mirror of https://github.com/msberends/AMR.git
357 lines
12 KiB
R
357 lines
12 KiB
R
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# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis #
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# #
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# AUTHORS #
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# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
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# #
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# LICENCE #
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# This program is free software; you can redistribute it and/or modify #
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# it under the terms of the GNU General Public License version 2.0, #
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# as published by the Free Software Foundation. #
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# #
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# This program is distributed in the hope that it will be useful, #
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# but WITHOUT ANY WARRANTY; without even the implied warranty of #
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
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# GNU General Public License for more details. #
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# ==================================================================== #
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#' Class 'rsi'
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#'
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#' This transforms a vector to a new class \code{rsi}, which is an ordered factor with levels \code{S < I < R}. Invalid antimicrobial interpretations will be translated as \code{NA} with a warning.
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#' @rdname as.rsi
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#' @param x vector
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#' @return New class \code{rsi}
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#' @export
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#' @importFrom dplyr %>%
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#' @examples
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#' rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370)))
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#'
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#' rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370), "A", "B", "C"))
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as.rsi <- function(x) {
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if (is.rsi(x)) {
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x
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} else {
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x <- x %>% unlist()
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x.bak <- x
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na_before <- x[is.na(x) | x == ''] %>% length()
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x <- gsub('[^RSI]+', '', x %>% toupper())
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# needed for UMCG in cases of "S;S" but also "S;I"; the latter will be NA:
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x <- gsub('^S+$', 'S', x)
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x <- gsub('^I+$', 'I', x)
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x <- gsub('^R+$', 'R', x)
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x[!x %in% c('S', 'I', 'R')] <- NA
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na_after <- x[is.na(x) | x == ''] %>% length()
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if (na_before != na_after) {
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list_missing <- x.bak[is.na(x) & !is.na(x.bak) & x.bak != ''] %>%
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unique() %>%
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sort()
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list_missing <- paste0('"', list_missing , '"', collapse = ", ")
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warning(na_after - na_before, ' results truncated (',
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round(((na_after - na_before) / length(x)) / 100),
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'%) that were invalid antimicrobial interpretations: ',
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list_missing, call. = FALSE)
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}
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x <- x %>% toupper() %>% factor(levels = c("S", "I", "R"), ordered = TRUE)
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class(x) <- c('rsi', 'ordered', 'factor')
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x
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}
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}
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#' @rdname as.rsi
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#' @export
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#' @importFrom dplyr %>%
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is.rsi <- function(x) {
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class(x) %>% identical(c('rsi', 'ordered', 'factor'))
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}
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#' @exportMethod print.rsi
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#' @export
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#' @importFrom dplyr %>%
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#' @noRd
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print.rsi <- function(x, ...) {
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n_total <- x %>% length()
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x <- x[!is.na(x)]
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n <- x %>% length()
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S <- x[x == 'S'] %>% length()
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I <- x[x == 'I'] %>% length()
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R <- x[x == 'R'] %>% length()
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IR <- x[x %in% c('I', 'R')] %>% length()
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cat("Class 'rsi': ", n, " isolates\n", sep = '')
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cat('\n')
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cat('<NA>: ', n_total - n, '\n')
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cat('Sum of S: ', S, '\n')
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cat('Sum of IR: ', IR, '\n')
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cat('- Sum of R:', R, '\n')
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cat('- Sum of I:', I, '\n')
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cat('\n')
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print(c(
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`%S` = round((S / n) * 100, 1),
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`%IR` = round((IR / n) * 100, 1),
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`%I` = round((I / n) * 100, 1),
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`%R` = round((R / n) * 100, 1)
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))
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}
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#' @exportMethod summary.rsi
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#' @export
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#' @importFrom dplyr %>%
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#' @noRd
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summary.rsi <- function(object, ...) {
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x <- object
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n_total <- x %>% length()
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x <- x[!is.na(x)]
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n <- x %>% length()
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S <- x[x == 'S'] %>% length()
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I <- x[x == 'I'] %>% length()
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R <- x[x == 'R'] %>% length()
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IR <- x[x %in% c('I', 'R')] %>% length()
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lst <- c('rsi', n_total - n, S, IR, R, I)
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names(lst) <- c("Mode", "<NA>", "Sum S", "Sum IR", "Sum R", "Sum I")
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lst
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}
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#' @exportMethod plot.rsi
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#' @export
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#' @importFrom dplyr %>% group_by summarise filter mutate if_else
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#' @importFrom graphics plot text
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#' @noRd
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plot.rsi <- function(x, ...) {
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x_name <- deparse(substitute(x))
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data <- data.frame(x = x,
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y = 1,
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stringsAsFactors = TRUE) %>%
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group_by(x) %>%
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summarise(n = sum(y)) %>%
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filter(!is.na(x)) %>%
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mutate(s = round((n / sum(n)) * 100, 1))
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data$x <- factor(data$x, levels = c('S', 'I', 'R'), ordered = TRUE)
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ymax <- if_else(max(data$s) > 95, 105, 100)
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plot(x = data$x,
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y = data$s,
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lwd = 2,
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col = c('green', 'orange', 'red'),
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ylim = c(0, ymax),
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ylab = 'Percentage',
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xlab = 'Antimicrobial Interpretation',
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main = paste('Susceptibilty Analysis of', x_name),
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...)
