/
eaf_to_df.R
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/
eaf_to_df.R
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#' ELAN's .eaf file to dataframe
#'
#' Convert .eaf file from ELAN to a dataframe.
#'
#' @author George Moroz <agricolamz@gmail.com>
#' @author Kudrjashov Sergej <xenomirant@gmail.com>
#'
#' @param file_name string with a filename or path to the .eaf file
#' @return a dataframe with columns: \code{tier}, \code{id}, \code{content},
#' \code{tier_name}, \code{tier_type}, \code{tier_ref}, \code{event_local_id},
#' \code{dependent_on}, \code{time_start}, \code{time_end}, \code{source}, \code{media_url}
#' and attributes: \code{MEDIA_URL}, \code{MIME_TYPE}, \code{RELATIVE_MEDIA_URL}.
#'
#' @examples
#' eaf_to_df(system.file("extdata", "test.eaf", package = "phonfieldwork"))
#' @export
#' @importFrom xml2 read_xml
#' @importFrom xml2 xml_find_all
#' @importFrom xml2 xml_attr
#' @importFrom xml2 xml_text
#' @importFrom xml2 xml_children
#'
eaf_to_df <- function(file_name) {
# read file
l <- xml2::read_xml(file_name)
# extract tiers
t <- xml2::xml_find_all(l, "TIER")
# extract tiers
tier_names <- xml2::xml_attr(t, "TIER_ID")
# tier types
tier_types <- xml2::xml_attr(t, "LINGUISTIC_TYPE_REF")
#tier parent
tier_parent <- xml2::xml_attr(t, "PARENT_REF")
#tier_stereotype
tier_stereotype <- data.frame(xml2::xml_attr(xml2::xml_find_all(l, "LINGUISTIC_TYPE"),
"LINGUISTIC_TYPE_ID"), xml2::xml_attr(xml2::xml_find_all(l, "LINGUISTIC_TYPE"),
"CONSTRAINTS"))
colnames(tier_stereotype) <- c("tier_type", "stereotype")
# create list of dataframes
r <- lapply(seq_along(t), function(i) {
content <- xml2::xml_text(xml2::xml_find_all(
t[[i]],
"ANNOTATION/*/ANNOTATION_VALUE"
))
ts1 <- xml2::xml_attr(
xml2::xml_children(xml2::xml_children(t[[i]])),
"TIME_SLOT_REF1"
)
ts2 <- xml2::xml_attr(
xml2::xml_children(xml2::xml_children(t[[i]])),
"TIME_SLOT_REF2"
)
a_id <- xml2::xml_attr(
xml2::xml_children(xml2::xml_children(t[[i]])),
"ANNOTATION_ID"
)
ar <- xml2::xml_attr(
xml2::xml_children(xml2::xml_children(t[[i]])),
"ANNOTATION_REF"
)
if (length(content) > 0) {
data.frame(
tier = i,
id = seq_along(content),
content = content,
tier_name = tier_names[i],
tier_type = tier_types[i],
tier_ref = tier_parent[i],
ts_start = ts1,
ts_end = ts2,
a_id = a_id,
ar = ar,
stringsAsFactors = FALSE
)
}
})
# merge list of dataframes into dataframe
r <- do.call(rbind, r)
r$id_ <- 1:nrow(r)
r <- merge(r, tier_stereotype, by = 'tier_type')
r <- r[order(r$id_), ]
#r <- subset(r, select = -c(id_)) # is it important?
