diff --git a/DESCRIPTION b/DESCRIPTION index 7c259842..b7a7e584 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: AMR -Version: 0.5.0.9021 -Date: 2019-03-09 +Version: 0.5.0.9022 +Date: 2019-03-12 Title: Antimicrobial Resistance Analysis Authors@R: c( person( diff --git a/NEWS.md b/NEWS.md index a8cedcf8..77b96a89 100755 --- a/NEWS.md +++ b/NEWS.md @@ -24,7 +24,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git * Support for data from [WHONET](https://whonet.org/) and [EARS-Net](https://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net) (European Antimicrobial Resistance Surveillance Network): * Exported files from WHONET can be read and used in this package. For functions like `first_isolate()` and `eucast_rules()`, all parameters will be filled in automatically. * This package now knows all antibiotic abbrevations by EARS-Net (which are also being used by WHONET) - the `antibiotics` data set now contains a column `ears_net`. - * The function `as.mo()` now knows all WHONET species abbreviations too, because more than 1,600 microbial abbreviations were added to the `microorganisms.codes` data set. + * The function `as.mo()` now knows all WHONET species abbreviations too, because almost 2,000 microbial abbreviations were added to the `microorganisms.codes` data set. * New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class: ```r filter_aminoglycosides() @@ -100,8 +100,29 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git * Functions `atc_ddd()` and `atc_groups()` have been renamed `atc_online_ddd()` and `atc_online_groups()`. The old functions are deprecated and will be removed in a future version. * Function `guess_mo()` is now deprecated in favour of `as.mo()` and will be removed in future versions * Function `guess_atc()` is now deprecated in favour of `as.atc()` and will be removed in future versions -* Improvements for `as.mo()`:\ - * Incoercible results will now be considered 'unknown', MO code `UNKNOWN`. Properties of these will be translated on foreign systems in all language already previously supported: German, Dutch, French, Italian, Spanish and Portuguese: +* Improvements for `as.mo()`: + * Now handles incorrect spelling like `i` instead of `y` and `f` instead of `ph`: + ```r + # mo_fullname() uses as.mo() internally + + mo_fullname("Sthafilokockus aaureuz") + #> [1] "Staphylococcus aureus" + + mo_fullname("S. klossi") + #> [1] "Staphylococcus kloosii" + ``` + * Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default `allow_uncertain = TRUE` is equal to uncertainty level 2. Run `?as.mo` for more info about these levels. + ```r + # equal: + as.mo(..., allow_uncertain = TRUE) + as.mo(..., allow_uncertain = 2) + + # also equal: + as.mo(..., allow_uncertain = FALSE) + as.mo(..., allow_uncertain = 0) + ``` + Using `as.mo(..., allow_uncertain = 3)` could lead to very unreliable results. + * Incoercible results will now be considered 'unknown', MO code `UNKNOWN`. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese: ```r mo_genus("qwerty", language = "es") # Warning: @@ -164,6 +185,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git * Automatic parameter filling for `mdro()`, `key_antibiotics()` and `eucast_rules()` * Updated examples for resistance prediction (`resistance_predict()` function) * Fix for `as.mic()` to support more values ending in (several) zeroes +* if using different lengths of pattern and x in `%like%`, it will now return the call #### Other * Updated licence text to emphasise GPL 2.0 and that this is an R package. diff --git a/R/data.R b/R/data.R index 3bfacf79..ace145ef 100755 --- a/R/data.R +++ b/R/data.R @@ -188,7 +188,7 @@ catalogue_of_life <- list( #' Translation table for microorganism codes #' #' A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with \code{\link{set_mo_source}}. -#' @format A \code{\link{data.frame}} with 4,731 observations and 2 variables: +#' @format A \code{\link{data.frame}} with 5,171 observations and 2 variables: #' \describe{ #' \item{\code{certe}}{Commonly used code of a microorganism} #' \item{\code{mo}}{ID of the microorganism in the \code{\link{microorganisms}} data set} diff --git a/R/like.R b/R/like.R index 7e3f4d08..f606c986 100755 --- a/R/like.R +++ b/R/like.R @@ -56,7 +56,7 @@ like <- function(x, pattern) { if (length(pattern) > 1) { if (length(x) != length(pattern)) { pattern <- pattern[1] - warning('only the first element of argument `pattern` used for `%like%`', call. = FALSE) + warning('only the first element of argument `pattern` used for `%like%`', call. = TRUE) } else { # x and pattern are of same length, so items with each other res <- vector(length = length(pattern)) diff --git a/R/mo.R b/R/mo.R index 5cfc5b9b..953b6aac 100755 --- a/R/mo.R +++ b/R/mo.R @@ -21,7 +21,7 @@ #' Transform to microorganism ID #' -#' Use this function to determine a valid microorganism ID (\code{mo}). Determination is done using intelligent rules and the complete taxonomic kingdoms Archaea, Bacteria, Protozoa, Viruses and most microbial species from the kingdom Fungi (see Source), so the input can be almost anything: a full name (like \code{"Staphylococcus aureus"}), an abbreviated name (like \code{"S. aureus"}), an abbreviation known in the field (like \code{"MRSA"}), or just a genus. You could also \code{\link{select}} a genus and species column, zie Examples. +#' Use this function to determine a valid microorganism ID (\code{mo}). Determination is done using intelligent rules and the complete taxonomic kingdoms Bacteria, Chromista, Protozoa, Archaea, Viruses, and most microbial species from the kingdom Fungi (see Source). The input can be almost anything: a full name (like \code{"Staphylococcus aureus"}), an abbreviated name (like \code{"S. aureus"}), an abbreviation known in the field (like \code{"MRSA"}), or just a genus. Please see Examples. #' @param x a character vector or a \code{data.frame} with one or two columns #' @param Becker a logical to indicate whether \emph{Staphylococci} should be categorised into Coagulase Negative \emph{Staphylococci} ("CoNS") and Coagulase Positive \emph{Staphylococci} ("CoPS") instead of their own species, according to Karsten Becker \emph{et al.