mirror of https://github.com/msberends/AMR.git
as.mo speedup: assigned to namespace
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@ -1,6 +1,6 @@
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Package: AMR
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Version: 0.4.0.9007
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Date: 2018-10-23
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Date: 2018-10-29
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Title: Antimicrobial Resistance Analysis
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Authors@R: c(
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person(
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81
R/mo.R
81
R/mo.R
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@ -44,7 +44,7 @@
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#' | | | ----> subspecies, a 3-4 letter acronym
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#' | | ----> species, a 3-4 letter acronym
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#' | ----> genus, a 5-7 letter acronym, mostly without vowels
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#' ----> taxonomic kingdom, either Bacteria (B), Fungi (F) or Protozoa (P)
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#' ----> taxonomic kingdom, either B (Bacteria), F (Fungi) or P (Protozoa)
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#' }
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#'
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#' Use the \code{\link{mo_property}} functions to get properties based on the returned code, see Examples.
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@ -176,10 +176,11 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain =
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# remove empty values (to later fill them in again)
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x <- x[!is.na(x) & !is.null(x) & !identical(x, "")]
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MOs <- NULL # will be set later, if needed
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MOs_mostprevalent <- NULL # will be set later, if needed
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MOs_allothers <- NULL # will be set later, if needed
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MOs_old <- NULL # will be set later, if needed
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# These data.tables are available because of .onAttach:
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# MOs
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# MOs_mostprevalent
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# MOs_allothers
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# MOs_old
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# defined df to check for
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if (!is.null(reference_df)) {
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@ -232,10 +233,6 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain =
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)
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} else {
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MOs <- as.data.table(AMR::microorganisms)
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setkey(MOs, prevalence, tsn)
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MOs_mostprevalent <- MOs[prevalence != 9999,]
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x_backup <- trimws(x, which = "both")
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x_species <- paste(x_backup, "species")
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# translate to English for supported languages of mo_property
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@ -421,17 +418,20 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain =
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next
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}
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# try splitting of characters and then find ID ----
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# like esco = E. coli, klpn = K. pneumoniae, stau = S. aureus
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x_split <- x
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x_length <- nchar(x_trimmed[i])
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x_split[i] <- paste0(x_trimmed[i] %>% substr(1, x_length / 2) %>% trimws(),
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'.* ',
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x_trimmed[i] %>% substr((x_length / 2) + 1, x_length) %>% trimws())
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found <- MOs_mostprevalent[fullname %like% paste0('^', x_split[i]), ..property][[1]]
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if (length(found) > 0) {
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x[i] <- found[1L]
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next
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# try splitting of characters in the middle and then find ID ----
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# only when text length is 6 or lower
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# like esco = E. coli, klpn = K. pneumoniae, stau = S. aureus, staaur = S. aureus
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if (nchar(x_trimmed[i]) <= 6) {
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x_split <- x
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x_length <- nchar(x_trimmed[i])
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x_split[i] <- paste0(x_trimmed[i] %>% substr(1, x_length / 2) %>% trimws(),
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'.* ',
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x_trimmed[i] %>% substr((x_length / 2) + 1, x_length) %>% trimws())
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found <- MOs_mostprevalent[fullname %like% paste0('^', x_split[i]), ..property][[1]]
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if (length(found) > 0) {
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x[i] <- found[1L]
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next
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}
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}
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# try any match with text before and after original search string ----
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@ -450,10 +450,6 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain =
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# }
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# THEN TRY ALL OTHERS ----
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if (is.null(MOs_allothers)) {
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MOs_allothers <- MOs[prevalence == 9999,]
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}
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found <- MOs_allothers[tolower(fullname) == tolower(x_backup[i]), ..property][[1]]
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# most probable: is exact match in fullname
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if (length(found) > 0) {
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@ -508,17 +504,20 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain =
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next
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}
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# try splitting of characters and then find ID ----
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# like esco = E. coli, klpn = K. pneumoniae, stau = S. aureus
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x_split <- x
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x_length <- nchar(x_trimmed[i])
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x_split[i] <- paste0(x_trimmed[i] %>% substr(1, x_length / 2) %>% trimws(),
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'.* ',
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x_trimmed[i] %>% substr((x_length / 2) + 1, x_length) %>% trimws())
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found <- MOs_allothers[fullname %like% paste0('^', x_split[i]), ..property][[1]]
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if (length(found) > 0) {
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x[i] <- found[1L]
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next
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# try splitting of characters in the middle and then find ID ----
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# only when text length is 6 or lower
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# like esco = E. coli, klpn = K. pneumoniae, stau = S. aureus, staaur = S. aureus
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if (nchar(x_trimmed[i]) <= 6) {
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x_split <- x
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x_length <- nchar(x_trimmed[i])
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x_split[i] <- paste0(x_trimmed[i] %>% substr(1, x_length / 2) %>% trimws(),
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'.* ',
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x_trimmed[i] %>% substr((x_length / 2) + 1, x_length) %>% trimws())
