R/para_conc.R
In gederajeg/paracorp: Concordancer for parallel, bilingual corpora
Defines functions
para_conc
Documented in
para_conc
#' Parallel concordance
#'
#' @description A function to generate a concordance from parallel, bilingual corpora.
#' @param source_text character vector of the source-text corpora
#' @param target_text character vector of the target-text corpora
#' @param pattern regular expression search pattern for the source-text node word
#' @param case_insensitive logical; whether the search pattern is case insensitive. Default to FALSE
#' @param conc_sample random sample of the concordance lines
#' @param filename file name of the parallel concordance output
#'
#' @return A tibble of parallel concordance with source-text node word and its left and right context, and their target-text translation. By default, \code{para_conc()} also automatically saves the concordance into a tab-separated plain text named \code{"parallel_conc.txt"}. Users can specify their own output file name.
#' @export
#' @importFrom rlang .data
#' @importFrom dplyr arrange
#' @importFrom dplyr bind_rows
#' @importFrom dplyr desc
#' @importFrom dplyr mutate
#' @importFrom purrr map
#' @importFrom purrr map_df
#' @importFrom readr write_tsv
#' @importFrom stringr regex
#' @importFrom stringr str_which
#' @importFrom stringr str_locate_all
#' @importFrom stringr str_count
#' @importFrom stringr str_sub
#' @importFrom stringr str_trim
#' @importFrom stringr str_c
#' @importFrom stringr str_replace
#' @importFrom tibble tibble
#'
#' @examples para_conc(sci_en, sci_id, pattern = "should", conc_sample = 20)
#' # we delete the automatic output file to remove warning in R CMD check
#' unlink("parallel_conc.txt")
#'
#' # example when automatic output file is suppressed with filename = FALSE
#' # and only producing a tibble/data frame.
#' para_conc(sci_en, sci_id,
#' pattern = "should",
#' conc_sample = 20,
#' filename = FALSE) # suppress automatic output
para_conc <- function(source_text = "The source text corpus",
target_text = "The target text corpus",
pattern = "Search pattern for words in the source text",
case_insensitive = FALSE,
conc_sample = 25,
filename = "parallel_conc.txt") {
m_st <- source_text; rm(source_text)
m_tt <- target_text; rm(target_text)
search_term <- pattern
samples <- conc_sample
# check if the user wants to directly save the concordance output into tab-separated plain text
if (is.character(filename)) {
message(paste("The output concordance file (called: '", filename,"') will be saved in this directory: '", getwd(), "'\n", sep = ""))
message("The output concordance will ALSO be returned as a tibble data frame in the R console.\n")
cat("LEFT\tNODE\tRIGHT\tTRANSLATION", file = filename, sep = "\n")
} else if (filename == FALSE) {
message("The output concordance will be returned as a tibble data frame in the R console.\n")
}
for (i in seq_along(search_term)) {
m_id <- stringr::str_which(m_st, stringr::regex(search_term[i], ignore_case = case_insensitive))
if ((length(m_id) >= 1) == TRUE) {
m <- m_st[m_id]
message("Detecting the match/pattern...\n")
m_loc <- stringr::str_locate_all(m,
stringr::regex(search_term[i],
ignore_case = case_insensitive))
m_loc <- purrr::map(m_loc, tibble::as_tibble)
m_loc <- purrr::map_df(m_loc, dplyr::bind_rows)
# duplicate the number of subset text as many as the number of the match
m1 <- rep(m, stringr::str_count(m,
stringr::regex(search_term[i],
ignore_case = case_insensitive)))
m_id <- rep(m_id, stringr::str_count(m,
stringr::regex(search_term[i],
ignore_case = case_insensitive)))
if (samples) {
message(paste("You choose to generate a ",
samples,
" random-sample of the concordance lines.\n",
sep = ""))
if (samples < length(m1)) {
# if the requested sample number is fewer than the number of matches, run the sampling
message(paste("Creating a ",
samples,
" random-sample of the concordance lines...\n",
sep = ""))
# sample count
sample_count <- sample(1:length(m1), samples)
# retrieve random sample sentences
st_sample <- m1[sample_count]
tt_sample <- m_tt[m_id[sample_count]]
m_loc1 <- m_loc[sample_count, ]
} else if (samples == length(m1)) {
# if the requested sample number is equal to the number of matches, retrieve all matches
extent <- "equal to"