} [1]. #' @@ -29,7 +29,7 @@ #' @param Lancefield a logical to indicate whether beta-haemolytic \emph{Streptococci} should be categorised into Lancefield groups instead of their own species, according to Rebecca C. Lancefield [2]. These \emph{Streptococci} will be categorised in their first group, e.g. \emph{Streptococcus dysgalactiae} will be group C, although officially it was also categorised into groups G and L. #' #' This excludes \emph{Enterococci} at default (who are in group D), use \code{Lancefield = "all"} to also categorise all \emph{Enterococci} as group D. -#' @param allow_uncertain a logical to indicate whether the input should be checked for less possible results, see Details +#' @param allow_uncertain a logical (\code{TRUE} or \code{FALSE}) or a value between 0 and 3 to indicate whether the input should be checked for less possible results, see Details #' @param reference_df a \code{data.frame} to use for extra reference when translating \code{x} to a valid \code{mo}. See \code{\link{set_mo_source}} and \code{\link{get_mo_source}} to automate the usage of your own codes (e.g. used in your analysis or organisation). #' @rdname as.mo #' @aliases mo @@ -58,9 +58,9 @@ #' \strong{Intelligent rules} \cr #' This function uses intelligent rules to help getting fast and logical results. It tries to find matches in this order: #' \itemize{ -#' \item{Taxonomic kingdom: it first searches in Bacteria, then Fungi, then Protozoa} -#' \item{Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones (see section \emph{Microbial prevalence of pathogens in humans})} #' \item{Valid MO codes and full names: it first searches in already valid MO code and known genus/species combinations} +#' \item{Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones (see \emph{Microbial prevalence of pathogens in humans} below)} +#' \item{Taxonomic kingdom: it first searches in Bacteria/Chromista, then Fungi, then Protozoa, then Viruses} #' \item{Breakdown of input values: from here it starts to breakdown input values to find possible matches} #' } #' @@ -73,15 +73,19 @@ #' This means that looking up human pathogenic microorganisms takes less time than looking up human non-pathogenic microorganisms. #' #' \strong{Uncertain results} \cr -#' When using \code{allow_uncertain = TRUE} (which is the default setting), it will use additional rules if all previous rules failed to get valid results. These are: +#' The algorithm can additionally use three different levels of uncertainty to guess valid results. The default is \code{allow_uncertain = TRUE}, which is uqual to uncertainty level 2. Using \code{allow_uncertain = FALSE} will skip all of these additional rules: #' \itemize{ -#' \item{It tries to look for previously accepted (but now invalid) taxonomic names} -#' \item{It strips off values between brackets and the brackets itself, and re-evaluates the input with all previous rules} -#' \item{It strips off words from the end one by one and re-evaluates the input with all previous rules} -#' \item{It strips off words from the start one by one and re-evaluates the input with all previous rules} -#' \item{It tries to look for some manual changes which are not (yet) published to the Catalogue of Life (like \emph{Propionibacterium} being \emph{Cutibacterium})} +#' \item{(uncertainty level 1): It tries to look for only matching genera} +#' \item{(uncertainty level 1): It tries to look for previously accepted (but now invalid) taxonomic names} +#' \item{(uncertainty level 1): It tries to look for some manual changes which are not (yet) published to the Catalogue of Life (like \emph{Propionibacterium} being \emph{Cutibacterium})} +#' \item{(uncertainty level 2): It strips off values between brackets and the brackets itself, and re-evaluates the input with all previous rules} +#' \item{(uncertainty level 2): It strips off words from the end one by one and re-evaluates the input with all previous rules} +#' \item{(uncertainty level 3): It strips off words from the start one by one and re-evaluates the input with all previous rules} +#' \item{(uncertainty level 3): It tries any part of the name} #' } #' +#' You can also use e.g. \code{as.mo(..., allow_uncertain = 1)} to only allow up to level 1 uncertainty. +#' #' Examples: #' \itemize{ #' \item{\code{"Streptococcus group B (known as S. agalactiae)"}. The text between brackets will be removed and a warning will be thrown that the result \emph{Streptococcus group B} (\code{B_STRPT_GRB}) needs review.} @@ -96,7 +100,7 @@ #' Use \code{mo_renamed()} to get a vector with all values that could be coerced based on an old, previously accepted taxonomic name. #' #' \strong{Microbial prevalence of pathogens in humans} \cr -#' The intelligent rules takes into account microbial prevalence of pathogens in humans. It uses three groups and every (sub)species is in the group it matches first. These groups are: +#' The intelligent rules takes into account microbial prevalence of pathogens in humans. It uses three groups and all (sub)species are in only one group. These groups are: #' \itemize{ #' \item{1 (most prevalent): class is Gammaproteobacteria \strong{or} genus is one of: \emph{Enterococcus}, \emph{Staphylococcus}, \emph{Streptococcus}.} #' \item{2: phylum is one of: Proteobacteria, Firmicutes, Actinobacteria, Sarcomastigophora \strong{or} genus is one of: \emph{Aspergillus}, \emph{Bacteroides}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Chryseobacterium}, \emph{Cryptococcus}, \emph{Elisabethkingia}, \emph{Flavobacterium}, \emph{Fusobacterium}, \emph{Giardia}, \emph{Leptotrichia}, \emph{Mycoplasma}, \emph{Prevotella}, \emph{Rhodotorula}, \emph{Treponema}, \emph{Trichophyton}, \emph{Ureaplasma}.