonnuniqueIds <- sum(duplicated(row.names(Fid_data))) + cat("dim Fid_data: ", dim(Fid_data), "\n") + cat("IDs: ", rownames(Fid_data), "\n") + cat("non-unique IDs?", NonnuniqueIds, "\n") + if (NonnuniqueIds > 0) { + warning("There are duplicated IDs: ", Fid_data[duplicated(Fid_data)]) + } + + + # Return the results ---------------------------------------------- + return(list(Fid_data = endTreatment("ReadFids", begin_info, Fid_data), Fid_info = Fid_info)) + +} + diff -r cbea5e9fd0b4 -r 5e64657b4fe5 ReadFids_wrapper.R --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/ReadFids_wrapper.R Wed Mar 28 08:05:12 2018 -0400 @@ -0,0 +1,158 @@ +#!/usr/local/public/bin/Rscript --vanilla --slave --no-site-file + +## 08122016_ReadFids_wrapper.R +## Manon Martin +## manon.martin@uclouvain.be + +##====================================================== +##====================================================== +# Preamble +##====================================================== +##====================================================== + +runExampleL <- FALSE + + +##------------------------------ +## Options +##------------------------------ +strAsFacL <- options()$stringsAsFactors +options(stringsAsFactors = FALSE) +options(warn=1) + +##------------------------------ +## Libraries laoding +##------------------------------ +library(batch) +library(ggplot2) +library(gridExtra) +library(reshape2) + + +# R script call +source_local <- function(fname) +{ + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + source(paste(base_dir, fname, sep="/")) +} +#Import the different functions +source_local("ReadFids_script.R") +source_local("DrawFunctions.R") +##------------------------------ +## Errors ????????????????????? +##------------------------------ + + +##------------------------------ +## Constants +##------------------------------ +topEnvC <- environment() +flagC <- "\n" + + +##------------------------------ +## Script +##------------------------------ +if(!runExampleL) + argLs <- parseCommandArgs(evaluate=FALSE) + +sink(argLs$logOut) + +##====================================================== +##====================================================== +## Parameters Loading +##====================================================== +##====================================================== + + ## Inputs + # Path + ## Bruker FIDs +fileType="Bruker" +zipfile= argLs[["fidzipfile"]] +directory=unzip(zipfile, list=F) +path=paste(getwd(),strsplit(directory[1],"/")[[1]][2],sep="/") + + +# other inputs from ReadFids +l = argLs[["title_line"]] +subdirs <- argLs[["subdirectories"]] +dirs.names <- argLs[["dirs_names"]] + + +# Outputs +# dataMatrix <- argLs[["dataMatrix"]] +# sampleMetadata <- argLs[["sampleMetadata"]] +logOut <- argLs[["logOut"]] +nomGraphe <- argLs[["graphOut"]] + + + +## Checking arguments +##------------------- +error.stock <- "\n" + +if(length(error.stock) > 1) + stop(error.stock) + + + +##====================================================== +##====================================================== +## Computation +##====================================================== +##====================================================== +sink(logOut,append=TRUE) + +if(length(warnings())>0){ # or !is.null(warnings()) + print("something happened") +} + +## Starting +cat("\nStart of 'ReadFids' Galaxy module call: ", as.character(Sys.time()), "\n\n", sep = "") + +outputs <- ReadFids(path = path, l=l, subdirs = subdirs, dirs.names = dirs.names) + +data_matrix <- outputs[["Fid_data"]] # Data matrix +data_sample <- outputs[["Fid_info"]] # Sample metadata + + + +pdf(nomGraphe, onefile = TRUE, width = 13, height = 13) +title = "Raw FID data" +DrawSignal(data_matrix, subtype = "stacked", + ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, + xlab = "Frequency", num.stacked = 4, + main = title, createWindow=FALSE) +invisible(dev.off()) + +##====================================================== +##====================================================== +## Saving +##====================================================== +##====================================================== + +# Data matrix +write.table(data_matrix,file=argLs$dataMatrix, quote=FALSE, row.names=TRUE, sep="\t", col.names=TRUE) + +# Sample metadata +write.table(data_sample,file=argLs$sampleMetadata, quote=FALSE, row.names=TRUE, sep="\t", col.names=TRUE) + +# log file +# write.table(t(data.frame(argLs)), file = argLs$logOut, col.names = FALSE, quote=FALSE) + +# input arguments +cat("\n INPUT and OUTPUT ARGUMENTS :\n") + +argLs + +## Ending + +cat("\nEnd of 'ReadFids' Galaxy module call: ", as.character(Sys.time()), sep = "") + +sink() + + +options(stringsAsFactors = strAsFacL) + +rm(list = ls()) \ No newline at end of file diff -r cbea5e9fd0b4 -r 5e64657b4fe5 ReadFids_xml.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/ReadFids_xml.xml Wed Mar 28 08:05:12 2018 -0400 @@ -0,0 +1,211 @@ + + Read Bruker NMR raw files + + + macros.xml + + + + + + + + ## Wrapper + Rscript $__tool_directory__/ReadFids_wrapper.R + + ## File input + fidzipfile $fidzipfile + + ## Title line + title_line $title_line + + ## Subdirectories + subdirectories $subdirectories + + ## Use subdirectories names as FID names? + dirs_names $dirs_names + + ## Outputs + dataMatrix $dataMatrix + sampleMetadata $sampleMetadata + logOut $logOut + graphOut $graphOut + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +@HELP_AUTHORS@ + + +============= +NMR Read +============= + +----------- +Description +----------- + +Nuclear Magnetic Resonance Bruker files reading (from the PEPS-NMR R package (https://github.com/ManonMartin/PEPSNMR)) + +----------------- +Workflow position +----------------- + +**Upstream tools** + +========================= ================= ======= +Name output file format +========================= ================= ======= +NA NA NA +========================= ================= ======= + + +**Downstream tools** + ++-----------------------+--------------------------+--------+ +| Name | Output file | Format | ++=======================+==========================+========+ +|NMR_Preprocessing | dataMatrix | Tabular| ++-----------------------+--------------------------+--------+ +|NMR_Preprocessing | sampleMetadata | Tabular| ++-----------------------+--------------------------+--------+ +|NMR_Preprocessing | NMR_Read_log | TXT | ++-----------------------+--------------------------+--------+ +|NMR_Preprocessing | NMR_Read_graph | PDF | ++-----------------------+--------------------------+--------+ +|NMR_Alignement | dataMatrix | Tabular| ++-----------------------+--------------------------+--------+ +|NMR_Bucketing | dataMatrix | Tabular| ++-----------------------+--------------------------+--------+ +|Normalization | dataMatrix | Tabular| ++-----------------------+--------------------------+--------+ +|Univariate | variableMetadata | Tabular| ++-----------------------+--------------------------+--------+ +|Multivariate | sampleMetadata | Tabular| ++-----------------------+--------------------------+--------+ +| | variableMetadata | Tabular| ++-----------------------+--------------------------+--------+ + + +----------- +Input files +----------- + ++---------------------------+-----------------+ +| Parameter : num + label | Format | ++===========================+=================+ +| 1 : Choose your inputs | zip | ++---------------------------+-----------------+ + + +**Choose your inputs** + + | Zip file (recommended) of FID Bruker files: you can put a zip file containing your FID Bruker files: myinputs.zip. + + +---------- +Parameters +---------- + +FID Title line + | Line in the acqus file to find the FID title (name) + | + +subdirectories + | Organization of individual's files + | TRUE: will search inside subdirectories for FIDs and will merge them to have unique FID and info matrices. + | + +dirs_names + | Use the (sub)directories names as FID names? + | + + +------------ +Output files +------------ + +NMR_Read_dataMatrix + | tabular output + | Data matrix with n rows (samples) and p columns (time) containing the raw FIDs. + | + +NMR_Read_sampleMetadata + | tabular output + | Data matrix with n rows (samples) containing the acquisition parameters for each sample. + | + +NMR_Read_log + | Text output + | Contains warnings + | + + +NMR_Read_graph + | pdf output + | line plots of FID + | + + +Creating the zip file +----------------------- + +.. class:: warningmark you must use the 7Zip software (http://www.7-zip.org/) to zip under Windows. + +Must contain at least the following files for every sample: fid, acqu and acqus + +.. image:: ./static/images/ReadFids.png + + + +**Possible structure and parameters values:** + + +(1) use title file and presence of sub-directories: set the FID Title line, subdirectories = TRUE, dirs_names = FALSE +(2) use title file and no sub-directories: set the FID Title line, subdirectories = FALSE, dirs_names = FALSE +(3) don't use title file and presence of sub-directories: subdirectories = TRUE, dirs_names = TRUE +(4) don't use title file and no sub-directories: subdirectories = FALSE, dirs_names = TRUE + + +@HELP_CHANGELOG@ + + + + + + diff -r cbea5e9fd0b4 -r 5e64657b4fe5 macros.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/macros.xml Wed Mar 28 08:05:12 2018 -0400 @@ -0,0 +1,71 @@ + + + 3.2.0 + + + + r-batch + r-ggplot2 + r-gridextra + r-reshape2 + + + + + + + + + + + + +.. class:: infomark + +**Authors** Manon Martin (manon.martin@uclouvain.be) and Marie Tremblay-Franco (marie.tremblay-franco@inra.fr; Galaxy integration) + +.. class:: infomark + +| Contact support@workflow4metabolomics.org for any questions or concerns about the Galaxy implementation of this tool. + +--------------------------------------------------- + + + + + +--------------------------------------------------- + +Changelog/News +-------------- +**Version 3.2.0** + +* Updated R scripts and the help section of NMR_ReadFids and NMR_preprocessing +* Added sections +* Created a variableMetadata file in output of the NMR_preprocessing module +* Homogenised the input-output file names with the other modules +* Suppressed the option ptw for the baseline correction, set to TRUE all the time now +* Shift referencing: other values than 0 are admitted +* The log file recovers the input/output parameters +* Added an exclusion zone for the computation of the Baseline Correction criterion +* Switched Internal Referencing (goes second) and Zero Order Phase Correction (goes first) + +**Version 3.1.0** + +* Implementation of NMR_ReadFids and NMR_preprocessing + + + + + + @PhDThesis{Rousseau2011, + title = {Statistical contribution to the analysis of metabonomics data in $^1$H NMR spectroscopy}, + author = {Rousseau, R.}, + school = {Institut de Statistique, Biostatistique et Sciences Actuarielles, Universit{\'e} catholique de Louvain}, + year = {2011}} + + 10.1093/bioinformatics/btu813 + + + + diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/.Rhistory diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/Apodization_wrapper_Manon.R --- a/nmr_preprocessing/Apodization_wrapper_Manon.R Tue May 23 03:32:51 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,187 +0,0 @@ -#!/usr/local/public/bin/Rscript --vanilla --slave --no-site-file - -## 12012017_Apodization_wrapper.R -## Manon Martin -## manon.martin@uclouvain.be - - -#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -# Use of runExampleL ? -#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ - -runExampleL <- FALSE -# -# if(runExampleL) { -# ##------------------------------ -# ## Example of arguments -# ##------------------------------ -# argLs <- list(StudyDir = "Tlse_BPASourisCerveau", -# upper = "10.0", -# lower = "0.50", -# bucket.width = "0.01", -# exclusion = "TRUE", -# exclusion.zone = list(c(6.5,4.5)), -# graph="Overlay") -# -# argLs <- c(argLs, -# list(dataMatrixOut = paste(directory,"_NmrBucketing_dataMatrix.tsv",sep=""), -# sampleMetadataOut = paste(directory,"_NmrBucketing_sampleMetadata.tsv",sep=""), -# variableMetadataOut = paste(directory,"_NmrBucketing_variableMetadata.tsv",sep=""), -# graphOut = paste(directory,"_NmrBucketing_graph.pdf",sep=""), -# logOut = paste(directory,"_NmrBucketing_log.txt",sep=""))) -# } - - - -##------------------------------ -## Options -##------------------------------ -strAsFacL <- options()$stringsAsFactors -#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -# stringsAsFactors = FALSE utilis?? o?? ?? -#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -options(stringsAsFactors = FALSE) - - - - -##------------------------------ -## Libraries loading -##------------------------------ -# For parseCommandArgs function -library(batch) - -# R script call -source_local <- function(fname) -{ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - source(paste(base_dir, fname, sep="/")) -} -#Import the different functions -source_local("Apodization_Manon.R") - -##------------------------------ -## Errors ????????????????????? -##------------------------------ - - -##------------------------------ -## Constants -##------------------------------ -#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -# interviennent ou ? -#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ - -topEnvC <- environment() -flagC <- "\n" - - -##------------------------------ -## Script -##------------------------------ -if(!runExampleL) - argLs <- parseCommandArgs(evaluate=FALSE) # If FALSE valeurs par d??faut d??finies dans le software - - -## Parameters Loading -##------------------- -## Inputs -# data - -# --- Galaxy_preformatted data -# data <- read.table(argLs[["dataMatrix"]],check.names=FALSE,header=TRUE,sep="\t") -# rownames(data) <- data[,1] -# data <- data[,-1] -# --- - -# --- data from ReadFids -Fid_data <- read.table(argLs[["dataMatrixOut"]],check.names=FALSE,header=TRUE,sep="\t") -Fid_info <- read.table(argLs[["sampleOut"]],check.names=FALSE,header=TRUE,sep="\t") -# --- - -# other inputs (cf. XML wrapper) -DT = argLs[["DT"]] -type.apod = argLs[["ApodizationMethod"]] - -# set default values for optional arguments -phase=0 -rectRatio=1/2 -gaussLB=1 -expLB=1 - -# change the default values -if (type.apod %in% c("cos2", "hanning", "hamming")) { - phase = argLs[["phase"]] -} - -if (type.apod == "blockexp") { - rectRatio = argLs[["rectRatio"]] - expLB = argLs[["expLB"]] -} - -if (type.apod == "blockcos2") { - rectRatio = argLs[["rectRatio"]] -} - -if (type.apod == "gauss") { -gaussLB = argLs[["gaussLB"]] -} - -if (type.apod == "exp") { - expLB = argLs[["expLB"]] -} - -plotWindow = FALSE -returnFactor = FALSE - - - -#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -# Utility of Outputs ?? -#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -# Outputs -dataMatrixOut <- argLs[["dataMatrixOut"]] # Names from Saving - - - -## Checking arguments -##------------------- -error.stock <- "\n" - -#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -# error.stock utilis?? ou ? -#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -if(length(error.stock) > 1) - stop(error.stock) - - -## Computation -##------------ -outputs <- Apodization(Fid_data = Fid_data, Fid_info = Fid_info, DT = DT, - type.apod = type.apod, phase = phase, rectRatio = rectRatio, - gaussLB = gaussLB, expLB = expLB, plotWindow = plotWindow, returnFactor = returnFactor) - -data_matrix <- outputs # Data matrix - - - -## Saving -##------- -# Data matrix -data_matrix <- cbind(rownames(data_matrix),data_matrix) -colnames(data_matrix) <- c("Sample",colnames(data_matrix)[-1]) -write.table(data_matrix,file=argLs$dataMatrixOut,quote=FALSE,row.names=FALSE,sep="\t") - - - -## Ending -##--------------------- - -cat("\nEnd of 'Apodization' Galaxy module call: ", as.character(Sys.time()), sep = "") - -## sink(NULL) - -options(stringsAsFactors = strAsFacL) - -rm(list = ls()) \ No newline at end of file diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/DrawFunctions.R --- a/nmr_preprocessing/DrawFunctions.R Tue May 23 03:32:51 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,257 +0,0 @@ -require(ggplot2) -require(gridExtra) -require(reshape2) - - -Draw <- function(Signal_data, type.draw = c("signal", "pca"), output = c("default", - "window", "png", "pdf"), dirpath = ".", filename = "%003d", height = 480, - width = 640, pdf.onefile = TRUE, ...) { - - # Data initialisation and checks ---------------------------------------------- - type.draw <- match.arg(type.draw) - output <- match.arg(output) - fullpath <- paste(file.path(dirpath, filename), output, sep = ".") - createFile <- TRUE - createWindow <- FALSE - - # Drawing -------------------------------------------------------------------- - # output - switch(output, default = { - createFile <- FALSE - }, window = { - createWindow <- TRUE - createFile <- FALSE - }, png = { - grDevices::png(fullpath, width, height) - }, pdf = { - grDevices::pdf(fullpath, width = width/72, height = height/72, - onefile = pdf.onefile) - }, { - stop("Unknown output type.") - }) - - # Drawing type (signal/spectrum or PCA) - funs <- list(signal = DrawSignal, pca = DrawPCA) - if (type.draw %in% names(funs)) { - fun <- funs[[type.draw]] - } else { - stop(paste("Unknown type:", type.draw)) - } - - # Plot finalisation ---------------------------------------------- - if (is.vector(Signal_data)) { - Signal_data <- vec2mat(Signal_data) - } - fun(Signal_data, createWindow = createWindow, ...) - if (createFile) { - grDevices::dev.off() - } -} - - - -##### DrawSignal - -DrawSignal <- function(Signal_data, subtype = c("stacked", "together", - "separate", "diffmean", "diffmedian", "diffwith"), - ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, - xlab = "rowname", RowNames = NULL, row = 1, num.stacked = 4, - main = NULL, createWindow) { - # nticks - - # Data initialisation and checks ---------------------------------------------- - - subtype <- match.arg(subtype) - - - n <- nrow(Signal_data) - m <- ncol(Signal_data) - - - scale <- colnames(Signal_data) - - num.plot <- sum(ReImModArg) - - Var <- rowname <- value <- NULL # only for R CMD check - - # Drawing array - if (num.plot <= 0) { - stop("Nothing selected in ReImModArg.") - } else if (num.plot <= 2) { - if (vertical) { - nrow <- num.plot - ncol <- 1 - } else { - nrow <- 1 - ncol <- num.plot - } - } else { - nrow <- 2 - ncol <- 2 - } - - # RowNames - if (is.null(RowNames)) { - RowNames <- rownames(Signal_data) - if (is.null(RowNames)) { - RowNames <- 1:n - } - } else { - if (!is.vector(RowNames)) { - stop("RowNames is not a vector") - } - if (length(RowNames) != n) { - stop(paste("RowNames has length", length(RowNames), "and there are", n, "FIDs.")) - } - } - - if (n == 1) { - RowNames <- deparse(substitute(Signal_data)) - } - - elements <- list() - if (ReImModArg[1]) { - elements[["Re"]] <- Re(Signal_data) - } - if (ReImModArg[2]) { - elements[["Im"]] <- Im(Signal_data) - } - if (ReImModArg[3]) { - elements[["Mod"]] <- Mod(Signal_data) - } - if (ReImModArg[4]) { - elements[["Arg"]] <- Arg(Signal_data) - } - - - - - # Drawing -------------------------------------------------------------------- - - y = x = NULL # only for R CMD check - - - # SEPARATE or STACKED =============== - if (subtype == "separate" | subtype == "stacked") { - - i <- 1 - while (i <= n) { - if (createWindow) { - grDevices::dev.new(noRStudioGD = TRUE) - } - if (subtype == "separate") { - # The other uses gridExtra to do that - graphics::par(mfrow = c(nrow, ncol)) - } - plots <- list() - if (subtype == "separate") { - last <- i - } else { - last <- min(i + num.stacked - 1, n) - } - for (name in names(elements)) { - if (subtype == "separate") { - if (n == 1) { - df <- data.frame(x = as.numeric(scale), y = elements[[name]]) - } else {df <- data.frame(x = as.numeric(scale), y = elements[[name]][i, ]) - } - - plots[[name]] <- ggplot2::ggplot(data = df, ggplot2::aes(x = x, y = y)) + - ggplot2::geom_line() + - ggplot2::theme(legend.position = "none") + - ggplot2::labs(x = xlab, y = name) + - ggplot2::ggtitle(RowNames[i]) + - ggplot2::theme_bw() - - if ((df[1, "x"] - df[(dim(df)[1]), "x"]) > 0) { - plots[[name]] <- plots[[name]] + ggplot2::scale_x_reverse() - } - - } else { - - if (n == 1 ) { - melted <- data.frame(rowname = rep(name, m), - Var = as.numeric(scale), value = elements[[name]][i,]) - } else if (last==i){ - melted <- data.frame(rowname = rep(rownames(elements[[name]])[i], m), - Var = as.numeric(scale), value = elements[[name]][i,]) - } else {melted <- reshape2::melt(elements[[name]][i:last, ], - varnames = c("rowname", "Var")) - } - - - plots[[name]] <- ggplot2::ggplot(data = melted, ggplot2::aes(x = Var, y = value)) + - ggplot2::geom_line() + - ggplot2::facet_grid(rowname ~ ., scales = "free_y") + - ggplot2::theme(legend.position = "none") + - ggplot2::labs(x = xlab, y = name) + - ggplot2::ggtitle(label = main) + - ggplot2::theme_bw() - - if ((melted[1, "Var"] - melted[(dim(melted)[1]), "Var"]) > 0) { - plots[[name]] <- plots[[name]] + ggplot2::scale_x_reverse() - } - } - } - - if (subtype == "stacked") { - do.call(gridExtra::grid.arrange, c(plots, list(nrow = nrow, ncol = ncol))) - } - i <- last + 1 - } - } else if (subtype %in% c("together", "diffmean", "diffmedian", "diffwith")) { - - # TOGHETER or DIFFMEAN or DIFFMEDIAN or DIFFWITH =============== - - rainbow_colors <- grDevices::rainbow(n) - - if (createWindow) { - grDevices::dev.new(noRStudioGD = TRUE) - } - graphics::par(mfrow = c(nrow, ncol)) - - plots <- list() - - # Loop for Re, Im, Mod and Arg - for (name in names(elements)) { - # Get this part of the signal - element <- elements[[name]] - - # Express the signal according to a reference if asked by `subtype' - if (subtype == "diffmean") { - element <- sweep(element, MARGIN = 2, colMeans(element), `-`) - } else if (subtype == "diffmedian") { - element <- sweep(element, MARGIN = 2, matrixStats::colMedians(element), `-`) - } else if (subtype == "diffwith") { - element <- sweep(element, MARGIN = 2, element[row, ], `-`) - if (row == 1 & n > 1) { - # Since we use plot on the first row and lines on the following, the y - # scale is calculated at the first row so if the first row is all 0, it - # causes problems - tmp <- element[1, ] - element[1, ] <- element[2, ] - element[2, ] <- tmp - } - } - - - melted <- reshape2::melt(elements[[name]], varnames = c("rowname", "Var")) - - - plots[[name]] <- ggplot2::ggplot(melted, ggplot2::aes(x = Var, - y = value, group = rowname, colour = rowname)) + ggplot2::geom_line() + - ggplot2::labs(x = xlab, y = name) + ggplot2::scale_colour_discrete(name = NULL) + - ggplot2::ggtitle(main) - - if ((melted[1, "Var"] - melted[(dim(melted)[1]), "Var"]) > - 0) { - plots[[name]] <- plots[[name]] + ggplot2::scale_x_reverse() - } - - do.call(gridExtra::grid.arrange, c(plots, list(nrow = nrow, - ncol = ncol))) - } - } - - -} diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/Int_Funct.R --- a/nmr_preprocessing/Int_Funct.R Tue May 23 03:32:51 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,236 +0,0 @@ -beginTreatment <- function(name, Signal_data = NULL, Signal_info = NULL, - force.real = FALSE) { - - cat("Begin", name, "\n") - - - # Formatting the Signal_data and Signal_info ----------------------- - - vec <- is.vector(Signal_data) - if (vec) { - Signal_data <- vec2mat(Signal_data) - } - if (is.vector(Signal_info)) { - Signal_info <- vec2mat(Signal_info) - } - if (!is.null(Signal_data)) { - if (!is.matrix(Signal_data)) { - stop("Signal_data is not a matrix.") - } - if (!is.complex(Signal_data) && !is.numeric(Signal_data)) { - stop("Signal_data contains non-numerical values.") - } - } - if (!is.null(Signal_info) && !is.matrix(Signal_info)) { - stop("Signal_info is not a matrix.") - } - - - Original_data <- Signal_data - - # Extract the real part of the spectrum --------------------------- - - if (force.real) { - if (is.complex(Signal_data)) { - Signal_data <- Re(Signal_data) - } else { - # The signal is numeric Im(Signal_data) is zero anyway so let's avoid - # using complex(real=...,imaginary=0) which would give a complex signal - # in endTreatment() - force.real <- FALSE - } - } - - - # Return the formatted data and metadata entries -------------------- - - return(list(start = proc.time(), vec = vec, force.real = force.real, - Original_data = Original_data, Signal_data = Signal_data, Signal_info = Signal_info)) -} - -binarySearch <- function(a, target, lower = TRUE) { - # search the index i in a such that a[i] == target - # if it doesn't exists and lower, it searches the closer a[i] such that a[i] < target - # if !lower, it seraches the closer a[i] such that a[i] > target - # a should be monotone but can be increasing or decreasing - - # if a is increasing INVARIANT: a[amin] < target < a[amax] - N <- length(a) - if ((a[N] - target) * (a[N] - a[1]) <= 0) { - return(N) - } - if ((a[1] - target) * (a[N] - a[1]) >= 0) { - return(1) - } - amin <- 1 - amax <- N - while (amin + 1 < amax) { - amid <- floor((amin + amax)/2) - if ((a[amid] - target) * (a[amax] - a[amid]) < 0) { - amin <- amid - } else if ((a[amid] - target) * (a[amax] - a[amid]) > 0) { - amax <- amid - } else { - # a[amid] == a[amax] or a[amid] == target In both cases, a[amid] == - # target - return(amid) - } - } - if (xor(lower, a[amin] > a[amax])) { - # (lower && a[amin] < a[amax]) || (!lower && a[min] > a[max]) - # If increasing and we want the lower, we take amin - # If decreasing and we want the bigger, we take amin too - return(amin) - } else { - return(amax) - } -} - -checkArg <- function(arg, checks, can.be.null=FALSE) { - check.list <- list(bool=c(is.logical, "a boolean"), - int =c(function(x){x%%1==0}, "an integer"), - num =c(is.numeric, "a numeric"), - str =c(is.character, "a string"), - pos =c(function(x){x>0}, "positive"), - pos0=c(function(x){x>=0}, "positive or zero"), - l1 =c(function(x){length(x)==1}, "of length 1") - ) - if (is.null(arg)) { - if (!can.be.null) { - stop(deparse(substitute(arg)), " is null.") - } - } else { - if (is.matrix(arg)) { - stop(deparse(substitute(arg)), " is not scalar.") - } - for (c in checks) { - if (!check.list[[c]][[1]](arg)) { - stop(deparse(substitute(arg)), " is not ", check.list[[c]][[2]], ".") - } - } - } -} - -endTreatment <- function(name, begin_info, Signal_data) { - - # begin_info: object outputted from beginTreatment - - - # Formatting the entries and printing process time ----------------------- - end_time <- proc.time() # record it as soon as possible - start_time <- begin_info[["start"]] - delta_time <- end_time - start_time - delta <- delta_time[] - cat("End", name, "\n") - cat("It lasted", round(delta["user.self"], 3), "s user time,", round(delta["sys.self"],3), - "s system time and", round(delta["elapsed"], 3), "s elapsed time.\n") - - - if (begin_info[["force.real"]]) { - # The imaginary part is left untouched - i <- complex(real = 0, imaginary = 1) - Signal_data <- Signal_data + i * Im(begin_info[["Original_data"]]) - } - - if (begin_info[["vec"]]) { - Signal_data <- Signal_data[1, ] - } - - # Return the formatted data and metadata entries -------------------- - return(Signal_data) -} - -Interpol <- function(t, y) { - # y: sample - # t : warping function - - m <- length(y) - # t <= m-1 - # because if t > m-1, y[ti+1] will be NA when we compute g - valid <- 1 <= t & t <= m-1 # FIXME it was '<' in Bubble v2 - s <- (1:m)[valid] - ti <- floor(t[s]) - tr <- t[s] - ti - g <- y[ti + 1] - y[ti] - f <- y[ti] + tr * g - list(f=f, s=s, g=g) -} - -vec2mat <- function(vec) { - - return(matrix(vec, nrow = 1, dimnames = list(c(1), names(vec)))) - -} - -getArg <- function(arg, info, argname, can.be.absent=FALSE) { - if (is.null(arg)) { - start <- paste("impossible to get argument", argname, "it was not given directly and"); - if (!is.matrix(info)) { - stop(paste(start, "the info matrix was not given")) - } - if (!(argname %in% colnames(info))) { - if (can.be.absent) { - return(NULL) - } else { - stop(paste(start, "is not in the info matrix")) - } - } - if (nrow(info) < 1) { - stop(paste(start, "the info matrix has no row")) - } - arg <- info[1,argname] - if (is.na(arg)) { - stop(paste(start, "it is NA in the info matrix")) - } - } - return(arg) -} - -binarySearch <- function(a, target, lower = TRUE) { - # search the index i in a such that a[i] == target - # if it doesn't exists and lower, it searches the closer a[i] such that a[i] < target - # if !lower, it seraches the closer a[i] such that a[i] > target - # a should be monotone but can be increasing or decreasing - - # if a is increasing INVARIANT: a[amin] < target < a[amax] - N <- length(a) - if ((a[N] - target) * (a[N] - a[1]) <= 0) { - return(N) - } - if ((a[1] - target) * (a[N] - a[1]) >= 0) { - return(1) - } - amin <- 1 - amax <- N - while (amin + 1 < amax) { - amid <- floor((amin + amax)/2) - if ((a[amid] - target) * (a[amax] - a[amid]) < 0) { - amin <- amid - } else if ((a[amid] - target) * (a[amax] - a[amid]) > 0) { - amax <- amid - } else { - # a[amid] == a[amax] or a[amid] == target In both cases, a[amid] == - # target - return(amid) - } - } - if (xor(lower, a[amin] > a[amax])) { - # (lower && a[amin] < a[amax]) || (!lower && a[min] > a[max]) - # If increasing and we want the lower, we take amin - # If decreasing and we want the bigger, we take amin too - return(amin) - } else { - return(amax) - } -} - -# returns the discrete borders of the interval for a numeric vector a - -indexInterval <- function (a, from, to, inclusive=TRUE) { - # If inclusive and from <= to, we need to take the lower - # If not inclusive and from > to, we need to take the lower too - lowerFrom <- xor(inclusive, from > to) - fromIndex <- binarySearch(a, from, lowerFrom) - toIndex <- binarySearch(a, to, !lowerFrom) - return(fromIndex:toIndex) -} diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/NmrPreprocessing_script.R --- a/nmr_preprocessing/NmrPreprocessing_script.R Tue May 23 03:32:51 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,1162 +0,0 @@ -## ========================== -# Internal functions -## ========================== - -# beginTreatment -beginTreatment <- function(name, Signal_data = NULL, Signal_info = NULL, - force.real = FALSE) { - - cat("Begin", name, "\n") - - - # Formatting the Signal_data and Signal_info ----------------------- - - vec <- is.vector(Signal_data) - if (vec) { - Signal_data <- vec2mat(Signal_data) - } - if (is.vector(Signal_info)) { - Signal_info <- vec2mat(Signal_info) - } - if (!is.null(Signal_data)) { - if (!is.matrix(Signal_data)) { - stop("Signal_data is not a matrix.") - } - if (!is.complex(Signal_data) && !is.numeric(Signal_data)) { - stop("Signal_data contains non-numerical values.") - } - } - if (!is.null(Signal_info) && !is.matrix(Signal_info)) { - stop("Signal_info is not a matrix.") - } - - - Original_data <- Signal_data - - # Extract the real part of the spectrum --------------------------- - - if (force.real) { - if (is.complex(Signal_data)) { - Signal_data <- Re(Signal_data) - } else { - # The signal is numeric Im(Signal_data) is zero anyway so let's avoid - # using complex(real=...,imaginary=0) which would give a complex signal - # in endTreatment() - force.real <- FALSE - } - } - - - # Return the formatted data and metadata entries -------------------- - - return(list(start = proc.time(), vec = vec, force.real = force.real, - Original_data = Original_data, Signal_data = Signal_data, Signal_info = Signal_info)) -} - -# endTreatment -endTreatment <- function(name, begin_info, Signal_data) { - - # begin_info: object outputted from beginTreatment - - - # Formatting the entries and printing process time ----------------------- - end_time <- proc.time() # record it as soon as possible - start_time <- begin_info[["start"]] - delta_time <- end_time - start_time - delta <- delta_time[] - cat("End", name, "\n") - cat("It lasted", round(delta["user.self"], 3), "s user time,", round(delta["sys.self"],3), - "s system time and", round(delta["elapsed"], 3), "s elapsed time.