# ==================================================================== #
# TITLE                                                                #
# Antimicrobial Resistance (AMR) Analysis                              #
#                                                                      #
# AUTHORS                                                              #
# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl)           #
#                                                                      #
# LICENCE                                                              #
# This program is free software; you can redistribute it and/or modify #
# it under the terms of the GNU General Public License version 2.0,    #
# as published by the Free Software Foundation.                        #
#                                                                      #
# This program is distributed in the hope that it will be useful,      #
# but WITHOUT ANY WARRANTY; without even the implied warranty of       #
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the        #
# GNU General Public License for more details.                         #
# ==================================================================== #

#' Properties of an ATC code
#'
#' Gets data from the WHO to determine properties of an ATC (e.g. an antibiotic) like name, defined daily dose (DDD) or standard unit. \strong{This function requires an internet connection.}
#' @param atc_code a character or character vector with ATC code(s) of antibiotic(s)
#' @param property property of an ATC code. Valid values are \code{"ATC code"}, \code{"Name"}, \code{"DDD"}, \code{"U"} (\code{"unit"}), \code{"Adm.R"} en \code{"Note"}.
#' @param administration type of administration, see \emph{Details}
#' @param url url of website of the WHO. The sign \code{\%s} can be used as a placeholder for ATC codes.
#' @details
#' Abbreviations for the property \code{"Adm.R"} (parameter \code{administration}):
#' \itemize{
#'   \item{\code{"Implant"}}{ = Implant}
#'   \item{\code{"Inhal"}}{ = Inhalation}
#'   \item{\code{"Instill"}}{ = Instillation}
#'   \item{\code{"N"}}{ = nasal}
#'   \item{\code{"O"}}{ = oral}
#'   \item{\code{"P"}}{ = parenteral}
#'   \item{\code{"R"}}{ = rectal}
#'   \item{\code{"SL"}}{ = sublingual/buccal}
#'   \item{\code{"TD"}}{ = transdermal}
#'   \item{\code{"V"}}{ = vaginal}
#' }
#'
#' Abbreviations for the property \code{"U"} (unit):
#' \itemize{
#'   \item{\code{"g"}}{ = gram}
#'   \item{\code{"mg"}}{ = milligram}
#'   \item{\code{"mcg"}}{ = microgram}
#'   \item{\code{"U"}}{ = unit}
#'   \item{\code{"TU"}}{ = thousand units}
#'   \item{\code{"MU"}}{ = million units}
#'   \item{\code{"mmol"}}{ = millimole}
#'   \item{\code{"ml"}}{ = milliliter (e.g. eyedrops)}
#' }
#' @export
#' @importFrom dplyr %>% progress_estimated
#' @importFrom xml2 read_html
#' @importFrom rvest html_nodes html_table
#' @source \url{https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/}
#' @examples
#' \donttest{
#' atc_property("J01CA04", "DDD", "O") # oral DDD (Defined Daily Dose) of amoxicillin
#' atc_property("J01CA04", "DDD", "P") # parenteral DDD (Defined Daily Dose) of amoxicillin
#' }
atc_property <- function(atc_code,
                         property,
                         administration = 'O',
                         url = 'https://www.whocc.no/atc_ddd_index/?code=%s&showdescription=no') {

  # property <- property %>% tolower()
  #
  if (property %like% 'unit') {
    property <- 'U'
  }

  # validation of properties
  valid_properties.bak <- c("ATC code", "Name", "DDD", "U", "Adm.R", "Note")
  valid_properties <- valid_properties.bak #%>% tolower()
  if (!property %in% valid_properties) {
    stop('Invalid `property`, use one of ', paste(valid_properties, collapse = ", "), '.')
  }

  returnvalue <- rep(NA_character_, length(atc_code))
  if (property == 'DDD') {
    returnvalue <- rep(NA_real_, length(atc_code))
  }

  progress <- progress_estimated(n = length(atc_code))

  for (i in 1:length(atc_code)) {

    progress$tick()$print()

    atc_url <- sub('%s', atc_code[i], url, fixed = TRUE)
    tbl <- xml2::read_html(atc_url) %>%
      rvest::html_nodes('table') %>%
      rvest::html_table(header = TRUE)

    if (length(tbl) == 0) {
      warning('ATC not found: ', atc_code[i], '. Please check ', atc_url, '.', call. = FALSE)
      returnvalue[i] <- NA
      next
    }

    tbl <- tbl[[1]]

    if (property == 'Name') {
      returnvalue[i] <- tbl[1, 2]
    } else {

      names(returnvalue)[i] <- tbl[1, 2] %>% as.character()

      if (!'Adm.R' %in% colnames(tbl) | is.na(tbl[1, 'Adm.R'])) {
        returnvalue[i] <- NA
        next
      } else {
        for (j in 1:nrow(tbl)) {
          if (tbl[j, 'Adm.R'] == administration) {
            returnvalue[i] <- tbl[j, property]
          }
        }
      }
    }
  }