} @@ -130,6 +134,7 @@ #' as.mo("S aureus") #' as.mo("Staphylococcus aureus") #' as.mo("Staphylococcus aureus (MRSA)") +#' as.mo("Sthafilokkockus aaureuz") # handles incorrect spelling #' as.mo("MRSA") # Methicillin Resistant S. aureus #' as.mo("VISA") # Vancomycin Intermediate S. aureus #' as.mo("VRSA") # Vancomycin Resistant S. aureus @@ -202,8 +207,8 @@ as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain = TRUE, ) } else if (all(x %in% AMR::microorganisms$mo) - & isFALSE(Becker) - & isFALSE(Lancefield)) { + & isFALSE(Becker) + & isFALSE(Lancefield)) { y <- x } else if (all(tolower(x) %in% microorganismsDT$fullname_lower) @@ -284,6 +289,15 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, fullname = character(0), mo = character(0)) failures <- character(0) + if (isTRUE(allow_uncertain)) { + # default to uncertainty level 2 + allow_uncertain <- 2 + } else { + allow_uncertain <- as.integer(allow_uncertain) + if (!allow_uncertain %in% c(0:3)) { + stop("`allow_uncertain` must be a number between 0 (none) and 3 (all), or TRUE (= 2) or FALSE (= 0).", call. = FALSE) + } + } x_input <- x # already strip leading and trailing spaces x <- trimws(x, which = "both") @@ -387,6 +401,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, # remove spp and species x <- trimws(gsub(" +(spp.?|ssp.?|sp.? |ss ?.?|subsp.?|subspecies|biovar |serovar |species)", " ", x_backup, ignore.case = TRUE), which = "both") + x_backup_without_spp <- x x_species <- paste(x, "species") # translate to English for supported languages of mo_property x <- gsub("(Gruppe|gruppe|groep|grupo|gruppo|groupe)", "group", x, ignore.case = TRUE) @@ -400,12 +415,21 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, x <- gsub("(alpha|beta|gamma) ha?emoly", "\\1-haemoly", x) # remove genus as first word x <- gsub("^Genus ", "", x) + # allow characters that resemble others + x <- gsub("[iy]+", "[iy]+", x, ignore.case = TRUE) + x <- gsub("[sz]+", "[sz]+", x, ignore.case = TRUE) + x <- gsub("(c|k|q|qu)+", "(c|k|q|qu)+", x, ignore.case = TRUE) + x <- gsub("(ph|f|v)+", "(ph|f|v)+", x, ignore.case = TRUE) + x <- gsub("(th|t)+", "(th|t)+", x, ignore.case = TRUE) + x <- gsub("a+", "a+", x, ignore.case = TRUE) + x <- gsub("e+", "e+", x, ignore.case = TRUE) + x <- gsub("o+", "o+", x, ignore.case = TRUE) # but spaces before and after should be omitted x <- trimws(x, which = "both") x_trimmed <- x x_trimmed_species <- paste(x_trimmed, "species") - x_trimmed_without_group <- gsub(" group$", "", x_trimmed, ignore.case = TRUE) + x_trimmed_without_group <- gsub(" gro.u.p$", "", x_trimmed, ignore.case = TRUE) # remove last part from "-" or "/" x_trimmed_without_group <- gsub("(.*)[-/].*", "\\1", x_trimmed_without_group) # replace space and dot by regex sign @@ -423,6 +447,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, # cat(paste0('x_withspaces_end_only "', x_withspaces_end_only, '"\n')) # cat(paste0('x_withspaces_start_end "', x_withspaces_start_end, '"\n')) # cat(paste0('x_backup "', x_backup, '"\n')) + # cat(paste0('x_backup_without_spp "', x_backup_without_spp, '"\n')) # cat(paste0('x_trimmed "', x_trimmed, '"\n')) # cat(paste0('x_trimmed_species "', x_trimmed_species, '"\n')) # cat(paste0('x_trimmed_without_group "', x_trimmed_without_group, '"\n')) @@ -440,12 +465,19 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, next } - if (any(x_trimmed[i] %in% c(NA, "", "xxx", "con"))) { + found <- microorganismsDT[fullname_lower %in% tolower(c(x_backup[i], x_backup_without_spp[i])), ..property][[1]] + # most probable: is exact match in fullname + if (length(found) > 0) { + x[i] <- found[1L] + next + } + + if (any(x_backup_without_spp[i] %in% c(NA, "", "xxx", "con"))) { x[i] <- NA_character_ next } - if (tolower(x_trimmed[i]) %in% c("other", "none", "unknown")) { + if (tolower(x_backup_without_spp[i]) %in% c("other", "none", "unknown")) { # empty and nonsense values, ignore without warning x[i] <- microorganismsDT[mo == "UNKNOWN", ..property][[1]] next @@ -472,7 +504,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, next } - if (x_trimmed[i] %like% "virus") { + if (x_backup_without_spp[i] %like% "virus") { # there is no fullname like virus, so don't try to coerce it x[i] <- microorganismsDT[mo == "UNKNOWN", ..property][[1]] failures <- c(failures, x_backup[i]) @@ -481,100 +513,100 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, # translate known trivial abbreviations to genus + species ---- if (!is.na(x_trimmed[i])) { - if (toupper(x_trimmed[i]) %in% c('MRSA', 'MSSA', 'VISA', 'VRSA')) { + if (toupper(x_backup_without_spp[i]) %in% c('MRSA', 'MSSA', 'VISA', 'VRSA')) { x[i] <- microorganismsDT[mo == 'B_STPHY_AUR', ..property][[1]][1L] next } - if (toupper(x_trimmed[i]) %in% c('MRSE', 'MSSE')) { + if (toupper(x_backup_without_spp[i]) %in% c('MRSE', 'MSSE')) { x[i] <- microorganismsDT[mo == 'B_STPHY_EPI', ..property][[1]][1L] next } - if (toupper(x_trimmed[i]) == "VRE" - | x_trimmed[i] %like% '(enterococci|enterokok|enterococo)[a-z]*?$') { + if (toupper(x_backup_without_spp[i]) == "VRE" + | x_backup_without_spp[i] %like% '(enterococci|enterokok|enterococo)[a-z]*?$') { x[i] <- microorganismsDT[mo == 'B_ENTRC', ..property][[1]][1L] next } - if (toupper(x_trimmed[i]) %in% c("EHEC", "EPEC", "EIEC", "STEC", "ATEC")) { + if (toupper(x_backup_without_spp[i]) %in% c("EHEC", "EPEC", "EIEC", "STEC", "ATEC")) { x[i] <- microorganismsDT[mo == 'B_ESCHR_COL', ..property][[1]][1L] next } - if (toupper(x_trimmed[i]) == 'MRPA') { + if (toupper(x_backup_without_spp[i]) == 'MRPA') { # multi resistant P. aeruginosa x[i] <- microorganismsDT[mo == 'B_PSDMN_AER', ..property][[1]][1L] next } - if (toupper(x_trimmed[i]) == 'CRS' - | toupper(x_trimmed[i]) == 'CRSM') { + if (toupper(x_backup_without_spp[i]) == 'CRS' + | toupper(x_backup_without_spp[i]) == 'CRSM') { # co-trim resistant S. maltophilia x[i] <- microorganismsDT[mo == 'B_STNTR_MAL', ..property][[1]][1L] next } - if (toupper(x_trimmed[i]) %in% c('PISP', 'PRSP', 'VISP', 'VRSP')) { + if (toupper(x_backup_without_spp[i]) %in% c('PISP', 'PRSP', 'VISP', 'VRSP')) { # peni I, peni R, vanco I, vanco R: S. pneumoniae x[i] <- microorganismsDT[mo == 'B_STRPT_PNE', ..property][[1]][1L] next } - if (x_trimmed[i] %like% '^G[ABCDFGHK]S$') { + if (x_backup_without_spp[i] %like% '^G[ABCDFGHK]S$') { # Streptococci, like GBS = Group B Streptococci (B_STRPT_GRB) - x[i] <- microorganismsDT[mo == gsub("G([ABCDFGHK])S", "B_STRPT_GR\\1", x_trimmed[i], ignore.case = TRUE), ..property][[1]][1L] + x[i] <- microorganismsDT[mo == gsub("G([ABCDFGHK])S", "B_STRPT_GR\\1", x_backup_without_spp[i], ignore.case = TRUE), ..property][[1]][1L] next } - if (x_trimmed[i] %like% '(streptococ|streptokok).* [ABCDFGHK]$') { + if (x_backup_without_spp[i] %like% '(streptococ|streptokok).