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(v2.1.1.9154) documentation fix

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dr. M.S. (Matthijs) Berends 2025-02-22 22:07:56 +01:00
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10 changed files with 34 additions and 368 deletions

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@ -1,5 +1,5 @@
Package: AMR
Version: 2.1.1.9153
Version: 2.1.1.9154
Date: 2025-02-22
Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR)

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@ -1,4 +1,4 @@
# AMR 2.1.1.9153
# AMR 2.1.1.9154
*(this beta version will eventually become v3.0. We're happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using [the instructions here](https://msberends.github.io/AMR/#latest-development-version).)*

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@ -1,6 +1,6 @@
Metadata-Version: 2.2
Name: AMR
Version: 2.1.1.9153
Version: 2.1.1.9154
Summary: A Python wrapper for the AMR R package
Home-page: https://github.com/msberends/AMR
Author: Matthijs Berends

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@ -2,7 +2,7 @@ from setuptools import setup, find_packages
setup(
name='AMR',
version='2.1.1.9153',
version='2.1.1.9154',
packages=find_packages(),
install_requires=[
'rpy2',

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@ -81,20 +81,24 @@
#' some_sir_values <- random_sir(50, prob_SIR = c(0.55, 0.05, 0.30))
#'
#'
#' # Plotting using base R's plot() ---------------------------------------
#'
#' plot(some_mic_values)
#' plot(some_disk_values)
#' plot(some_sir_values)
#'
#' # when providing the microorganism and antibiotic, colours will show interpretations:
#' plot(some_mic_values, mo = "S. aureus", ab = "ampicillin")
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "nl")
#' \donttest{
#' # Plotting using ggplot2's autoplot() for MIC, disk, and SIR -----------
#' if (require("ggplot2")) {
#' autoplot(some_mic_values)
#' }
#' if (require("ggplot2")) {
#' # when providing the microorganism and antibiotic, colours will show interpretations:
#' autoplot(some_mic_values, mo = "Escherichia coli", ab = "cipro")
#' }
#' if (require("ggplot2")) {
#' # support for 20 languages, various guidelines, and many options
#' autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro",
#' guideline = "CLSI 2024", language = "no",
#' title = "Disk diffusion from the North")
#' }
#'
#'
#' # Plotting using scale_x_mic() -----------------------------------------
#' \donttest{
#' if (require("ggplot2")) {
#' mic_plot <- ggplot(data.frame(mics = as.mic(c(0.25, "<=4", 4, 8, 32, ">=32")),
#' counts = c(1, 1, 2, 2, 3, 3)),
@ -142,22 +146,10 @@
#' aes(group, mic)) +
#' geom_boxplot() +
#' geom_violin(linetype = 2, colour = "grey", fill = NA) +
#' scale_y_mic(mic_range = c(NA, 2))
#' scale_y_mic(mic_range = c(NA, 0.25))
#' }
#'
#'
#' # Plotting using scale_fill_mic() -----------------------------------------
#' some_counts <- as.integer(runif(20, 5, 50))
