Package 'utile.visuals'

Append a ggplot2 table to the bottom of a ggplot2 plot

Description

Aligns axes and combines a ggplot2 plot and table into a single plot. Can handle legends.

Usage

append_table(
  plot = NULL,
  table = NULL,
  plot.height = 1,
  table.height = 0.1,
  plot.width = 1,
  legend.width = 0.2,
  legend.offset = -15
)

Arguments

plot	A ggplot2::ggplot() object. If a legend is present, it will be extracted.
table	A ggplot2::ggplot object. If a legend is present, it will be removed and ignored.
plot.height	A numeric. Height of plot relative to table. Defaults to 1.
table.height	A numeric. Height of table relative to plot. Defaults to 0.1.
plot.width	A numeric. Width of plot relative to legend. Ignored if no legend present in plot. Defaults to 1.
legend.width	A numeric. Width of legend relative to plot. Ignored if no legend present in plot. Defaults 0.2.
legend.offset	A numeric. Vertical offset of legend box. Used to raise or lower. Ignored if no legend present in plot. Defaults to -15.

Value

A ggplot2 tableGrob object. Use grid::grid.draw() to open in RStudio viewer. Works with ggplot2::ggsave() out of the box.

Note

To ensure proper alignment, double check that both plots use the same scale and breaks!

Examples

library(survival)
library(ggplot2)
library(grid) # grid.draw() finished plot

# Data with group names specified
data_diabetic <- diabetic
data_diabetic$trt <- as.factor(data_diabetic$trt)
levels(data_diabetic$trt) <- c('None', 'Laser')

# Survival Model
fit <- survfit(Surv(time, status) ~ trt, data = data_diabetic)
fit <- survfit0(fit)

# Kaplan Meier (KM) Plot
plot_km <- ggplot(
 data = data.frame(
  time = fit$time,
  surv = fit$surv,
  conf.low = fit$lower,
  conf.high = fit$upper,
  strata = rep(names(fit$strata), fit$strata)
 ),
 mapping = aes(x = time, y = surv)
) +
  geom_step(aes(color = strata)) +
  geom_stepconfint(aes(ymin = conf.low, ymax = conf.high, fill = strata), alpha = 0.3) +
  coord_cartesian(c(0, 50)) + # Note scale set here!
  scale_x_continuous(expand = c(0.02,0)) +
  labs(x = 'Time', y = 'Freedom From Event') +
  scale_color_manual(
    values = c('#d83641', '#1A45A7'),
    name = 'Treatment',
    labels = c('Laser', 'None'),
    aesthetics = c('colour', 'fill')) +
  theme_basic()

# Risk Table
tbl_risk <- ggrisktable(fit, c(0, 10, 20, 30, 40, 50)) +
  coord_cartesian(c(0, 50)) +
  scale_x_continuous(expand = c(0.02,0)) +
  theme_risk()

# Combine KM plot and risk table
plot_cmbd <- append_table(
  plot = plot_km,
  table = tbl_risk
)

# Draw in RStudio viewer
grid.newpage()
grid.draw(plot_cmbd)

---

Step function confidence intervals for ggplot2

Description

Produces a step function confidence interval for survival curves.

Usage

geom_stepconfint(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  na.rm = FALSE,
  ...
)

Arguments

mapping	Aesthetic mappings with aes() function. Like geom_ribbon(), you must provide columns for x, ymin (lower limit), ymax (upper limit).
data	The data to be displayed in this layer. Can inherit from ggplot parent.
stat	The statistical transformation to use on the data for this layer, as a string. Defaults to 'identity'.
position	Position adjustment, either as a string, or the result of a call to a position adjustment function.
na.rm	If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.
...	Optional. Any other ggplot geom_ribbon() arguments.

Note

Adapted from the survminer package <https://github.com/kassambara/survminer>.

Examples

library(survival)
library(ggplot2)

fit <- survfit(Surv(time, status) ~ trt, data = diabetic)
fit <- survfit0(fit) # connect origin

ggplot(
  data = data.frame(
    time = fit$time,
    surv = fit$surv,
    conf.low = fit$lower,
    conf.high = fit$upper,
    strata = rep(names(fit$strata), fit$strata)
  ),
  mapping = aes(x = time, y = surv)
) +
  geom_step(aes(color = strata)) +
  geom_stepconfint(aes(ymin = conf.low, ymax = conf.high, fill = strata), alpha = 0.3) +
  coord_cartesian(c(0, 50)) +
  scale_x_continuous(expand = c(0.02,0)) +
  labs(x = 'Time', y = 'Freedom From Event') +
  scale_color_manual(
    values = c('#d83641', '#1A45A7'),
    name = 'Treatment',
    labels = c('None', 'Laser'),
    aesthetics = c('colour', 'fill')) +
  theme_basic()

---

Create a ggplot2 table showing the number at risk

Description

A simple wrapper function which calculates the numbers at risk for a survival model and a given set of time points then creates a ggplot2 table with them.

Usage

ggrisktable(
  fit = NULL,
  times = NULL,
  text.color = "black",
  strata.order = NULL
)

Arguments

fit	Required. survival::survfit() object.
times	Required. Numeric. One or more time points to calculate the number at risk for.
text.color	Optional. Character. Color of text within table. Defaults to 'black'.
strata.order	Optional. Character. Ordered names of strata factor levels.

Value

An unformatted ggplot2 table showing the number at risk.

Examples

library(survival)

fit <- survfit(Surv(time, status) ~ trt, data = diabetic)

ggrisktable(
   fit = fit,
   times = c(0, 10, 20, 30, 40, 50),
   strata.order = c('0', '1')
) + theme_risk()

---

Add a panel border to a ggplot2 plot

Description

A simple ggplot2 theme which replaces the axis lines with a bordered panel.

Usage

panel_border(base_size = 12, base_color = NULL)

Arguments

base_size	A numeric. Base size. Used to calculate line size and spacing.
base_color	A character. Base color for lines.

Note

This should be placed after the primary theme for the plot.

Examples

library(ggplot2)

ggplot(datasets::mtcars, aes(x = wt, y = hp, color = as.factor(cyl))) +
  geom_point() +
  facet_wrap(~as.logical(am)) +
  theme_basic() +
  panel_border()

---

Minimalist theme for ggplot2

Description

A minimalist ggplot2 theme which removes most background elements and lines.

Usage

theme_basic(
  base_size = 12,
  base_family = NULL,
  base_color = "black",
  base_line_size = base_size/12,
  base_rect_size = base_size/12
)

Arguments

base_size	A numeric. Base font size.
base_family	A numeric. Base font family.
base_color	A character. Base color for lines and text.
base_line_size	A numeric. Base line element size.
base_rect_size	A numeric. Base rectangle element size.

Note

Recommend exporting as PNG or TIFF to preserve background transparency.

Examples

library(ggplot2)

ggplot(datasets::mtcars, aes(x = wt, y = hp, color = as.factor(cyl))) +
  geom_point() +
  theme_basic()

---

Minimalist risk table theme for ggplot2

Description

A minimalist ggplot2 theme which removes most background elements and lines.

Usage

theme_risk(
  base_size = 12,
  base_family = NULL,
  base_color = "black",
  base_line_size = base_size/12,
  base_rect_size = base_size/12
)

Arguments

base_size	A numeric. Base font size.
base_family	A numeric. Base font family.
base_color	A character. Base color for lines and text.
base_line_size	A numeric. Base line element size.
base_rect_size	A numeric. Base rectangle element size.

Note

Recommend exporting as PNG or TIFF to preserve background transparency.

See Also

ggrisktable

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