message(paste("The requested number of samples (", samples, ") is ",
extent,
" the number of matches (", length(m1), ").\nAll (", length(m1), ") matches will be returned.\n",
sep = ""))
st_sample <- m1
tt_sample <- m_tt[m_id]
m_loc1 <- m_loc
} else if (samples > length(m1)) {
# if the requested sample number is greater than the number of matches, retrieve all matches
extent <- "greater than"
message(paste("The requested number of samples (", samples, ") is ",
extent,
" the number of matches (", length(m1), ").\nAll (", length(m1), ") matches will be returned.\n",
sep = ""))
st_sample <- m1
tt_sample <- m_tt[m_id]
m_loc1 <- m_loc
}
} else {
message("Retrieving all occurrences of the search pattern...\n")
st_sample <- m1
tt_sample <- m_tt[m_id]
m_loc1 <- m_loc
}
# extract match
message("Generating the concordance for the match/pattern...\n")
node <- stringr::str_sub(st_sample, start = m_loc1$start, end = m_loc1$end)
node_tag <- stringr::str_c("\t<NODE>", node, "</NODE>\t", sep = "")
left <- stringr::str_sub(st_sample, start = 1, end = (m_loc1$start - 1))
right <- stringr::str_sub(st_sample, start = (m_loc1$end + 1), end = nchar(st_sample))
# create concordance
# LEFT <- stringr::str_sub(left, start = (nchar(left) - context_char), end = nchar(left))
LEFT <- replace(left, nchar(left) == 0, "~")
NODE <- node
# RIGHT <- stringr::str_sub(right, start = 1, end = context_char)
RIGHT <- replace(right, nchar(right) == 0, "~")
TRANSLATION <- tt_sample
concord_df <- tibble::tibble(LEFT, NODE, RIGHT, TRANSLATION)
concord_df <- dplyr::mutate(concord_df,
LEFT = stringr::str_trim(.data$LEFT),
NODE = stringr::str_trim(.data$NODE),
RIGHT = stringr::str_trim(.data$RIGHT))
concord_df <- dplyr::mutate(concord_df,
LEFT = stringr::str_replace(LEFT, "^-", '"-'),
RIGHT = stringr::str_replace(RIGHT, "^-", '"-'),
TRANSLATION = stringr::str_replace(TRANSLATION, "^-", '"-'))
if (is.character(filename)) {
message(paste("Saving the output concordance file (called: '",
filename,
"') in '",
getwd(),
"'.\n",
sep = ""))
readr::write_tsv(dplyr::arrange(concord_df, dplyr::desc(NODE), RIGHT),
filename,
append = TRUE)
return(dplyr::arrange(concord_df, dplyr::desc(NODE), RIGHT))
} else if (filename == FALSE) {
return(dplyr::arrange(concord_df, dplyr::desc(NODE), RIGHT))
}
} else {
message("Sorry; NO match(es) found! Try another corpus/pattern!\nN.B. Have you also checked that the source-text language matches with the language of the search pattern?")
}
}
}
gederajeg/paracorp documentation built on Jan. 2, 2022, 4:33 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions para_conc
Documented in para_conc
#' Parallel concordance
#'
#' @description A function to generate a concordance from parallel, bilingual corpora.
#' @param source_text character vector of the source-text corpora
#' @param target_text character vector of the target-text corpora
#' @param pattern regular expression search pattern for the source-text node word
#' @param case_insensitive logical; whether the search pattern is case insensitive. Default to FALSE
#' @param conc_sample random sample of the concordance lines
#' @param filename file name of the parallel concordance output
#'
#' @return A tibble of parallel concordance with source-text node word and its left and right context, and their target-text translation. By default, \code{para_conc()} also automatically saves the concordance into a tab-separated plain text named \code{"parallel_conc.txt"}. Users can specify their own output file name.
#' @export
#' @importFrom rlang .data
#' @importFrom dplyr arrange
#' @importFrom dplyr bind_rows
#' @importFrom dplyr desc
#' @importFrom dplyr mutate
#' @importFrom purrr map
#' @importFrom purrr map_df
#' @importFrom readr write_tsv
#' @importFrom stringr regex
#' @importFrom stringr str_which
#' @importFrom stringr str_locate_all
#' @importFrom stringr str_count
#' @importFrom stringr str_sub
#' @importFrom stringr str_trim
#' @importFrom stringr str_c
#' @importFrom stringr str_replace
#' @importFrom tibble tibble
#'
#' @examples para_conc(sci_en, sci_id, pattern = "should", conc_sample = 20)
#' # we delete the automatic output file to remove warning in R CMD check
#' unlink("parallel_conc.txt")
#'
#' # example when automatic output file is suppressed with filename = FALSE
#' # and only producing a tibble/data frame.