r <- subset(r, select = c(2, 3, 4, 5, 1, 11, 6, 7, 8, 9, 10))
if (length(r) > 0) {
# extract info about time
ts <- data.frame(
ts_id = xml2::xml_attr(
xml2::xml_find_all(l, "TIME_ORDER/TIME_SLOT"), "TIME_SLOT_ID"
),
time_value = as.numeric(xml2::xml_attr(
xml2::xml_find_all(l, "TIME_ORDER/TIME_SLOT"), "TIME_VALUE"
)) / 1000,
stringsAsFactors = FALSE
)
# df with time markers
tm <- r[is.na(r$ar), c("ts_start", "ts_end", "a_id")]
# df without time markers
wtm <- r[!is.na(r$ar), c("a_id", "ar")]
# create df with all time stamp
while (nrow(tm) < nrow(r)) {
df <- unique(merge(
x = wtm,
y = tm,
by.x = "ar",
by.y = "a_id"
)[, c("ts_start", "ts_end", "a_id")])
tm <- unique(rbind(tm, df))
}
# result df with time stamps
r <- merge(r[, -c(8:9)], tm)
# merge with time stamp df ts_start column
r <- merge(r, ts, by.x = "ts_start", by.y = "ts_id")
names(r)[names(r) == "time_value"] <- "time_start"
# merge with time stamp df ts_end column
r <- merge(r, ts, by.x = "ts_end", by.y = "ts_id")
names(r)[names(r) == "time_value"] <- "time_end"
#fix issues with Symbolic Subdivision stereotype
r_sub <- r[which(r$stereotype == 'Symbolic_Subdivision'), ]
un_r_sub <- unique(r_sub$ar)
loc_res <- lapply(un_r_sub, function(i){
df_loc <- r_sub[r_sub$ar == i, ]
time_start <- df_loc[1, ]$time_start
time_end <- df_loc[1, ]$time_end
round(seq(from = time_start, to = time_end, length.out = nrow(df_loc)+1), digits = 3)
})
loc <- list()
r_sub[, 12] <- unlist(lapply(loc_res, function(i){
loc <- append(loc, i[1:length(i)-1])
}))
r_sub[, 13] <- unlist(lapply(loc_res, function(i){
loc <- append(loc, i[2:length(i)])
}))
r[row.names(r) %in% row.names(r_sub), ] <- r_sub
#fix issues with Symbolic Association stereotype
r_sub <- r[which(r$stereotype == 'Symbolic_Association'), ]
r_sub[, 12] <- unlist(lapply(row.names(r_sub), function(i) {
r[r$a_id == r_sub[i, ]$ar, ]$time_start
}))
r_sub[, 13] <- unlist(lapply(row.names(r_sub), function(i) {
r[r$a_id == r_sub[i, ]$ar, ]$time_end
}))
r[row.names(r) %in% row.names(r_sub), ] <- r_sub
#fix issues with Time Subdivision stereotype
r_sub <- r[which(r$stereotype == 'Time_Subdivision'), ]
r_sub <- r_sub[order(r_sub$tier_name, decreasing = FALSE), ]
if (sum(is.na(r_sub$time_start)) + sum(is.na(r_sub$time_end)) != 0) {
r_loc_sub <- r_sub[which(is.na(r_sub$time_start) | is.na(r_sub$time_end)), ]
na_end <- r_loc_sub[which(!is.na(r_loc_sub$time_end)), ]
na_start <- r_loc_sub[which(!is.na(r_loc_sub$time_start)), ]
loc_res <- lapply(seq(length.out = nrow(na_start)), function(i) {
id_start <- na_start[i, 5]
id_end <- na_end[i, 5]
time_start <- na_start[i, 12]
time_end <- na_end[i, 13]
round(seq(from = time_start, to = time_end, length.out = id_end-id_start+2), digits = 3)
})
loc <- list()
r_loc_sub[, 12] <- unlist(lapply(loc_res, function(i){
loc <- append(loc, i[1:length(i)-1])
}))
r_loc_sub[, 13] <- unlist(lapply(loc_res, function(i){
loc <- append(loc, i[2:length(i)])
}))
r_sub[row.names(r_sub) %in% row.names(r_loc_sub), ] <- r_loc_sub
r[row.names(r) %in% row.names(r_sub), ] <- r_sub
}
# make sorting and remove some columns
r <- r[order(r$time_start, r$tier), -c(1:2)]
names(r)[names(r) == 'ar'] <- 'dependent_on'
names(r)[names(r) == 'a_id'] <- 'event_local_id'
r <- r[, c(2,3,4,5,6,7,8,1,9,10,11)]
#connected file
attr(r, 'MEDIA_URL') <- xml2::xml_attr(xml2::xml_children(xml2::xml_find_all(l, 'HEADER'))[1], 'MEDIA_URL')
attr(r, 'MIME_TYPE') <- xml2::xml_attr(xml2::xml_children(xml2::xml_find_all(l, 'HEADER'))[1], 'MIME_TYPE')
attr(r, 'RELATIVE_MEDIA_URL') <- xml2::xml_attr(xml2::xml_children(xml2::xml_find_all(l, 'HEADER'))[1], 'RELATIVE_MEDIA_URL')
r$source <- basename(file_name)
r$media_url <- attr(r, 'MEDIA_URL')
return(r)
}
}