#'
#' if (require("ggplot2")) {
#' ggplot(data.frame(mic = some_mic_values,
#' group = some_groups,
#' counts = some_counts),
#' aes(group, counts, fill = mic)) +
#' geom_col() +
#' scale_fill_mic(mic_range = c(0.5, 16))
#' }
#'
#' # Plotting using scale_x_sir() -----------------------------------------
#' if (require("ggplot2")) {
#' ggplot(data.frame(x = c("I", "R", "S"),
@ -191,42 +183,22 @@
#' if (require("ggplot2")) {
#' plain +
#' scale_y_mic(mic_range = c(0.005, 32), name = "Our MICs!") +
#' scale_colour_sir(language = "nl", eucast_I = FALSE,
#' name = "In Dutch!")
#' scale_colour_sir(language = "pt",
#' name = "Support in 20 languages")
#' }
#'
#'
#' # Plotting using ggplot2's autoplot() ----------------------------------
#' if (require("ggplot2")) {
#' autoplot(some_mic_values)
#' }
#' if (require("ggplot2")) {
#' autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
#' }
#' if (require("ggplot2")) {
#' autoplot(some_sir_values)
#' }
#' # Plotting using base R's plot() ---------------------------------------
#'
#' plot(some_mic_values)
#' # when providing the microorganism and antibiotic, colours will show interpretations:
#' plot(some_mic_values, mo = "S. aureus", ab = "ampicillin")
#'
#' # Plotting using scale_y_percent() -------------------------------------
#' if (require("ggplot2")) {
#' p <- ggplot(data.frame(mics = as.mic(c(0.25, "<=4", 4, 8, 32, ">=32")),
#' counts = c(1, 1, 2, 2, 3, 3)),
#' aes(mics, counts / sum(counts))) +
#' geom_col()
#' print(p)
#' plot(some_disk_values)
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
#' plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "nl")
#'
#' p2 <- p +
#' scale_y_percent() +
#' theme_sir()
#' print(p2)
#'
#' p +
#' scale_y_percent(breaks = seq(from = 0, to = 1, by = 0.1),
#' limits = c(0, 1)) +
#' theme_sir()
#' }
#' }
#' plot(some_sir_values)
NULL
create_scale_mic <- function(aest, keep_operators, mic_range = NULL, ...) {
@ -243,12 +215,12 @@ create_scale_mic <- function(aest, keep_operators, mic_range = NULL, ...) {
scale$mic_limits_set <- limits_set
scale$transform <- function(x) {
as.double(rescale_mic(x = as.double(x), keep_operators = keep_operators, mic_range = mic_range, as.mic = TRUE))
as.double(rescale_mic(x = as.double(as.mic(x)), keep_operators = keep_operators, mic_range = mic_range, as.mic = TRUE))
}
scale$transform_df <- function(self, df) {
stop_if(all(is.na(df[[aest]])),
"`scale_", aest, "_mic()`: All MIC values are `NA`. Check your input data.", call = FALSE)
self$mic_values_rescaled <- rescale_mic(x = as.double(df[[aest]]), keep_operators = keep_operators, mic_range = mic_range, as.mic = TRUE)
self$mic_values_rescaled <- rescale_mic(x = as.double(as.mic(df[[aest]])), keep_operators = keep_operators, mic_range = mic_range, as.mic = TRUE)
# create new breaks and labels here
lims <- range(self$mic_values_rescaled, na.rm = TRUE)
# support inner and outer mic_range settings (e.g., data ranges 0.5-8 and mic_range is set to 0.025-64)