\n") - - - if (begin_info[["force.real"]]) { - # The imaginary part is left untouched - i <- complex(real = 0, imaginary = 1) - Signal_data <- Signal_data + i * Im(begin_info[["Original_data"]]) - } - - if (begin_info[["vec"]]) { - Signal_data <- Signal_data[1, ] - } - - # Return the formatted data and metadata entries -------------------- - return(Signal_data) -} - -# checkArg -checkArg <- function(arg, checks, can.be.null=FALSE) { - check.list <- list(bool=c(is.logical, "a boolean"), - int =c(function(x){x%%1==0}, "an integer"), - num =c(is.numeric, "a numeric"), - str =c(is.character, "a string"), - pos =c(function(x){x>0}, "positive"), - pos0=c(function(x){x>=0}, "positive or zero"), - l1 =c(function(x){length(x)==1}, "of length 1") - ) - if (is.null(arg)) { - if (!can.be.null) { - stop(deparse(substitute(arg)), " is null.") - } - } else { - if (is.matrix(arg)) { - stop(deparse(substitute(arg)), " is not scalar.") - } - for (c in checks) { - if (!check.list[[c]][[1]](arg)) { - stop(deparse(substitute(arg)), " is not ", check.list[[c]][[2]], ".") - } - } - } -} - -# getArg -getArg <- function(arg, info, argname, can.be.absent=FALSE) { - if (is.null(arg)) { - start <- paste("impossible to get argument", argname, "it was not given directly and"); - if (!is.matrix(info)) { - stop(paste(start, "the info matrix was not given")) - } - if (!(argname %in% colnames(info))) { - if (can.be.absent) { - return(NULL) - } else { - stop(paste(start, "is not in the info matrix")) - } - } - if (nrow(info) < 1) { - stop(paste(start, "the info matrix has no row")) - } - arg <- info[1,argname] - if (is.na(arg)) { - stop(paste(start, "it is NA in the info matrix")) - } - } - return(arg) -} - -# binarySearch -binarySearch <- function(a, target, lower = TRUE) { - # search the index i in a such that a[i] == target - # if it doesn't exists and lower, it searches the closer a[i] such that a[i] < target - # if !lower, it seraches the closer a[i] such that a[i] > target - # a should be monotone but can be increasing or decreasing - - # if a is increasing INVARIANT: a[amin] < target < a[amax] - N <- length(a) - if ((a[N] - target) * (a[N] - a[1]) <= 0) { - return(N) - } - if ((a[1] - target) * (a[N] - a[1]) >= 0) { - return(1) - } - amin <- 1 - amax <- N - while (amin + 1 < amax) { - amid <- floor((amin + amax)/2) - if ((a[amid] - target) * (a[amax] - a[amid]) < 0) { - amin <- amid - } else if ((a[amid] - target) * (a[amax] - a[amid]) > 0) { - amax <- amid - } else { - # a[amid] == a[amax] or a[amid] == target In both cases, a[amid] == - # target - return(amid) - } - } - if (xor(lower, a[amin] > a[amax])) { - # (lower && a[amin] < a[amax]) || (!lower && a[min] > a[max]) - # If increasing and we want the lower, we take amin - # If decreasing and we want the bigger, we take amin too - return(amin) - } else { - return(amax) - } -} - -# Interpol -Interpol <- function(t, y) { - # y: sample - # t : warping function - - m <- length(y) - # t <= m-1 - # because if t > m-1, y[ti+1] will be NA when we compute g - valid <- 1 <= t & t <= m-1 # FIXME it was '<' in Bubble v2 - s <- (1:m)[valid] - ti <- floor(t[s]) - tr <- t[s] - ti - g <- y[ti + 1] - y[ti] - f <- y[ti] + tr * g - list(f=f, s=s, g=g) -} - -# vec2mat -vec2mat <- function(vec) { - - return(matrix(vec, nrow = 1, dimnames = list(c(1), names(vec)))) - -} - -# binarySearch -binarySearch <- function(a, target, lower = TRUE) { - # search the index i in a such that a[i] == target - # if it doesn't exists and lower, it searches the closer a[i] such that a[i] < target - # if !lower, it seraches the closer a[i] such that a[i] > target - # a should be monotone but can be increasing or decreasing - - # if a is increasing INVARIANT: a[amin] < target < a[amax] - N <- length(a) - if ((a[N] - target) * (a[N] - a[1]) <= 0) { - return(N) - } - if ((a[1] - target) * (a[N] - a[1]) >= 0) { - return(1) - } - amin <- 1 - amax <- N - while (amin + 1 < amax) { - amid <- floor((amin + amax)/2) - if ((a[amid] - target) * (a[amax] - a[amid]) < 0) { - amin <- amid - } else if ((a[amid] - target) * (a[amax] - a[amid]) > 0) { - amax <- amid - } else { - # a[amid] == a[amax] or a[amid] == target In both cases, a[amid] == - # target - return(amid) - } - } - if (xor(lower, a[amin] > a[amax])) { - # (lower && a[amin] < a[amax]) || (!lower && a[min] > a[max]) - # If increasing and we want the lower, we take amin - # If decreasing and we want the bigger, we take amin too - return(amin) - } else { - return(amax) - } -} - - -# indexInterval -indexInterval <- function (a, from, to, inclusive=TRUE) { - # If inclusive and from <= to, we need to take the lower - # If not inclusive and from > to, we need to take the lower too - lowerFrom <- xor(inclusive, from > to) - fromIndex <- binarySearch(a, from, lowerFrom) - toIndex <- binarySearch(a, to, !lowerFrom) - return(fromIndex:toIndex) -} - - - -## ========================== -# FirstOrderPhaseCorrection -## ========================== -FirstOrderPhaseCorrection <- function(Fid_data, Fid_info = NULL, group_delay = NULL) { - - # Data initialisation and checks ---------------------------------------------- - - begin_info <- beginTreatment("FirstOrderPhaseCorrection", Fid_data, Fid_info) - Fid_data <- begin_info[["Signal_data"]] - Fid_info <- begin_info[["Signal_info"]] - checkArg(group_delay, c("num", "pos0"), can.be.null = TRUE) - # if Fid_info and group_delay are NULL, getArg will generate an error - - group_delay <- getArg(group_delay, Fid_info, "GRPDLY", can.be.absent = TRUE) - - if (is.null(group_delay)) { - - # See DetermineBrukerDigitalFilter.m in matNMR MATLAB library - group_delay_matrix <- matrix(c(44.75, 46, 46.311, 33.5, 36.5, 36.53, 66.625, - 48, 47.87, 59.0833, 50.1667, 50.229, 68.5625, 53.25, 53.289, 60.375, - 69.5, 69.551, 69.5313, 72.25, 71.6, 61.0208, 70.1667, 70.184, 70.0156, - 72.75, 72.138, 61.3438, 70.5, 70.528, 70.2578, 73, 72.348, 61.5052, 70.6667, - 70.7, 70.3789, 72.5, 72.524, 61.5859, 71.3333, NA, 70.4395, 72.25, NA, - 61.6263, 71.6667, NA, 70.4697, 72.125, NA, 61.6465, 71.8333, NA, 70.4849, - 72.0625, NA, 61.6566, 71.9167, NA, 70.4924, 72.0313, NA), nrow = 21, - ncol = 3, byrow = TRUE, dimnames = list(c(2, 3, 4, 6, 8, 12, 16, 24, - 32, 48, 64, 96, 128, 192, 256, 384, 512, 768, 1024, 1536, 2048), - c(10, 11, 12))) - decim <- Fid_info[1, "DECIM"] - dspfvs <- Fid_info[1, "DSPFVS"] - if (!(toString(decim) %in% rownames(group_delay_matrix))) { - stop(paste("Invalid DECIM", decim, "it should be one of", rownames(group_delay_matrix))) - } - if (!(toString(dspfvs) %in% colnames(group_delay_matrix))) { - stop(paste("Invalid DSPFVS", dspfvs, "it should be one of", colnames(group_delay_matrix))) - } - group_delay <- group_delay_matrix[toString(decim), toString(dspfvs)] - if (is.na(group_delay)) { - stop(paste("Invalid DECIM", decim, "for DSPFVS", dspfvs)) - } - } - m <- ncol(Fid_data) - - - # FirstOrderPhaseCorrection ---------------------------------------------- - - # We do the shifting in the Fourier domain because the shift can be non-integer. - # That way we automatically have the circular behaviour of the shift and the - # interpolation if it is non-integer. - - Spectrum <- t(stats::mvfft(t(Fid_data)))/m - Omega <- (0:(m - 1))/m - i <- complex(real = 0, imaginary = 1) - Spectrum <- sweep(Spectrum, MARGIN = 2, exp(i * group_delay * 2 * pi * Omega), `*`) - Fid_data <- t(stats::mvfft(t(Spectrum), inverse = TRUE)) - - # Data finalisation ---------------------------------------------- - - return(endTreatment("FirstOrderPhaseCorrection", begin_info, Fid_data)) -} - - - -## ========================== -# SolventSuppression -## ========================== -SolventSuppression <- function(Fid_data, lambda.ss = 1e+06, ptw.ss = TRUE, - plotSolvent = F, returnSolvent = F) { - - # Data initialisation and checks ---------------------------------------------- - - begin_info <- beginTreatment("SolventSuppression", Fid_data) - Fid_data <- begin_info[["Signal_data"]] - checkArg(ptw.ss, c("bool")) - checkArg(lambda.ss, c("num", "pos0")) - - - # difsm function definition for the smoother ----------------------------------- - - if (ptw.ss) { - # Use of the function in ptw that smoothes signals with a finite difference - # penalty of order 2 - difsm <- ptw::difsm - } else { - # Or manual implementation based on sparse matrices for large data series (cf. - # Eilers, 2003. 'A perfect smoother') - difsm <- function(y, d = 2, lambda) { - - m <- length(y) - # Sparse identity matrix m x m - E <- Matrix::Diagonal(m) - D <- Matrix::diff(E, differences = d) - A <- E + lambda.ss * Matrix::t(D) %*% D - # base::chol does not take into account that A is sparse and is extremely slow - C <- Matrix::chol(A) - x <- Matrix::solve(C, Matrix::solve(Matrix::t(C), y)) - return(as.numeric(x)) - } - } - - # Solvent Suppression ---------------------------------------------- - - n <- dim(Fid_data)[1] - if (returnSolvent) { - SolventRe <- Fid_data - SolventIm <- Fid_data - } - for (i in 1:n) { - FidRe <- Re(Fid_data[i, ]) - FidIm <- Im(Fid_data[i, ]) - solventRe <- difsm(FidRe, lambda = lambda.ss) - solventIm <- difsm(FidIm, lambda = lambda.ss) - - if (plotSolvent) { - m <- length(FidRe) - graphics::plot(1:m, FidRe, type = "l", col = "red") - graphics::lines(1:m, solventRe, type = "l", col = "blue") - graphics::plot(1:m, FidIm, type = "l", col = "red") - graphics::lines(1:m, solventIm, type = "l", col = "blue") - } - FidRe <- FidRe - solventRe - FidIm <- FidIm - solventIm - Fid_data[i, ] <- complex(real = FidRe, imaginary = FidIm) - if (returnSolvent) { - SolventRe[i, ] <- solventRe - SolventIm[i, ] <- solventIm - } - } - - - # Data finalisation ---------------------------------------------- - - Fid_data <- endTreatment("SolventSuppression", begin_info, Fid_data) - if (returnSolvent) { - return(list(Fid_data = Fid_data, SolventRe = Re(SolventRe), SolventIm = Im(SolventIm))) - } else { - return(Fid_data) - } -} - - - - - -## ========================== -# Apodization -# ============================= -Apodization <- function(Fid_data, Fid_info = NULL, DT = NULL, - type.apod = c("exp","cos2", "blockexp", "blockcos2", - "gauss", "hanning", "hamming"), phase = 0, rectRatio = 1/2, - gaussLB = 1, expLB = 1, plotWindow = F, returnFactor = F) { - - # Data initialisation and checks ---------------------------------------------- - begin_info <- beginTreatment("Apodization", Fid_data, Fid_info) - Fid_data <- begin_info[["Signal_data"]] - Fid_info <- begin_info[["Signal_info"]] - # Data check - type.apod <- match.arg(type.apod) - checkArg(DT, c("num", "pos"), can.be.null = TRUE) - checkArg(phase, c("num")) - - # Apodization ---------------------------------------------- - DT <- getArg(DT, Fid_info, "DT") # Dwell Time - m <- ncol(Fid_data) - t <- (1:m) * DT # Time - rectSize <- ceiling(rectRatio * m) - gaussLB <- (gaussLB/(sqrt(8 * log(2)))) - # Define the types of apodization: - switch(type.apod, exp = { - # exponential - Factor <- exp(-expLB * t) - }, cos2 = { - # cos^2 - c <- cos((1:m) * pi/(2 * m) - phase * pi/2) - Factor <- c * c - }, blockexp = { - # block and exponential - Factor <- c(rep.int(1, rectSize), rep.int(0, m - rectSize)) - # | rectSize | 1 ___________ | \ 0 \____ - Factor[(rectSize + 1):m] <- exp(-expLB * t[1:(m - rectSize)]) - }, blockcos2 = { - # block and cos^2 - Factor <- c(rep.int(1, rectSize), rep.int(0, m - rectSize)) - c <- cos((1:(m - rectSize)) * pi/(2 * (m - rectSize))) - Factor[(rectSize + 1):m] <- c * c - }, gauss = { - # gaussian - Factor <- exp(-(gaussLB * t)^2/2) - Factor <- Factor/max(Factor) - }, hanning = { - # Hanning - Factor <- 0.5 + 0.5 * cos((1:m) * pi/m - phase * pi) - }, hamming = { - # Hamming - Factor <- 0.54 + 0.46 * cos((1:m) * pi/m - phase * pi) - }) - if (plotWindow) { - graphics::plot(1:m, Factor, "l") - # dev.off() # device independent, it is the responsability of the - # caller to do it - } - # Apply the apodization factor on the spectra - Fid_data <- sweep(Fid_data, MARGIN = 2, Factor, `*`) - - # Data finalisation ---------------------------------------------- - Fid_data <- endTreatment("Apodization", begin_info, Fid_data) - if (returnFactor) { - return(list(Fid_data = Fid_data, Factor = Factor)) - } else { - return(Fid_data) - } -} - - -## ==================================================== -# FourierTransform -## ==================================================== - - -# fftshift1D2D -fftshift1D2D <- function(x) { - vec <- F - if (is.vector(x)) { - x <- vec2mat(x) - vec <- T - } - m <- dim(x)[2] - p <- ceiling(m/2) - new_index <- c((p + 1):m, 1:p) - y <- x[, new_index, drop = vec] -} - -# FourierTransform -FourierTransform <- function(Fid_data, Fid_info = NULL, SW_h = NULL, SW = NULL, O1 = NULL, reverse.axis = TRUE) { - - # Data initialisation and checks ---------------------------------------------- - begin_info <- beginTreatment("FourierTransform", Fid_data, Fid_info) - Fid_data <- begin_info[["Signal_data"]] - Fid_info <- begin_info[["Signal_info"]] - - m <- ncol(Fid_data) - n <- nrow(Fid_data) - - if (is.null(SW_h)) { - SW_h <- getArg(SW_h, Fid_info, "SW_h") - } - - if (is.null(SW)) { - SW <- getArg(SW, Fid_info, "SW") # Sweep Width in ppm (semi frequency scale in ppm) - } - - if (is.null(O1)) { - O1 <- getArg(O1, Fid_info, "O1") - } - - - checkArg(reverse.axis, c("bool")) - - # Fourier Transformation ---------------------------------------------- - # mvfft does the unnormalized fourier transform (see ?mvfft), so we need divide - # by m. It does not matter a lot in our case since the spectrum will be - # normalized. - - # FT - RawSpect_data <- fftshift1D2D(t(stats::mvfft(t(Fid_data))))/m - # recover the frequencies values - f <- ((0:(m - 1)) - floor(m/2)) * Fid_info[1, "SW_h"]/m - - if(reverse.axis == TRUE) { - revind <- rev(1:m) - RawSpect_data <- RawSpect_data[,revind] # reverse the spectrum - } - - colnames(RawSpect_data) <- f - - - # PPM conversion ---------------------------------------------- - - # The Sweep Width has to be the same since the column names are the same - - ppmInterval <- SW/m # FIXME divide by two ?? - - O1index <- binarySearch(a = f, target = O1, lower = TRUE) - - end <- O1index - m - start <- O1index -1 - ppmScale <- (start:end) * ppmInterval - RawSpect_data <- matrix(RawSpect_data, nrow = n, ncol = -(end - start) + 1, dimnames = - list(rownames(RawSpect_data), ppmScale)) - - - # Data finalisation ---------------------------------------------- - return(endTreatment("FourierTransform", begin_info, RawSpect_data)) -} - - - -## ==================================================== -# InternalReferencing -## ==================================================== - -InternalReferencing <- function(Spectrum_data, Fid_info, method = c("max", "thres"), - range = c("near0", "all", "window"), ppm.ref = 0, - shiftHandling = c("zerofilling", "cut", "NAfilling", - "circular"), c = 2, pc = 0.02, fromto.RC = NULL, - ppm = TRUE, rowindex_graph = NULL) { - - - - # Data initialisation and checks ---------------------------------------------- - - begin_info <- beginTreatment("InternalReferencing", Spectrum_data, Fid_info) - Spectrum_data <- begin_info[["Signal_data"]] - Fid_info <- begin_info[["Signal_info"]] - - - # Check input arguments - range <- match.arg(range) - shiftHandling <- match.arg(shiftHandling) - method <- match.arg(method) - plots <- NULL - - - checkArg(ppm, c("bool")) - checkArg(unlist(fromto.RC), c("num"), can.be.null = TRUE) - checkArg(pc, c("num")) - checkArg(ppm.ref, c("num")) - checkArg(rowindex_graph, "num", can.be.null = TRUE) - - # fromto.RC - if (!is.null(fromto.RC)) { - diff <- diff(unlist(fromto.RC))[1:length(diff(unlist(fromto.RC)))%%2 !=0] - for (i in 1:length(diff)) { - if (ppm == TRUE & diff[i] >= 0) { - stop(paste("Invalid region removal because from <= to in ppm")) - } else if (ppm == FALSE & diff[i] <= 0) {stop(paste("Invalid region removal because from >= to in column index"))} - } - } - - - - # findTMSPpeak function ---------------------------------------------- - findTMSPpeak <- function(ft, c = 2) { - ft <- Re(ft) # extraction de la partie réelle - N <- length(ft) - thres <- 99999 - i <- 1000 # Start at point 1000 to find the peak - vect <- ft[1:i] - while (vect[i] <= (c * thres)) { - cumsd <- stats::sd(vect) - cummean <- mean(vect) - thres <- cummean + 3 * cumsd - i <- i + 1 - vect <- ft[1:i] - } - v <- i - if (is.na(v)) { - warning("No peak found, need to lower the threshold.") - return(NA) - } else { - # recherche dans les 1% de points suivants du max trouve pour etre au sommet du - # pic - d <- which.max(ft[v:(v + N * 0.01)]) - new.peak <- v + d - 1 # nouveau pic du TMSP si d > 0 - - if (names(which.max(ft[v:(v + N * 0.01)])) != names(which.max(ft[v:(v + N * 0.03)]))) { - # recherche dans les 3% de points suivants du max trouve pour eviter un faux - # positif - warning("the TMSP peak might be located further away, increase the threshold to check.") - } - return(new.peak) - } - } - - - # Apply the method ('thres' or 'max') on spectra - # ---------------------------------------------- - - n <- nrow(Spectrum_data) - m <- ncol(Spectrum_data) - - # The Sweep Width has to be the same since the column names are the same - SW <- Fid_info[1, "SW"] # Sweep Width in ppm (semi frequency scale in ppm) - ppmInterval <- SW/m # FIXME divide by two ?? - - if (range == "all") { - Data <- Spectrum_data - } else { - if (range == "near0") { - fromto.RC <- list(c(-(SW * pc)/2, (SW * pc)/2)) # automatic fromto values in ppm - } - - # if ppm == TRUE, then fromto is in the colnames values, else, in the column - # index - if (ppm == TRUE) { - colindex <- as.numeric(colnames(Spectrum_data)) - } else { - colindex <- 1:m - } - - - Int <- vector("list", length(fromto.RC)) - for (i in 1:length(fromto.RC)) { - Int[[i]] <- indexInterval(colindex, from = fromto.RC[[i]][1], - to = fromto.RC[[i]][2], inclusive = TRUE) - } - - vector <- rep(0, m) - vector[unlist(Int)] <- 1 - if (n > 1) { - Data <- sweep(Spectrum_data, MARGIN = 2, FUN = "*", vector) # Cropped_Spectrum - } else { - Data <- Spectrum_data * vector - } # Cropped_Spectrum - } - - - if (method == "thres") { - TMSPpeaks <- apply(Data, 1, findTMSPpeak) - } else { - TMSPpeaks <- apply(abs(Re(Data)), 1, which.max) - } - - # TMSPpeaks is an column index - maxpeak <- max(TMSPpeaks) - minpeak <- min(TMSPpeaks) - - - - # Shift spectra according to the TMSPpeaks found -------------------------------- - # Depends on the shiftHandling - - if (shiftHandling %in% c("zerofilling", "NAfilling", "cut")) { - fill <- NA - if (shiftHandling == "zerofilling") { - fill <- 0 - } - - start <- maxpeak - 1 - end <- minpeak - m - - ppmScale <- (start:end) * ppmInterval - - # check if ppm.ref in is the ppmScale interval - if(ppm.ref < min(ppmScale) | ppm.ref > max(ppmScale)) { - warning("ppm.ref = ", ppm.ref, " is not in the ppm interval [", - round(min(ppmScale),2), ",", round(max(ppmScale),2), "], and is set to its default value 0") - ppm.ref = 0 - } - - ppmScale <- ppmScale + ppm.ref - - Spectrum_data_calib <- matrix(fill, nrow = n, ncol = -(end - start) + 1, - dimnames = list(rownames(Spectrum_data), ppmScale)) - for (i in 1:n) { - shift <- (1 - TMSPpeaks[i]) + start - Spectrum_data_calib[i, (1 + shift):(m + shift)] <- Spectrum_data[i, ] - } - - if (shiftHandling == "cut") { - Spectrum_data_calib = as.matrix(stats::na.omit(t(Spectrum_data_calib))) - Spectrum_data_calib = t(Spectrum_data_calib) - base::attr(Spectrum_data_calib, "na.action") <- NULL - } - - - } else { - # circular - start <- 1 - maxpeak - end <- m - maxpeak - - ppmScale <- (start:end) * ppmInterval - - # check if ppm.ref in is the ppmScale interval - if(ppm.ref < min(ppmScale) | ppm.ref > max(ppmScale)) { - warning("ppm.ref = ", ppm.ref, " is not in the ppm interval [", - round(min(ppmScale),2), ",", round(max(ppmScale),2), "], and is set to its default value 0") - ppm.ref = 0 - } - ppmScale <- ppmScale + ppm.ref - - Spectrum_data_calib <- matrix(nrow=n, ncol=end-start+1, - dimnames=list(rownames(Spectrum_data), ppmScale)) - for (i in 1:n) { - shift <- (maxpeak-TMSPpeaks[i]) - Spectrum_data_calib[i,(1+shift):m] <- Spectrum_data[i,1:(m-shift)] - if (shift > 0) { - Spectrum_data_calib[i,1:shift] <- Spectrum_data[i,(m-shift+1):m] - } - } - } - - - - - # Plot of the spectra --------------------------------------------------- - - ppm = xstart = value = xend = Legend = NULL # only for R CMD check - - - # with the search zone for TMSP and the location of the peaks just found - if (!is.null(rowindex_graph)) { - - if (range == "window") { - if (ppm == TRUE) { - fromto <- fromto.RC - } else { - fromto <- list() - idcol <- as.numeric(colnames(Spectrum_data)) - for (i in 1:length(fromto.RC)) { - fromto[[i]] <- as.numeric(colnames(Spectrum_data))[fromto.RC[[i]]] - } - } - } else { - fromto <- fromto.RC - } - - # TMSPloc in ppm - TMSPloc <- as.numeric(colnames(Spectrum_data))[TMSPpeaks[rowindex_graph]] - - # num plot per window - num.stacked <- 6 - - # rectanglar bands of color for the search zone - rects <- data.frame(xstart = sapply(fromto, function(x) x[[1]]), - xend = sapply(fromto, function(x) x[[2]]), - Legend = "TMSP search zone and location") - - # vlines for TMSP peak - addlines <- data.frame(rowname = rownames(Spectrum_data)[rowindex_graph],TMSPloc) - - nn <- length(rowindex_graph) - i <- 1 - j <- 1 - plots <- vector(mode = "list", length = ceiling(nn/num.stacked)) - - while (i <= nn) { - - last <- min(i + num.stacked - 1, nn) - - melted <- reshape2::melt(Re(Spectrum_data[i:last, ]), - varnames = c("rowname", "ppm")) - - plots[[j]] <- ggplot2::ggplot() + ggplot2::theme_bw() + - ggplot2::geom_line(data = melted, - ggplot2::aes(x = ppm, y = value)) + - ggplot2::geom_rect(data = rects, ggplot2::aes(xmin = xstart, xmax = xend, - ymin = -Inf, ymax = Inf, fill = Legend), alpha = 0.4) + - ggplot2::facet_grid(rowname ~ ., scales = "free_y") + - ggplot2::theme(legend.position = "none") + - ggplot2::geom_vline(data = addlines, ggplot2::aes(xintercept = TMSPloc), - color = "red", show.legend = TRUE) + - ggplot2::ggtitle("TMSP peak search zone and location") + - ggplot2::theme(legend.position = "top", legend.text = ggplot2::element_text()) - - - - if ((melted[1, "ppm"] - melted[(dim(melted)[1]), "ppm"]) > 0) { - plots[[j]] <- plots[[j]] + ggplot2::scale_x_reverse() - } - - i <- last + 1 - j <- j + 1 - } - - plots - } - - - # Return the results ---------------------------------------------- - Spectrum_data <- endTreatment("InternalReferencing", begin_info, Spectrum_data_calib) - - if (is.null(plots)) { - return(Spectrum_data) - } else { - return(list(Spectrum_data, plots)) - } - -} - - - -## ==================================================== -# ZeroOrderPhaseCorrection -## ==================================================== - -ZeroOrderPhaseCorrection <- function(Spectrum_data, method = c("rms", "manual", "max"), - plot_rms = NULL, returnAngle = FALSE, createWindow = TRUE, - angle = NULL, plot_spectra = FALSE, - ppm = TRUE, exclude = list(c(5.1,4.5))) { - - - # Data initialisation and checks ---------------------------------------------- - - # Entry arguments definition: - # plot_rms : graph of rms criterion returnAngle : if TRUE, returns avector of - # optimal angles createWindow : for plot_rms plots angle : If angle is not NULL, - # spectra are rotated according to the angle vector values - # plot_spectra : if TRUE, plot rotated spectra - - - - begin_info <- beginTreatment("ZeroOrderPhaseCorrection", Spectrum_data) - Spectrum_data <- begin_info[["Signal_data"]] - n <- nrow(Spectrum_data) - m <- ncol(Spectrum_data) - - rnames <- rownames(Spectrum_data) - - # Check input arguments - method <- match.arg(method) - checkArg(ppm, c("bool")) - checkArg(unlist(exclude), c("num"), can.be.null = TRUE) - - - # method in c("max", "rms") ----------------------------------------- - if (method %in% c("max", "rms")) { - # angle is found by optimization - - # rms function to be optimised - rms <- function(ang, y, meth = c("max", "rms")) { - # if (debug_plot) { graphics::abline(v=ang, col='gray60') } - roty <- y * exp(complex(real = 0, imaginary = ang)) # spectrum rotation - Rey <- Re(roty) - - if (meth == "rms") { - ReyPos <- Rey[Rey >= 0] # select positive intensities - POSss <- sum((ReyPos)^2, na.rm = TRUE) # SS for positive intensities - ss <- sum((Rey)^2, na.rm = TRUE) # SS for all intensities - return(POSss/ss) # criterion : SS for positive values / SS for all intensities - } else { - maxi <- max(Rey, na.rm = TRUE) - return(maxi) - } - } - - - # Define the interval where to search for (by defining Data) - if (is.null(exclude)) { - Data <- Spectrum_data - } else { - - # if ppm == TRUE, then fromto is in the colnames values, else, in the column - # index - if (ppm == TRUE) { - colindex <- as.numeric(colnames(Spectrum_data)) - } else { - colindex <- 1:m - } - - # Second check for the argument exclude - diff <- diff(unlist(exclude))[1:length(diff(unlist(exclude)))%%2 !=0] - for (i in 1:length(diff)) { - if (ppm == TRUE & diff[i] >= 0) { - stop(paste("Invalid region removal because from <= to in ppm")) - } else if (ppm == FALSE & diff[i] <= 0) {stop(paste("Invalid region removal because from >= to in column index"))} - } - - - Int <- vector("list", length(exclude)) - for (i in 1:length(exclude)) { - Int[[i]] <- indexInterval(colindex, from = exclude[[i]][1], - to = exclude[[i]][2], inclusive = TRUE) - } - - vector <- rep(1, m) - vector[unlist(Int)] <- 0 - if (n > 1) { - Data <- sweep(Spectrum_data, MARGIN = 2, FUN = "*", vector) # Cropped_Spectrum - } else { - Data <- Spectrum_data * vector - } # Cropped_Spectrum - } - - - # angles computation - Angle <- c() - for (k in 1:n) - { - # The function is rms is periodic (period 2pi) and it seems that there is a phase - # x such that rms is unimodal (i.e. decreasing then increasing) on the interval - # [x; x+2pi]. However, if we do the optimization for example on [x-pi; x+pi], - # instead of being decreasing then increasing, it might be increasing then - # decreasing in which case optimize, thinking it is a valley will have to choose - # between the left or the right of this hill and if it chooses wrong, it will end - # up at like x-pi while the minimum is close to x+pi. - - # Supposing that rms is unimodal, the classical 1D unimodal optimization will - # work in either [-pi;pi] or [0;2pi] (this is not easy to be convinced by that I - # agree) and we can check which one it is simply by the following trick - - f0 <- rms(0, Data[k, ],meth = method) - fpi <- rms(pi, Data[k, ], meth = method) - if (f0 < fpi) { - interval <- c(-pi, pi) - } else { - interval <- c(0, 2 * pi) - } - - # graphs of rms criteria - debug_plot <- F # rms should not plot anything now, only when called by optimize - if (!is.null(plot_rms) && rnames[k] %in% plot_rms) { - x <- seq(min(interval), max(interval), length.out = 100) - y <- rep(1, 100) - for (K in (1:100)) { - y[K] <- rms(x[K], Data[k, ], meth = method) - } - if (createWindow == TRUE) { - grDevices::dev.new(noRStudioGD = FALSE) - } - graphics::plot(x, y, main = rownames(Data)[k]) - debug_plot <- T - } - - # Best angle - best <- stats::optimize(rms, interval = interval, maximum = TRUE, - y = Data[k,], meth = method) - ang <- best[["maximum"]] - - - if (debug_plot) { - graphics::abline(v = ang, col = "black") - # grDevices::dev.off() - } - - # Spectrum rotation - Spectrum_data[k, ] <- Spectrum_data[k, ] * exp(complex(real = 0, imaginary = ang)) - Angle <- c(Angle, ang) - } - - - - - } else { - # method is "manual" ------------------------------------------------------- - # if Angle is already specified and no optimisation is needed - - if (!is.vector(angle)) { - stop("angle is not a vector") - } - - if (!is.numeric(angle)) { - stop("angle is not a numeric") - } - - if (length(angle) != n) { - stop(paste("angle has length", length(angle), "and there are", n, "spectra to rotate.")) - } - for (k in 1:n) { - Spectrum_data[k, ] <- Spectrum_data[k, ] * exp(complex(real = 0, imaginary = - angle[k])) - } - } - - - - # Draw spectra - if (plot_spectra == TRUE) { - nn <- ceiling(n/4) - i <- 1 - for (k in 1:nn) { - if (createWindow == TRUE) { - grDevices::dev.new(noRStudioGD = FALSE) - } - graphics::par(mfrow = c(4, 2)) - while (i <= n) { - last <- min(i + 4 - 1, n) - graphics::plot(Re(Spectrum_data[i, ]), type = "l", ylab = "intensity", - xlab = "Index", main = paste0(rownames(Spectrum_data)[i], " - Real part")) - graphics::plot(Im(Spectrum_data[i, ]), type = "l", ylab = "intensity", - xlab = "Index", main = paste0(rownames(Spectrum_data)[i], " - Imaginary part")) - i <- i + 1 - } - i <- last + 1 - } - } - - - # Data finalisation ---------------------------------------------- - - Spectrum_data <- endTreatment("ZeroOrderPhaseCorrection", begin_info, Spectrum_data) - if (returnAngle) { - return(list(Spectrum_data = Spectrum_data, Angle = Angle)) - } else { - return(Spectrum_data) - } -} - - - -## ==================================================== -# Baseline Correction -## ==================================================== -BaselineCorrection <- function(Spectrum_data, ptw.bc = TRUE, maxIter = 42, - lambda.bc = 1e+07, p.bc = 0.05, eps = 1e-08, - returnBaseline = F) { - - # Data initialisation ---------------------------------------------- - begin_info <- beginTreatment("BaselineCorrection", Spectrum_data, force.real = T) - Spectrum_data <- begin_info[["Signal_data"]] - p <- p.bc - lambda <- lambda.bc - n <- dim(Spectrum_data)[1] - - # Data check - checkArg(ptw.bc, c("bool")) - checkArg(maxIter, c("int", "pos")) - checkArg(lambda, c("num", "pos0")) - checkArg(p.bc, c("num", "pos0")) - checkArg(eps, c("num", "pos0")) - checkArg(returnBaseline, c("bool")) - - - - # Baseline Correction implementation definition ---------------------- - - # 2 Ways: either use the function asysm from the ptw package or by - # built-in functions - if (ptw.bc) { - asysm <- ptw::asysm - } else { - difsmw <- function(y, lambda, w, d) { - # Weighted smoothing with a finite difference penalty cf Eilers, 2003. - # (A perfect smoother) - # y: signal to be smoothed - # lambda: smoothing parameter - # w: weights (use0 zeros for missing values) - # d: order of differences in penalty (generally 2) - m <- length(y) - W <- Matrix::Diagonal(x=w) - E <- Matrix::Diagonal(m) - D <- Matrix::diff(E, differences = d) - C <- Matrix::chol(W + lambda * t(D) %*% D) - x <- Matrix::solve(C, Matrix::solve(t(C), w * y)) - return(as.numeric(x)) - - } - asysm <- function(y, lambda, p, eps) { - # Baseline estimation with asymmetric least squares - # y: signal - # lambda: smoothing parameter (generally 1e5 to 1e8) - # p: asymmetry parameter (generally 0.001) - # d: order of differences in penalty (generally 2) - # eps: 1e-8 in ptw package - m <- length(y) - w <- rep(1, m) - i <- 1 - repeat { - z <- difsmw(y, lambda, w, d = 2) - w0 <- w - w <- p * (y > z + eps | y < 0) + (1 - p) * (y <= z + eps) - if (sum(abs(w - w0)) == 0) { - break - } - i <- i + 1 - if (i > maxIter) { - warning("cannot find Baseline estimation in asysm") - break - } - } - return(z) - } - } - - # Baseline estimation ---------------------------------------------- - Baseline <- matrix(NA, nrow = nrow(Spectrum_data), ncol = ncol(Spectrum_data)) - - for (k in 1:n) { - Baseline[k, ] <- asysm(y = Spectrum_data[k, ], lambda = lambda, p = p, eps = eps) - if (F & k == 1) { - m <- ncol(Spectrum_data) - graphics::plot(1:m, Spectrum_data[k, ], type = "l", col = "red") - graphics::lines(1:m, Baseline[k, ], type = "l", col = "blue") - graphics::lines(1:m, Spectrum_data[k, ] - Baseline[k, ], type = "l", - col = "green") - } - - Spectrum_data[k, ] <- Spectrum_data[k, ] - Baseline[k, ] - } - - # Data finalisation ---------------------------------------------- - Spectrum_data <- endTreatment("BaselineCorrection", begin_info, Spectrum_data) # FIXME create removeImaginary filter ?? - - if (returnBaseline) { - return(list(Spectrum_data = Spectrum_data, Baseline = Baseline)) - } else { - return(Spectrum_data) - } -} - - - -## ==================================================== -# NegativeValuesZeroing -## ==================================================== - -NegativeValuesZeroing <- function(Spectrum_data) { - # Data initialisation and checks ---------------------------------------------- - begin_info <- beginTreatment("NegativeValuesZeroing", Spectrum_data, force.real = T) - Spectrum_data <- begin_info[["Signal_data"]] - - # NegativeValuesZeroing ---------------------------------------------- - Spectrum_data[Spectrum_data < 0] <- 0 - - # Data finalisation ---------------------------------------------- - return(endTreatment("NegativeValuesZeroing", begin_info, Spectrum_data)) -} - - -## ==================================================== -# Warping -## ==================================================== diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/NmrPreprocessing_wrapper.R --- a/nmr_preprocessing/NmrPreprocessing_wrapper.R Tue May 23 03:32:51 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,370 +0,0 @@ -#!/usr/local/public/bin/Rscript --vanilla --slave --no-site-file - -## 170116_NmrPreprocessing.R -## Manon Martin and Marie Tremblay-Franco - -##====================================================== -##====================================================== -# Preamble -##====================================================== -##====================================================== - -runExampleL <- FALSE - -##------------------------------ -## Options -##------------------------------ -strAsFacL <- options()$stringsAsFactors -options(stringsAsFactors = FALSE) - -##------------------------------ -## Libraries laoding -##------------------------------ -library(batch) -library(ptw) -library(Matrix) -library(ggplot2) -library(gridExtra) -library(reshape2) - - -# R script call -source_local <- function(fname) -{ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - source(paste(base_dir, fname, sep="/")) -} -#Import the different functions -source_local("NmrPreprocessing_script.R") -source_local("DrawFunctions.R") - -##------------------------------ -## Errors ????????????????????? -##------------------------------ - - -##------------------------------ -## Constants -##------------------------------ -topEnvC <- environment() -flagC <- "\n" - - -##------------------------------ -## Script -##------------------------------ -if(!runExampleL) - argLs <- parseCommandArgs(evaluate=FALSE) - -# log file -print(argLs[["logOut"]]) - -## Starting -cat("\nStart of 'Preprocessing' Galaxy module call: ", as.character(Sys.time()), sep = "") - - -##====================================================== -##====================================================== -## Parameters Loading -##====================================================== -##====================================================== - -# graphical inputs -FirstOPCGraph <- argLs[["FirstOPCGraph"]] -SSGraph <- argLs[["SSGraph"]] -ApodGraph <- argLs[["ApodGraph"]] -FTGraph <- argLs[["FTGraph"]] -SRGraph <- argLs[["SRGraph"]] -ZeroOPCGraph <- argLs[["ZeroOPCGraph"]] -BCGraph <- argLs[["BCGraph"]] -FinalGraph <- argLs[["FinalGraph"]] - - -# 1rst order phase correction ------------------------ - # Inputs - ## Data matrix -Fid_data0 <- read.table(argLs[["dataMatrixFid"]],header=TRUE, check.names=FALSE, sep='\t') -# Fid_data0 <- Fid_data0[,-1] -Fid_data0 <- as.matrix(Fid_data0) - - ## Samplemetadata -samplemetadataFid <- read.table(argLs[["sampleMetadataFid"]],check.names=FALSE,header=TRUE,sep="\t") -samplemetadataFid <- as.matrix(samplemetadataFid) - - -# water and solvent(s) correction ------------------------ - # Inputs -lambda <- argLs[["lambda"]] -ptwSS1 <- argLs[["ptwSS"]] -ptwSS <- FALSE -if (ptwSS1=="YES") - ptwSS <- TRUE - - -# apodization ----------------------------------------- - # Inputs -phase=0 -rectRatio=1/2 -gaussLB=1 -expLB=1 -apodization <- argLs[["apodizationMethod"]] - -if (apodization=='exp'){ - expLB <- argLs[["expLB"]] - } else if (apodization=='cos2'){ - phase <- argLs[["phase"]] - } else if (apodization=='hanning'){ - phase <- argLs[["phase"]] - } else if (apodization=='hamming'){ - phase <- argLs[["phase"]] - } else if (apodization=='blockexp'){ - rectRatio <- argLs[["rectRatio"]] - expLB <- argLs[["expLB"]] - } else if (apodization=='blockcos2'){ - rectRatio <- argLs[["rectRatio"]] - } else if (apodization=='gauss'){ - rectRatio <- argLs[["rectRatio"]] - gaussLB <- argLs[["gaussLB"]] - } - - -# Fourier transform ---------------------------------- - # Inputs - - -# Internal referencering ---------------------------------- - # Inputs -shiftTreshold = 2 # c -ppm = TRUE -shiftReferencingRangeList = NULL # fromto.RC -pctNear0 = 0.02 # pc -rowindex_graph = NULL -ppm_ref = 0 # ppm.ref - -# -# shiftReferencing <- argLs[["shiftReferencing"]] -# print(shiftReferencing) -# -# if (shiftReferencing=="YES") -# { -# - # shiftReferencingMethod <- argLs[["shiftReferencingMethod"]] - # - # if (shiftReferencingMethod == "thres") { - # shiftTreshold <- argLs[["shiftTreshold"]] - # } - - shiftReferencingRange <- argLs[["shiftReferencingRange"]] - - if (shiftReferencingRange == "near0"){ - pctNear0 <- argLs[["pctNear0"]] - } - - if (shiftReferencingRange == "window"){ - shiftReferencingRangeList <- list() - for(i in which(names(argLs)=="shiftReferencingRangeLeft")) - { - shiftReferencingRangeLeft <- argLs[[i]] - shiftReferencingRangeRight <- argLs[[i+1]] - shiftReferencingRangeList <- c(shiftReferencingRangeList,list(c(shiftReferencingRangeLeft,shiftReferencingRangeRight))) - } - } - - shiftHandling <- argLs[["shiftHandling"]] - - - -# } - - -# Zero Order Phase Correction ------------------------------- - # Inputs -plot_rms = NULL -returnAngle = FALSE -createWindow = TRUE -angle = NULL -plot_spectra = FALSE -ppm = TRUE -exclude = NULL -zeroOrderPhaseMethod <- argLs[["zeroOrderPhaseMethod"]] - -if (zeroOrderPhaseMethod=='manual'){ - angle <- argLs[["angle"]] -} - -excludeZoneZeroPhase <- argLs[["excludeZoneZeroPhase.choice"]] -if (excludeZoneZeroPhase == 'YES') { - excludeZoneZeroPhaseList <- list() - for(i in which(names(argLs)=="excludeZoneZeroPhase_left")) { - excludeZoneZeroPhaseLeft <- argLs[[i]] - excludeZoneZeroPhaseRight <- argLs[[i+1]] - excludeZoneZeroPhaseList <- c(excludeZoneZeroPhaseList,list(c(excludeZoneZeroPhaseLeft,excludeZoneZeroPhaseRight))) - } - exclude <- excludeZoneZeroPhaseList -} - - -# Baseline Correction ------------------------------- - # Inputs -ptwBc <- as.logical(argLs[["ptwBc"]]) -maxIter <- argLs[["maxIter"]] -lambdaBc <- argLs[["lambdaBc"]] -pBc <- argLs[["pBc"]] -epsilon <- argLs[["epsilon"]] - - - -# transformation of negative values ------------------------------- - # Inputs -NegativetoZero <- argLs[["NegativetoZero"]] - - - # Outputs -nomGraphe <- argLs[["graphOut"]] -dataMatrixOut <- argLs[["dataMatrixOut"]] -log <- argLs[["logOut"]] - - - -## Checking arguments -##------------------- -error.stock <- "\n" - -if(length(error.stock) > 1) - stop(error.stock) - - -##====================================================== -##====================================================== -## Computation -##====================================================== -##====================================================== - -pdf(nomGraphe, onefile = TRUE, width = 13, height = 13) - -# FirstOrderPhaseCorrection --------------------------------- -Fid_data <- FirstOrderPhaseCorrection(Fid_data0, Fid_info = samplemetadataFid, group_delay = NULL) - -if (FirstOPCGraph == "YES") { - title = "FIDs after First Order Phase Correction" - DrawSignal(Fid_data, subtype = "stacked", - ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, - xlab = "Frequency", num.stacked = 4, - main = title, createWindow=FALSE) -} - -# SolventSuppression --------------------------------- -Fid_data <- SolventSuppression(Fid_data, lambda.ss = lambda, ptw.ss = ptwSS, plotSolvent = F, returnSolvent = F) - -if (SSGraph == "YES") { - title = "FIDs after Solvent Suppression " - DrawSignal(Fid_data, subtype = "stacked", - ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, - xlab = "Frequency", num.stacked = 4, - main = title, createWindow=FALSE) -} - - -# Apodization --------------------------------- -Fid_data <- Apodization(Fid_data, Fid_info = samplemetadataFid, DT = NULL, - type.apod = apodization, phase = phase, rectRatio = rectRatio, gaussLB = gaussLB, expLB = expLB, plotWindow = F, returnFactor = F) - -if (ApodGraph == "YES") { - title = "FIDs after Apodization" - DrawSignal(Fid_data, subtype = "stacked", - ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, - xlab = "Frequency", num.stacked = 4, - main = title, createWindow=FALSE) -} - - -# FourierTransform --------------------------------- -Spectrum_data <- FourierTransform(Fid_data, Fid_info = samplemetadataFid, reverse.axis = TRUE) - - -if (FTGraph == "YES") { - title = "Fourier transformed spectra" - DrawSignal(Spectrum_data, subtype = "stacked", - ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, - xlab = "Frequency", num.stacked = 4, - main = title, createWindow=FALSE) -} - -# InternalReferencing --------------------------------- -# if (shiftReferencing=="YES") { -Spectrum_data <- InternalReferencing(Spectrum_data, samplemetadataFid, method = "max", range = shiftReferencingRange, - ppm.ref = 0, shiftHandling = shiftHandling,ppm = TRUE, - c = shiftTreshold, fromto.RC = shiftReferencingRangeList, pc = pctNear0) - -if (SRGraph == "YES") { - title = "Spectra after Shift Referencing" - DrawSignal(Spectrum_data, subtype = "stacked", - ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, - xlab = "Frequency", num.stacked = 4, - main = title, createWindow=FALSE) -} - -# } - -# ZeroOrderPhaseCorrection --------------------------------- -Spectrum_data <- ZeroOrderPhaseCorrection(Spectrum_data, method = zeroOrderPhaseMethod, - plot_rms = plot_rms, returnAngle = returnAngle, - createWindow = createWindow,angle = angle, - plot_spectra = plot_spectra, - ppm = ppm, exclude = exclude) - -if (ZeroOPCGraph == "YES") { -title = "Spectra after Zero Order Phase Correction" -DrawSignal(Spectrum_data, subtype = "stacked", - ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, - xlab = "Frequency", num.stacked = 4, - main = title, createWindow=FALSE) -} - -# BaselineCorrection --------------------------------- -Spectrum_data <- BaselineCorrection(Spectrum_data, ptw.bc = ptwBc, maxIter = maxIter, lambda.bc = lambdaBc, p.bc = pBc, eps = epsilon, returnBaseline = F) - -if (BCGraph == "YES") { -title = "Spectra after Baseline Correction" -DrawSignal(Spectrum_data, subtype = "stacked", - ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, - xlab = "Frequency", num.stacked = 4, - main = title, createWindow=FALSE) -} - - -# NegativeValuesZeroing --------------------------------- -if (NegativetoZero=="YES") { - Spectrum_data <- NegativeValuesZeroing(Spectrum_data) -} - -if (FinalGraph == "YES") { - title = "Final preprocessed spectra" - DrawSignal(Spectrum_data, subtype = "stacked", - ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, - xlab = "Frequency", num.stacked = 