  cat('\n')
  returnvalue

}

#' Name of an antibiotic
#'
#' Convert antibiotic codes (from a laboratory information system like MOLIS or GLIMS) to a (trivial) antibiotic name or ATC code, or vice versa. This uses the data from \code{\link{antibiotics}}.
#' @param abcode a code or name, like \code{"AMOX"}, \code{"AMCL"} or \code{"J01CA04"}
#' @param from,to type to transform from and to. See \code{\link{antibiotics}} for its column names. WIth \code{from = "guess"} the from will be guessed from \code{"atc"}, \code{"molis"} and \code{"umcg"}.
#' @param textbetween text to put between multiple returned texts
#' @param tolower return output as lower case with function \code{\link{tolower}}.
#' @keywords ab antibiotics
#' @source \code{\link{antibiotics}}
#' @export
#' @importFrom dplyr %>% filter select slice
#' @examples
#' abname("AMCL")
#' # "amoxicillin and enzyme inhibitor"
#'
#' abname("AMCL+GENT")
#' # "amoxicillin and enzyme inhibitor + gentamicin"
#'
#' abname(c("AMCL", "GENT"))
#' # "amoxicillin and enzyme inhibitor" "gentamicin"
#'
#' abname("AMCL", to = "trivial_nl")
#' # "Amoxicilline/clavulaanzuur"
#'
#' abname("AMCL", to = "atc")
#' # "J01CR02"
#'
#' abname("J01CR02", from = "atc", to = "umcg")
#' # "AMCL"
abname <- function(abcode, from = c("guess", "atc", "molis", "umcg"), to = 'official', textbetween = ' + ', tolower = FALSE) {

  antibiotics <- AMR::antibiotics

  from <- from[1]
  if (from == "guess") {
    for (i in 1:3) {
      if (abcode[1] %in% (antibiotics %>% pull(i))) {
        from <- colnames(antibiotics)[i]
      }
    }
    if (from == "guess") {
      from <- "umcg"
    }
  }

  colnames(antibiotics) <- colnames(antibiotics) %>% tolower()
  from <- from %>% tolower()
  to <- to %>% tolower()

  if (!from %in% colnames(antibiotics) |
      !to %in% colnames(antibiotics)) {
    stop(paste0('Invalid `from` or `to`. Choose one of ',
                colnames(antibiotics) %>% paste(collapse = ","), '.'), call. = FALSE)
  }

  abcode <- as.character(abcode)

  for (i in 1:length(abcode)) {
    drug <- abcode[i]
    if (!grepl('+', drug, fixed = TRUE) & !grepl(' en ', drug, fixed = TRUE)) {
      # only 1 drug
      if (drug %in% (antibiotics %>% pull(from))) {
        abcode[i] <-
          antibiotics %>%
          filter(.[, from] == drug) %>%
          select(to) %>%
          slice(1) %>%
          as.character()
      } else {
        # not found
        warning('Code "', drug, '" not found in antibiotics list.', call. = FALSE)
        abcode[i] <- NA
      }
    } else {
      # more than 1 drug
      if (grepl('+', drug, fixed = TRUE)) {
        drug.group <-
          strsplit(drug, '+', fixed = TRUE) %>%
          unlist() %>%
          trimws('both')
      } else if (grepl(' en ', drug, fixed = TRUE)) {
        drug.group <-
          strsplit(drug, ' en ', fixed = TRUE) %>%
          unlist() %>%
          trimws('both')
      } else {
        warning('Invalid concat.')
        abcode[i] <- NA
        next
      }

      for (j in 1:length(drug.group)) {
        drug.group[j] <-
          antibiotics %>%
          filter(.[, from] == drug.group[j]) %>%
          select(to) %>%
          slice(1) %>%
          as.character()
        if (j > 1 & to %in% c('official', 'trivial_nl')) {
          drug.group[j] <- drug.group[j] %>% tolower()
        }
      }
      abcode[i] <- paste(drug.group, collapse = textbetween)
    }
  }