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text(x = data$x,
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y = data$s + 5,
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labels = paste0(data$s, '% (n = ', data$n, ')'))
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}
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#' Class 'mic'
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#'
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#' This transforms a vector to a new class\code{mic}, which is an ordered factor valid MIC values as levels. Invalid MIC values will be translated as \code{NA} with a warning.
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#' @rdname as.mic
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#' @param x vector
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#' @param na.rm a logical indicating whether missing values should be removed
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#' @return New class \code{mic}
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#' @export
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#' @importFrom dplyr %>%
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as.mic <- function(x, na.rm = FALSE) {
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if (is.mic(x)) {
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x
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} else {
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x <- x %>% unlist()
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if (na.rm == TRUE) {
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x <- x[!is.na(x)]
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}
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x.bak <- x
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# comma to dot
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x <- gsub(',', '.', x, fixed = TRUE)
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# starting dots must start with 0
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x <- gsub('^[.]', '0.', x)
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# <=0.2560.512 should be 0.512
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x <- gsub('.*[.].*[.]', '0.', x)
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# remove ending .0
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x <- gsub('[.]0$', '', x)
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# remove all after last digit
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x <- gsub('[^0-9]$', '', x)
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# remove last zeroes
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x <- gsub('[.]?0+$', '', x)
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lvls <- c("<0.002", "<=0.002", "0.002", ">=0.002", ">0.002",
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"<0.003", "<=0.003", "0.003", ">=0.003", ">0.003",
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"<0.004", "<=0.004", "0.004", ">=0.004", ">0.004",
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"<0.006", "<=0.006", "0.006", ">=0.006", ">0.006",
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"<0.008", "<=0.008", "0.008", ">=0.008", ">0.008",
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"<0.012", "<=0.012", "0.012", ">=0.012", ">0.012",
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"<0.016", "<=0.016", "0.016", ">=0.016", ">0.016",
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"<0.023", "<=0.023", "0.023", ">=0.023", ">0.023",
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"<0.03", "<=0.03", "0.03", ">=0.03", ">0.03",
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"<0.032", "<=0.032", "0.032", ">=0.032", ">0.032",
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"<0.047", "<=0.047", "0.047", ">=0.047", ">0.047",
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"<0.05", "<=0.05", "0.05", ">=0.05", ">0.05",
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"<0.06", "<=0.06", "0.06", ">=0.06", ">0.06",
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"<0.0625", "<=0.0625", "0.0625", ">=0.0625", ">0.0625",
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"<0.064", "<=0.064", "0.064", ">=0.064", ">0.064",
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"<0.09", "<=0.09", "0.09", ">=0.09", ">0.09",
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"<0.094", "<=0.094", "0.094", ">=0.094", ">0.094",
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"<0.12", "<=0.12", "0.12", ">=0.12", ">0.12",
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"<0.125", "<=0.125", "0.125", ">=0.125", ">0.125",
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"<0.128", "<=0.128", "0.128", ">=0.128", ">0.128",
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"<0.19", "<=0.19", "0.19", ">=0.19", ">0.19",
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"<0.25", "<=0.25", "0.25", ">=0.25", ">0.25",
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"<0.256", "<=0.256", "0.256", ">=0.256", ">0.256",
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"<0.38", "<=0.38", "0.38", ">=0.38", ">0.38",
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"<0.5", "<=0.5", "0.5", ">=0.5", ">0.5",
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"<0.512", "<=0.512", "0.512", ">=0.512", ">0.512",
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"<0.75", "<=0.75", "0.75", ">=0.75", ">0.75",
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"<1", "<=1", "1", ">=1", ">1",
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"<1.5", "<=1.5", "1.5", ">=1.5", ">1.5",
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"<2", "<=2", "2", ">=2", ">2",
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"<3", "<=3", "3", ">=3", ">3",
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"<4", "<=4", "4", ">=4", ">4",
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"<6", "<=6", "6", ">=6", ">6",
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"<8", "<=8", "8", ">=8", ">8",
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"<10", "<=10", "10", ">=10", ">10",
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"<12", "<=12", "12", ">=12", ">12",
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"<16", "<=16", "16", ">=16", ">16",
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"<20", "<=20", "20", ">=20", ">20",
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"<24", "<=24", "24", ">=24", ">24",
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"<32", "<=32", "32", ">=32", ">32",
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"<40", "<=40", "40", ">=40", ">40",
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"<48", "<=48", "48", ">=48", ">48",
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"<64", "<=64", "64", ">=64", ">64",
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"<80", "<=80", "80", ">=80", ">80",
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"<96", "<=96", "96", ">=96", ">96",
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"<128", "<=128", "128", ">=128", ">128",
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"<160", "<=160", "160", ">=160", ">160",
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"<256", "<=256", "256", ">=256", ">256",
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"<320", "<=320", "320", ">=320", ">320",
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"<512", "<=512", "512", ">=512", ">512",