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@ -1,6 +1,6 @@
This knowledge base contains all context you must know about the AMR package for R. You are a GPT trained to be an assistant for the AMR package in R. You are an incredible R specialist, especially trained in this package and in the tidyverse.
First and foremost, you are trained on version 2.1.1.9153. Remember this whenever someone asks which AMR package version youre at.
First and foremost, you are trained on version 2.1.1.9154. Remember this whenever someone asks which AMR package version youre at.
Below are the contents of the file, the file, and all the files (documentation) in the package. Every file content is split using 100 hypens.
----------------------------------------------------------------------------------------------------
@ -7540,159 +7540,6 @@ The interpretation of "I" will be named "Increased exposure" for all EUCAST guid
For interpreting MIC values as well as disk diffusion diameters, the default guideline is EUCAST 2024, unless the package option \code{\link[=AMR-options]{AMR_guideline}} is set. See \code{\link[=as.sir]{as.sir()}} for more information.
}
}
\examples{
some_mic_values <- random_mic(size = 100)
some_disk_values <- random_disk(size = 100, mo = "Escherichia coli", ab = "cipro")
some_sir_values <- random_sir(50, prob_SIR = c(0.55, 0.05, 0.30))
# Plotting using base R's plot() ---------------------------------------
plot(some_mic_values)
plot(some_disk_values)
plot(some_sir_values)
# when providing the microorganism and antibiotic, colours will show interpretations:
plot(some_mic_values, mo = "S. aureus", ab = "ampicillin")
plot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "nl")
# Plotting using scale_x_mic() -----------------------------------------
\donttest{
if (require("ggplot2")) {
mic_plot <- ggplot(data.frame(mics = as.mic(c(0.25, "<=4", 4, 8, 32, ">=32")),
counts = c(1, 1, 2, 2, 3, 3)),
aes(mics, counts)) +
geom_col()
mic_plot +
labs(title = "without scale_x_mic()")
}
if (require("ggplot2")) {
mic_plot +
scale_x_mic() +
labs(title = "with scale_x_mic()")
}
if (require("ggplot2")) {
mic_plot +
scale_x_mic(keep_operators = "all") +
labs(title = "with scale_x_mic() keeping all operators")
}
if (require("ggplot2")) {
mic_plot +
scale_x_mic(mic_range = c(1, 16)) +
labs(title = "with scale_x_mic() using a manual 'within' range")
}
if (require("ggplot2")) {
mic_plot +
scale_x_mic(mic_range = c(0.032, 256)) +
labs(title = "with scale_x_mic() using a manual 'outside' range")
}
# Plotting using scale_y_mic() -----------------------------------------
some_groups <- sample(LETTERS[1:5], 20, replace = TRUE)
if (require("ggplot2")) {
ggplot(data.frame(mic = some_mic_values,
group = some_groups),
aes(group, mic)) +
geom_boxplot() +
geom_violin(linetype = 2, colour = "grey", fill = NA) +
scale_y_mic()
}
if (require("ggplot2")) {
ggplot(data.frame(mic = some_mic_values,
group = some_groups),
aes(group, mic)) +
geom_boxplot() +
geom_violin(linetype = 2, colour = "grey", fill = NA) +
scale_y_mic(mic_range = c(NA, 2))
}
# Plotting using scale_fill_mic() -----------------------------------------
some_counts <- as.integer(runif(20, 5, 50))
if (require("ggplot2")) {
ggplot(data.frame(mic = some_mic_values,
group = some_groups,
counts = some_counts),
aes(group, counts, fill = mic)) +
geom_col() +
scale_fill_mic(mic_range = c(0.5, 16))
}
# Plotting using scale_x_sir() -----------------------------------------
if (require("ggplot2")) {
ggplot(data.frame(x = c("I", "R", "S"),
y = c(45,323, 573)),
aes(x, y)) +
geom_col() +
scale_x_sir()
}
# Plotting using scale_y_mic() and scale_colour_sir() ------------------
if (require("ggplot2")) {
plain <- ggplot(data.frame(mic = some_mic_values,
group = some_groups,
sir = as.sir(some_mic_values,
mo = "E. coli",
ab = "cipro")),
aes(x = group, y = mic, colour = sir)) +
theme_minimal() +
geom_boxplot(fill = NA, colour = "grey") +
geom_jitter(width = 0.25)
plain
}
if (require("ggplot2")) {
# and now with our MIC and SIR scale functions:
plain +
scale_y_mic() +
scale_colour_sir()
}
if (require("ggplot2")) {
plain +
scale_y_mic(mic_range = c(0.005, 32), name = "Our MICs!") +
scale_colour_sir(language = "nl", eucast_I = FALSE,
name = "In Dutch!")
}
# Plotting using ggplot2's autoplot() ----------------------------------
if (require("ggplot2")) {
autoplot(some_mic_values)
}
if (require("ggplot2")) {
autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
}
if (require("ggplot2")) {
autoplot(some_sir_values)
}
# Plotting using scale_y_percent() -------------------------------------
if (require("ggplot2")) {
p <- ggplot(data.frame(mics = as.mic(c(0.25, "<=4", 4, 8, 32, ">=32")),
counts = c(1, 1, 2, 2, 3, 3)),
aes(mics, counts / sum(counts))) +
geom_col()
print(p)
p2 <- p +
scale_y_percent() +
theme_sir()
print(p2)
p +
scale_y_percent(breaks = seq(from = 0, to = 1, by = 0.1),
limits = c(0, 1)) +
theme_sir()
}
}
}

