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mirror of https://github.com/msberends/AMR.git synced 2025-07-11 06:21:56 +02:00

(v2.1.1.9118) move ggplot2 plotting functions to general 'plotting' man page

This commit is contained in:
2024-12-14 19:41:15 +01:00
parent bfef094bbc
commit d7de1bc33d
18 changed files with 332 additions and 291 deletions

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@ -3,11 +3,6 @@
\name{ggplot_sir}
\alias{ggplot_sir}
\alias{geom_sir}
\alias{facet_sir}
\alias{scale_y_percent}
\alias{scale_sir_colours}
\alias{theme_sir}
\alias{labels_sir_count}
\title{AMR Plots with \code{ggplot2}}
\usage{
ggplot_sir(
@ -46,28 +41,6 @@ geom_sir(
combine_SI = TRUE,
...
)
facet_sir(facet = c("interpretation", "antibiotic"), nrow = NULL)
scale_y_percent(
breaks = function(x) seq(0, max(x, na.rm = TRUE), 0.1),
limits = NULL
)
scale_sir_colours(..., aesthetics = "fill")
theme_sir()
labels_sir_count(
position = NULL,
x = "antibiotic",
translate_ab = "name",
minimum = 30,
language = get_AMR_locale(),
combine_SI = TRUE,
datalabels.size = 3,
datalabels.colour = "grey15"
)
}
\arguments{
\item{data}{a \link{data.frame} with column(s) of class \code{\link{sir}} (see \code{\link[=as.sir]{as.sir()}})}
@ -121,23 +94,20 @@ Use these functions to create bar plots for AMR data analysis. All functions rel
}
\details{
At default, the names of antibiotics will be shown on the plots using \code{\link[=ab_name]{ab_name()}}. This can be set with the \code{translate_ab} argument. See \code{\link[=count_df]{count_df()}}.
\subsection{The Functions}{
\code{\link[=geom_sir]{geom_sir()}} will take any variable from the data that has an \code{\link{sir}} class (created with \code{\link[=as.sir]{as.sir()}}) using \code{\link[=sir_df]{sir_df()}} and will plot bars with the percentage S, I, and R. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis.
\code{\link[=facet_sir]{facet_sir()}} creates 2d plots (at default based on S/I/R) using \code{\link[ggplot2:facet_wrap]{ggplot2::facet_wrap()}}.
\code{\link[=scale_y_percent]{scale_y_percent()}} transforms the y axis to a 0 to 100\% range using \code{\link[ggplot2:scale_continuous]{ggplot2::scale_y_continuous()}}.
\code{\link[=scale_sir_colours]{scale_sir_colours()}} sets colours to the bars (green for S, yellow for I, and red for R). with multilingual support. The default colours are colour-blind friendly, while maintaining the convention that e.g. 'susceptible' should be green and 'resistant' should be red.
\code{\link[=theme_sir]{theme_sir()}} is a [ggplot2 theme][\code{\link[ggplot2:theme]{ggplot2::theme()}} with minimal distraction.
\code{\link[=labels_sir_count]{labels_sir_count()}} print datalabels on the bars with percentage and amount of isolates using \code{\link[ggplot2:geom_text]{ggplot2::geom_text()}}.
Additional functions include:
\itemize{
\item \code{\link[=facet_sir]{facet_sir()}} creates 2d plots (at default based on S/I/R) using \code{\link[ggplot2:facet_wrap]{ggplot2::facet_wrap()}}.
\item \code{\link[=scale_y_percent]{scale_y_percent()}} transforms the y axis to a 0 to 100\% range using \code{\link[ggplot2:scale_continuous]{ggplot2::scale_y_continuous()}}.
\item \code{\link[=scale_sir_colours]{scale_sir_colours()}} sets colours to the bars (green for S, yellow for I, and red for R). with multilingual support. The default colours are colour-blind friendly, while maintaining the convention that e.g. 'susceptible' should be green and 'resistant' should be red.
\item \code{\link[=theme_sir]{theme_sir()}} is a [ggplot2 theme][\code{\link[ggplot2:theme]{ggplot2::theme()}} with minimal distraction.
\item \code{\link[=labels_sir_count]{labels_sir_count()}} print datalabels on the bars with percentage and amount of isolates using \code{\link[ggplot2:geom_text]{ggplot2::geom_text()}}.
}
\code{\link[=ggplot_sir]{ggplot_sir()}} is a wrapper around all above functions that uses data as first input. This makes it possible to use this function after a pipe (\verb{\%>\%}). See \emph{Examples}.
}
}
\examples{
\donttest{
if (require("ggplot2") && require("dplyr")) {