Package 'certeplot2'

Methods for plot2()

Description

These are the implemented methods for different S3 classes to be used in plot2(). Since they have an extensive list of arguments, they are placed here on a separate manual page.

Usage

## S3 method for class 'bug_drug_combinations'
plot2(
  .data,
  x = ab,
  y = value,
  category = name,
  facet = mo,
  type = "column",
  x.title = FALSE,
  y.title = FALSE,
  category.title = NULL,
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  tag = NULL,
  title.linelength = 60,
  title.colour = getOption("plot2.colour_font_primary", "black"),
  subtitle.linelength = 60,
  subtitle.colour = getOption("plot2.colour_font_secondary", "grey35"),
  na.replace = "",
  na.rm = FALSE,
  facet.position = "top",
  facet.fill = NULL,
  facet.bold = TRUE,
  facet.italic = FALSE,
  facet.size = 10,
  facet.margin = 8,
  facet.repeat_lbls_x = TRUE,
  facet.repeat_lbls_y = TRUE,
  facet.fixed_y = NULL,
  facet.fixed_x = TRUE,
  facet.drop = FALSE,
  facet.nrow = NULL,
  facet.relative = FALSE,
  x.date_breaks = NULL,
  x.date_labels = NULL,
  x.date_remove_years = NULL,
  category.focus = NULL,
  colour = get_colour("certe_sir2", 7),
  colour_fill = NULL,
  colour_opacity = 0,
  x.lbl_angle = ifelse(horizontal, 0, 90),
  x.lbl_align = NULL,
  x.lbl_italic = FALSE,
  x.lbl_taxonomy = TRUE,
  x.remove = FALSE,
  x.position = "bottom",
  x.max_items = Inf,
  x.max_txt = "(rest, x%n)",
  category.max_items = Inf,
  category.max_txt = "(rest, x%n)",
  facet.max_items = Inf,
  facet.max_txt = "(rest, x%n)",
  x.breaks = NULL,
  x.n_breaks = NULL,
  x.transform = "identity",
  x.expand = NULL,
  x.limits = NULL,
  x.labels = NULL,
  x.character = NULL,
  x.drop = FALSE,
  x.mic = FALSE,
  x.zoom = FALSE,
  y.remove = FALSE,
  y.24h = FALSE,
  y.age = FALSE,
  y.scientific = NULL,
  y.percent = FALSE,
  y.percent_break = 0.1,
  y.breaks = NULL,
  y.n_breaks = NULL,
  y.limits = NULL,
  y.labels = NULL,
  y.expand = NULL,
  y.transform = "identity",
  y.position = "left",
  y.zoom = FALSE,
  y_secondary = NULL,
  y_secondary.type = type,
  y_secondary.title = TRUE,
  y_secondary.colour = "certeroze",
  y_secondary.colour_fill = "certeroze6",
  y_secondary.scientific = NULL,
  y_secondary.percent = FALSE,
  y_secondary.labels = NULL,
  category.labels = NULL,
  category.percent = FALSE,
  category.breaks = NULL,
  category.limits = NULL,
  category.expand = 0,
  category.midpoint = NULL,
  category.transform = "identity",
  category.date_breaks = NULL,
  category.date_labels = NULL,
  category.character = NULL,
  x.sort = NULL,
  category.sort = FALSE,
  facet.sort = TRUE,
  x.complete = NULL,
  category.complete = NULL,
  facet.complete = NULL,
  datalabels = TRUE,
  datalabels.round = ifelse(y.percent, 2, 1),
  datalabels.format = "%n",
  datalabels.colour = "grey25",
  datalabels.colour_fill = NULL,
  datalabels.size = (3 * text_factor),
  datalabels.angle = 0,
  datalabels.lineheight = 1,
  decimal.mark = dec_mark(),
  big.mark = big_mark(),
  summarise_function = base::sum,
  stacked = FALSE,
  stackedpercent = TRUE,
  horizontal = TRUE,
  reverse = TRUE,
  smooth = NULL,
  smooth.method = NULL,
  smooth.formula = NULL,
  smooth.se = TRUE,
  smooth.level = 0.95,
  smooth.alpha = 0.25,
  smooth.linewidth = 0.75,
  smooth.linetype = 3,
  smooth.colour = NULL,
  size = NULL,
  linetype = 1,
  linewidth = NULL,
  binwidth = NULL,
  width = NULL,
  jitter_seed = NA,
  violin_scale = "count",
  legend.position = NULL,
  legend.title = NULL,
  legend.reverse = TRUE,
  legend.barheight = 6,
  legend.barwidth = 1.5,
  legend.nbin = 300,
  legend.italic = FALSE,
  sankey.node_width = 0.15,
  sankey.node_whitespace = 0.03,
  sankey.alpha = 0.5,
  sankey.remove_axes = NULL,
  zoom = FALSE,
  sep = " / ",
  print = FALSE,
  text_factor = 1,
  font = getOption("plot2.font"),
  theme = getOption("plot2.theme", "theme_minimal2"),
  background = getOption("plot2.colour_background", "white"),
  markdown = TRUE,
  data = NULL,
  minimum = 30,
  remove_intrinsic_resistant = TRUE,
  language = "nl",
  ...
)