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@ -196,156 +196,3 @@ The interpretation of "I" will be named "Increased exposure" for all EUCAST guid
For interpreting MIC values as well as disk diffusion diameters, the default guideline is EUCAST 2024, unless the package option \code{\link[=AMR-options]{AMR_guideline}} is set. See \code{\link[=as.sir]{as.sir()}} for more information.
}
}
\examples{
some_mic_values <- random_mic(size = 100)
some_disk_values <- random_disk(size = 100, mo = "Escherichia coli", ab = "cipro")
some_sir_values <- random_sir(50, prob_SIR = c(0.55, 0.05, 0.30))
# Plotting using base R's plot() ---------------------------------------
plot(some_mic_values)
plot(some_disk_values)
plot(some_sir_values)
# when providing the microorganism and antibiotic, colours will show interpretations:
plot(some_mic_values, mo = "S. aureus", ab = "ampicillin")
plot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "nl")
# Plotting using scale_x_mic() -----------------------------------------
\donttest{
if (require("ggplot2")) {
mic_plot <- ggplot(data.frame(mics = as.mic(c(0.25, "<=4", 4, 8, 32, ">=32")),
counts = c(1, 1, 2, 2, 3, 3)),
aes(mics, counts)) +
geom_col()
mic_plot +
labs(title = "without scale_x_mic()")
}
if (require("ggplot2")) {
mic_plot +
scale_x_mic() +
labs(title = "with scale_x_mic()")
}
if (require("ggplot2")) {
mic_plot +
scale_x_mic(keep_operators = "all") +
labs(title = "with scale_x_mic() keeping all operators")
}
if (require("ggplot2")) {
mic_plot +
scale_x_mic(mic_range = c(1, 16)) +
labs(title = "with scale_x_mic() using a manual 'within' range")
}
if (require("ggplot2")) {
mic_plot +
scale_x_mic(mic_range = c(0.032, 256)) +
labs(title = "with scale_x_mic() using a manual 'outside' range")
}
# Plotting using scale_y_mic() -----------------------------------------
some_groups <- sample(LETTERS[1:5], 20, replace = TRUE)
if (require("ggplot2")) {
ggplot(data.frame(mic = some_mic_values,
group = some_groups),
aes(group, mic)) +
geom_boxplot() +
geom_violin(linetype = 2, colour = "grey", fill = NA) +
scale_y_mic()
}
if (require("ggplot2")) {
ggplot(data.frame(mic = some_mic_values,
group = some_groups),
aes(group, mic)) +
geom_boxplot() +
geom_violin(linetype = 2, colour = "grey", fill = NA) +
scale_y_mic(mic_range = c(NA, 2))
}
# Plotting using scale_fill_mic() -----------------------------------------
some_counts <- as.integer(runif(20, 5, 50))
if (require("ggplot2")) {
ggplot(data.frame(mic = some_mic_values,
group = some_groups,
counts = some_counts),
aes(group, counts, fill = mic)) +
geom_col() +
scale_fill_mic(mic_range = c(0.5, 16))
}
# Plotting using scale_x_sir() -----------------------------------------
if (require("ggplot2")) {
ggplot(data.frame(x = c("I", "R", "S"),
y = c(45,323, 573)),
aes(x, y)) +
geom_col() +
scale_x_sir()
}
# Plotting using scale_y_mic() and scale_colour_sir() ------------------
if (require("ggplot2")) {
plain <- ggplot(data.frame(mic = some_mic_values,
group = some_groups,
sir = as.sir(some_mic_values,
mo = "E. coli",
ab = "cipro")),
aes(x = group, y = mic, colour = sir)) +
theme_minimal() +
geom_boxplot(fill = NA, colour = "grey") +
geom_jitter(width = 0.25)
plain
}
if (require("ggplot2")) {
# and now with our MIC and SIR scale functions:
plain +
scale_y_mic() +
scale_colour_sir()
}
if (require("ggplot2")) {
plain +
scale_y_mic(mic_range = c(0.005, 32), name = "Our MICs!") +
scale_colour_sir(language = "nl", eucast_I = FALSE,
name = "In Dutch!")
}
# Plotting using ggplot2's autoplot() ----------------------------------
if (require("ggplot2")) {
autoplot(some_mic_values)
}
if (require("ggplot2")) {
autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
}
if (require("ggplot2")) {
autoplot(some_sir_values)
}
# Plotting using scale_y_percent() -------------------------------------
if (require("ggplot2")) {
p <- ggplot(data.frame(mics = as.mic(c(0.25, "<=4", 4, 8, 32, ">=32")),
counts = c(1, 1, 2, 2, 3, 3)),
aes(mics, counts / sum(counts))) +
geom_col()
print(p)
p2 <- p +
scale_y_percent() +
theme_sir()
print(p2)
p +
scale_y_percent(breaks = seq(from = 0, to = 1, by = 0.1),
limits = c(0, 1)) +
theme_sir()
}
}
}