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combine_journal_lists.R
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combine_journal_lists.R
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#' @title combine journals and output csv file
#'
#' @import data.table
#' @importFrom stringr str_trim str_to_lower str_count str_replace_all str_glue str_squish
#' @importFrom stringi stri_escape_unicode
#' @importFrom usethis use_data
#' @return NULL
#' @keywords combine journals and output CSV
#' @examples
#' \dontrun{
#' journalabbr:::combine_journal_lists()
#' }
# set_wd()
# here::dr_here()
current_dir <- dirname(basename(normalizePath(path.expand("."))))
# script_dir <- dirname(rstudioapi::getSourceEditorContext()$path)
setwd(current_dir)
cat(stringr::str_glue("\n===== 当前工作目录为: {getwd()} ====\n"))
combine_journal_lists <- function(csvdir = file.path(".", "metadata", "journals"), format = c("rda", "js"), jspath = "./data.ts") {
if (!require("pacman")) install.packages("pacman")
pacman::p_load(data.table, purrr, stringr)
remove_trailing_separator <- function(input_path) {
# get the system separator
system_separator <- .Platform$file.sep
if (substr(input_path, nchar(input_path), nchar(input_path)) == system_separator) {
input_path <- substr(input_path, 1, nchar(input_path) - 1)
}
return(input_path)
}
csvdir <- remove_trailing_separator(csvdir)
# check input
if (!is.character(csvdir) || !is.character(format) || !is.character(jspath)) {
stop("The input parameter must be a character type.")
}
if (!format %in% c("rda", "js")) {
stop("The format parameter must be one of 'rda' or 'js'.")
}
journal <- journal_abbr <- journal_lower <- fz_count_dot <- fz_count_abbrlen <- fz_count_upper <- NULL
filedf <- tibble::tribble(
~file, ~weight,
"./woodward_library_new.csv", 2,
"./metadata/journals/journal_abbreviations_acs.csv", 3,
"./metadata/journals/journal_abbreviations_aea.csv", 3,
"./metadata/journals/journal_abbreviations_astronomy.csv", 3,
"./metadata/journals/journal_abbreviations_ams.csv", 3,
"./metadata/journals/journal_abbreviations_annee-philologique.csv", 3,
"./metadata/journals/journal_abbreviations_dainst.csv", 3,
"./metadata/journals/journal_abbreviations_entrez.csv", 3,
"./metadata/journals/journal_abbreviations_general.csv", 3,
"./metadata/journals/journal_abbreviations_geology_physics_variations.csv", 3,
"./metadata/journals/journal_abbreviations_geology_physics.csv", 3,
"./metadata/journals/journal_abbreviations_ieee.csv", 3,
"./metadata/journals/journal_abbreviations_lifescience.csv", 3,
"./metadata/journals/journal_abbreviations_mathematics.csv", 3,
"./metadata/journals/journal_abbreviations_mechanical.csv", 3,
"./metadata/journals/journal_abbreviations_medicus.csv", 3,
"./metadata/journals/journal_abbreviations_meteorology.csv", 3,
"./metadata/journals/journal_abbreviations_sociology.csv", 3,
"./metadata/journals/journal_abbreviations_webofscience-dotless.csv", 3,
"./metadata/journals/journal_abbreviations_webofscience-dots.csv", 3,
)
exclude_files <- c(
"./metadata/journals/journal_abbreviations_ieee_strings.csv"
)
# automatically add new files
newfile <- list.files(path = csvdir, pattern = "\\.csv", full.names = T)
newfile <- newfile[!newfile %in% exclude_files]
newfile_diff <- setdiff(newfile, filedf$file)
print(stringr::str_glue("New files: {newfile_diff}"))
if (length(newfile_diff) > 0) {
for (i in newfile_diff) {
filedf <- tibble::add_row(filedf, file = i, weight = 3)
}
}
filedf <- filedf[filedf$file != "./metadata/journals/journal_abbreviations_ieee_strings.csv", ]
filedf <- unique(filedf)
filelist <- filedf$file
dt_list <- list()
k <- 1
for (i in filelist) {
if (file.exists(i)) {
dt_list[[k]] <- data.table::fread(i, sep = ",", header = FALSE, fill = TRUE)
dt_list[[k]][, "originFile" := i]
k <- k + 1
} else {
print(stringr::str_glue("file not exists: {i}"))
}
}
dt <- data.table::rbindlist(dt_list, fill = TRUE) # Merge multiple data