## S3 method for class 'antibiogram'
plot2(
  .data,
  x = NULL,
  y = NULL,
  category = NULL,
  facet = NULL,
  type = NULL,
  x.title = NULL,
  y.title = NULL,
  category.title = NULL,
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  tag = NULL,
  title.linelength = 60,
  title.colour = getOption("plot2.colour_font_primary", "black"),
  subtitle.linelength = 60,
  subtitle.colour = getOption("plot2.colour_font_secondary", "grey35"),
  na.replace = "",
  na.rm = FALSE,
  facet.position = "top",
  facet.fill = NULL,
  facet.bold = TRUE,
  facet.italic = FALSE,
  facet.size = 10,
  facet.margin = 8,
  facet.repeat_lbls_x = TRUE,
  facet.repeat_lbls_y = TRUE,
  facet.fixed_y = NULL,
  facet.fixed_x = TRUE,
  facet.drop = FALSE,
  facet.nrow = NULL,
  facet.relative = FALSE,
  x.date_breaks = NULL,
  x.date_labels = NULL,
  x.date_remove_years = NULL,
  category.focus = NULL,
  colour = getOption("plot2.colour", "ggplot2"),
  colour_fill = NULL,
  colour_opacity = 0,
  x.lbl_angle = 0,
  x.lbl_align = NULL,
  x.lbl_italic = FALSE,
  x.lbl_taxonomy = FALSE,
  x.remove = FALSE,
  x.position = "bottom",
  x.max_items = Inf,
  x.max_txt = "(rest, x%n)",
  category.max_items = Inf,
  category.max_txt = "(rest, x%n)",
  facet.max_items = Inf,
  facet.max_txt = "(rest, x%n)",
  x.breaks = NULL,
  x.n_breaks = NULL,
  x.transform = "identity",
  x.expand = NULL,
  x.limits = NULL,
  x.labels = NULL,
  x.character = NULL,
  x.drop = FALSE,
  x.mic = FALSE,
  x.zoom = FALSE,
  y.remove = FALSE,
  y.24h = FALSE,
  y.age = FALSE,
  y.scientific = NULL,
  y.percent = FALSE,
  y.percent_break = 0.1,
  y.breaks = NULL,
  y.n_breaks = NULL,
  y.limits = NULL,
  y.labels = NULL,
  y.expand = NULL,
  y.transform = "identity",
  y.position = "left",
  y.zoom = FALSE,
  y_secondary = NULL,
  y_secondary.type = type,
  y_secondary.title = TRUE,
  y_secondary.colour = "certeroze",
  y_secondary.colour_fill = "certeroze6",
  y_secondary.scientific = NULL,
  y_secondary.percent = FALSE,
  y_secondary.labels = NULL,
  category.labels = NULL,
  category.percent = FALSE,
  category.breaks = NULL,
  category.limits = NULL,
  category.expand = 0,
  category.midpoint = NULL,
  category.transform = "identity",
  category.date_breaks = NULL,
  category.date_labels = NULL,
  category.character = NULL,
  x.sort = NULL,
  category.sort = TRUE,
  facet.sort = TRUE,
  x.complete = NULL,
  category.complete = NULL,
  facet.complete = NULL,
  datalabels = TRUE,
  datalabels.round = ifelse(y.percent, 2, 1),
  datalabels.format = "%n",
  datalabels.colour = "grey25",
  datalabels.colour_fill = NULL,
  datalabels.size = (3 * text_factor),
  datalabels.angle = 0,
  datalabels.lineheight = 1,
  decimal.mark = dec_mark(),
  big.mark = big_mark(),
  summarise_function = base::sum,
  stacked = FALSE,
  stackedpercent = FALSE,
  horizontal = FALSE,
  reverse = horizontal,
  smooth = NULL,
  smooth.method = NULL,
  smooth.formula = NULL,
  smooth.se = TRUE,
  smooth.level = 0.95,
  smooth.alpha = 0.25,
  smooth.linewidth = 0.75,
  smooth.linetype = 3,
  smooth.colour = NULL,
  size = NULL,
  linetype = 1,
  linewidth = NULL,
  binwidth = NULL,
  width = NULL,
  jitter_seed = NA,
  violin_scale = "count",
  legend.position = NULL,
  legend.title = NULL,
  legend.reverse = FALSE,
  legend.barheight = 6,
  legend.barwidth = 1.5,
  legend.nbin = 300,
  legend.italic = FALSE,
  sankey.node_width = 0.15,
  sankey.node_whitespace = 0.03,
  sankey.alpha = 0.5,
  sankey.remove_axes = NULL,
  zoom = FALSE,
  sep = " / ",
  print = FALSE,
  text_factor = 1,
  font = getOption("plot2.font"),
  theme = getOption("plot2.theme", "theme_minimal2"),
  background = getOption("plot2.colour_background", "white"),
  markdown = TRUE,
  data = NULL,
  ...
)