* [ABCDFGHK]$') { # Streptococci in different languages, like "estreptococos grupo B" - x[i] <- microorganismsDT[mo == gsub(".*(streptococ|streptokok|estreptococ).* ([ABCDFGHK])$", "B_STRPT_GR\\2", x_trimmed[i], ignore.case = TRUE), ..property][[1]][1L] + x[i] <- microorganismsDT[mo == gsub(".*(streptococ|streptokok|estreptococ).* ([ABCDFGHK])$", "B_STRPT_GR\\2", x_backup_without_spp[i], ignore.case = TRUE), ..property][[1]][1L] next } - if (x_trimmed[i] %like% 'group [ABCDFGHK] (streptococ|streptokok|estreptococ)') { + if (x_backup_without_spp[i] %like% 'group [ABCDFGHK] (streptococ|streptokok|estreptococ)') { # Streptococci in different languages, like "Group A Streptococci" - x[i] <- microorganismsDT[mo == gsub(".*group ([ABCDFGHK]) (streptococ|streptokok|estreptococ).*", "B_STRPT_GR\\1", x_trimmed[i], ignore.case = TRUE), ..property][[1]][1L] + x[i] <- microorganismsDT[mo == gsub(".*group ([ABCDFGHK]) (streptococ|streptokok|estreptococ).*", "B_STRPT_GR\\1", x_backup_without_spp[i], ignore.case = TRUE), ..property][[1]][1L] next } # CoNS/CoPS in different languages (support for German, Dutch, Spanish, Portuguese) ---- - if (x[i] %like% '[ck]oagulas[ea] negatie?[vf]' + if (x_backup_without_spp[i] %like% '[ck]oagulas[ea] negatie?[vf]' | x_trimmed[i] %like% '[ck]oagulas[ea] negatie?[vf]' - | x[i] %like% '[ck]o?ns[^a-z]?$') { + | x_backup_without_spp[i] %like% '[ck]o?ns[^a-z]?$') { # coerce S. coagulase negative x[i] <- microorganismsDT[mo == 'B_STPHY_CNS', ..property][[1]][1L] next } - if (x[i] %like% '[ck]oagulas[ea] positie?[vf]' + if (x_backup_without_spp[i] %like% '[ck]oagulas[ea] positie?[vf]' | x_trimmed[i] %like% '[ck]oagulas[ea] positie?[vf]' - | x[i] %like% '[ck]o?ps[^a-z]?$') { + | x_backup_without_spp[i] %like% '[ck]o?ps[^a-z]?$') { # coerce S. coagulase positive x[i] <- microorganismsDT[mo == 'B_STPHY_CPS', ..property][[1]][1L] next } - if (x[i] %like% 'gram[ -]?neg.*' + if (x_backup_without_spp[i] %like% 'gram[ -]?neg.*' | x_trimmed[i] %like% 'gram[ -]?neg.*') { - # coerce S. coagulase positive + # coerce Gram negatives x[i] <- microorganismsDT[mo == 'B_GRAMN', ..property][[1]][1L] next } - if (x[i] %like% 'gram[ -]?pos.*' + if (x_backup_without_spp[i] %like% 'gram[ -]?pos.*' | x_trimmed[i] %like% 'gram[ -]?pos.*') { - # coerce S. coagulase positive + # coerce Gram positives x[i] <- microorganismsDT[mo == 'B_GRAMP', ..property][[1]][1L] next } - if (grepl("[sS]almonella [A-Z][a-z]+ ?.*", x_trimmed[i], ignore.case = FALSE)) { - if (x_trimmed[i] %like% "Salmonella group") { + if (grepl("[sS]almonella [A-Z][a-z]+ ?.*", x_backup_without_spp[i], ignore.case = FALSE)) { + if (x_backup_without_spp[i] %like% "Salmonella group") { # Salmonella Group A to Z, just return S. species for now x[i] <- microorganismsDT[mo == 'B_SLMNL', ..property][[1]][1L] - notes <- c(notes, - magenta(paste0("Note: ", - italic("Salmonella"), " ", trimws(gsub("Salmonella", "", x_trimmed[i])), - " was considered ", - italic("Salmonella species"), - " (B_SLMNL)"))) + options(mo_renamed = c(getOption("mo_renamed"), + magenta(paste0("Note: ", + italic("Salmonella"), " ", trimws(gsub("Salmonella", "", x_backup_without_spp[i])), + " was considered ", + italic("Salmonella species"), + " (B_SLMNL)")))) } else { # Salmonella with capital letter species like "Salmonella Goettingen" - they're all S. enterica x[i] <- microorganismsDT[mo == 'B_SLMNL_ENT', ..property][[1]][1L] - notes <- c(notes, - magenta(paste0("Note: ", - italic("Salmonella"), " ", trimws(gsub("Salmonella", "", x_trimmed[i])), - " was considered a subspecies of ", - italic("Salmonella enterica"), - " (B_SLMNL_ENT)"))) + options(mo_renamed = c(getOption("mo_renamed"), + magenta(paste0("Note: ", + italic("Salmonella"), " ", trimws(gsub("Salmonella", "", x_backup_without_spp[i])), + " was considered a subspecies of ", + italic("Salmonella enterica"), + " (B_SLMNL_ENT)")))) } next } @@ -588,8 +620,8 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, x[i] <- found[1L] next } - if (nchar(x_trimmed[i]) >= 6) { - found <- microorganismsDT[fullname_lower %like% paste0(x_withspaces_start_only[i], "[a-z]+ species"), ..property][[1]] + if (nchar(x_backup_without_spp[i]) >= 6) { + found <- microorganismsDT[fullname_lower %like% paste0("^", x_backup_without_spp[i], "[a-z]+"), ..property][[1]] if (length(found) > 0) { x[i] <- found[1L] next @@ -621,7 +653,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, } # allow no codes less than 4 characters long, was already checked for WHONET above - if (nchar(x_trimmed[i]) < 4) { + if (nchar(x_backup_without_spp[i]) < 4) { x[i] <- microorganismsDT[mo == "UNKNOWN", ..property][[1]] failures <- c(failures, x_backup[i]) next @@ -633,22 +665,23 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, c.x_trimmed_without_group, d.x_withspaces_start_end, e.x_withspaces_start_only, - f.x_withspaces_end_only) { + f.x_withspaces_end_only, + g.x_backup_without_spp) { - found <- data_to_check[fullname_lower %in% tolower(c(a.x_backup, b.x_trimmed)), ..property][[1]] - # most probable: is exact match in fullname + # try probable: trimmed version of fullname ---- + found <- data_to_check[fullname_lower %in% tolower(g.x_backup_without_spp), ..property][[1]] if (length(found) > 0) { return(found[1L]) } - - found <- data_to_check[fullname_lower == tolower(c.x_trimmed_without_group), ..property][[1]] - if (length(found) > 0) { + found <- data_to_check[fullname_lower %like% b.x_trimmed + | fullname_lower %like% c.x_trimmed_without_group, ..property][[1]] + if (length(found) > 0 & nchar(g.x_backup_without_spp) >= 6) { return(found[1L]) } # try any match keeping spaces ---- found <- data_to_check[fullname %like% d.x_withspaces_start_end, ..property][[1]] - if (length(found) > 0 & nchar(b.x_trimmed) >= 6) { + if (length(found) > 0 & nchar(g.x_backup_without_spp) >= 6) { return(found[1L]) } @@ -658,7 +691,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, return(found[1L]) } found <- data_to_check[fullname %like% e.x_withspaces_start_only, ..property][[1]] - if (length(found) > 0 & nchar(b.x_trimmed) >= 6) { + if (length(found) > 0 & nchar(g.x_backup_without_spp) >= 6) { return(found[1L]) } @@ -671,12 +704,12 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, # try splitting of characters in the middle and then find ID ---- # only when text length is 6 or lower # like esco = E. coli, klpn = K. pneumoniae, stau = S. aureus, staaur = S. aureus - if (nchar(b.x_trimmed) <= 6) { - x_length <- nchar(b.x_trimmed) + if (nchar(g.x_backup_without_spp) <= 6) { + x_length <- nchar(g.x_backup_without_spp) x_split <- paste0("^", - b.x_trimmed %>% substr(1, x_length / 2), + g.x_backup_without_spp %>% substr(1, x_length / 2), '.