4, - main = title, createWindow=FALSE) -} - -invisible(dev.off()) - -##====================================================== -##====================================================== -## Saving -##====================================================== -##====================================================== - -# Data Matrix -write.table(t(Re(Spectrum_data)),file=argLs$dataMatrixOut, quote=FALSE, row.names=TRUE, sep="\t", col.names=TRUE) - - -## Ending - -cat("\nEnd of 'Preprocessing' Galaxy module call: ", as.character(Sys.time()), sep = "") - -sink() - -options(stringsAsFactors = strAsFacL) - -rm(list = ls()) diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/NmrPreprocessing_xml.xml --- a/nmr_preprocessing/NmrPreprocessing_xml.xml Tue May 23 03:32:51 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,400 +0,0 @@ - - Preprocessing of 1D NMR spectra - - - - - - - ## Wrapper - Rscript $__tool_directory__/NmrPreprocessing_wrapper.R - - ## First order phase correction - ## Graphical display - FirstOPCGraph $FirstOPCGraph - ## Data matrix of FID spectra - dataMatrixFid $dataMatrixFid - ## Sample metadata matrix - sampleMetadataFid $sampleMetadataFid - - - ## Water and / or solvents suppression - ## Smoothing parameter - lambda $lambda - ptwSS $ptwSS - ## Graphical display - SSGraph $SSGraph - - - ## Apodization - ## Graphical display - ApodGraph $ApodGraph - - apodizationMethod $apodizationMethod.method - #if $apodizationMethod.method == "exp": - ## Line broadening for the exponential window - expLB $apodizationMethod.expLB - #end if - #if $apodizationMethod.method == "cos2": - ## Phase - phase $apodizationMethod.phase - #end if - #if $apodizationMethod.method == "hanning": - ## Phase - phase $apodizationMethod.phase - #end if - #if $apodizationMethod.method == "hamming": - ## Phase - phase $apodizationMethod.phase - #end if - #if $apodizationMethod.method == "blockexp": - ## Proportion of signal in the window - rectRatio $apodizationMethod.rectRatio - expLB $apodizationMethod.expLB - #end if - #if $apodizationMethod.method == "blockcos2": - ## Proportion of signal in the window - rectRatio $apodizationMethod.rectRatio - #end if - #if $apodizationMethod.method == "gauss": - ## Line broadening for the gaussian window - gaussLB $apodizationMethod.gaussLB - #end if - - ## Fourier transform - ## Graphical display - FTGraph $FTGraph - - - ## Shift referencing - ## Graphical display - SRGraph $SRGraph - - ## Definition of the search zone - shiftReferencingRange $shiftReferencingRange.method - #if $shiftReferencingRange.method == "near0": - pctNear0 $shiftReferencingRange.pctNear0 - #end if - #if $shiftReferencingRange.method == "window": - #for $i in $shiftReferencingRange.conditions: - shiftReferencingRangeLeft ${i.shiftReferencingRangeLeft} - shiftReferencingRangeRight ${i.shiftReferencingRangeRight} - #end for - #end if - shiftHandling $shiftHandling - - - - ## Zero order phase correction - ## Graphical display - ZeroOPCGraph $ZeroOPCGraph - - zeroOrderPhaseMethod $zeroOrderPhaseMethod - - excludeZoneZeroPhase.choice ${excludeZoneZeroPhase.choice} - #if str($excludeZoneZeroPhase.choice) == "YES": - #for $i in $excludeZoneZeroPhase.conditions: - excludeZoneZeroPhase_left ${i.excludeZoneZeroPhase_left} - excludeZoneZeroPhase_right ${i.excludeZoneZeroPhase_right} - #end for - #end if - - - ## Baseline correction - ## Graphical display - BCGraph $BCGraph - ptwBc $ptwBc - maxIter $maxIter - lambdaBc $lambdaBc - pBc $pBc - epsilon $epsilon - - - ## sets negative intensities to zero - NegativetoZero $NegativetoZero - - ## final spectra - ## Graphical display - FinalGraph $FinalGraph - - - ## Outputs - dataMatrixOut $dataMatrixOut - graphOut $graphOut - logOut $logOut - - - - - - - - ## First order phase correction - - - - - - ## Water and / or solvents suppression - - - - - - - - - - - - ## Apodization - - - - - - - - - - - ## Fourier transform - - - - - - ## shift Referencing - - - - - - - - - - - - - - - - ## zero Order Phase Correction - - - - - - - - - - - - - - - - - - - - - - - - - - - ## baseline correction - - - - - - - - - - - - - - - - - ## NegativetoZero - - - - - - ## final spectra - - - - - - - - - - - - - - - -.. class:: infomark - -**Authors** Manon Martin (manon.martin@uclouvain.be) and Marie Tremblay-Franco (marie.tremblay-franco@inra.fr; Galaxy integration) - - -.. class:: infomark - -**Please cite** -Rousseau, R. (2011). Statistical contribution to the analysis of metabonomics data in 1H NMR spectroscopy (Doctoral dissertation, PhD thesis. -Institut de statistique, biostatistique et sciences actuarielles, Université catholique de Louvain, Belgium). - - -===================== -Spectra preprocessing -===================== - ------------ -Description ------------ - -These steps correspond to the following steps in the PEPS-NMR R library (https://github.com/ManonMartin/PEPSNMR): - -* Group Delay suppression (First order phase correction) -* Removal of solvent residuals signal from the FID -* Apodization to increase the Signal-to-Noise ratio of the FID -* Fourier transformation -* Shift referencing to calibrate the spectra with internal compound referencing -* Zero order phase correction -* Baseline correction -* Setting of negatives values to 0 - ----------------------- - Steps parameters ----------------------- - -**Apodization** ----------------------- - -The **types of apodization** are: - -* exp: The signal is multiplied by a decreasing exponential exp(-t/LineBroadening). - -* cos2: The signal is multiplied by the value of a cosinus squared from 0 (where its value is 1) until pi/2 (where its value is 0). - -* blockexp: The first part of the signal (described by the proportion of signal in the window) is left unchanged and the second is multiplied by exp(-t/LineBroadening) starting at value 1. - -* blockcos2: The first part is left unchanged as with blockexp and the second part is multiplied by a cosinus squared where its value starts at 1 at the end of the block and ends at 0 at the end of the signal. - -* gauss: The signal is multiplied by a gaussian window centered at the beginning of the FID and with sigma=1/LineBroadening. - -* hanning: The signal is multiplied by a hanning window : 0.5 + 0.5 cos. - -* hamming: The signal is multiplied by a hamming window : 0.54 + 0.46 cos. - - -**Shift referencing** ----------------------- - -The **searching window** can be adapted: - -* near0: the search concentrates around the 0ppm. - -* all: search accross the whole ppm axis. - -* window: the search is operated in the windows defined by the search_zone bounds. - - -**shiftHandling**: spectra can be shifted differently, we can handle misalignment of the left and right of the spectrum by different ways: - -* zerofilling: The extremities at which a spectrum is not defined are replaced by 0. It makes sense since in practice the spectrum is close to zero at the extremities. - -* NAfilling: The extremities at which a spectrum is not defined are replaced by NA. - -* circular: The spectra are shifted circularly which means that the end of a spectrum is reproduced at the beginning. - -* cut: The ppm values for which some spectra are not defined are removed. - - - -**Zero Order Phase correction** ------------------------------------ - -**Zero Order Phase correction method**: - -* rms: A positiveness criterion is applied on the spectrum with a quantile probability parameter to trim the values. - -* manual: A vector of angles are specified wth the angle argument to manually rotate the spectra. - -* max: Optimization of the maximal spectral intensity. - - -** Exclusion area(s) for the Zero order phase correction**: enables to optimize the criterion with excluded spectral window(s), by default the water region is excluded. - - -**Baseline computation** ----------------------------- -**Baseline computation method**: either use ptw (YES) or an in-house R routine (NO). - -**Smoothing parameter**: the larger it is, the smoother the estimated baseline will be. - -**Asymmetry parameter**: the smaller it is, the less the estimated baseline will try to follow peaks when it is under the spectrum and the more it will try to be under the spectrum. - - - - - - diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/ReadFids.R --- a/nmr_preprocessing/ReadFids.R Tue May 23 03:32:51 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,382 +0,0 @@ -################################################################################################ -# -# Read FIDs in Bruker format -# -# -################################################################################################ - -# ReadFid ============================================================================== -ReadFid <- function(path) { - - # Read 1D FID using Bruker XWinNMR and TopSpin format. It is inspired of the - # matNMR matlab library which deals with 2D FID and also other formats - # Read also the parameters in the acqus file - - paramFile <- file.path(path, "acqus") - # BYTEORDA: 0 -> Little Endian 1 -> Big Endian - params <- readParams(paramFile, c("TD", "BYTORDA", "DIGMOD", "DECIM", "DSPFVS", - "SW_h", "SW", "O1")) - - if (params[["DSPFVS"]] >= 20) { - # The group delay first order phase correction is given directly from version 20 - grpdly <- readParams(paramFile, c("GRPDLY")) - params[["GRPDLY"]] <- grpdly[["GRPDLY"]] - } - TD <- params[["TD"]] - endianness <- if (params$BYTORDA) - "big" else "little" - if (TD%%2 != 0) { - stop(paste("Only even numbers are allowed for size in TD because it is complex - data with the real and imaginary part for each element.", - "The TD value is in the", paramFile, "file")) - } - - # Interpret params Dwell Time, time between 2 data points in the FID - params[["DT"]] <- 1/(2 * params[["SW_h"]]) - - # Read fid - fidFile <- file.path(path, "fid") - fidOnDisk <- readBin(fidFile, what = "int", n = TD, size = 4L, endian = endianness) - - # Real size that is on disk (it should be equal to TD2, except for TopSpin/Bruker - # (which is our case) according to matNMR as just discussed - TDOnDisk <- length(fidOnDisk) - if (TDOnDisk < TD) { - warning("Size is smaller than expected, the rest is filled with zero so the size is the same for every fid") - fidGoodSize <- sapply(vector("list", length = TD), function(x) 0) - fidGoodSize[1:TDOnDisk] <- fidOnDisk - - } else if (TDOnDisk > TD) { - warning("Size is bigger than expected, the rest ignored so the size is the same for every fid") - fidGoodSize <- fidOnDisk(1:TD) - - } else { - fidGoodSize <- fidOnDisk - } - - fidRePart <- fidGoodSize[seq(from = 1, to = TD, by = 2)] - fidImPart <- fidGoodSize[seq(from = 2, to = TD, by = 2)] - fid <- complex(real = fidRePart, imaginary = fidImPart) - - return(list(fid = fid, params = params)) -} - - - - -# getDirsContainingFid ============================================================================== -getDirsContainingFid <- function(path) { - subdirs <- dir(path, full.names = TRUE) - if (length(subdirs) > 0) { - cond <- sapply(subdirs, function(x) { - content <- dir(x) - # subdirs must contain fid, acqu and acqus files - return("fid" %in% content && "acqu" %in% content && "acqus" %in% content) - }) - subdirs <- subdirs[cond] - } - return(subdirs) -} - - - - - - -# beginTreatment ============================================================================== - -beginTreatment <- function(name, Signal_data = NULL, Signal_info = NULL, - force.real = FALSE) { - - cat("Begin", name, "\n") - - - # Formatting the Signal_data and Signal_info ----------------------- - - vec <- is.vector(Signal_data) - if (vec) { - Signal_data <- vec2mat(Signal_data) - } - if (is.vector(Signal_info)) { - Signal_info <- vec2mat(Signal_info) - } - if (!is.null(Signal_data)) { - if (!is.matrix(Signal_data)) { - stop("Signal_data is not a matrix.") - } - if (!is.complex(Signal_data) && !is.numeric(Signal_data)) { - stop("Signal_data contains non-numerical values.") - } - } - if (!is.null(Signal_info) && !is.matrix(Signal_info)) { - stop("Signal_info is not a matrix.") - } - - - Original_data <- Signal_data - - # Extract the real part of the spectrum --------------------------- - - if (force.real) { - if (is.complex(Signal_data)) { - Signal_data <- Re(Signal_data) - } else { - # The signal is numeric Im(Signal_data) is zero anyway so let's avoid - # using complex(real=...,imaginary=0) which would give a complex signal - # in endTreatment() - force.real <- FALSE - } - } - - - # Return the formatted data and metadata entries -------------------- - - return(list(start = proc.time(), vec = vec, force.real = force.real, - Original_data = Original_data, Signal_data = Signal_data, Signal_info = Signal_info)) -} - - -# endTreatment ============================================================================== - -endTreatment <- function(name, begin_info, Signal_data) { - end_time = proc.time() # record it as soon as possible - start_time = begin_info[["start"]] - delta_time = end_time - start_time - delta = delta_time[] - cat("End", name, "\n") - cat("It lasted", - round(delta["user.self"], 3), "s user time,", - round(delta["sys.self"] , 3), "s system time and", - round(delta["elapsed"] , 3), "s elapsed time.\n") - if (begin_info[["force.real"]]) { - # The imaginary part is left untouched - i <- complex(real=0, imaginary=1) - Signal_data = Signal_data + i * Im(begin_info[["Original_data"]]) - } - if (begin_info[["vec"]]) { - Signal_data = Signal_data[1,] - } - return(Signal_data) -} - - -# checkArg ============================================================================== - -checkArg <- function(arg, checks, can.be.null=FALSE) { - check.list <- list(bool=c(is.logical, "a boolean"), - int =c(function(x){x%%1==0}, "an integer"), - num =c(is.numeric, "a numeric"), - str =c(is.character, "a string"), - pos =c(function(x){x>0}, "positive"), - pos0=c(function(x){x>=0}, "positive or zero"), - l1 =c(function(x){length(x)==1}, "of length 1") - ) - if (is.null(arg)) { - if (!can.be.null) { - stop(deparse(substitute(arg)), " is null.") - } - } else { - if (is.matrix(arg)) { - stop(deparse(substitute(arg)), " is not scalar.") - } - for (c in checks) { - if (!check.list[[c]][[1]](arg)) { - stop(deparse(substitute(arg)), " is not ", check.list[[c]][[2]], ".") - } - } - } -} - - -# getArg ============================================================================== - -getArg <- function(arg, info, argname, can.be.absent=FALSE) { - if (is.null(arg)) { - start <- paste("impossible to get argument", argname, "it was not given directly and"); - if (!is.matrix(info)) { - stop(paste(start, "the info matrix was not given")) - } - if (!