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# ==================================================================== # |
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# TITLE # |
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# Antimicrobial Resistance (AMR) Analysis for R # |
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# # |
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# SOURCE # |
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# https://github.com/msberends/AMR # |
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# # |
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# LICENCE # |
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# (c) 2018-2020 Berends MS, Luz CF et al. # |
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# Developed at the University of Groningen, the Netherlands, in # |
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# collaboration with non-profit organisations Certe Medical # |
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# Diagnostics & Advice, and University Medical Center Groningen. # |
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# # |
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# This R package is free software; you can freely use and distribute # |
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# it for both personal and commercial purposes under the terms of the # |
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# GNU General Public License version 2.0 (GNU GPL-2), as published by # |
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# the Free Software Foundation. # |
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# We created this package for both routine data analysis and academic # |
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# research and it was publicly released in the hope that it will be # |
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # |
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# # |
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# Visit our website for the full manual and a complete tutorial about # |
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# how to conduct AMR analysis: https://msberends.github.io/AMR/ # |
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# ==================================================================== # |
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|
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#' Random MIC values/disk zones/RSI generation |
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#' |
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#' These functions can be used for generating random MIC values and disk diffusion diameters, for AMR analysis practice. |
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#' @inheritSection lifecycle Maturing lifecycle |
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#' @param size desired size of the returned vector |
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#' @param mo any character that can be coerced to a valid microorganism code with [as.mo()] |
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#' @param ab any character that can be coerced to a valid antimicrobial agent code with [as.ab()] |
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#' @param prob_RSI a vector of length 3: the probabilities for R (1st value), S (2nd value) and I (3rd value) |
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#' @param ... extension for future versions, not used at the moment |
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#' @details The base R function [sample()] is used for generating values. |
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#' |
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#' Generated values are based on the latest EUCAST guideline implemented in the [rsi_translation] data set. To create specific generated values per bug or drug, set the `mo` and/or `ab` parameter. |
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#' @return class `<mic>` for [random_mic()] (see [as.mic()]) and class `<disk>` for [random_disk()] (see [as.disk()]) |
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#' @name random |
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#' @rdname random |
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#' @export |
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#' @inheritSection AMR Read more on our website! |
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#' @examples |
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#' random_mic(100) |
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#' random_disk(100) |
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#' random_rsi(100) |
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#' |
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#' \donttest{ |
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#' # make the random generation more realistic by setting a bug and/or drug: |
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#' random_mic(100, "Klebsiella pneumoniae") # range 0.0625-64 |
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#' random_mic(100, "Klebsiella pneumoniae", "meropenem") # range 0.0625-16 |
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#' random_mic(100, "Streptococcus pneumoniae", "meropenem") # range 0.0625-4 |
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#' |
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#' random_disk(100, "Klebsiella pneumoniae") # range 11-50 |
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#' random_disk(100, "Klebsiella pneumoniae", "ampicillin") # range 6-14 |
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#' random_disk(100, "Streptococcus pneumoniae", "ampicillin") # range 16-22 |
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#' } |
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random_mic <- function(size, mo = NULL, ab = NULL, ...) { |
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random_exec("MIC", size = size, mo = mo, ab = ab) |
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} |
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|
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#' @rdname random |
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#' @export |
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random_disk <- function(size, mo = NULL, ab = NULL, ...) { |
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random_exec("DISK", size = size, mo = mo, ab = ab) |
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} |
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#' @rdname random |
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#' @export |
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random_rsi <- function(size, prob_RSI = c(0.33, 0.33, 0.33), ...) { |
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sample(as.rsi(c("R", "S", "I")), size = size, replace = TRUE, prob = prob_RSI) |
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} |
