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https://github.com/msberends/AMR.git
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(v0.6.1.9046) ggplot fix
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@ -14,8 +14,11 @@ ggplot_rsi(data, position = NULL, x = "Antibiotic",
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fill = "Interpretation", facet = NULL, breaks = seq(0, 1, 0.1),
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limits = NULL, translate_ab = "name", combine_SI = TRUE,
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combine_IR = FALSE, language = get_locale(), fun = count_df,
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nrow = NULL, datalabels = FALSE, datalabels.size = 3,
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datalabels.colour = "white", ...)
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nrow = NULL, colours = c(S = "#61a8ff", SI = "#61a8ff", I =
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"#61f7ff", IR = "#ff6961", R = "#ff6961"), datalabels = TRUE,
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datalabels.size = 2.5, datalabels.colour = "gray15", title = NULL,
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subtitle = NULL, caption = NULL, x.title = NULL, y.title = NULL,
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...)
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geom_rsi(position = NULL, x = c("Antibiotic", "Interpretation"),
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fill = "Interpretation", translate_ab = "name",
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@ -26,12 +29,14 @@ facet_rsi(facet = c("Interpretation", "Antibiotic"), nrow = NULL)
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scale_y_percent(breaks = seq(0, 1, 0.1), limits = NULL)
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scale_rsi_colours()
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scale_rsi_colours(colours = c(S = "#61a8ff", SI = "#61a8ff", I =
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"#61f7ff", IR = "#ff6961", R = "#ff6961"))
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theme_rsi()
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labels_rsi_count(position = NULL, x = "Antibiotic",
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datalabels.size = 3, datalabels.colour = "white")
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translate_ab = "name", combine_SI = TRUE, combine_IR = FALSE,
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datalabels.size = 3, datalabels.colour = "gray15")
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}
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\arguments{
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\item{data}{a \code{data.frame} with column(s) of class \code{"rsi"} (see \code{\link{as.rsi}})}
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@ -60,19 +65,31 @@ labels_rsi_count(position = NULL, x = "Antibiotic",
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\item{nrow}{(when using \code{facet}) number of rows}
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\item{datalabels}{show datalabels using \code{labels_rsi_count}, will at default only be shown when \code{fun = count_df}}
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\item{colours}{a named vector with colours for the bars. The names must be one or more of: S, SI, I, IR, R or be \code{FALSE} to use default \code{ggplot2} colours.}
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\item{datalabels}{show datalabels using \code{labels_rsi_count}, will only be shown when \code{fun = count_df}}
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\item{datalabels.size}{size of the datalabels}
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\item{datalabels.colour}{colour of the datalabels}
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\item{title}{text to show as title of the plot}
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\item{subtitle}{text to show as subtitle of the plot}
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\item{caption}{text to show as caption of the plot}
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\item{x.title}{text to show as x axis description}
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\item{y.title}{text to show as y axis description}
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\item{...}{other parameters passed on to \code{geom_rsi}}
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}
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\description{
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Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on internal \code{\link[ggplot2]{ggplot}} functions.
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Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on internal \code{\link[ggplot2]{ggplot}2} functions.
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}
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\details{
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At default, the names of antibiotics will be shown on the plots using \code{\link{ab_name}}. This can be set with the option \code{get_antibiotic_names} (a logical value), so change it e.g. to \code{FALSE} with \code{options(get_antibiotic_names = FALSE)}.
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At default, the names of antibiotics will be shown on the plots using \code{\link{ab_name}}. This can be set with the \code{translate_ab} parameter. See \code{\link{count_df}}.
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\strong{The functions}\cr
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\code{geom_rsi} will take any variable from the data that has an \code{rsi} class (created with \code{\link{as.rsi}}) using \code{fun} (\code{\link{count_df}} at default, can also be \code{\link{portion_df}}) and will plot bars with the percentage R, I and S. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis.
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@ -81,7 +98,7 @@ At default, the names of antibiotics will be shown on the plots using \code{\lin
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\code{scale_y_percent} transforms the y axis to a 0 to 100\% range using \code{\link[ggplot2]{scale_continuous}}.
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\code{scale_rsi_colours} sets colours to the bars: green for S, yellow for I and red for R, using \code{\link[ggplot2]{scale_brewer}}.
