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| #' Read an MTrackJ Data File (`.mdf`) | ||
| #' | ||
| #' Reads an MTrackJ Data File (`.mdf`) file in a data.frame. | ||
| #' | ||
| #' @param file MTrackJ Data File (`.mdf`) file with tracking data. | ||
| #' @param drop.Z drop z-coordinate (for 2D data) | ||
| #' @param include.point.numbers include the point numbers in the mdf file | ||
| #' (**NB** these can be different from the time/frame points) | ||
| #' @param include.channel include channel information | ||
| #' @param generate.unique.ids combine cluster and id columns to get unique ids | ||
| #' @param text character string: if file is not supplied and this is, then data | ||
| #' are read from the value of text via a text connection. Notice that a literal | ||
| #' string can be used to include (small) data sets within R code. | ||
| #' @param fileEncoding character string: if non-empty declares the encoding to | ||
| #' be used on a file (not a connection) so the character data can be re-encoded | ||
| #' as they are written. See [base::file()]. | ||
| #' | ||
| #' @family mdftracks functions | ||
| #' | ||
| #' @export | ||
| #' | ||
| #' @seealso [MTrackJ Data Format](https://imagescience.org/meijering/software/mtrackj/format/) | ||
| #' | ||
| #' @examples | ||
| #' read.mdf(system.file("extdata", "example.mdf", package = 'mdftracks')) | ||
| #' | ||
| read.mdf <- function(file, drop.Z = F, include.point.numbers = FALSE, | ||
| include.channel = F, generate.unique.ids = F, text, | ||
| fileEncoding = "") { | ||
| if (missing(file) && !missing(text)) { | ||
| file <- textConnection(text, encoding = "UTF-8") | ||
| on.exit(close(file)) | ||
| } | ||
| if (is.character(file)) { | ||
| file <- if (nzchar(fileEncoding)) | ||
| file(file, "rt", encoding = fileEncoding) | ||
| else file(file, "rt") | ||
| on.exit(close(file)) | ||
| } | ||
| if (!inherits(file, "connection")) | ||
| stop("'file' must be a character string or connection") | ||
| if (!isOpen(file, "rt")) { | ||
| open(file, "rt") | ||
| on.exit(close(file)) | ||
| } | ||
|
|
||
| # Read first line | ||
| mdf.lines <- readLines(file, n = 1) | ||
| if(!grepl(sprintf(pkg.env$mtrackj.header, '[0-9]+(.[0-9]+)*'), mdf.lines)) { | ||
| stop("does not appear to be an MTrackJ Data File") | ||
| } | ||
| # message(mdf.lines) # Print mdf version info from file | ||
| mdf.lines <- c(mdf.lines, readLines(file)) | ||
|
|
||
| cluster.bounds <- getClusterBounds(mdf.lines) | ||
| cluster.lines.list <- getClusterLines(mdf.lines, cluster.bounds) | ||
| cluster.track.list <- lapply(cluster.lines.list, getClusterTracks) | ||
|
|
||
| # Add cluster number | ||
| cluster.track.list <- mapply(function(df, id) { | ||
| df$cluster <- id | ||
| df | ||
| }, cluster.track.list, cluster.bounds$id, SIMPLIFY = F) | ||
| # Merge to one data frame | ||
| df <- do.call(rbind, cluster.track.list) | ||
|
|
||
| # Select columns of interest | ||
| cols <- c('cluster', 'id', 'time', 'x', 'y') | ||
| if(!drop.Z) { cols <- c(cols, "z")} | ||
| if(include.point.numbers) { cols <- c(cols, "point")} | ||
| if(include.channel) { cols <- c(cols, "channel")} | ||
| df <- df[, cols] | ||
|
|
||
| # Generate unique ids | ||
| if(generate.unique.ids) { | ||
| if(length(unique(df$cluster)) == 1) { | ||
| # Only one cluster, uid = id | ||
| df$uid <- df$id | ||
| } else { | ||
| # Multiple clusters, create uid based on cl and id | ||
| df$uid <- as.numeric(factor(paste(df$cluster, df$id, sep = "."))) | ||
| } | ||
| } | ||
|
|
||
| attr(df, "doc") <- paste0("Read from ", mdf.lines[[1]]) | ||
| df | ||
| } | ||
|
|
||
| getTrackBounds <- function(mdf.lines) { | ||
| track.lines <- grep("^Track", mdf.lines) | ||
| track.nrs <- as.numeric(sapply(strsplit(mdf.lines[track.lines], " "), "[[", 2)) | ||
| data.frame(id = track.nrs, begin = track.lines + 1, end = c(track.lines[-1], length(mdf.lines))) | ||
| } | ||
|
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|
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||
| getClusterBounds <- function(mdf.lines) { | ||
| cluster.lines <- grep("^Cluster", mdf.lines) | ||
| cluster.nrs <- as.numeric(sapply(strsplit(mdf.lines[cluster.lines], " "), "[[", 2)) | ||
| # -1 for the last line in the file | ||
| data.frame(id = cluster.nrs, begin = cluster.lines + 1, end = c(cluster.lines[-1], length(mdf.lines)) - 1) | ||
| } | ||
|
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||
|
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| getClusterLines <- function(mdf.lines, cluster.bounds) { | ||
| cluster.bounds.l <- split(cluster.bounds, cluster.bounds$id) | ||
| cluster.lines.l <- invisible(lapply(cluster.bounds.l, function(x) { | ||
| mdf.lines[x$begin:x$end] | ||
| })) | ||
| } | ||
|
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|
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| #' @importFrom utils read.delim | ||
| getClusterTracks <- function(cluster.lines) { | ||
| track.bounds <- getTrackBounds(cluster.lines) | ||
| track.bounds.l <- split(track.bounds, track.bounds$id) | ||
| track.df.l <- invisible(lapply(track.bounds.l, function(x) { | ||
| # Get correct rows from cluster.lines | ||
| t <- cluster.lines[x$begin:x$end] | ||
| # Filter out Point lines | ||
| t <- t[grep("^Point", t)] | ||
| # Read lines as data frame | ||
| t.df <- read.delim(sep = " ", header = F, text = t) | ||
| # Rename columns | ||
| colnames(t.df) <- c('id', 'point', 'x', 'y', 'z', 'time', 'channel') | ||
| # Put in the correct track id | ||
| t.df$id <- x$id | ||
|
|
||
| t.df | ||
| })) | ||
| # Bind list together to get the DF, then convert to data matrix (make numeric), | ||
| # then back to DF | ||
| as.data.frame(data.matrix(do.call(rbind, track.df.l)), stringsAsFactors = F) | ||
| } |
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