## S3 method for class 'sir_df'
plot2(
  .data,
  x = NULL,
  y = isolates,
  category = interpretation,
  facet = antibiotic,
  type = "column",
  x.title = TRUE,
  y.title = FALSE,
  category.title = NULL,
  title = FALSE,
  subtitle = NULL,
  caption = NULL,
  tag = NULL,
  title.linelength = 60,
  title.colour = getOption("plot2.colour_font_primary", "black"),
  subtitle.linelength = 60,
  subtitle.colour = getOption("plot2.colour_font_secondary", "grey35"),
  na.replace = "",
  na.rm = FALSE,
  facet.position = "top",
  facet.fill = NULL,
  facet.bold = TRUE,
  facet.italic = FALSE,
  facet.size = 10,
  facet.margin = 8,
  facet.repeat_lbls_x = TRUE,
  facet.repeat_lbls_y = TRUE,
  facet.fixed_y = NULL,
  facet.fixed_x = TRUE,
  facet.drop = FALSE,
  facet.nrow = NULL,
  facet.relative = FALSE,
  x.date_breaks = NULL,
  x.date_labels = NULL,
  x.date_remove_years = NULL,
  category.focus = NULL,
  colour = get_colour("certe_sir2", 5),
  colour_fill = NULL,
  colour_opacity = 0,
  x.lbl_angle = 0,
  x.lbl_align = NULL,
  x.lbl_italic = FALSE,
  x.lbl_taxonomy = TRUE,
  x.remove = FALSE,
  x.position = "bottom",
  x.max_items = Inf,
  x.max_txt = "(rest, x%n)",
  category.max_items = Inf,
  category.max_txt = "(rest, x%n)",
  facet.max_items = Inf,
  facet.max_txt = "(rest, x%n)",
  x.breaks = NULL,
  x.n_breaks = NULL,
  x.transform = "identity",
  x.expand = NULL,
  x.limits = NULL,
  x.labels = NULL,
  x.character = NULL,
  x.drop = FALSE,
  x.mic = FALSE,
  x.zoom = FALSE,
  y.remove = FALSE,
  y.24h = FALSE,
  y.age = FALSE,
  y.scientific = NULL,
  y.percent = FALSE,
  y.percent_break = 0.1,
  y.breaks = NULL,
  y.n_breaks = NULL,
  y.limits = NULL,
  y.labels = NULL,
  y.expand = NULL,
  y.transform = "identity",
  y.position = "left",
  y.zoom = FALSE,
  y_secondary = NULL,
  y_secondary.type = type,
  y_secondary.title = TRUE,
  y_secondary.colour = "certeroze",
  y_secondary.colour_fill = "certeroze6",
  y_secondary.scientific = NULL,
  y_secondary.percent = FALSE,
  y_secondary.labels = NULL,
  category.labels = NULL,
  category.percent = FALSE,
  category.breaks = NULL,
  category.limits = NULL,
  category.expand = 0,
  category.midpoint = NULL,
  category.transform = "identity",
  category.date_breaks = NULL,
  category.date_labels = NULL,
  category.character = NULL,
  x.sort = NULL,
  category.sort = FALSE,
  facet.sort = TRUE,
  x.complete = NULL,
  category.complete = NULL,
  facet.complete = NULL,
  datalabels = TRUE,
  datalabels.round = ifelse(y.percent, 2, 1),
  datalabels.format = "%n",
  datalabels.colour = "grey25",
  datalabels.colour_fill = NULL,
  datalabels.size = (3 * text_factor),
  datalabels.angle = 0,
  datalabels.lineheight = 1,
  decimal.mark = dec_mark(),
  big.mark = big_mark(),
  summarise_function = base::sum,
  stacked = FALSE,
  stackedpercent = TRUE,
  horizontal = FALSE,
  reverse = TRUE,
  smooth = NULL,
  smooth.method = NULL,
  smooth.formula = NULL,
  smooth.se = TRUE,
  smooth.level = 0.95,
  smooth.alpha = 0.25,
  smooth.linewidth = 0.75,
  smooth.linetype = 3,
  smooth.colour = NULL,
  size = NULL,
  linetype = 1,
  linewidth = NULL,
  binwidth = NULL,
  width = NULL,
  jitter_seed = NA,
  violin_scale = "count",
  legend.position = NULL,
  legend.title = NULL,
  legend.reverse = FALSE,
  legend.barheight = 6,
  legend.barwidth = 1.5,
  legend.nbin = 300,
  legend.italic = FALSE,
  sankey.node_width = 0.15,
  sankey.node_whitespace = 0.03,
  sankey.alpha = 0.5,
  sankey.remove_axes = NULL,
  zoom = FALSE,
  sep = " / ",
  print = FALSE,
  text_factor = 1,
  font = getOption("plot2.font"),
  theme = getOption("plot2.theme", "theme_minimal2"),
  background = getOption("plot2.colour_background", "white"),
  markdown = TRUE,
  data = NULL,
  ...
)

## S3 method for class 'qc_test'
plot2(
  .data,
  x = x,
  y = y,
  category = rule,
  facet = NULL,
  type = "point",
  x.title = "Index",
  y.title = "Value",
  category.title = NULL,
  title = paste0("QC Chart (", attributes(.data)$guideline, ")"),
  subtitle = NULL,
  caption = NULL,
  tag = NULL,
  title.linelength = 60,
  title.colour = getOption("plot2.colour_font_primary", "black"),
  subtitle.linelength = 60,
  subtitle.colour = getOption("plot2.colour_font_secondary", "grey35"),
  na.replace = "",
  na.rm = FALSE,
  facet.position = "top",
  facet.fill = NULL,
  facet.bold = TRUE,
  facet.italic = FALSE,
  facet.size = 10,
  facet.margin = 8,
  facet.repeat_lbls_x = TRUE,
  facet.repeat_lbls_y = TRUE,
  facet.fixed_y = NULL,
  facet.fixed_x = TRUE,
  facet.drop = FALSE,
  facet.nrow = NULL,
  facet.relative = FALSE,
  x.date_breaks = NULL,
  x.date_labels = NULL,
  x.date_remove_years = NULL,
  category.focus = NULL,
  colour = get_colour(c(Observation = "grey75", `Rule 1` = "certeblauw", `Rule 2` =
    "certegroen", `Rule 3` = "certeroze", `Rule 4` = "certegeel", `Rule 5` = "certelila",
    `Rule 6` = "certebruin", `Rule 7` = "certeblauw2", `Rule 8` = "certegroen2")),
  colour_fill = NULL,
  colour_opacity = 0,
  x.lbl_angle = 0,
  x.lbl_align = NULL,
  x.lbl_italic = FALSE,
  x.lbl_taxonomy = FALSE,
  x.remove = FALSE,
  x.position = "bottom",
  x.max_items = Inf,
  x.max_txt = "(rest, x%n)",
  category.max_items = Inf,
  category.max_txt = "(rest, x%n)",
  facet.max_items = Inf,
  facet.max_txt = "(rest, x%n)",
  x.breaks = NULL,
  x.n_breaks = NULL,
  x.transform = "identity",
  x.expand = NULL,
  x.limits = NULL,
  x.labels = NULL,
  x.character = NULL,
  x.drop = FALSE,
  x.mic = FALSE,
  x.zoom = TRUE,
  y.remove = FALSE,
  y.24h = FALSE,
  y.age = FALSE,
  y.scientific = NULL,
  y.percent = FALSE,
  y.percent_break = 0.1,
  y.breaks = NULL,
  y.n_breaks = NULL,
  y.limits = NULL,
  y.labels = NULL,
  y.expand = NULL,
  y.transform = "identity",
  y.position = "left",
  y.zoom = TRUE,
  y_secondary = NULL,
  y_secondary.type = type,
  y_secondary.title = TRUE,
  y_secondary.colour = "certeroze",
  y_secondary.colour_fill = "certeroze6",
  y_secondary.scientific = NULL,
  y_secondary.percent = FALSE,
  y_secondary.labels = NULL,
  category.labels = NULL,
  category.percent = FALSE,
  category.breaks = NULL,
  category.limits = NULL,
  category.expand = 0,
  category.midpoint = NULL,
  category.transform = "identity",
  category.date_breaks = NULL,
  category.date_labels = NULL,
  category.character = NULL,
  x.sort = NULL,
  category.sort = TRUE,
  facet.sort = TRUE,
  x.complete = NULL,
  category.complete = NULL,
  facet.complete = NULL,
  datalabels = TRUE,
  datalabels.round = ifelse(y.percent, 2, 1),
  datalabels.format = "%n",
  datalabels.colour = "grey25",
  datalabels.colour_fill = NULL,
  datalabels.size = (3 * text_factor),
  datalabels.angle = 0,
  datalabels.lineheight = 1,
  decimal.mark = dec_mark(),
  big.mark = big_mark(),
  summarise_function = base::sum,
  stacked = FALSE,
  stackedpercent = FALSE,
  horizontal = FALSE,
  reverse = horizontal,
  smooth = NULL,
  smooth.method = NULL,
  smooth.formula = NULL,
  smooth.se = TRUE,
  smooth.level = 0.95,
  smooth.alpha = 0.25,
  smooth.linewidth = 0.75,
  smooth.linetype = 3,
  smooth.colour = NULL,
  size = 2,
  linetype = 1,
  linewidth = NULL,
  binwidth = NULL,
  width = NULL,
  jitter_seed = NA,
  violin_scale = "count",
  legend.position = "right",
  legend.title = NULL,
  legend.reverse = FALSE,
  legend.barheight = 6,
  legend.barwidth = 1.5,
  legend.nbin = 300,
  legend.italic = FALSE,
  sankey.node_width = 0.15,
  sankey.node_whitespace = 0.03,
  sankey.alpha = 0.5,
  sankey.remove_axes = NULL,
  zoom = TRUE,
  sep = " / ",
  print = FALSE,
  text_factor = 1,
  font = getOption("plot2.font"),
  theme = getOption("plot2.theme", "theme_minimal2"),
  background = getOption("plot2.colour_background", "white"),
  markdown = TRUE,
  data = NULL,
  ...
)

