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unit tests
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Package: AMR
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Package: AMR
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Version: 1.8.2.9104
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Version: 1.8.2.9105
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Date: 2023-01-30
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Date: 2023-01-30
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Title: Antimicrobial Resistance Data Analysis
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Title: Antimicrobial Resistance Data Analysis
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Description: Functions to simplify and standardise antimicrobial resistance (AMR)
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Description: Functions to simplify and standardise antimicrobial resistance (AMR)
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2
NEWS.md
2
NEWS.md
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# AMR 1.8.2.9104
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# AMR 1.8.2.9105
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*(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)*
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*(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)*
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@ -722,9 +722,9 @@ format_class <- function(class, plural = FALSE) {
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class <- "input created with `custom_eucast_rules()`"
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class <- "input created with `custom_eucast_rules()`"
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}
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}
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if (any(c("mo", "ab", "sir") %in% class)) {
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if (any(c("mo", "ab", "sir") %in% class)) {
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class <- paste0("of class <", class[1L], ">")
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class <- paste0("of class '", class[1L], "'")
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}
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}
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class[class == class.bak] <- paste0("of class <", class[class == class.bak], ">")
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class[class == class.bak] <- paste0("of class '", class[class == class.bak], "'")
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# output
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# output
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vector_or(class, quotes = FALSE, sort = FALSE)
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vector_or(class, quotes = FALSE, sort = FALSE)
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}
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}
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@ -854,7 +854,7 @@ meet_criteria <- function(object,
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}
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}
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), na.rm = TRUE),
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), na.rm = TRUE),
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"the data provided in argument `", obj_name,
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"the data provided in argument `", obj_name,
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"` must contain at least one column of class <", contains_column_class, ">. ",
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"` must contain at least one column of class '", contains_column_class, "'. ",
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"See ?as.", contains_column_class, ".",
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"See ?as.", contains_column_class, ".",
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call = call_depth
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call = call_depth
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)
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)
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24
R/mo.R
24
R/mo.R
@ -800,25 +800,31 @@ print.mo_uncertainties <- function(x, ...) {
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return(invisible(NULL))
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return(invisible(NULL))
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}
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}
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cat(word_wrap("Matching scores are based on the resemblance between the input and the full taxonomic name, and the pathogenicity in humans. See `?mo_matching_score`.\n\n", add_fn = font_blue))
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add_MO_lookup_to_AMR_env()
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add_MO_lookup_to_AMR_env()
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cat(word_wrap("Matching scores are based on the resemblance between the input and the full taxonomic name, and the pathogenicity in humans. See `?mo_matching_score`.\n\n", add_fn = font_blue))
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col_red <- function(x) font_rose_bg(font_black(x, collapse = NULL), collapse = NULL)
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col_orange <- function(x) font_orange_bg(font_black(x, collapse = NULL), collapse = NULL)
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col_yellow <- function(x) font_yellow_bg(font_black(x, collapse = NULL), collapse = NULL)
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col_green <- function(x) font_green_bg(font_black(x, collapse = NULL), collapse = NULL)
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if (has_colour()) {
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if (has_colour()) {
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cat(word_wrap("Colour keys: ",
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cat(word_wrap("Colour keys: ",
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font_red_bg(" 0.000-0.499 "),
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col_red(" 0.000-0.499 "),
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font_orange_bg(" 0.500-0.599 "),
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col_orange(" 0.500-0.599 "),
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font_yellow_bg(" 0.600-0.699 "),
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col_yellow(" 0.600-0.699 "),
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font_green_bg(" 0.700-1.000"),
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col_green(" 0.700-1.000"),
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add_fn = font_blue
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add_fn = font_blue
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), font_green_bg(" "), "\n", sep = "")
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), font_green_bg(" "), "\n", sep = "")
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}
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}
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score_set_colour <- function(text, scores) {
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score_set_colour <- function(text, scores) {
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# set colours to scores
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# set colours to scores
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text[scores >= 0.7] <- font_green_bg(text[scores >= 0.7], collapse = NULL)
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text[scores >= 0.7] <- col_green(text[scores >= 0.7])
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text[scores >= 0.6 & scores < 0.7] <- font_yellow_bg(text[scores >= 0.6 & scores < 0.7], collapse = NULL)
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text[scores >= 0.6 & scores < 0.7] <- col_yellow(text[scores >= 0.6 & scores < 0.7])
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text[scores >= 0.5 & scores < 0.6] <- font_orange_bg(text[scores >= 0.5 & scores < 0.6], collapse = NULL)
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text[scores >= 0.5 & scores < 0.6] <- col_orange(text[scores >= 0.5 & scores < 0.6])
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text[scores < 0.5] <- font_red_bg(text[scores < 0.5], collapse = NULL)
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text[scores < 0.5] <- col_red(text[scores < 0.5])
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text
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text
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}
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}
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@ -195,6 +195,20 @@ if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0")) {
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as.sir(guideline = "CLSI") %>%
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as.sir(guideline = "CLSI") %>%
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pull(amox_disk) %>%
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pull(amox_disk) %>%
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is.sir())
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is.sir())
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# used by group_by() on sir_calc_df(), check some internals to see if grouped calculation without tidyverse works
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groups <- example_isolates %>%
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group_by(mo) %>%
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attributes() %>%
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.$groups
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expect_equal(nrow(groups),
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90)
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expect_equal(class(groups$.rows),
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c("vctrs_list_of", "vctrs_vctr", "list"))
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expect_equal(groups$.rows[[1]],
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c(101, 524, 1368))
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expect_equal(example_isolates[c(101, 524, 1368), "mo", drop = TRUE],
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rep(groups$mo[1], 3))
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}
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}
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# frequency tables
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# frequency tables
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if (AMR:::pkg_is_available("cleaner")) {
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if (AMR:::pkg_is_available("cleaner")) {
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21
man/antibiogram_wisca.Rd
Normal file
21
man/antibiogram_wisca.Rd
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/antibiogram.R
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\name{antibiogram_wisca}
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\alias{antibiogram_wisca}
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\title{Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted (WISCA)}
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\usage{
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antibiogram_wisca(
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x,
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...,
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antibiotics = where(is.sir),
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type = c("traditional", "combined", "syndromic", "WISCA"),
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col_mo = NULL,
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minimum = 30
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)
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}
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\arguments{
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\item{x}{a \link{data.frame} containing at least a column with microorganisms and columns with antibiotic results (class 'sir', see \code{\link[=as.sir]{as.sir()}})}
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}
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\description{
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Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted (WISCA)
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}
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