* ', - b.x_trimmed %>% substr((x_length / 2) + 1, x_length)) + g.x_backup_without_spp %>% substr((x_length / 2) + 1, x_length)) found <- data_to_check[fullname %like% x_split, ..property][[1]] if (length(found) > 0) { return(found[1L]) @@ -701,7 +734,8 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, c.x_trimmed_without_group = x_trimmed_without_group[i], d.x_withspaces_start_end = x_withspaces_start_end[i], e.x_withspaces_start_only = x_withspaces_start_only[i], - f.x_withspaces_end_only = x_withspaces_end_only[i]) + f.x_withspaces_end_only = x_withspaces_end_only[i], + g.x_backup_without_spp = x_backup_without_spp[i]) if (!empty_result(x[i])) { next } @@ -712,7 +746,8 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, c.x_trimmed_without_group = x_trimmed_without_group[i], d.x_withspaces_start_end = x_withspaces_start_end[i], e.x_withspaces_start_only = x_withspaces_start_only[i], - f.x_withspaces_end_only = x_withspaces_end_only[i]) + f.x_withspaces_end_only = x_withspaces_end_only[i], + g.x_backup_without_spp = x_backup_without_spp[i]) if (!empty_result(x[i])) { next } @@ -723,7 +758,8 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, c.x_trimmed_without_group = x_trimmed_without_group[i], d.x_withspaces_start_end = x_withspaces_start_end[i], e.x_withspaces_start_only = x_withspaces_start_only[i], - f.x_withspaces_end_only = x_withspaces_end_only[i]) + f.x_withspaces_end_only = x_withspaces_end_only[i], + g.x_backup_without_spp = x_backup_without_spp[i]) if (!empty_result(x[i])) { next } @@ -752,31 +788,23 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, } # check for uncertain results ---- - if (allow_uncertain == TRUE) { + uncertain_fn <- function(a.x_backup, +b.x_trimmed, + c.x_withspaces_start_end, +d.x_withspaces_start_only, + f.x_withspaces_end_only, +g.x_backup_without_spp) { - uncertain_fn <- function(a.x_backup, b.x_trimmed, c.x_withspaces_start_end, d.x_withspaces_start_only, f.x_withspaces_end_only) { + if (allow_uncertain == 0) { + # do not allow uncertainties + return(NA_character_) + } - # (1) look for genus only, part of name ---- - if (nchar(b.x_trimmed) > 4 & !b.x_trimmed %like% " ") { - if (!grepl("^[A-Z][a-z]+", b.x_trimmed, ignore.case = FALSE)) { - # not when input is like Genustext, because then Neospora would lead to Actinokineospora - found <- microorganismsDT[fullname_lower %like% paste(b.x_trimmed, "species"), ..property][[1]] - if (length(found) > 0) { - x[i] <- found[1L] - uncertainties <<- rbind(uncertainties, - data.frame(uncertainty = 2, - input = a.x_backup, - fullname = microorganismsDT[mo == found[1L], fullname][[1]], - mo = found[1L])) - return(x) - } - } - } - - # (2) look again for old taxonomic names, now for G. species ---- + if (allow_uncertain >= 1) { + # (1) look again for old taxonomic names, now for G. species ---- found <- microorganisms.oldDT[fullname %like% c.x_withspaces_start_end | fullname %like% d.x_withspaces_start_only] - if (NROW(found) > 0 & nchar(b.x_trimmed) >= 6) { + if (NROW(found) > 0 & nchar(g.x_backup_without_spp) >= 6) { if (property == "ref") { # when property is "ref" (which is the case in mo_ref, mo_authors and mo_year), return the old value, so: # mo_ref("Chlamydia psittaci) = "Page, 1968" (with warning) @@ -798,7 +826,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, return(x) } - # (3) not yet implemented taxonomic changes in Catalogue of Life ---- + # (2) not yet implemented taxonomic changes in Catalogue of Life ---- found <- suppressMessages(suppressWarnings(exec_as.mo(TEMPORARY_TAXONOMY(b.x_trimmed), clear_options = FALSE, allow_uncertain = FALSE))) if (!empty_result(found)) { found_result <- found @@ -810,12 +838,31 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, mo = found_result[1L])) return(found[1L]) } + } + + if (allow_uncertain >= 2) { + # (3) look for genus only, part of name ---- + if (nchar(g.x_backup_without_spp) > 4 & !b.x_trimmed %like% " ") { + if (!grepl("^[A-Z][a-z]+", b.x_trimmed, ignore.case = FALSE)) { + # not when input is like Genustext, because then Neospora would lead to Actinokineospora + found <- microorganismsDT[fullname_lower %like% paste(b.x_trimmed, "species"), ..property][[1]] + if (length(found) > 0) { + x[i] <- found[1L] + uncertainties <<- rbind(uncertainties, + data.frame(uncertainty = 2, + input = a.x_backup, + fullname = microorganismsDT[mo == found[1L], fullname][[1]], + mo = found[1L])) + return(x) + } + } + } # (4) strip values between brackets ---- a.x_backup_stripped <- gsub("( *[(].*[)] *)", " ", a.x_backup) a.x_backup_stripped <- trimws(gsub(" +", " ", a.x_backup_stripped)) found <- suppressMessages(suppressWarnings(exec_as.mo(a.x_backup_stripped, clear_options = FALSE, allow_uncertain = FALSE))) - if (!empty_result(found) & nchar(b.x_trimmed) >= 6) { + if (!empty_result(found) & nchar(g.x_backup_without_spp) >= 6) { found_result <- found found <- microorganismsDT[mo == found, ..property][[1]] uncertainties <<- rbind(uncertainties, @@ -828,26 +875,30 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, # (5) try to strip off one element from end and check the remains ---- x_strip <- a.x_backup %>% strsplit(" ") %>% unlist() - if (length(x_strip) > 1 & nchar(b.x_trimmed) >= 6) { + if (length(x_strip) > 1) { for (i in 1:(length(x_strip) - 1)) { x_strip_collapsed <- paste(x_strip[1:(length(x_strip) - i)], collapse = " ") - found <- suppressMessages(suppressWarnings(exec_as.mo(x_strip_collapsed, clear_options = FALSE, allow_uncertain = FALSE))) - if (!empty_result(found)) { - found_result <- found - found <- microorganismsDT[mo == found, ..property][[1]] - uncertainties <<- rbind(uncertainties, - data.frame(uncertainty = 2, - input = a.x_backup, - fullname = microorganismsDT[mo == found_result[1L], fullname][[1]], - mo = found_result[1L])) - return(found[1L]) + if (nchar(x_strip_collapsed) >= 4) { + found <- suppressMessages(suppressWarnings(exec_as.mo(x_strip_collapsed, clear_options = FALSE, allow_uncertain = FALSE))) + if (!empty_result(found)) { + found_result <- found + found <- microorganismsDT[mo == found, ..property][[1]] + uncertainties <<- rbind(uncertainties, + data.frame(uncertainty = 2, + input = a.x_backup, + fullname = microorganismsDT[mo == found_result[1L], fullname][[1]], + mo = found_result[1L])) + return(found[1L]) + } } } } + } + if (allow_uncertain >= 3) { # (6) try to strip off one element from start and check the remains ---- x_strip <- a.x_backup %>% strsplit(" ") %>% unlist() - if (length(x_strip) > 1 & nchar(b.x_trimmed) >= 6) { + if (length(x_strip) > 1 & nchar(g.x_backup_without_spp) >= 6) { for (i in 2:(length(x_strip))) { x_strip_collapsed <- paste(x_strip[i:length(x_strip)], collapse = " ") found <- suppressMessages(suppressWarnings(exec_as.mo(x_strip_collapsed, clear_options = FALSE, allow_uncertain = FALSE))) @@ -868,7 +919,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, found <- microorganismsDT[fullname %like% f.x_withspaces_end_only] if (nrow(found) > 0) { found_result <- found[["mo"]] - if (!empty_result(found_result)) { + if (!empty_result(found_result) & nchar(g.x_backup_without_spp) >= 6) { found <- microorganismsDT[mo == found_result[1L], ..property][[1]] uncertainties <<- rbind(uncertainties, data.frame(uncertainty = 3, @@ -878,16 +929,21 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, return(found[1L]) } } - - # didn't found in uncertain results too - return(NA_character_) } - x[i] <- uncertain_fn(x_backup[i], x_trimmed[i], x_withspaces_start_end[i], x_withspaces_start_only[i], x_withspaces_end_only[i]) - if (!empty_result(x[i])) { - next - } + # didn't found in uncertain results too + return(NA_character_) } + x[i] <- uncertain_fn(x_backup[i], + x_trimmed[i], + x_withspaces_start_end[i], + x_withspaces_start_only[i], + x_withspaces_end_only[i], + x_backup_without_spp[i]) + if (!empty_result(x[i])) { + next + } + # not found ---- x[i] <- microorganismsDT[mo == "UNKNOWN", ..property][[1]] @@ -899,19 +955,19 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, failures <- failures[!failures %in% c(NA, NULL, NaN)] if (length(failures) > 0 & clear_options == TRUE) { options(mo_failures = sort(unique(failures))) - plural <- c("value", "it", "is") + plural <- c("value", "it", "was") if (n_distinct(failures) > 1) { - plural <- c("values", "them", "are") + plural <- c("values", "them", "were") } total_failures <- length(x_input[x_input %in% failures & !x_input %in% c(NA, NULL, NaN)]) total_n <- length(x_input[!x_input %in% c(NA, NULL, NaN)]) - msg <- paste0("\n", nr2char(n_distinct(failures)), " unique ", plural[1], + msg <- paste0(nr2char(n_distinct(failures)), " unique ", plural[1], " (^= ", percent(total_failures / total_n, round = 1, force_zero = TRUE), ") could not be coerced and ", plural[3], " considered 'unknown'") if (n_distinct(failures) <= 10) { msg <- paste0(msg, ": ", paste('"', unique(failures), '"', sep = "", collapse = ', ')) } - msg <- paste0(msg, ". Use mo_failures() to review ", plural[2], ".") + msg <- paste0(msg, ". Use mo_failures() to review ", plural[2], ". Edit the `allow_uncertain` parameter if needed (see ?as.mo).") warning(red(msg), call. = FALSE, immediate. = TRUE) # thus will always be shown, even if >= warnings @@ -1026,7 +1082,7 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, } empty_result <- function(x) { - x %in% c(NA, "UNKNOWN") + all(x %in% c(NA, "UNKNOWN")) } TEMPORARY_TAXONOMY <- function(x) { @@ -1124,6 +1180,9 @@ mo_uncertainties <- function() { #' @export #' @noRd print.mo_uncertainties <- function(x, ...) { + if (NROW(x) == 0) { + return(NULL) + } cat(paste0(bold(nrow(x), "unique result(s) guessed with uncertainty:"), "\n(1 = ", green("renamed"), ", 2 = ", yellow("uncertain"), diff --git a/R/zzz.R b/R/zzz.R index 78dccdcf..6d4a87df 100755 --- a/R/zzz.R +++ b/R/zzz.R @@ -25,28 +25,25 @@ backports::import(pkgname) # register data - if (!all(c("microorganismsDT", "microorganisms.oldDT") %in% ls(envir = asNamespace("AMR")))) { + microorganisms.oldDT <- as.data.table(AMR::microorganisms.old) + microorganisms.oldDT$fullname_lower <- tolower(microorganisms.oldDT$fullname) + setkey(microorganisms.oldDT, col_id, fullname) - microorganisms.oldDT <- as.data.table(AMR::microorganisms.old) - microorganisms.oldDT$fullname_lower <- tolower(microorganisms.oldDT$fullname) - setkey(microorganisms.oldDT, col_id, fullname) + assign(x = "microorganisms", + value = make(), + envir = asNamespace("AMR")) - assign(x = "microorganisms", - value = make(), - envir = asNamespace("AMR")) + assign(x = "microorganismsDT", + value = make_DT(), + envir = asNamespace("AMR")) - assign(x = "microorganismsDT", - value = make_DT(), - envir = asNamespace("AMR")) + assign(x = "microorganisms.oldDT", + value = microorganisms.oldDT, + envir = asNamespace("AMR")) - assign(x = "microorganisms.oldDT", - value = microorganisms.oldDT, - envir = asNamespace("AMR")) - - assign(x = "mo_codes_v0.5.0", - value = make_trans_tbl(), - envir = asNamespace("AMR")) - } + assign(x = "mo_codes_v0.5.0", + value = make_trans_tbl(), + envir = asNamespace("AMR")) } #' @importFrom dplyr mutate case_when @@ -88,8 +85,8 @@ make_DT <- function() { microorganismsDT <- as.data.table(make()) microorganismsDT$fullname_lower <- tolower(microorganismsDT$fullname) setkey(microorganismsDT, - kingdom, prevalence, + kingdom, fullname) microorganismsDT } diff --git a/data/microorganisms.codes.rda b/data/microorganisms.codes.rda index e5254a13..8b7b005e 100644 Binary files a/data/microorganisms.codes.rda and b/data/microorganisms.codes.rda differ diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html index f4aca6a7..5e593eff 100644 --- a/docs/LICENSE-text.html +++ b/docs/LICENSE-text.html @@ -78,7 +78,7 @@ AMR (for R) - 0.5.0.9021 + 0.5.0.9022 diff --git a/docs/articles/benchmarks.html b/docs/articles/benchmarks.html index 6848bcaa..9f9c9b39 100644 --- a/docs/articles/benchmarks.html +++ b/docs/articles/benchmarks.html @@ -40,7 +40,7 @@ AMR (for R) - 0.5.0.9021 + 0.5.0.9022 @@ -192,7 +192,7 @@