## S3 method for class 'early_warning_cluster'
plot2(
  .data,
  x = NULL,
  y = NULL,
  category = NULL,
  facet = NULL,
  type = "line",
  x.title = ifelse(attributes(.data)$period_length_months == 12, "Maand in periode",
    "Week in periode"),
  y.title = paste0("Cases (", attributes(.data)$moving_average_days,
    "-daags zwevend gemiddelde)"),
  category.title = "Periode",
  title = paste0(n_distinct(.data$clusters$cluster), " cluster",
    ifelse(n_distinct(.data$clusters$cluster) != 1, "s", "")),
  subtitle = NULL,
  caption = paste0("O.b.v. uitbijter-vrije geschiedenis (coeff = ",
    format2(attributes(.data)$remove_outliers_coefficient), ") met pct = ",
    format2(attributes(.data)$threshold_percentile)),
  tag = NULL,
  title.linelength = 60,
  title.colour = getOption("plot2.colour_font_primary", "black"),
  subtitle.linelength = 60,
  subtitle.colour = getOption("plot2.colour_font_secondary", "grey35"),
  na.replace = "",
  na.rm = FALSE,
  facet.position = "top",
  facet.fill = NULL,
  facet.bold = TRUE,
  facet.italic = FALSE,
  facet.size = 10,
  facet.margin = 8,
  facet.repeat_lbls_x = TRUE,
  facet.repeat_lbls_y = TRUE,
  facet.fixed_y = NULL,
  facet.fixed_x = TRUE,
  facet.drop = FALSE,
  facet.nrow = NULL,
  facet.relative = FALSE,
  x.date_breaks = "1 month",
  x.date_labels = "mmm",
  x.date_remove_years = FALSE,
  category.focus = NULL,
  colour = getOption("plot2.colour", "ggplot2"),
  colour_fill = NULL,
  colour_opacity = 0,
  x.lbl_angle = 0,
  x.lbl_align = NULL,
  x.lbl_italic = FALSE,
  x.lbl_taxonomy = FALSE,
  x.remove = FALSE,
  x.position = "bottom",
  x.max_items = Inf,
  x.max_txt = "(rest, x%n)",
  category.max_items = Inf,
  category.max_txt = "(rest, x%n)",
  facet.max_items = Inf,
  facet.max_txt = "(rest, x%n)",
  x.breaks = seq(0, 9999, 14),
  x.n_breaks = NULL,
  x.transform = "identity",
  x.expand = NULL,
  x.limits = NULL,
  x.labels = function(x) x/7,
  x.character = NULL,
  x.drop = FALSE,
  x.mic = FALSE,
  x.zoom = FALSE,
  y.remove = FALSE,
  y.24h = FALSE,
  y.age = FALSE,
  y.scientific = NULL,
  y.percent = FALSE,
  y.percent_break = 0.1,
  y.breaks = NULL,
  y.n_breaks = NULL,
  y.limits = NULL,
  y.labels = NULL,
  y.expand = NULL,
  y.transform = "identity",
  y.position = "left",
  y.zoom = FALSE,
  y_secondary = NULL,
  y_secondary.type = type,
  y_secondary.title = TRUE,
  y_secondary.colour = "certeroze",
  y_secondary.colour_fill = "certeroze6",
  y_secondary.scientific = NULL,
  y_secondary.percent = FALSE,
  y_secondary.labels = NULL,
  category.labels = md_to_expression,
  category.percent = FALSE,
  category.breaks = NULL,
  category.limits = NULL,
  category.expand = 0,
  category.midpoint = NULL,
  category.transform = "identity",
  category.date_breaks = NULL,
  category.date_labels = NULL,
  category.character = TRUE,
  x.sort = NULL,
  category.sort = "asc",
  facet.sort = TRUE,
  x.complete = NULL,
  category.complete = NULL,
  facet.complete = NULL,
  datalabels = TRUE,
  datalabels.round = ifelse(y.percent, 2, 1),
  datalabels.format = "%n",
  datalabels.colour = "grey25",
  datalabels.colour_fill = NULL,
  datalabels.size = (2.5 * text_factor),
  datalabels.angle = 0,
  datalabels.lineheight = 1,
  decimal.mark = dec_mark(),
  big.mark = big_mark(),
  summarise_function = base::sum,
  stacked = FALSE,
  stackedpercent = FALSE,
  horizontal = FALSE,
  reverse = horizontal,
  smooth = NULL,
  smooth.method = NULL,
  smooth.formula = NULL,
  smooth.se = TRUE,
  smooth.level = 0.95,
  smooth.alpha = 0.25,
  smooth.linewidth = 0.75,
  smooth.linetype = 3,
  smooth.colour = NULL,
  size = NULL,
  linetype = 1,
  linewidth = NULL,
  binwidth = NULL,
  width = NULL,
  jitter_seed = NA,
  violin_scale = "count",
  legend.position = "right",
  legend.title = NULL,
  legend.reverse = FALSE,
  legend.barheight = 6,
  legend.barwidth = 1.5,
  legend.nbin = 300,
  legend.italic = FALSE,
  sankey.node_width = 0.15,
  sankey.node_whitespace = 0.03,
  sankey.alpha = 0.5,
  sankey.remove_axes = NULL,
  zoom = FALSE,
  sep = " / ",
  print = FALSE,
  text_factor = 1,
  font = getOption("plot2.font"),
  theme = getOption("plot2.theme", "theme_minimal2"),
  background = getOption("plot2.colour_background", "white"),
  markdown = TRUE,
  data = NULL,
  ...
)