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random_exec <- function(type, size, mo = NULL, ab = NULL) { |
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df <- rsi_translation %pm>% |
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pm_filter(guideline %like% "EUCAST") %pm>% |
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pm_arrange(pm_desc(guideline)) %pm>% |
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subset(guideline == max(guideline) & |
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method == type) |
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|
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if (!is.null(mo)) { |
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mo_coerced <- as.mo(mo) |
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mo_include <- c(mo_coerced, |
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as.mo(mo_genus(mo_coerced)), |
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as.mo(mo_family(mo_coerced)), |
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as.mo(mo_order(mo_coerced))) |
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df_new <- df %pm>% |
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subset(mo %in% mo_include) |
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if (nrow(df_new) > 0) { |
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df <- df_new |
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} else { |
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warning_("No rows found that match mo '", mo, "', ignoring parameter `mo`", call = FALSE) |
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} |
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} |
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|
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if (!is.null(ab)) { |
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ab_coerced <- as.ab(ab) |
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df_new <- df %pm>% |
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subset(ab %in% ab_coerced) |
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if (nrow(df_new) > 0) { |
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df <- df_new |
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} else { |
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warning_("No rows found that match ab '", ab, "', ignoring parameter `ab`", call = FALSE) |
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} |
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} |
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|
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if (type == "MIC") { |
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# all valid MIC levels |
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valid_range <- as.mic(levels(as.mic(1))) |
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set_range_max <- max(df$breakpoint_R) |
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if (log(set_range_max, 2) %% 1 == 0) { |
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# return powers of 2 |
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valid_range <- unique(as.double(valid_range)) |
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# add one higher MIC level to set_range_max |
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set_range_max <- 2 ^ (log(set_range_max, 2) + 1) |
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set_range <- as.mic(valid_range[log(valid_range, 2) %% 1 == 0 & valid_range <= set_range_max]) |
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} else { |
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# no power of 2, return factors of 2 to left and right side |
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valid_mics <- suppressWarnings(as.mic(set_range_max / (2 ^ c(-3:3)))) |
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set_range <- valid_mics[!is.na(valid_mics)] |
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} |
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return(as.mic(sample(set_range, size = size, replace = TRUE))) |
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} else if (type == "DISK") { |
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set_range <- seq(from = as.integer(min(df$breakpoint_R)), |
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to = as.integer(max(df$breakpoint_S)), |
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by = 1) |
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out <- sample(set_range, size = size, replace = TRUE) |
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out[out < 6] <- sample(c(6:10), length(out[out < 6]), replace = TRUE) |
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out[out > 50] <- sample(c(40:50), length(out[out > 50]), replace = TRUE) |
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return(as.disk(out)) |
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} |
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} |
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<h1>Random MIC values/disk zones/RSI generation</h1> |
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<small class="dont-index">Source: <a href='https://github.com/msberends/AMR/blob/master/R/random.R'><code>R/random.R</code></a></small> |
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<div class="hidden name"><code>random.Rd</code></div> |
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<div class="ref-description"> |
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<p>These functions can be used for generating random MIC values and disk diffusion diameters, for AMR analysis practice.</p> |
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</div> |
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|
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<pre class="usage"><span class='fu'>random_mic</span><span class='op'>(</span><span class='va'>size</span>, mo <span class='op'>=</span> <span class='cn'>NULL</span>, ab <span class='op'>=</span> <span class='cn'>NULL</span>, <span class='va'>...</span><span class='op'>)</span> |
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|
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<span class='fu'>random_disk</span><span class='op'>(</span><span class='va'>size</span>, mo <span class='op'>=</span> <span class='cn'>NULL</span>, ab <span class='op'>=</span> <span class='cn'>NULL</span>, <span class='va'>...</span><span class='op'>)</span> |
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|
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<span class='fu'>random_rsi</span><span class='op'>(</span><span class='va'>size</span>, prob_RSI <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='fl'>0.33</span>, <span class='fl'>0.33</span>, <span class='fl'>0.33</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span></pre> |
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|
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<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> |
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<table class="ref-arguments"> |