dt <- dt[, c("V1", "V2", "originFile"), with = FALSE]
dt <- merge(dt, filedf, sort = F, all.x = T, by.x = "originFile", by.y = "file")
dt <- dt[, c("V1", "V2", "originFile", "weight"), with = FALSE]
cat(sprintf("After the merger, there are %d journals in total.\n", dt[, .N]))
setnames(
dt, c("V1", "V2", "originFile", "weight"),
c("journal", "journal_abbr", "originFile", "weight")
)
dt <- dt[, lapply(.SD, str_squish)]
dt_1 <- copy(dt)
dt_2 <- copy(dt)
dt_3 <- copy(dt)
dt_1[, journal := str_replace_all(journal, "(?<= )\\&(?= )", "&")]
dt_1[, journal := str_replace_all(journal, "(?<= )\\\\&(?= )", "&")]
dt_1[, journal := str_replace_all(journal, "(?<= )[aA][nN][dD](?= )", "&")]
dt_2[, journal := str_replace_all(journal, "(?<= )&(?= )", "and")]
dt_2[, journal := str_replace_all(journal, "(?<= )\\\\&(?= )", "and")]
dt_2[, journal := str_replace_all(journal, "(?<= )\\&(?= )", "and")]
dt_3[, journal := str_replace_all(journal, "(?<= )&(?= )", "\\\\&")]
dt_3[, journal := str_replace_all(journal, "(?<= )[aA][nN][dD](?= )", "\\\\&")]
dt_3[, journal := str_replace_all(journal, "(?<= )\\&(?= )", "\\\\&")]
dt <- unique(rbindlist(list(dt_1, dt_2, dt_3), use.names = TRUE, fill = TRUE))
cat(sprintf("After 'and' and '&' are replaced and merged, there are %d journals in total.\n", dt[, .N]))
############ 1. Journal special value processing
#### 1.1 Delete lines with backslashes and forward slashes -- journals are too special
dt <- dt[!grepl(pattern = "\\\\", journal), ]
dt <- dt[!grepl(pattern = "/{1,10}", journal), ]
#### 1.2 Delete lines with double quotes -- journals are too special
dt <- dt[!grepl(pattern = '"', journal), ]
##### 1.3 Delete journals whose journal field is more than 80 or less than 5 characters
dt <- dt[nchar(journal) <= 80 & nchar(journal) >= 5, ]
# dt <- dt[!grepl(pattern = "\\\\", journal_abbr), ]
# dt <- dt[!grepl(pattern = "/{1,10}", journal_abbr), ]
dt <- dt[!grepl(pattern = '"', journal_abbr), ]
########### 2. Journal field to lowercase and add some auxiliary columns to help filter duplicate journals later.
dt[, journal_lower := str_to_lower(journal)]
dt[, fz_count_dot := str_count(journal_abbr, "\\.")] # Calculate the number of dots in the abbr field.
dt[, fz_count_abbrlen := str_length(journal_abbr)] # Calculate the length of the abbr field.
# Calculate the number of uppercase letters in the abbr field.
dt[, fz_count_upper := str_count(journal_abbr, "[A-Z]")]
########## 3. Remove duplicate items, Filter according to certain conditions.
dt_new <- dt[dt[, .I[order(weight, -fz_count_dot, -fz_count_upper, fz_count_abbrlen)[1]], by = journal_lower]$V1, ]
dt_new_sub <- dt_new[, c("journal_lower", "journal_abbr", "originFile"), with = FALSE]
stopifnot(uniqueN(dt_new_sub[, c("journal_lower"), with = FALSE]) == dt_new_sub[, .N])
cat(sprintf(
"Delete duplicate items. Finally, a total of %d journals with abbreviations were used.\n",
dt_new_sub[, .N]
))
if (format != "js") {
# Only save as RDA format
abbrtable_sys <- dt_new_sub[, lapply(.SD, stringi::stri_escape_unicode)]
usethis::use_data(abbrtable_sys, compress = "xz", internal = TRUE, overwrite = TRUE, version = 3)
} else {
dtf <- dt_new_sub
data.table::fwrite(dtf, file = "data_new.csv")
if (file.exists(jspath)) {
file.remove(jspath)
}
# output js file, for zotero-journalabbr repo
cat("const journal_abbr = {\n ", file = jspath, append = F, sep = "")
s0 <- dtf[, paste0('"', journal_lower, '": "', journal_abbr, '"')]
cat(s0, file = jspath, append = T, sep = ",\n ")
cat("};\n\nexport { journal_abbr };", file = jspath, append = T, sep = "")
# output rda file, for journalabbr repo
abbrtable_sys <- dt_new_sub[, lapply(.SD, stringi::stri_escape_unicode)]
usethis::use_data(abbrtable_sys, compress = "xz", internal = TRUE, overwrite = TRUE, version = 3)
}
}
combine_journal_lists(csvdir = file.path(".", "metadata", "journals"), format = "js", jspath = "./data_new.ts")