Arguments

.data, data	data to plot
x	plotting 'direction' for the x axis. This can be: A single variable from .data, such as x = column1 A function to calculate over one or more variables from .data, such as x = format(column1, "%Y"), or x = ifelse(column1 == "A", "Group A", "Other") Multiple variables from .data, such as x = c(column1, column2, column2), or using selection helpers such as x = where(is.character) or x = starts_with("var_") (only allowed and required for Sankey plots using type = "sankey")
y	values to use for plotting along the y axis. This can be: A single variable from .data, such as y = column1 Multiple variables from .data, such as y = c(column1, column2) or y = c(name1 = column1, "name 2" = column2), or using selection helpers such as y = where(is.double) or y = starts_with("var_") (multiple variables only allowed if category is not set) A function to calculate over .data returning a single value, such as y = n() for the row count, or based on other variables such as y = n_distinct(person_id), y = max(column1), or y = median(column2) / column3 A function to calculate over .data returning multiple values, such as y = quantile(column1, c(0.25, 0.75)) or y = range(age) (multiple values only allowed if category is not set)
category, facet	plotting 'direction' (category is called 'fill' and 'colour' in ggplot2). This can be: A single variable from .data, such as category = column1 A function to calculate over one or more variables from .data, such as category = median(column2) / column3, or facet = ifelse(column1 == "A", "Group A", "Other") Multiple variables from .data, such as facet = c(column1, column2) (use sep to control the separator character) One or more variables from .data using selection helpers, such as category = where(is.double) or facet = starts_with("var_") The category can also be a date or date/time (class Date or POSIXt).
type, y_secondary.type	type of visualisation to use. This can be: A ggplot2 geom name or their abbreviation such as "col" and "point". All geoms are supported (including geom_blank()). Full function names can be used (e.g., "geom_histogram"), but they can also be abbreviated (e.g., "h", "hist"). The following geoms can be abbreviated by their first character: area ("a"), boxplot ("b"), column ("c"), histogram ("h"), jitter ("j"), line ("l"), point ("p"), ribbon ("r"), and violin ("v"). Please note: in ggplot2, 'bars' and 'columns' are equal, while it is common to many people that 'bars' are oriented horizontally and 'columns' are oriented vertically since Microsoft Excel has been using these terms this way for many years. For this reason, type = "bar" will set type = "col" and horizontal = TRUE. One of these additional types: "barpercent" (short: "bp"), which is effectively a shortcut to set type = "col" and horizontal = TRUE and x.max_items = 10 and x.sort = "freq-desc" and datalabels.format = "%n (%p)". "linedot" (short: "ld"), which sets type = "line" and adds two point geoms using add_point(); one with large white dots and one with smaller dots using the colours set in colour. This is essentially equal to base R plot(..., type = "b") but with closed shapes. "dumbbell" (short: "d"), which sets type = "point" and horizontal = TRUE, and adds a line between the points (using geom_segment()). The line colour cannot be changed. This plot type is only possible when the category has two distinct values. "sankey" (short: "s") creates a Sankey plots using category for the flows and requires x to contain multiple variables from .data. At default, it also sets x.expand = c(0.05, 0.05) and y.limits = c(NA, NA) and y.expand = c(0.01, 0.01). The so-called 'nodes' (the 'blocks' with text) are considered the datalabels, so you can set the text size and colour of the nodes using datalabels.size, datalabels.colour, and datalabels.colour_fill. The transparency of the flows can be set using sankey.alpha, and the width of the nodes can be set using sankey.node_width. Sankey plots can also be flipped using horizontal = TRUE. Left blank. In this case, the type will be determined automatically: "boxplot" if there is no x axis or if the length of unique values per x axis item is at least 3, "point" if both the y and x axes are numeric, and the option "plot2.default_type" otherwise (which defaults to "col"). Use type = "blank" or type = "geom_blank" to not add a geom.
title, subtitle, caption, tag, x.title, y.title, category.title, legend.title, y_secondary.title	a title to use. This can be: A character, which supports markdown by using md_to_expression() internally if markdown = TRUE (which is the default) A function to calculate over .data, such as title = paste("Based on n =", n_distinct(person_id), "individuals") or subtitle = paste("Total rows:", n()), see Examples An expression, e.g. using parse(text = "...") The category.title defaults to TRUE if the legend items are numeric.
title.linelength	maximum number of characters per line in the title, before a linebreak occurs
title.colour	text colour of the title
subtitle.linelength	maximum number of characters per line in the subtitle, before a linebreak occurs
subtitle.colour	text colour of the subtitle
na.replace	character to put in place of NA values if na.rm = FALSE
na.rm	remove NA values from showing in the plot
facet.position, facet.fill, facet.bold, facet.italic, facet.size, facet.margin, facet.repeat_lbls_x, facet.repeat_lbls_y, facet.drop, facet.nrow, facet.relative	additional settings for the plotting direction facet
facet.fixed_y	a logical to indicate whether all y scales should have the same limits. Defaults to TRUE only if the coefficient of variation (standard deviation divided by mean) of the maximum values of y is less than 25%.
facet.fixed_x	a logical to indicate whether all x scales should have the same breaks. This acts like the inverse of x.drop.
x.date_breaks	breaks to use when the x axis contains dates, will be determined automatically if left blank. This accepts values such as "1 day" and "2 years".
x.date_labels	labels to use when the x axis contains dates, will be determined automatically if left blank. This accepts 'Excel' date-language such as "d mmmm yyyy".