Benchmarks

Matthijs S. Berends

-

09 March 2019

+

12 March 2019

@@ -217,14 +217,14 @@ times = 10) print(S.aureus, unit = "ms", signif = 3) #> Unit: milliseconds -#> expr min lq mean median uq max neval -#> as.mo("sau") 16.60 16.60 25.2 16.80 18.00 58.3 10 -#> as.mo("stau") 31.60 31.80 44.8 32.40 72.20 76.7 10 -#> as.mo("staaur") 16.60 16.60 26.4 16.70 17.30 71.9 10 -#> as.mo("STAAUR") 16.50 16.60 16.6 16.60 16.70 16.8 10 -#> as.mo("S. aureus") 24.50 24.60 29.0 24.70 25.00 66.6 10 -#> as.mo("S. aureus") 24.30 24.60 24.6 24.60 24.70 24.9 10 -#> as.mo("Staphylococcus aureus") 7.45 7.47 11.9 7.53 7.97 50.0 10 +#> expr min lq mean median uq max neval +#> as.mo("sau") 16.70 16.8 25.70 17.00 19.60 59.7 10 +#> as.mo("stau") 39.10 39.2 43.70 39.30 40.60 80.4 10 +#> as.mo("staaur") 16.70 16.8 24.60 17.00 18.20 58.9 10 +#> as.mo("STAAUR") 16.70 16.7 22.70 16.80 17.20 74.5 10 +#> as.mo("S. aureus") 29.70 29.7 46.70 29.80 71.30 110.0 10 +#> as.mo("S. aureus") 29.60 29.7 36.10 29.70 33.10 83.7 10 +#> as.mo("Staphylococcus aureus") 7.03 7.1 7.14 7.14 7.17 7.3 10

In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 100 milliseconds, this is only 10 input values per second. The second input is the only one that has to be looked up thoroughly. All the others are known codes (the first one is a WHONET code) or common laboratory codes, or common full organism names like the last one. Full organism names are always preferred.

To achieve this speed, the as.mo function also takes into account the prevalence of human pathogenic microorganisms. The downside is of course that less prevalent microorganisms will be determined less fast. See this example for the ID of Thermus islandicus (B_THERMS_ISL), a bug probably never found before in humans:

T.islandicus <- microbenchmark(as.mo("theisl"),
@@ -235,13 +235,13 @@
                                  times = 10)
 print(T.islandicus, unit = "ms", signif = 3)
 #> Unit: milliseconds
-#>                         expr   min    lq  mean median  uq max neval
-#>              as.mo("theisl") 262.0 263.0 284.0  284.0 304 308    10
-#>              as.mo("THEISL") 263.0 264.0 293.0  304.0 306 308    10
-#>       as.mo("T. islandicus") 142.0 142.0 151.0  143.0 147 187    10
-#>      as.mo("T.  islandicus") 142.0 142.0 169.0  184.0 185 194    10
-#>  as.mo("Thermus islandicus")  67.9  68.1  93.3   90.3 116 130    10
-

That takes 7.8 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like Thermus islandicus) are almost fast - these are the most probable input from most data sets.

+#> expr min lq mean median uq max neval +#> as.mo("theisl") 417.0 419.0 450.0 460.0 464.0 474 10 +#> as.mo("THEISL") 415.0 416.0 443.0 458.0 460.0 468 10 +#> as.mo("T. islandicus") 281.0 281.0 299.0 285.0 325.0 352 10 +#> as.mo("T. islandicus") 292.0 298.0 341.0 336.0 340.0 495 10 +#> as.mo("Thermus islandicus") 66.2 66.5 75.5 66.9 68.2 112 10 +

That takes 10.9 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like Thermus islandicus) are almost fast - these are the most probable input from most data sets.

In the figure below, we compare Escherichia coli (which is very common) with Prevotella brevis (which is moderately common) and with Thermus islandicus (which is very uncommon):

par(mar = c(5, 16, 4, 2)) # set more space for left margin text (16)
 
@@ -286,9 +286,9 @@
                          times = 10)
 print(run_it, unit = "ms", signif = 3)
 #> Unit: milliseconds
-#>            expr min  lq mean median  uq max neval
-#>  mo_fullname(x) 734 810  840    817 860 973    10
-

So transforming 500,000 values (!!) of 50 unique values only takes 0.82 seconds (817 ms). You only lose time on your unique input values.

+#> expr min lq mean median uq max neval +#> mo_fullname(x) 794 834 863 844 876 1050 10 +

So transforming 500,000 values (!!) of 50 unique values only takes 0.84 seconds (844 ms). You only lose time on your unique input values.