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"<1024", "<=1024", "1024", ">=1024", ">1024")
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x <- x %>% as.character()
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na_before <- x[is.na(x) | x == ''] %>% length()
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x[!x %in% lvls] <- NA
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na_after <- x[is.na(x) | x == ''] %>% length()
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if (na_before != na_after) {
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list_missing <- x.bak[is.na(x) & !is.na(x.bak) & x.bak != ''] %>%
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unique() %>%
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sort()
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list_missing <- paste0('"', list_missing , '"', collapse = ", ")
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warning(na_after - na_before, ' results truncated (',
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round(((na_after - na_before) / length(x)) / 100),
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'%) that were invalid MICs: ',
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list_missing, call. = FALSE)
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}
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x <- factor(x = x,
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levels = lvls,
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ordered = TRUE)
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class(x) <- c('mic', 'ordered', 'factor')
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x
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}
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}
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#' @rdname as.mic
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#' @export
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#' @importFrom dplyr %>%
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is.mic <- function(x) {
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class(x) %>% identical(c('mic', 'ordered', 'factor'))
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}
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#' @exportMethod as.double.mic
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#' @export
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#' @importFrom dplyr %>%
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#' @noRd
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as.double.mic <- function(x, ...) {
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as.double(gsub('(<=)|(>=)', '', as.character(x)))
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}
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#' @exportMethod as.integer.mic
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#' @export
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#' @importFrom dplyr %>%
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#' @noRd
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as.integer.mic <- function(x, ...) {
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as.integer(gsub('(<=)|(>=)', '', as.character(x)))
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}
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#' @exportMethod as.numeric.mic
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#' @export
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#' @importFrom dplyr %>%
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#' @noRd
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as.numeric.mic <- function(x, ...) {
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as.numeric(gsub('(<=)|(>=)', '', as.character(x)))
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}
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#' @exportMethod print.mic
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#' @export
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#' @importFrom dplyr %>% tibble group_by summarise pull
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#' @noRd
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print.mic <- function(x, ...) {
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n_total <- x %>% length()
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x <- x[!is.na(x)]
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n <- x %>% length()
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cat("Class 'mic': ", n, " isolates\n", sep = '')
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cat('\n')
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cat('<NA> ', n_total - n, '\n')
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cat('\n')
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tbl <- tibble(x = x, y = 1) %>% group_by(x) %>% summarise(y = sum(y))
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cnt <- tbl %>% pull(y)
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names(cnt) <- tbl %>% pull(x)
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print(cnt)
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}
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#' @exportMethod summary.mic
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#' @export
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#' @importFrom dplyr %>% tibble group_by summarise pull
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#' @noRd
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summary.mic <- function(object, ...) {
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x <- object
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n_total <- x %>% length()
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x <- x[!is.na(x)]
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n <- x %>% length()
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return(c("Mode" = 'mic',
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"NA" = n_total - n,
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"Min." = sort(x)[1] %>% as.character(),
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"Max." = sort(x)[n] %>% as.character()
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))
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cat("Class 'mic': ", n, " isolates\n", sep = '')
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|
|
cat('\n')
|
||
|
|
cat('<NA> ', n_total - n, '\n')
|
||
|
|
cat('\n')
|
||
|
|
tbl <- tibble(x = x, y = 1) %>% group_by(x) %>% summarise(y = sum(y))
|
||
|
|
cnt <- tbl %>% pull(y)
|
||
|
|
names(cnt) <- tbl %>% pull(x)
|
||
|
|
print(cnt)
|
||
|
|
}
|
||
|
|
|
||
|
|
#' @exportMethod plot.mic
|
||
|
|
#' @export
|
||
|
|
#' @importFrom dplyr %>% group_by summarise
|
||
|
|
#' @importFrom graphics plot text
|
||
|
|
#' @noRd
|
||
|
|
plot.mic <- function(x, ...) {
|
||
|
|
x_name <- deparse(substitute(x))
|
||
|
|
|
||
|
|
data <- data.frame(mic = x, cnt = 1) %>%
|
||
|
|
group_by(mic) %>%
|
||
|
|
summarise(cnt = sum(cnt)) %>%
|
||
|
|
droplevels()
|
||
|
|
|
||
|
|
plot(x = data$mic,
|
||
|
|
y = data$cnt,
|
||
|
|
lwd = 2,
|
||
|
|
ylim = c(-0.5, max(5, max(data$cnt))),
|
||
|
|
ylab = 'Frequency',
|
||
|
|
xlab = 'MIC value',
|
||
|
|
main = paste('MIC values of', x_name),
|
||
|
|
...)
|
||
|
|
text(x = data$mic,
|
||
|
|
y = -0.5,
|
||
|
|
labels = paste('n =', data$cnt))
|
||
|
|
}
|