x.date_remove_years	a logical to indicate whether the years of all x values must be unified. This will set the years of all x values to 1970 if the data does not contain a leap year, and to 1972 otherwise. This allows to plot years on the category while maintaining a date range on x. The default is FALSE, unless category contains all years present in x.
category.focus	a value of category that should be highlighted, meaning that all other values in category will be greyed out. This can also be a numeric value between 1 and the length of unique values of category, e.g. category.focus = 2 to focus on the second legend item.
colour	get_colour(s) to set, will be evaluated with get_colour() if set. This can also be one of the viridis colours with automatic implementation for any plot: "viridis", "magma", "inferno", "plasma", "cividis", "rocket", "mako" or "turbo". Also, this can also be a named vector to match values of category, see Examples. Using a named vector can also be used to manually sort the values of category.
colour_fill	get_colour(s) to be used for filling, will be determined automatically if left blank and will be evaluated with get_colour()
colour_opacity	amount of opacity for colour/colour_fill (0 = solid, 1 = transparent)
x.lbl_angle	angle to use for the x axis in a counter-clockwise direction (i.e., a value of 90 will orient the axis labels from bottom to top, a value of 270 will orient the axis labels from top to bottom)
x.lbl_align	alignment for the x axis between 0 (left aligned) and 1 (right aligned)
x.lbl_italic	logical to indicate whether the x labels should in in italics
x.lbl_taxonomy	a logical to transform all words of the x labels into italics that are in the microorganisms data set of the AMR package. This uses md_to_expression() internally and will set x.labels to parse expressions.
x.remove, y.remove	a logical to indicate whether the axis labels and title should be removed
x.position, y.position	position of the axis
x.max_items, category.max_items, facet.max_items	number of maximum items to use, defaults to infinite. All other values will be grouped and summarised using the summarise_function function. Please note: the sorting will be applied first, allowing to e.g. plot the top n most frequent values of the x axis by combining x.sort = "freq-desc" with ⁠x.max_items =⁠ n.
x.max_txt, category.max_txt, facet.max_txt	the text to use of values not included number of ⁠*.max_items⁠. The placeholder ⁠%n⁠ will be replaced with the outcome of the summarise_function function, the placeholder ⁠%p⁠ will be replaced with the percentage.
x.breaks, y.breaks	a breaks function or numeric vector to use for the axis
x.n_breaks, y.n_breaks	number of breaks, only useful if x.breaks cq. y.breaks is NULL
x.transform, y.transform, category.transform	a transformation function to use, e.g. "log2". This can be: "asinh", "asn", "atanh", "boxcox", "compose", "date", "exp", "hms", "identity", "log", "log10", "log1p", "log2", "logit", "modulus", "probability", "probit", "pseudo_log", "reciprocal", "reverse", "sqrt", "time", "timespan", "yj".
x.expand, y.expand	expansion to use for the axis, can be length 1 or 2. x.expand defaults to 0.5 and y.expand defaults to 0.25, except for sf objects (then both default to 0).
x.limits, y.limits	limits to use for the axis, can be length 1 or 2. Use NA for the highest or lowest value in the data, e.g. y.limits = c(0, NA) to have the y scale start at zero.
x.labels, y.labels, y_secondary.labels	a labels function or character vector to use for the axis
x.character	a logical to indicate whether the values of the x axis should be forced to character. The default is FALSE, except for years (values between 2000 and 2050) and months (values from 1 to 12).
x.drop	logical to indicate whether factor levels should be dropped
x.mic	logical to indicate whether the x axis should be formatted as MIC values, by dropping all factor levels and adding missing factors of 2
x.zoom, y.zoom	a logical to indicate if the axis should be zoomed on the data, by setting x.limits = c(NA, NA) and x.expand = 0 for the x axis, or y.limits = c(NA, NA) and y.expand = 0 for the y axis
y.24h	a logical to indicate whether the y labels and breaks should be formatted as 24-hour sequences
y.age	a logical to indicate whether the y labels and breaks should be formatted as ages in years
y.scientific, y_secondary.scientific	a logical to indicate whether the y labels should be formatted in scientific notation. Defaults to TRUE only if the range of the y values spans more than 10e5.
y.percent, y_secondary.percent	a logical to indicate whether the y labels should be formatted as percentages
y.percent_break	a value on which the y axis should have breaks
y_secondary	values to use for plotting along the secondary y axis. This functionality is poorly supported by ggplot2 and might give unexpected results. Setting the secondary y axis will set the colour to the axis titles.
y_secondary.colour, y_secondary.colour_fill	colours to set for the secondary y axis, will be evaluated with get_colour()
category.labels, category.percent, category.breaks, category.expand, category.midpoint	settings for the plotting direction category.
category.limits	limits to use for a numeric category, can be length 1 or 2. Use NA for the highest or lowest value in the data, e.g. category.limits = c(0, NA) to have the scale start at zero.
category.date_breaks	breaks to use when the category contains dates, will be determined automatically if left blank. This will be passed on to seq.Date(by = ...) and thus can be: a number, taken to be in days, or a character string containing one of "day", "week", "month", "quarter" or "year" (optionally preceded by an integer and a space, and/or followed by "s").
category.date_labels	labels to use when the category contains dates, will be determined automatically if left blank. This accepts 'Excel' date-language such as "d mmmm yyyy".
category.character	a logical to indicate whether the values of the category should be forced to character. The default is FALSE, except for years (values between 2000 and 2050) and months (values from 1 to 12).