@@ -301,9 +301,9 @@ print(run_it, unit = "ms", signif = 3) #> Unit: milliseconds #> expr min lq mean median uq max neval -#> A 11.200 11.300 11.400 11.400 11.600 11.600 10 -#> B 22.200 22.400 26.800 22.600 22.800 63.700 10 -#> C 0.328 0.564 0.525 0.568 0.577 0.591 10

+#> A 10.900 11.100 11.200 11.200 11.300 11.400 10 +#> B 27.300 27.900 28.300 28.000 28.100 31.500 10 +#> C 0.319 0.326 0.472 0.563 0.568 0.579 10

So going from mo_fullname("Staphylococcus aureus") to "Staphylococcus aureus" takes 0.0006 seconds - it doesn’t even start calculating if the result would be the same as the expected resulting value. That goes for all helper functions:

run_it <- microbenchmark(A = mo_species("aureus"),
                          B = mo_genus("Staphylococcus"),
@@ -317,14 +317,14 @@
 print(run_it, unit = "ms", signif = 3)
 #> Unit: milliseconds
 #>  expr   min    lq  mean median    uq   max neval
-#>     A 0.318 0.376 0.414  0.419 0.449 0.537    10
-#>     B 0.343 0.397 0.437  0.447 0.479 0.522    10
-#>     C 0.325 0.380 0.486  0.482 0.554 0.703    10
-#>     D 0.334 0.337 0.381  0.372 0.426 0.434    10
-#>     E 0.304 0.322 0.356  0.335 0.393 0.460    10
-#>     F 0.295 0.323 0.370  0.362 0.424 0.463    10
-#>     G 0.296 0.321 0.362  0.348 0.387 0.470    10
-#>     H 0.289 0.335 0.355  0.351 0.387 0.421    10
+#> A 0.308 0.332 0.396 0.393 0.457 0.498 10 +#> B 0.349 0.376 0.419 0.444 0.462 0.467 10 +#> C 0.351 0.398 0.529 0.555 0.628 0.702 10 +#> D 0.302 0.330 0.378 0.381 0.424 0.465 10 +#> E 0.282 0.329 0.371 0.374 0.384 0.539 10 +#> F 0.281 0.354 0.364 0.366 0.402 0.444 10 +#> G 0.275 0.309 0.347 0.351 0.380 0.420 10 +#> H 0.279 0.306 0.356 0.363 0.404 0.411 10

Of course, when running mo_phylum("Firmicutes") the function has zero knowledge about the actual microorganism, namely S. aureus. But since the result would be "Firmicutes" too, there is no point in calculating the result. And because this package ‘knows’ all phyla of all known bacteria (according to the Catalogue of Life), it can just return the initial value immediately.

@@ -351,13 +351,13 @@ print(run_it, unit = "ms", signif = 4) #> Unit: milliseconds #> expr min lq mean median uq max neval -#> en 15.57 15.87 24.21 20.71 37.98 38.78 10 -#> de 28.79 34.96 53.24 52.02 56.97 95.22 10 -#> nl 28.31 29.29 47.74 40.57 58.94 97.03 10 -#> es 28.97 30.43 42.78 34.70 51.47 72.11 10 -#> it 27.71 29.15 38.88 31.19 35.10 76.86 10 -#> fr 28.37 29.28 40.89 41.73 50.43 56.78 10 -#> pt 27.82 29.03 42.49 29.84 50.14 94.96 10
+#> en 16.61 17.17 17.23 17.28 17.38 17.56 10 +#> de 28.83 28.85 29.31 29.50 29.63 29.67 10 +#> nl 29.08 29.44 33.71 29.65 29.72 71.15 10 +#> es 28.86 29.52 38.07 29.70 30.60 72.14 10 +#> it 28.71 29.48 34.04 29.63 31.28 71.09 10 +#> fr 29.32 29.47 41.44 29.53 62.86 73.16 10 +#> pt 29.05 29.43 33.93 29.62 30.93 71.00 10

Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.

diff --git a/docs/articles/benchmarks_files/figure-html/unnamed-chunk-5-1.png b/docs/articles/benchmarks_files/figure-html/unnamed-chunk-5-1.png index a6412a79..22db0a14 100644 Binary files a/docs/articles/benchmarks_files/figure-html/unnamed-chunk-5-1.png and b/docs/articles/benchmarks_files/figure-html/unnamed-chunk-5-1.png differ diff --git a/docs/articles/index.html b/docs/articles/index.html index d4d7734d..fefc0597 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -78,7 +78,7 @@ AMR (for R) - 0.5.0.9021 + 0.5.0.9022 diff --git a/docs/authors.html b/docs/authors.html index 6c9d4a73..0cae75ad 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -78,7 +78,7 @@ AMR (for R) - 0.5.0.9021 + 0.5.0.9022 diff --git a/docs/index.html b/docs/index.html index 9735202a..131bee7f 100644 --- a/docs/index.html +++ b/docs/index.html @@ -42,7 +42,7 @@ AMR (for R) - 0.5.0.9021 + 0.5.0.9022 diff --git a/docs/news/index.html b/docs/news/index.html index 3c187f88..7bc98225 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -78,7 +78,7 @@ AMR (for R) - 0.5.0.9021 + 0.5.0.9022 @@ -267,7 +267,7 @@ This data is updated annually - check the included version with the new function
  • @@ -347,14 +347,35 @@ These functions use as.atc()
  • Functions atc_ddd() and atc_groups() have been renamed atc_online_ddd() and atc_online_groups(). The old functions are deprecated and will be removed in a future version.
  • Function guess_mo() is now deprecated in favour of as.mo() and will be removed in future versions
  • Function guess_atc() is now deprecated in favour of as.atc() and will be removed in future versions
    • -
  • Improvements for as.mo():\ +
  • Improvements for as.mo(): -
    mo_genus("qwerty", language = "es")
-# Warning: 
-# one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.
-#> [1] "(género desconocido)"
    +
    # mo_fullname() uses as.mo() internally
+
+mo_fullname("Sthafilokockus aaureuz")
+#> [1] "Staphylococcus aureus"
+
+mo_fullname("S. klossi")
+#> [1] "Staphylococcus kloosii"
    + +
    # equal:
+as.mo(..., allow_uncertain = TRUE)
+as.mo(..., allow_uncertain = 2)
+
+# also equal:
+as.mo(..., allow_uncertain = FALSE)
+as.mo(..., allow_uncertain = 0)
    +Using as.mo(..., allow_uncertain = 3) could lead to very unreliable results. + +
    mo_genus("qwerty", language = "es")
+# Warning: 
+# one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.
+#> [1] "(género desconocido)"