(argname %in% colnames(info))) { - if (can.be.absent) { - return(NULL) - } else { - stop(paste(start, "is not in the info matrix")) - } - } - if (nrow(info) < 1) { - stop(paste(start, "the info matrix has no row")) - } - arg <- info[1,argname] - if (is.na(arg)) { - stop(paste(start, "it is NA in the info matrix")) - } - } - return(arg) -} - - - -# getTitle ============================================================================== - -# Get the name of the signal from the title file or fromt the name of the subdirectory -# Get the name of the signal from the title file or fromt the name of the subdirectory - -getTitle <- function(path, l, subdirs) { - title <- NULL - title_file <- file.path(file.path(file.path(path, "pdata"), "1"), "title") - if (file.exists(title_file)) { - lines <- readLines(title_file, warn = FALSE) - if (length(lines) >= 1) { - first_line <- gsub("^\\s+|\\s+$", "", lines[l]) - if (nchar(first_line) >= 1) { - title <- first_line - } else { - warning(paste("The first line of the title file is blank for directory ", - path)) - } - } else { - warning(paste("The title file is empty for directory ", path)) - } - } else { - warning(paste("Title file doesn't exists for directory ", path, "\n the repertory name is used instead")) - } - if (is.null(title)) { - if(subdirs) { - separator <- .Platform$file.sep - path_elem <- strsplit(path,separator)[[1]] - title <- paste(path_elem[length(path_elem)-1], path_elem[length(path_elem)], sep = "_") - } else{title <- basename(path)} - } - return(title) -} - - - -# readParams ============================================================================== -# Read parameter values for Fid_info in the ReadFids function - -readParams <- function(file, paramsName) { - - isDigit <- function(c) { - return(suppressWarnings(!is.na(as.numeric(c)))) - } - lines <- readLines(file) - params <- sapply(paramsName, function(x) NULL) - - for (paramName in paramsName) { - # Find the line with the parameter I add a '$' '=' in the pattern so that for - # example 'TD0' is not found where I look for 'TD' and LOCSW and WBSW when I look - # for 'SW' - pattern <- paste("\\$", paramName, "=", sep = "") - occurences <- grep(pattern, lines) - if (length(occurences) == 0L) { - stop(paste(file, "has no field", pattern)) - } - if (length(occurences) > 1L) { - warning(paste(file, "has more that one field", pattern, " I take the first one")) - } - line <- lines[occurences[1]] - - # Cut beginning and end of the line '##$TD= 65536' -> '65536' - igual = as.numeric(regexpr("=", line)) - - first <- igual - while (first <= nchar(line) & !isDigit(substr(line, first, first))) { - first <- first + 1 - } - last <- nchar(line) - while (last > 0 & !isDigit(substr(line, last, last))) { - last <- last - 1 - } - params[paramName] <- as.numeric(substr(line, first, last)) - } - return(params) -} - - - -# ReadFids ============================================================================== -ReadFids <- function(path, l = 1, subdirs = FALSE) { - - # Data initialisation and checks ---------------------------------------------- - begin_info <- beginTreatment("ReadFids") - checkArg(path, c("str")) - checkArg(l, c("pos")) - if (file.exists(path) == FALSE) { - stop(paste("Invalid path:", path)) - } - - - # Extract the FIDs and their info ---------------------------------------------- - - if (subdirs == FALSE) { - fidDirs <- getDirsContainingFid(path) - n <- length(fidDirs) - if (n == 0L) { - stop(paste("No valid fid in", path)) - } - fidNames <- sapply(X = fidDirs, FUN = getTitle, l = l, subdirs = subdirs, USE.NAMES = F) - for (i in 1:n) { - fidList <- ReadFid(fidDirs[i]) - fid <- fidList[["fid"]] - info <- fidList[["params"]] - m <- length(fid) - if (i == 1) { - Fid_data <- matrix(nrow = n, ncol = m, dimnames = list(fidNames, - info[["DT"]] * (0:(m - 1)))) - Fid_info <- matrix(nrow = n, ncol = length(info), dimnames = list(fidNames, - names(info))) - } - Fid_data[i, ] <- fid - Fid_info[i, ] <- unlist(info) - } - - } else { - maindirs <- dir(path, full.names = TRUE) - Fid_data <- numeric() - Fid_info <- numeric() - - fidDirs <- c() - for (j in maindirs) { - fd <- getDirsContainingFid(j) - n <- length(fd) - if (n > 0L) { - fidDirs <- c(fidDirs, fd) - } else {warning(paste("No valid fid in",j ))} - } - - fidNames <- sapply(X = fidDirs, FUN = getTitle, l = l, subdirs = subdirs, USE.NAMES = F) - for (i in 1:length(fidNames)) { - fidList <- ReadFid(fidDirs[i]) - fid <- fidList[["fid"]] - info <- fidList[["params"]] - m <- length(fid) - if (i == 1) { - Fid_data <- matrix(nrow = length(fidNames), ncol = m, dimnames = list(fidNames, - info[["DT"]] * (0:(m - 1)))) - Fid_info <- matrix(nrow = length(fidNames), ncol = length(info), dimnames = list(fidNames, - names(info))) - } - Fid_data[i, ] <- fid - Fid_info[i, ] <- unlist(info) - } - - - } - - # Check for non-unique IDs ---------------------------------------------- - NonnuniqueIds <- sum(duplicated(row.names(Fid_data))) - cat("dim Fid_data: ", dim(Fid_data), "\n") - cat("IDs: ", rownames(Fid_data), "\n") - cat("non-unique IDs?", NonnuniqueIds, "\n") - if (NonnuniqueIds > 0) { - warning("There are duplicated IDs: ", Fid_data[duplicated(Fid_data)]) - } - - - # Return the results ---------------------------------------------- - return(list(Fid_data = endTreatment("ReadFids", begin_info, Fid_data), Fid_info = Fid_info)) - -} - - diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/ReadFids_Manon.R --- a/nmr_preprocessing/ReadFids_Manon.R Tue May 23 03:32:51 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,386 +0,0 @@ -################################################################################################ -# -# Read FIDs in Bruker format -# -# -################################################################################################ - -# ReadFid ============================================================================== -ReadFid <- function(path) { - - # Read 1D FID using Bruker XWinNMR and TopSpin format. It is inspired of the - # matNMR matlab library which deals with 2D FID and also other formats - # Read also the parameters in the acqus file - - paramFile <- file.path(path, "acqus") - # BYTEORDA: 0 -> Little Endian 1 -> Big Endian - params <- readParams(paramFile, c("TD", "BYTORDA", "DIGMOD", "DECIM", "DSPFVS", - "SW_h", "SW", "O1")) - - if (params[["DSPFVS"]] >= 20) { - # The group delay first order phase correction is given directly from version 20 - grpdly <- readParams(paramFile, c("GRPDLY")) - params[["GRPDLY"]] <- grpdly[["GRPDLY"]] - } - TD <- params[["TD"]] - endianness <- if (params$BYTORDA) - "big" else "little" - if (TD%%2 != 0) { - stop(paste("Only even numbers are allowed for size in TD because it is complex - data with the real and imaginary part for each element.", - "The TD value is in the", paramFile, "file")) - } - - # Interpret params Dwell Time, time between 2 data points in the FID - params[["DT"]] <- 1/(2 * params[["SW_h"]]) - - # Read fid - fidFile <- file.path(path, "fid") - fidOnDisk <- readBin(fidFile, what = "int", n = TD, size = 4L, endian = endianness) - - # Real size that is on disk (it should be equal to TD2, except for TopSpin/Bruker - # (which is our case) according to matNMR as just discussed - TDOnDisk <- length(fidOnDisk) - if (TDOnDisk < TD) { - warning("Size is smaller than expected, the rest is filled with zero so the size is the same for every fid") - fidGoodSize <- sapply(vector("list", length = TD), function(x) 0) - fidGoodSize[1:TDOnDisk] <- fidOnDisk - - } else if (TDOnDisk > TD) { - warning("Size is bigger than expected, the rest ignored so the size is the same for every fid") - fidGoodSize <- fidOnDisk(1:TD) - - } else { - fidGoodSize <- fidOnDisk - } - - fidRePart <- fidGoodSize[seq(from = 1, to = TD, by = 2)] - fidImPart <- fidGoodSize[seq(from = 2, to = TD, by = 2)] - fid <- complex(real = fidRePart, imaginary = fidImPart) - - return(list(fid = fid, params = params)) -} - - - - -# getDirsContainingFid ============================================================================== -getDirsContainingFid <- function(path) { - subdirs <- dir(path, full.names = TRUE) - if (length(subdirs) > 0) { - cond <- sapply(subdirs, function(x) { - content <- dir(x) - # subdirs must contain fid, acqu and acqus files - return("fid" %in% content && "acqu" %in% content && "acqus" %in% content) - }) - subdirs <- subdirs[cond] - } - return(subdirs) -} - - - - - - -# beginTreatment ============================================================================== - -beginTreatment <- function(name, Signal_data = NULL, Signal_info = NULL, - force.real = FALSE) { - - cat("Begin", name, "\n") - - - # Formatting the Signal_data and Signal_info ----------------------- - - vec <- is.vector(Signal_data) - if (vec) { - Signal_data <- vec2mat(Signal_data) - } - if (is.vector(Signal_info)) { - Signal_info <- vec2mat(Signal_info) - } - if (!is.null(Signal_data)) { - if (!is.matrix(Signal_data)) { - stop("Signal_data is not a matrix.") - } - if (!is.complex(Signal_data) && !is.numeric(Signal_data)) { - stop("Signal_data contains non-numerical values.") - } - } - if (!is.null(Signal_info) && !is.matrix(Signal_info)) { - stop("Signal_info is not a matrix.") - } - - - Original_data <- Signal_data - - # Extract the real part of the spectrum --------------------------- - - if (force.real) { - if (is.complex(Signal_data)) { - Signal_data <- Re(Signal_data) - } else { - # The signal is numeric Im(Signal_data) is zero anyway so let's avoid - # using complex(real=...,imaginary=0) which would give a complex signal - # in endTreatment() - force.real <- FALSE - } - } - - - # Return the formatted data and metadata entries -------------------- - - return(list(start = proc.time(), vec = vec, force.real = force.real, - Original_data = Original_data, Signal_data = Signal_data, Signal_info = Signal_info)) -} - - -# endTreatment ============================================================================== - -endTreatment <- function(name, begin_info, Signal_data) { - end_time = proc.time() # record it as soon as possible - start_time = begin_info[["start"]] - delta_time = end_time - start_time - delta = delta_time[] - cat("End", name, "\n") - cat("It lasted", - round(delta["user.self"], 3), "s user time,", - round(delta["sys.self"] , 3), "s system time and", - round(delta["elapsed"] , 3), "s elapsed time.\n") - if (begin_info[["force.real"]]) { - # The imaginary part is left untouched - i <- complex(real=0, imaginary=1) - Signal_data = Signal_data + i * Im(begin_info[["Original_data"]]) - } - if (begin_info[["vec"]]) { - Signal_data = Signal_data[1,] - } - return(Signal_data) -} - - -# checkArg ============================================================================== - -checkArg <- function(arg, checks, can.be.null=FALSE) { - check.list <- list(bool=c(is.logical, "a boolean"), - int =c(function(x){x%%1==0}, "an integer"), - num =c(is.numeric, "a numeric"), - str =c(is.character, "a string"), - pos =c(function(x){x>0}, "positive"), - pos0=c(function(x){x>=0}, "positive or zero"), - l1 =c(function(x){length(x)==1}, "of length 1") - ) - if (is.null(arg)) { - if (!can.be.null) { - stop(deparse(substitute(arg)), " is null.") - } - } else { - if (is.matrix(arg)) { - stop(deparse(substitute(arg)), " is not scalar.") - } - for (c in checks) { - if (!check.list[[c]][[1]](arg)) { - stop(deparse(substitute(arg)), " is not ", check.list[[c]][[2]], ".") - } - } - } -} - - -# getArg ============================================================================== - -getArg <- function(arg, info, argname, can.be.absent=FALSE) { - if (is.null(arg)) { - start <- paste("impossible to get argument", argname, "it was not given directly and"); - if (!is.matrix(info)) { - stop(paste(start, "the info matrix was not given")) - } - if (!(argname %in% colnames(info))) { - if (can.be.absent) { - return(NULL) - } else { - stop(paste(start, "is not in the info matrix")) - } - } - if (nrow(info) < 1) { - stop(paste(start, "the info matrix has no row")) - } - arg <- info[1,argname] - if (is.na(arg)) { - stop(paste(start, "it is NA in the info matrix")) - } - } - return(arg) -} - - - -# getTitle ============================================================================== - -# Get the name of the signal from the title file or fromt the name of the subdirectory -# Get the name of the signal from the title file or fromt the name of the subdirectory - -getTitle <- function(path, l, subdirs) { - title <- NULL - title_file <- file.path(file.path(file.path(path, "pdata"), "1"), "title") - if (file.exists(title_file)) { - lines <- readLines(title_file, warn = FALSE) - if (length(lines) >= 1) { - first_line <- gsub("^\\s+|\\s+$", "", lines[l]) - if (nchar(first_line) >= 1) { - title <- first_line - } else { - warning(paste("The first line of the title file is blank for directory ", - path)) - } - } else { - warning(paste("The title file is empty for directory ", path)) - } - } else { - warning(paste("Title file doesn't exists for directory ", path, "\n the repertory name is used instead")) - } - if (is.null(title)) { - if(subdirs) { - separator <- .Platform$file.sep - path_elem <- strsplit(path,separator)[[1]] - title <- paste(path_elem[length(path_elem)-1], path_elem[length(path_elem)], sep = "_") - } else{title <- basename(path)} - } - return(title) -} - - - -# readParams ============================================================================== -# Read parameter values for Fid_info in the ReadFids function - -readParams <- function(file, paramsName) { - - isDigit <- function(c) { - return(suppressWarnings(!is.na(as.numeric(c)))) - } - lines <- readLines(file) - params <- sapply(paramsName, function(x) NULL) - - for (paramName in paramsName) { - # Find the line with the parameter I add a '$' '=' in the pattern so that for - # example 'TD0' is not found where I look for 'TD' and LOCSW and WBSW when I look - # for 'SW' - pattern <- paste("\\$", paramName, "=", sep = "") - occurences <- grep(pattern, lines) - if (length(occurences) == 0L) { - stop(paste(file, "has no field", pattern)) - } - if (length(occurences) > 1L) { - warning(paste(file, "has more that one field", pattern, " I take the first one")) - } - line <- lines[occurences[1]] - - # Cut beginning and end of the line '##$TD= 65536' -> '65536' - igual = as.numeric(regexpr("=", line)) - - first <- igual - while (first <= nchar(line) & !isDigit(substr(line, first, first))) { - first <- first + 1 - } - last <- nchar(line) - while (last > 0 & !isDigit(substr(line, last, last))) { - last <- last - 1 - } - params[paramName] <- as.numeric(substr(line, first, last)) - } - return(params) -} - - - -# ReadFids ============================================================================== -ReadFids <- function(path, l = 1, subdirs = FALSE, subdirs.names = FALSE) { - - # Data initialisation and checks ---------------------------------------------- - begin_info <- beginTreatment("ReadFids") - checkArg(path, c("str")) - checkArg(l, c("pos")) - if (file.exists(path) == FALSE) { - stop(paste("Invalid path:", path)) - } - - - # Extract the FIDs and their info ---------------------------------------------- - - if (subdirs == FALSE) { - fidDirs <- getDirsContainingFid(path) - n <- length(fidDirs) - if (n == 0L) { - stop(paste("No valid fid in", path)) - } - fidNames <- sapply(X = fidDirs, FUN = getTitle, l = l, subdirs = subdirs, USE.NAMES = F) - for (i in 1:n) { - fidList <- ReadFid(fidDirs[i]) - fid <- fidList[["fid"]] - info <- fidList[["params"]] - m <- length(fid) - if (i == 1) { - Fid_data <- matrix(nrow = n, ncol = m, dimnames = list(fidNames, - info[["DT"]] * (0:(m - 1)))) - Fid_info <- matrix(nrow = n, ncol = length(info), dimnames = list(fidNames, - names(info))) - } - Fid_data[i, ] <- fid - Fid_info[i, ] <- unlist(info) - } - - } else { - maindirs <- dir(path, full.names = TRUE) # subdirectories - Fid_data <- numeric() - Fid_info <- numeric() - - fidDirs <- c() - for (j in maindirs) { - fd <- getDirsContainingFid(j) # recoved FIDs from subdirectories - n <- length(fd) - if (n > 0L) { - fidDirs <- c(fidDirs, fd) - } else {warning(paste("No valid fid in",j ))} - } - - if (subdirs.names==TRUE) { - fidNames <- dir(path) - } else {fidNames <- sapply(X = fidDirs, FUN = getTitle, l = l, subdirs = subdirs, USE.NAMES = F)} - - for (i in 1:length(fidNames)) { - fidList <- ReadFid(fidDirs[i]) - fid <- fidList[["fid"]] - info <- fidList[["params"]] - m <- length(fid) - if (i == 1) { - Fid_data <- matrix(nrow = length(fidNames), ncol = m, dimnames = list(fidNames, - info[["DT"]] * (0:(m - 1)))) - Fid_info <- matrix(nrow = length(fidNames), ncol = length(info), dimnames = list(fidNames, - names(info))) - } - Fid_data[i, ] <- fid - Fid_info[i, ] <- unlist(info) - } - - - } - - # Check for non-unique IDs ---------------------------------------------- - NonnuniqueIds <- sum(duplicated(row.names(Fid_data))) - cat("dim Fid_data: ", dim(Fid_data), "\n") - cat("IDs: ", rownames(Fid_data), "\n") - cat("non-unique IDs?", NonnuniqueIds, "\n") - if (NonnuniqueIds > 0) { - warning("There are duplicated IDs: ", Fid_data[duplicated(Fid_data)]) - } - - - # Return the results ---------------------------------------------- - return(list(Fid_data = endTreatment("ReadFids", begin_info, Fid_data), Fid_info = Fid_info)) - -} - - - diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/ReadFids_wrapper.R --- a/nmr_preprocessing/ReadFids_wrapper.R Tue May 23 03:32:51 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,148 +0,0 @@ -#!