x.sort, category.sort, facet.sort	sorting of the plotting direction, defaults to TRUE, except for continuous values on the x axis (such as dates and numbers). Applying one of the sorting methods will transform the values to an ordered factor, which ggplot2 uses to orient the data. Valid values are: A manual vector of values TRUE: sort factors on their levels, otherwise sort ascending on alphabet, while maintaining numbers in the text (numeric sort) FALSE: sort according to the order in the data NULL: do not sort/transform at all "asc" or "alpha": sort as TRUE "desc": sort factors on their reversed levels, otherwise sort descending on alphabet, while maintaining numbers in the text (numeric sort) "order" or "inorder": sort as FALSE "freq" or "freq-desc": sort descending according to the frequencies of y computed by summarise_function (highest value first) "freq-asc": sort ascending according to the frequencies of y computed by summarise_function (lowest value first)
x.complete, category.complete, facet.complete	a value to complete the data. This makes use of tidyr::full_seq() and tidyr::complete(). For example, using x.complete = 0 will apply data |> complete(full_seq(x, ...), fill = list(x = 0)). Using value TRUE (e.g., x.complete = TRUE) is identical to using value 0.
datalabels	values to show as datalabels, see also datalabels.format. This can be: Left blank. This will default to the values of y in column-type plots, or when plotting spatial 'sf' data, the values of the first column. It will print a maximum of 25 labels unless datalabels = TRUE. TRUE or FALSE to force or remove datalabels A function to calculate over .data, such as datalabels = paste(round(column1), "\n", column2)
datalabels.round	number of digits to round the datalabels, applies to both "%n" and "%p" for replacement (see datalabels.format)
datalabels.format	format to use for datalabels. This can be a function (such as euros()) or a text. For the text, "%n" will be replaced by the count number, and "%p" will be replaced by the percentage of the total count. Use datalabels.format = NULL to not transform the datalabels.
datalabels.colour, datalabels.colour_fill, datalabels.size, datalabels.angle, datalabels.lineheight	settings for the datalabels
decimal.mark	decimal mark, defaults to dec_mark()
big.mark	thousands separator, defaults to big_mark()
summarise_function	a function to use if the data has to be summarised, see Examples. This can also be NULL, which will be converted to function(x) x.
stacked	a logical to indicate that values must be stacked
stackedpercent	a logical to indicate that values must be 100% stacked
horizontal	a logical to turn the plot 90 degrees using coord_flip(). This option also updates some theme options, so that e.g., x.lbl_italic will still apply to the original x axis.
reverse	a logical to reverse the values of category. Use legend.reverse to reverse the legend of category.
smooth	a logical to add a smooth. In histograms, this will add the density count as an overlaying line (default: TRUE). In all other cases, a smooth will be added using geom_smooth() (default: FALSE).
smooth.method, smooth.formula, smooth.se, smooth.level, smooth.alpha, smooth.linewidth, smooth.linetype, smooth.colour	settings for smooth
size	size of the geom. Defaults to 2 for geoms point and jitter, 5 for a dumbbell plots (using type = "dumbbell"), and to 0.75 otherwise.
linetype	linetype of the geom, only suitable for geoms that draw lines. Defaults to 1.
linewidth	linewidth of the geom, only suitable for geoms that draw lines. Defaults to: 0.5 for geoms that have no area (such as line), and for geoms boxplot/violin 0.1 for sf 0.25 for geoms that are continous and have fills (such as area) 1.0 for dumbbell plots (using type = "dumbbell") 0.5 otherwise (such as histogram and area)
binwidth	width of bins (only useful for geom = "histogram"), can be specified as a numeric value or as a function that calculates width from x, see geom_histogram(). It defaults to approx. diff(range(x)) divided by 12 to 22 based on the data.
width	width of the geom. Defaults to 0.75 for geoms boxplot, violin and jitter, and to 0.5 otherwise.
jitter_seed	seed (randomisation factor) to be set when using type = "jitter"
violin_scale	scale to be set when using type = "violin", can also be set to "area"
legend.position	position of the legend, must be "top", "right", "bottom", "left" or "none" (or NA or NULL), can be abbreviated. Defaults to "right" for numeric category values and 'sf' plots, and "top" otherwise.
legend.reverse, legend.barheight, legend.barwidth, legend.nbin, legend.italic	other settings for the legend
sankey.node_width	width of the vertical nodes in a Sankey plot (i.e., when type = "sankey")
sankey.node_whitespace	whitespace between the nodes
sankey.alpha	alpha of the flows in a Sankey plot (i.e., when type = "sankey")
sankey.remove_axes	logical to indicate whether all axes must be removed in a Sankey plot (i.e., when type = "sankey")
zoom	a logical to indicate if the plot should be scaled to the data, i.e., not having the x and y axes to start at 0. This will set x.zoom = TRUE and y.zoom = TRUE.
sep	separator character to use if multiple columns are given to either of the three directions: x, category and facet, e.g. facet = c(column1, column2)
print	a logical to indicate if the result should be printed instead of just returned
text_factor	text factor to use, which will apply to all texts shown in the plot
font	font (family) to use, can be set with options(plot2.font = "..."). Can be any installed system font or any of the > 1400 font names from Google Fonts. When using custom fonts in R Markdown, be sure to set the chunk option fig.showtext = TRUE, otherwise an informative error will be generated.
theme	a valid ggplot2 theme to apply, or NULL to use the default theme_grey(). This argument accepts themes (e.g., theme_bw()), functions (e.g., theme_bw) and characters themes (e.g., "theme_bw"). The default is theme_minimal2(), but can be set with options(plot2.theme = "...").
background	the background colour of the entire plot, can also be NA to remove it. Will be evaluated with get_colour(). Only applies when theme is not NULL.
markdown	a logical to turn all labels and titles into plotmath expressions, by converting common markdown language using the md_to_expression() function (defaults to TRUE)
minimum	minimum number of results, defaults to 30
remove_intrinsic_resistant	a logical to indicate that rows with 100% resistance must be removed from the data set before plotting
language	language to be used for antibiotic names
...	any argument to give to the geom. This will override automatically-set settings for the geom.