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\code{scale_rsi_colours} sets colours to the bars: pastel blue for S, pastel turquoise for I and pastel red for R, using \code{\link[ggplot2]{scale_brewer}}.
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\code{theme_rsi} is a \code{ggplot \link[ggplot2]{theme}} with minimal distraction.
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@ -103,7 +120,7 @@ ggplot(septic_patients \%>\% select(AMX, NIT, FOS, TMP, CIP)) +
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geom_rsi()
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# prettify the plot using some additional functions:
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df <- septic_patients[, c("AMX", "NIT", "FOS", "TMP", "CIP")]
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df <- septic_patients \%>\% select(AMX, NIT, FOS, TMP, CIP)
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ggplot(df) +
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geom_rsi() +
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scale_y_percent() +
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@ -130,6 +147,10 @@ septic_patients \%>\%
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linetype = 2,
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alpha = 0.25)
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septic_patients \%>\%
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select(AMX) \%>\%
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ggplot_rsi(colours = c(SI = "yellow"))
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# resistance of ciprofloxacine per age group
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septic_patients \%>\%
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mutate(first_isolate = first_isolate(.)) \%>\%
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@ -146,44 +167,44 @@ septic_patients \%>\%
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septic_patients \%>\%
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select(AMX, NIT, FOS, TMP, CIP) \%>\%
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ggplot_rsi() + scale_fill_viridis_d()
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# a shorter version which also adjusts data label colours:
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septic_patients \%>\%
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select(AMX, NIT, FOS, TMP, CIP) \%>\%
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ggplot_rsi(colours = FALSE)
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# it also supports groups (don't forget to use the group var on `x` or `facet`):
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septic_patients \%>\%
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select(hospital_id, AMX, NIT, FOS, TMP, CIP) \%>\%
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group_by(hospital_id) \%>\%
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ggplot_rsi(x = hospital_id,
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facet = Antibiotic,
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nrow = 1) +
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labs(title = "AMR of Anti-UTI Drugs Per Hospital",
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x = "Hospital")
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ggplot_rsi(x = "hospital_id",
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facet = "Antibiotic",
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nrow = 1,
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title = "AMR of Anti-UTI Drugs Per Hospital",
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x.title = "Hospital",
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datalabels = FALSE)
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# genuine analysis: check 2 most prevalent microorganisms
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# genuine analysis: check 3 most prevalent microorganisms
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septic_patients \%>\%
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# create new bacterial ID's, with all CoNS under the same group (Becker et al.)
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mutate(mo = as.mo(mo, Becker = TRUE)) \%>\%
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# filter on top three bacterial ID's
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filter(mo \%in\% top_freq(freq(.$mo), 3)) \%>\%
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# determine first isolates
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mutate(first_isolate = first_isolate(.,
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col_date = "date",
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col_patient_id = "patient_id",
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col_mo = "mo")) \%>\%
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# filter on first isolates
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filter(first_isolate == TRUE) \%>\%
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filter_first_isolate() \%>\%
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# get short MO names (like "E. coli")
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mutate(mo = mo_shortname(mo, Becker = TRUE)) \%>\%
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mutate(bug = mo_shortname(mo, Becker = TRUE)) \%>\%
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# select this short name and some antiseptic drugs
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select(mo, CXM, GEN, CIP) \%>\%
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select(bug, CXM, GEN, CIP) \%>\%
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# group by MO
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group_by(mo) \%>\%
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group_by(bug) \%>\%
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# plot the thing, putting MOs on the facet
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ggplot_rsi(x = Antibiotic,
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facet = mo,
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ggplot_rsi(x = "Antibiotic",
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facet = "bug",
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translate_ab = FALSE,
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nrow = 1) +
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labs(title = "AMR of Top Three Microorganisms In Blood Culture Isolates",
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subtitle = "Only First Isolates, CoNS grouped according to Becker et al. (2014)",
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x = "Microorganisms")
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nrow = 1,
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title = "AMR of Top Three Microorganisms In Blood Culture Isolates",
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subtitle = expression(paste("Only First Isolates, CoNS grouped according to Becker ", italic("et al."), " (2014)")),
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x.title = "Antibiotic (EARS-Net code)")
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}
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}
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