/usr/local/public/bin/Rscript --vanilla --slave --no-site-file - -## 08122016_ReadFids_wrapper.R -## Manon Martin -## manon.martin@uclouvain.be - -##====================================================== -##====================================================== -# Preamble -##====================================================== -##====================================================== - -runExampleL <- FALSE - - -##------------------------------ -## Options -##------------------------------ -strAsFacL <- options()$stringsAsFactors -options(stringsAsFactors = FALSE) -options(warn=1) - -##------------------------------ -## Libraries laoding -##------------------------------ -library(batch) -library(ggplot2) -library(gridExtra) -library(reshape2) - - -# R script call -source_local <- function(fname) -{ - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - source(paste(base_dir, fname, sep="/")) -} -#Import the different functions -source_local("ReadFids_Manon.R") -source_local("DrawFunctions.R") -##------------------------------ -## Errors ????????????????????? -##------------------------------ - - -##------------------------------ -## Constants -##------------------------------ -topEnvC <- environment() -flagC <- "\n" - - -##------------------------------ -## Script -##------------------------------ -if(!runExampleL) - argLs <- parseCommandArgs(evaluate=FALSE) - - -##====================================================== -##====================================================== -## Parameters Loading -##====================================================== -##====================================================== - - ## Inputs - # Path - ## Bruker FIDs -fileType="Bruker" -zipfile= argLs[["fidzipfile"]] -directory=unzip(zipfile, list=F) -path=paste(getwd(),strsplit(directory[1],"/")[[1]][2],sep="/") - - -# other inputs from ReadFids -l = argLs[["title_line"]] -subdirs <- argLs[["subdirectories"]] -subdirs.names <- argLs[["subdirs_names"]] - - -# Outputs -dataMatrixOut <- argLs[["dataMatrixOut"]] -sampleMetadataOut <- argLs[["sampleOut"]] -logOut <- argLs[["logOut"]] -nomGraphe <- argLs[["graphOut"]] - - - - -## Checking arguments -##------------------- -error.stock <- "\n" - -if(length(error.stock) > 1) - stop(error.stock) - - - -##====================================================== -##====================================================== -## Computation -##====================================================== -##====================================================== -sink(logOut,append=TRUE) - -if(length(warnings())>0){ # or !is.null(warnings()) - print("something happened") -} - -## Starting -cat("\nStart of 'ReadFids' Galaxy module call: ", as.character(Sys.time()), "\n\n", sep = "") - -outputs <- ReadFids(path = path, l=l, subdirs = subdirs, subdirs.names = subdirs.names) - -data_matrix <- outputs[["Fid_data"]] # Data matrix -data_sample <- outputs[["Fid_info"]] # Sample metadata - -pdf(nomGraphe, onefile = TRUE, width = 13, height = 13) -title = "Raw FID data" -DrawSignal(data_matrix, subtype = "stacked", - ReImModArg = c(TRUE, FALSE, FALSE, FALSE), vertical = T, - xlab = "Frequency", num.stacked = 4, - main = title, createWindow=FALSE) -invisible(dev.off()) - -##====================================================== -##====================================================== -## Saving -##====================================================== -##====================================================== - -# Data matrix -write.table(data_matrix,file=argLs$dataMatrixOut, quote=FALSE, row.names=TRUE, sep="\t", col.names=TRUE) - -# Sample metadata -write.table(data_sample,file=argLs$sampleOut, quote=FALSE, row.names=TRUE, sep="\t", col.names=TRUE) - -## Ending - -cat("\nEnd of 'ReadFids' Galaxy module call: ", as.character(Sys.time()), sep = "") - - -sink() - -options(stringsAsFactors = strAsFacL) - -rm(list = ls()) \ No newline at end of file diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/ReadFids_xml.xml --- a/nmr_preprocessing/ReadFids_xml.xml Tue May 23 03:32:51 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,174 +0,0 @@ - - Read NMR raw files - - - - - - - ## Wrapper - Rscript $__tool_directory__/ReadFids_wrapper.R - - ## File input - fidzipfile $fidzipfile - - ## Title line - title_line $title_line - - ## Subdirectories - subdirectories $subdirectories - - ## Use subdirectories names as FID names? - subdirs_names $subdirs_names - - ## Outputs - dataMatrixOut $dataMatrixOut - sampleOut $sampleOut - logOut $logOut - graphOut $graphOut - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -.. class:: infomark - -**Authors** Manon Martin (manon.martin@uclouvain.be) and Marie Tremblay-Franco (marie.tremblay-franco@inra.fr; Galaxy integration) - -.. class:: infomark - -**Please cite** -Rousseau, R. (2011). Statistical contribution to the analysis of metabonomics data in 1H NMR spectroscopy (Doctoral dissertation, PhD thesis. -Institut de statistique, biostatistique et sciences actuarielles, Université catholique de Louvain, Belgium). - - -============= -NMR Read -============= - ------------ -Description ------------ - -Nuclear Magnetic Resonance files reading (from the R 'SOAP' package) - ------------------ -Workflow position ------------------ - -**Upstream tools** - -========================= ================= ======= -Name output file format -========================= ================= ======= -NA NA NA -========================= ================= ======= - - -**Downstream tools** - -+---------------------------+----------------------+--------+ -| Name | Output file | Format | -+===========================+======================+========+ -|NMR_PreProcessing | dataMatrix.tsv | Tabular| -+---------------------------+----------------------+--------+ -| | sampleMetadata.tsv | Tabular| -+---------------------------+----------------------+--------+ -| | variableMetadata.tsv | Tabular| -+---------------------------+----------------------+--------+ -|NMR_Alignement | dataMatrix.tsv | Tabular| -+---------------------------+----------------------+--------+ -|NMR_Bucketing | dataMatrix.tsv | Tabular| -+---------------------------+----------------------+--------+ -|Normalization | dataMatrix.tsv | Tabular| -+---------------------------+----------------------+--------+ -|Univariate | variableMetadata.tsv | Tabular| -+---------------------------+----------------------+--------+ -|Multivariate | sampleMetadata.tsv | Tabular| -+---------------------------+----------------------+--------+ -| | variableMetadata.tsv | Tabular| -+---------------------------+----------------------+--------+ - - ------------ -Input files ------------ - -+---------------------------+-----------------+ -| Parameter : num + label | Format | -+===========================+=================+ -| 1 : Choose your inputs | FID | -+---------------------------+-----------------+ -| 1 : Choose your inputs | Jcamp-dx | -+---------------------------+-----------------+ - -**Choose your inputs** - - | Zip file (recommended) of FID Bruker files: you can put a zip file containing your FID Bruker files: myinputs.zip (containing all your conditions as sub-directories). - | Zip file (recommended) of Jcamp-dx files: you can put a zip file containing your Jcamp-dx files: myinputs.zip (containing all your conditions as sub-directories). - - ----------- -Parameters ----------- - -FID Title - | Line in the acqus file to find the FID title (name) - | - -subdirectories - | Organization of individual's files - | TRUE: will search inside subdirectories for FIDs and will merge them to have unique FID and info matrices. - | - ------------- -Output files ------------- - -dataMatrixOut.tsv - | tabular output - | Data matrix with n rows (samples) and p columns (time) containing the raw FIDs - | - -sampleOut.pdf - | tabular output - | Data matrix with n rows (samples) containing the acquisition parameters - -logOut.tsv - | Text output - | Contains warnings - | ---------------------------------------------------- - ---------------- -Example ---------------- - - - - - diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/ptw.R --- a/nmr_preprocessing/ptw.R Tue May 23 03:32:51 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,98 +0,0 @@ -ptw <- function (ref, samp, selected.traces, init.coef = c(0, 1, 0), - try = FALSE, warp.type = c("individual", "global"), optim.crit = c("WCC", - "RMS"), mode = c("forward", "backward"), smooth.param = ifelse(try, - 0, 1e+05), trwdth = 20, trwdth.res = trwdth, verbose = FALSE, - ...) -{ - optim.crit <- match.arg(optim.crit) - warp.type <- match.arg(warp.type) - mode <- match.arg(mode) - if (is.vector(ref)) - ref <- matrix(ref, nrow = 1) - if (is.vector(samp)) - samp <- matrix(samp, nrow = 1) - if (nrow(ref) > 1 && nrow(ref) != nrow(samp)) - stop("The number of references does not equal the number of samples") - if (length(dim(ref)) > 2) - stop("Reference cannot be an array") - if (length(dim(samp)) > 2) - stop("Sample cannot be an array") - if (nrow(samp) == 1) - warp.type <- "individual" - r <- nrow(samp) - if (!missing(selected.traces)) { - samp <- samp[selected.traces, , drop = FALSE] - if (nrow(ref) > 1) - ref <- ref[selected.traces, , drop = FALSE] - } - if (is.vector(init.coef)) - init.coef <- matrix(init.coef, nrow = 1) - if (warp.type == "global") { - if (nrow(init.coef) != 1) - stop("Only one warping function is allowed with global alignment.") - } - else { - if (nrow(init.coef) != nrow(samp)) - if (nrow(init.coef) == 1) { - init.coef <- matrix(init.coef, byrow = TRUE, - nrow = nrow(samp), ncol = length(init.coef)) - } - else { - stop("The number of warping functions does not match the number of samples") - } - } - if (warp.type == "individual") { - w <- matrix(0, nrow(samp), ncol(ref)) - a <- matrix(0, nrow(samp), ncol(init.coef)) - v <- rep(0, nrow(samp)) - warped.sample <- matrix(NA, nrow = nrow(samp), ncol = ncol(samp)) - for (i in 1:nrow(samp)) { - if (verbose & nrow(samp) > 1) - cat(ifelse(nrow(ref) == 1, paste("Warping sample", - i, "with the reference \n"), paste("Warping sample", - i, "with reference \n", i))) - if (nrow(ref) == 1) { - rfrnc <- ref - } - else { - rfrnc <- ref[i, , drop = FALSE] - } - quad.res <- pmwarp(rfrnc, samp[i, , drop = FALSE], - optim.crit, init.coef[i, ], try = try, mode = mode, - smooth.param = smooth.param, trwdth = trwdth, - trwdth.res = trwdth.res, ...) - w[i, ] <- quad.res$w - a[i, ] <- quad.res$a - v[i] <- quad.res$v - warped.sample[i, ] <- c(warp.sample(samp[i, , drop = FALSE], - w[i, ], mode = mode)) - } - } - else { - if (nrow(ref) == 1) - ref <- matrix(ref, nrow = nrow(samp), ncol = ncol(ref), - byrow = TRUE) - if (verbose) { - if (nrow(ref) == 1) { - cat("Simultaneous warping of samples with reference... \n") - } - else { - cat("Simultaneous warping of samples with references... \n") - } - } - quad.res <- pmwarp(ref, samp, optim.crit, c(init.coef), - try = try, mode = mode, smooth.param = smooth.param, - trwdth = trwdth, trwdth.res = trwdth.res, ...) - w <- t(as.matrix(quad.res$w)) - a <- t(as.matrix(quad.res$a)) - v <- quad.res$v - warped.sample <- t(warp.sample(samp, w, mode)) - } - if (verbose) - cat("\nFinished.\n") - result <- list(reference = ref, sample = samp, warped.sample = warped.sample, - warp.coef = a, warp.fun = w, crit.value = v, optim.crit = optim.crit, - mode = mode, warp.type = warp.type) - class(result) <- "ptw" - result -} \ No newline at end of file diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/static/images/NmrPreprocessing.png Binary file nmr_preprocessing/static/images/NmrPreprocessing.png has changed diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/test-data/MTBLS1.zip Binary file nmr_preprocessing/test-data/MTBLS1.zip has changed diff -r cbea5e9fd0b4 -r 5e64657b4fe5 nmr_preprocessing/test-data/MTBLS1_alignedSpectra.tabular --- a/nmr_preprocessing/test-data/MTBLS1_alignedSpectra.tabular Tue May 23 03:32:51 2017 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,29802 +0,0 @@ -ADG10003u_007 ADG10003u_009 ADG10003u_015 ADG10003u_017 ADG10003u_021 ADG10003u_023 ADG10003u_051 ADG10003u_053 ADG10003u_067 ADG10003u_071 ADG10003u_073 ADG10003u_087 ADG10003u_089 ADG10003u_097 -9.2997 -0.00172384578396177 -0.000133260203713335 0.00188546634303473 0.00145955595536551 0.00266060722603239 -0.00456406825398832 -0.00131195747929342 0.000299817194153485 0.000241533956195763 -0.00349445210212112 0.00449073847864704 -0.00150200410788306 -0.00479292634495511 -0.00845701750085149 -9.2994 -0.002312062118707 -0.000821498405692276 0.00530663314770368 0.0031937690024524 -0.00295334219789086 -0.00562040636826083 0.000544476077311362 0.000328645770514397 0.00269356222036034 -3.40676966964021e-05 0.00203230500493516 -0.000176706365633302 -0.00197312886982787 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