Details

For antimicrobial resistance (AMR) data analysis, use the bug_drug_combinations() or the sir_df() function from the AMR package on a data set with antibiograms. The result can be used as input for plot2().

The QC-test can be acquired with certestats::qc_test(). It applies the Nelson QC rules for a vector of values.

The detection of disease clusters can be done using certestats::early_warning_cluster(). Use size to alter the size of the triangles that indicate clusters.

Examples

# AMR DATA ANALYSIS ----------------------------------------------------
if (require("AMR")) {
  example_isolates[, c("mo", "AMX", "AMC", "ward")] |>
    antibiogram(mo_transform = "gramstain",
                language = "nl") |>
    plot2()
}

if (require("AMR")) {
  example_isolates[, c("mo", "AMX", "AMC", "ward")] |>
    antibiogram(mo_transform = "gramstain",
                language = "nl",
                syndromic_group = "ward") |>
    plot2()
}

# DISEASE CLUSTERS -----------------------------------------------------
cases <- data.frame(date = sample(seq(as.Date("2015-01-01"),
                                      as.Date("2022-12-31"),
                                      "1 day"),
                                  size = 300),
                    patient = sample(LETTERS, size = 300, replace = TRUE))
check <- certestats::early_warning_cluster(cases,
                                           minimum_cases = 1,
                                           threshold_percentile = 0.75)

check |> plot2()

---

Certe Scales for Aesthetics

Description

These scales apply the colours of Certe, using the 'certestyle' package.

Usage

scale_colour_certe_c(
  ...,
  values = NULL,
  space = "Lab",
  na.value = "grey50",
  guide = "colourbar",
  aesthetics = "colour"
)

scale_color_certe_c(
  ...,
  values = NULL,
  space = "Lab",
  na.value = "grey50",
  guide = "colourbar",
  aesthetics = "colour"
)

scale_fill_certe_c(
  ...,
  values = NULL,
  space = "Lab",
  na.value = "grey50",
  guide = "colourbar",
  aesthetics = "fill"
)

scale_colour_certe_d(colour = "certe")

scale_color_certe_d(colour = "certe")

scale_fill_certe_d(colour = "certe")

Arguments

...	Arguments passed on to continuous_scale scale_name The name of the scale that should be used for error messages associated with this scale. palette A palette function that when called with a numeric vector with values between 0 and 1 returns the corresponding output values (e.g., scales::pal_area()). breaks One of: NULL for no breaks waiver() for the default breaks computed by the transformation object A numeric vector of positions A function that takes the limits as input and returns breaks as output (e.g., a function returned by scales::extended_breaks()). Note that for position scales, limits are provided after scale expansion. Also accepts rlang lambda function notation. minor_breaks One of: NULL for no minor breaks waiver() for the default breaks (one minor break between each major break) A numeric vector of positions A function that given the limits returns a vector of minor breaks. Also accepts rlang lambda function notation. When the function has two arguments, it will be given the limits and major breaks. n.breaks An integer guiding the number of major breaks. The algorithm may choose a slightly different number to ensure nice break labels. Will only have an effect if breaks = waiver(). Use NULL to use the default number of breaks given by the transformation. labels One of: NULL for no labels waiver() for the default labels computed by the transformation object A character vector giving labels (must be same length as breaks) An expression vector (must be the same length as breaks). See ?plotmath for details. A function that takes the breaks as input and returns labels as output. Also accepts rlang lambda function notation. limits One of: NULL to use the default scale range A numeric vector of length two providing limits of the scale. Use NA to refer to the existing minimum or maximum A function that accepts the existing (automatic) limits and returns new limits. Also accepts rlang lambda function notation. Note that setting limits on positional scales will remove data outside of the limits. If the purpose is to zoom, use the limit argument in the coordinate system (see coord_cartesian()). rescaler A function used to scale the input values to the range [0, 1]. This is always scales::rescale(), except for diverging and n colour gradients (i.e., scale_colour_gradient2(), scale_colour_gradientn()). The rescaler is ignored by position scales, which always use scales::rescale(). Also accepts rlang lambda function notation. oob One of: Function that handles limits outside of the scale limits (out of bounds). Also accepts rlang lambda function notation. The default (scales::censor()) replaces out of bounds values with NA. scales::squish() for squishing out of bounds values into range. scales::squish_infinite() for squishing infinite values into range. trans Deprecated in favour of transform. call The call used to construct the scale for reporting messages. super The super class to use for the constructed scale
values	if colours should not be evenly positioned along the gradient this vector gives the position (between 0 and 1) for each colour in the colours vector. See rescale() for a convenience function to map an arbitrary range to between 0 and 1.
space	colour space in which to calculate gradient. Must be "Lab" - other values are deprecated.
na.value	Colour to use for missing values
guide	Type of legend. Use "colourbar" for continuous colour bar, or "legend" for discrete colour legend.
aesthetics	Character string or vector of character strings listing the name(s) of the aesthetic(s) that this scale works with. This can be useful, for example, to apply colour settings to the colour and fill aesthetics at the same time, via aesthetics = c("colour", "fill").
colour	a Certe colour set: "certe", "certe2", "certe3", etc. Will be evaluated with get_colour().

---