#' para_conc(sci_en, sci_id,
#' pattern = "should",
#' conc_sample = 20,
#' filename = FALSE) # suppress automatic output
para_conc <- function(source_text = "The source text corpus",
target_text = "The target text corpus",
pattern = "Search pattern for words in the source text",
case_insensitive = FALSE,
conc_sample = 25,
filename = "parallel_conc.txt") {
m_st <- source_text; rm(source_text)
m_tt <- target_text; rm(target_text)
search_term <- pattern
samples <- conc_sample
# check if the user wants to directly save the concordance output into tab-separated plain text
if (is.character(filename)) {
message(paste("The output concordance file (called: '", filename,"') will be saved in this directory: '", getwd(), "'\n", sep = ""))
message("The output concordance will ALSO be returned as a tibble data frame in the R console.\n")
cat("LEFT\tNODE\tRIGHT\tTRANSLATION", file = filename, sep = "\n")
} else if (filename == FALSE) {
message("The output concordance will be returned as a tibble data frame in the R console.\n")
}
for (i in seq_along(search_term)) {
m_id <- stringr::str_which(m_st, stringr::regex(search_term[i], ignore_case = case_insensitive))
if ((length(m_id) >= 1) == TRUE) {
m <- m_st[m_id]
message("Detecting the match/pattern...\n")
m_loc <- stringr::str_locate_all(m,
stringr::regex(search_term[i],
ignore_case = case_insensitive))
m_loc <- purrr::map(m_loc, tibble::as_tibble)
m_loc <- purrr::map_df(m_loc, dplyr::bind_rows)
# duplicate the number of subset text as many as the number of the match
m1 <- rep(m, stringr::str_count(m,
stringr::regex(search_term[i],
ignore_case = case_insensitive)))
m_id <- rep(m_id, stringr::str_count(m,
stringr::regex(search_term[i],
ignore_case = case_insensitive)))
if (samples) {
message(paste("You choose to generate a ",
samples,
" random-sample of the concordance lines.\n",
sep = ""))
if (samples < length(m1)) {
# if the requested sample number is fewer than the number of matches, run the sampling
message(paste("Creating a ",
samples,
" random-sample of the concordance lines...\n",
sep = ""))
# sample count
sample_count <- sample(1:length(m1), samples)
# retrieve random sample sentences
st_sample <- m1[sample_count]
tt_sample <- m_tt[m_id[sample_count]]
m_loc1 <- m_loc[sample_count, ]
} else if (samples == length(m1)) {
# if the requested sample number is equal to the number of matches, retrieve all matches
extent <- "equal to"
message(paste("The requested number of samples (", samples, ") is ",
extent,
" the number of matches (", length(m1), ").\nAll (", length(m1), ") matches will be returned.\n",
sep = ""))
st_sample <- m1
tt_sample <- m_tt[m_id]
m_loc1 <- m_loc
} else if (samples > length(m1)) {
# if the requested sample number is greater than the number of matches, retrieve all matches
extent <- "greater than"
message(paste("The requested number of samples (", samples, ") is ",
extent,
" the number of matches (", length(m1), ").\nAll (", length(m1), ") matches will be returned.\n",
sep = ""))
st_sample <- m1
tt_sample <- m_tt[m_id]
m_loc1 <- m_loc
}
} else {
message("Retrieving all occurrences of the search pattern...\n")
st_sample <- m1
tt_sample <- m_tt[m_id]
m_loc1 <- m_loc
}
# extract match
message("Generating the concordance for the match/pattern...\n")
node <- stringr::str_sub(st_sample, start = m_loc1$start, end = m_loc1$end)
node_tag <- stringr::str_c("\t<NODE>", node, "</NODE>\t", sep = "")
left <- stringr::str_sub(st_sample, start = 1, end = (m_loc1$start - 1))
right <- stringr::str_sub(st_sample, start = (m_loc1$end + 1), end = nchar(st_sample))
# create concordance
# LEFT <- stringr::str_sub(left, start = (nchar(left) - context_char), end = nchar(left))
LEFT <- replace(left, nchar(left) == 0, "~")
NODE <- node
# RIGHT <- stringr::str_sub(right, start = 1, end = context_char)
RIGHT <- replace(right, nchar(right) == 0, "~")
TRANSLATION <- tt_sample
concord_df <- tibble::tibble(LEFT, NODE, RIGHT, TRANSLATION)
concord_df <- dplyr::mutate(concord_df,
LEFT = stringr::str_trim(.data$LEFT),
NODE = stringr::str_trim(.data$NODE),
RIGHT = stringr::str_trim(.data$RIGHT))
concord_df <- dplyr::mutate(concord_df,
LEFT = stringr::str_replace(LEFT, "^-", '"-'),
RIGHT = stringr::str_replace(RIGHT, "^-", '"-'),
TRANSLATION = stringr::str_replace(TRANSLATION, "^-", '"-'))
if (is.character(filename)) {
message(paste("Saving the output concordance file (called: '",
filename,
"') in '",
getwd(),
"'.\n",
sep = ""))
readr::write_tsv(dplyr::arrange(concord_df, dplyr::desc(NODE), RIGHT),
filename,
append = TRUE)
return(dplyr::arrange(concord_df, dplyr::desc(NODE), RIGHT))
} else if (filename == FALSE) {
return(dplyr::arrange(concord_df, dplyr::desc(NODE), RIGHT))
}
} else {
message("Sorry; NO match(es) found! Try another corpus/pattern!\nN.B. Have you also checked that the source-text language matches with the language of the search pattern?")
}
}
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.