  if (tolower == TRUE) {
    abcode <- abcode %>% tolower()
  }

  abcode
}

#' Find bacteria ID based on genus/species
#'
#' Use this function to determine a valid ID based on a genus (and species). This input could be a full name (like \code{"Staphylococcus aureus"}), an abbreviated name (like \code{"S. aureus"}), or just a genus. You could also use a \code{\link{paste}} of a genus and species column to use the full name as input: \code{x = paste(df$genus, df$species)}, where \code{df} is your dataframe.
#' @param x character vector to determine \code{bactid}
#' @export
#' @importFrom dplyr %>% filter slice pull
#' @return Character (vector).
#' @seealso \code{\link{microorganisms}} for the dataframe that is being used to determine ID's.
#' @examples
#' # These examples all return "STAAUR", the ID of S. aureus:
#' guess_bactid("stau")
#' guess_bactid("STAU")
#' guess_bactid("staaur")
#' guess_bactid("S. aureus")
#' guess_bactid("S aureus")
#' guess_bactid("Staphylococcus aureus")
#' guess_bactid("MRSA") # Methicillin-resistant S. aureus
#' guess_bactid("VISA") # Vancomycin Intermediate S. aureus
guess_bactid <- function(x) {
  # remove dots and other non-text in case of "E. coli" except spaces
  x <- gsub("[^a-zA-Z ]+", "", x)
  # but spaces before and after should be omitted
  x <- trimws(x, which = "both")
  x.bak <- x
  # replace space by regex sign
  x <- gsub(" ", ".*", x, fixed = TRUE)
  # add start and stop
  x_species <- paste(x, 'species')
  x <- paste0('^', x, '$')

  for (i in 1:length(x)) {
    if (tolower(x[i]) == '^e.*coli$') {
      # avoid detection of Entamoeba coli in case of E. coli
      x[i] <- 'Escherichia coli'
    }
    if (tolower(x[i]) == '^h.*influenzae$') {
      # avoid detection of Haematobacter influenzae in case of H. influenzae
      x[i] <- 'Haemophilus influenzae'
    }
    if (tolower(x[i]) == '^st.*au$'
        | tolower(x[i]) == '^stau$'
        | tolower(x[i]) == '^staaur$') {
      # avoid detection of Staphylococcus auricularis in case of S. aureus
      x[i] <- 'Staphylococcus aureus'
    }
    if (tolower(x[i]) == '^p.*aer$') {
      # avoid detection of Pasteurella aerogenes in case of Pseudomonas aeruginosa
      x[i] <- 'Pseudomonas aeruginosa'
    }

    # translate known trivial names to genus+species
    if (toupper(x.bak[i]) == 'MRSA'
        | toupper(x.bak[i]) == 'VISA'
        | toupper(x.bak[i]) == 'VRSA') {
      x[i] <- 'Staphylococcus aureus'
    }
    if (toupper(x.bak[i]) == 'MRSE') {
      x[i] <- 'Staphylococcus epidermidis'
    }
    if (toupper(x.bak[i]) == 'VRE') {
      x[i] <- 'Enterococcus'
    }
    if (toupper(x.bak[i]) == 'MRPA') {
      # multi resistant P. aeruginosa
      x[i] <- 'Pseudomonas aeruginosa'
    }
    if (toupper(x.bak[i]) == 'PISP'
        | toupper(x.bak[i]) == 'PRSP') {
      # peni resistant S. pneumoniae
      x[i] <- 'Streptococcus pneumoniae'
    }
    if (toupper(x.bak[i]) == 'VISP'
        | toupper(x.bak[i]) == 'VRSP') {
      # vanco resistant S. pneumoniae
      x[i] <- 'Streptococcus pneumoniae'
    }

    # let's try the ID's first
    found <- AMR::microorganisms %>% filter(bactid == x.bak[i])

    if (nrow(found) == 0) {
      # now try exact match
      found <- AMR::microorganisms %>% filter(fullname == x[i])
    }
    if (nrow(found) == 0) {
      # try any match
      found <- AMR::microorganisms %>% filter(fullname %like% x[i])
    }
    if (nrow(found) == 0) {
      # try only genus, with 'species' attached
      found <- AMR::microorganisms %>% filter(fullname %like% x_species[i])
    }
    if (nrow(found) == 0) {
      # search for GLIMS code
      if (toupper(x.bak[i]) %in% toupper(AMR::microorganisms.umcg$mocode)) {
        found <- AMR::microorganisms.umcg %>% filter(toupper(mocode) == toupper(x.bak[i]))
      }
    }
    if (nrow(found) == 0) {
      # try splitting of characters and then find ID
      # like esco = E. coli, klpn = K. pneumoniae, stau = S. aureus
      x_split <- x
      x_length <- nchar(x.bak[i])
      x_split[i] <- paste0(x.bak[i] %>% substr(1, x_length / 2) %>% trimws(),
                     '.* ',
                     x.bak[i] %>% substr((x_length / 2) + 1, x_length) %>% trimws())
      found <- AMR::microorganisms %>% filter(fullname %like% paste0('^', x_split[i]))
    }
    if (nrow(found) == 0) {
      # try any match with text before and after original search string
      # so "negative rods" will be "GNR"
      if (x.bak[i] %like% "^Gram") {
        x.bak[i] <- gsub("^Gram", "", x.bak[i], ignore.case = TRUE)
        # remove leading and trailing spaces again
        x.bak[i] <- trimws(x.bak[i], which = "both")
      }
      found <- AMR::microorganisms %>% filter(fullname %like% x.bak[i])
    }

    if (nrow(found) != 0) {
      x[i] <- found %>%
        slice(1) %>%
        pull(bactid)
    } else {
      x[i] <- ""
    }
  }
  x
}