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<colgroup><col class="name" /><col class="desc" /></colgroup> |
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<tr> |
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<th>size</th> |
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<td><p>desired size of the returned vector</p></td> |
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</tr> |
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<tr> |
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<th>mo</th> |
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<td><p>any character that can be coerced to a valid microorganism code with <code><a href='as.mo.html'>as.mo()</a></code></p></td> |
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</tr> |
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<tr> |
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<th>ab</th> |
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<td><p>any character that can be coerced to a valid antimicrobial agent code with <code><a href='as.ab.html'>as.ab()</a></code></p></td> |
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</tr> |
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<tr> |
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<th>...</th> |
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<td><p>extension for future versions, not used at the moment</p></td> |
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</tr> |
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<tr> |
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<th>prob_RSI</th> |
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<td><p>a vector of length 3: the probabilities for R (1st value), S (2nd value) and I (3rd value)</p></td> |
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</tr> |
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</table> |
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<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> |
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<p>class <code><mic></code> for <code>random_mic()</code> (see <code><a href='as.mic.html'>as.mic()</a></code>) and class <code><disk></code> for <code>random_disk()</code> (see <code><a href='as.disk.html'>as.disk()</a></code>)</p> |
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<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2> |
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|
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<p>The base R function <code><a href='https://rdrr.io/r/base/sample.html'>sample()</a></code> is used for generating values.</p> |
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<p>Generated values are based on the latest EUCAST guideline implemented in the <a href='rsi_translation.html'>rsi_translation</a> data set. To create specific generated values per bug or drug, set the <code>mo</code> and/or <code>ab</code> parameter.</p> |
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<h2 class="hasAnchor" id="maturing-lifecycle"><a class="anchor" href="#maturing-lifecycle"></a>Maturing lifecycle</h2> |
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<p><img src='figures/lifecycle_maturing.svg' style=margin-bottom:5px /> <br /> |
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The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing</strong>. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome <a href='https://github.com/msberends/AMR/issues'>to suggest changes at our repository</a> or <a href='AMR.html'>write us an email (see section 'Contact Us')</a>.</p> |
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<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2> |
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<p>On our website <a href='https://msberends.github.io/AMR/'>https://msberends.github.io/AMR/</a> you can find <a href='https://msberends.github.io/AMR/articles/AMR.html'>a comprehensive tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.github.io/AMR/reference/'>complete documentation of all functions</a> and <a href='https://msberends.github.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>. As we would like to better understand the backgrounds and needs of our users, please <a href='https://msberends.github.io/AMR/survey.html'>participate in our survey</a>!</p> |
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<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> |
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<pre class="examples"><span class='fu'>random_mic</span><span class='op'>(</span><span class='fl'>100</span><span class='op'>)</span> |
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<span class='fu'>random_disk</span><span class='op'>(</span><span class='fl'>100</span><span class='op'>)</span> |
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<span class='fu'>random_rsi</span><span class='op'>(</span><span class='fl'>100</span><span class='op'>)</span> |
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<span class='co'># \donttest{</span> |
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<span class='co'># make the random generation more realistic by setting a bug and/or drug:</span> |
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<span class='fu'>random_mic</span><span class='op'>(</span><span class='fl'>100</span>, <span class='st'>"Klebsiella pneumoniae"</span><span class='op'>)</span> <span class='co'># range 0.0625-64</span> |
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<span class='fu'>random_mic</span><span class='op'>(</span><span class='fl'>100</span>, <span class='st'>"Klebsiella pneumoniae"</span>, <span class='st'>"meropenem"</span><span class='op'>)</span> <span class='co'># range 0.0625-16</span> |
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<span class='fu'>random_mic</span><span class='op'>(</span><span class='fl'>100</span>, <span class='st'>"Streptococcus pneumoniae"</span>, <span class='st'>"meropenem"</span><span class='op'>)</span> <span class='co'># range 0.0625-4</span> |
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<span class='fu'>random_disk</span><span class='op'>(</span><span class='fl'>100</span>, <span class='st'>"Klebsiella pneumoniae"</span><span class='op'>)</span> <span class='co'># range 11-50</span> |
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<span class='fu'>random_disk</span><span class='op'>(</span><span class='fl'>100</span>, <span class='st'>"Klebsiella pneumoniae"</span>, <span class='st'>"ampicillin"</span><span class='op'>)</span> <span class='co'># range 6-14</span> |
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<span class='fu'>random_disk</span><span class='op'>(</span><span class='fl'>100</span>, <span class='st'>"Streptococcus pneumoniae"</span>, <span class='st'>"ampicillin"</span><span class='op'>)</span> <span class='co'># range 16-22</span> |
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<span class='co'># }</span> |
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</pre> |
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