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found <- MOs_allothers[fullname %like% paste0('^', x_split[i]), ..property][[1]]
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if (length(found) > 0) {
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x[i] <- found[1L]
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next
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}
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}
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# # try any match with text before and after original search string ----
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@ -539,10 +538,6 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain =
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# MISCELLANEOUS ----
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# look for old taxonomic names ----
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if (is.null(MOs_old)) {
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MOs_old <- as.data.table(AMR::microorganisms.old)
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setkey(MOs_old, name, tsn_new)
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}
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found <- MOs_old[tolower(name) == tolower(x_backup[i])
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| tsn == x_trimmed[i]
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| name %like% x_withspaces[i],]
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@ -604,10 +599,6 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain =
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if (Becker == TRUE | Becker == "all") {
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# See Source. It's this figure:
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# https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4187637/figure/F3/
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if (is.null(MOs)) {
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MOs <- as.data.table(AMR::microorganisms)
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setkey(MOs, prevalence, tsn)
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}
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MOs_staph <- MOs[genus == "Staphylococcus"]
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setkey(MOs_staph, species)
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CoNS <- MOs_staph[species %in% c("arlettae", "auricularis", "capitis",
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@ -635,10 +626,6 @@ exec_as.mo <- function(x, Becker = FALSE, Lancefield = FALSE, allow_uncertain =
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# Lancefield ----
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if (Lancefield == TRUE | Lancefield == "all") {
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if (is.null(MOs)) {
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MOs <- as.data.table(AMR::microorganisms)
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setkey(MOs, prevalence, tsn)
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}
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# group A - S. pyogenes
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x[x == MOs[mo == 'B_STRPTC_PYO', ..property][[1]][1L]] <- MOs[mo == 'B_STRPTC_GRA', ..property][[1]][1L]
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# group B - S. agalactiae
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25
R/zzz.R
25
R/zzz.R
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@ -18,7 +18,7 @@
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#' The \code{AMR} Package
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#'
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#' Welcome to the \code{AMR} package. This page gives some additional contact information abount the authors.
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#' Welcome to the \code{AMR} package. This page gives some additional contact information about the authors.
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#' @details
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#' This package was intended to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and work with antibiotic properties by using evidence-based methods.
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#'
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@ -39,7 +39,7 @@
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#' 9700 RB Groningen
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#'
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#' If you have found a bug, please file a new issue at: \cr
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#' \url{https://github.com/msberends/AMR/issues}
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#' \url{https://gitlab.com/msberends/AMR/issues}
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#' @name AMR
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#' @rdname AMR
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NULL
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@ -47,3 +47,24 @@ NULL
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.onLoad <- function(libname, pkgname) {
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backports::import(pkgname)
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}
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.onAttach <- function(libname, pkgname) {
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# save data.tables to improve speed of as.mo:
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MOs <- data.table::as.data.table(AMR::microorganisms)
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data.table::setkey(MOs, prevalence, tsn)
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base::assign(x = "MOs",
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value = MOs,
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envir = base::as.environment("package:AMR"))
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base::assign(x = "MOs_mostprevalent",
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value = MOs[prevalence != 9999,],
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envir = base::as.environment("package:AMR"))
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base::assign(x = "MOs_allothers",
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value = MOs[prevalence == 9999,],
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envir = base::as.environment("package:AMR"))
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base::assign(x = "MOs_old",
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value = data.table::as.data.table(AMR::microorganisms.old),
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envir = base::as.environment("package:AMR"))
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}
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@ -4,7 +4,7 @@
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\alias{AMR}
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\title{The \code{AMR} Package}
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\description{
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Welcome to the \code{AMR} package. This page gives some additional contact information abount the authors.
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Welcome to the \code{AMR} package. This page gives some additional contact information about the authors.
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}
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\details{
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This package was intended to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and work with antibiotic properties by using evidence-based methods.
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@ -31,6 +31,6 @@ Post Office Box 30001 \cr
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9700 RB Groningen
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If you have found a bug, please file a new issue at: \cr
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\url{https://github.com/msberends/AMR/issues}
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\url{https://gitlab.com/msberends/AMR/issues}
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}
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@ -49,7 +49,7 @@ A microbial ID from this package (class: \code{mo}) typically looks like these e
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| | | ----> subspecies, a 3-4 letter acronym
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| | ----> species, a 3-4 letter acronym
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| ----> genus, a 5-7 letter acronym, mostly without vowels
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----> taxonomic kingdom, either Bacteria (B), Fungi (F) or Protozoa (P)
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----> taxonomic kingdom, either B (Bacteria), F (Fungi) or P (Protozoa)
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}
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Use the \code{\link{mo_property}} functions to get properties based on the returned code, see Examples.
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