knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width=7, fig.height=5 )
This vignette provides some tips for the most common customisations of graphics produced by
plot.incidence. Our graphics use ggplot2, which is a distinct graphical system from base
graphics. If you want advanced customisation of your incidence plots, we recommend following an
introduction to ggplot2.
This example uses the simulated Ebola Virus Disease (EVD) outbreak from the package
First, we load the data:
library(outbreaks) library(ggplot2) library(incidence) onset <- ebola_sim_clean$linelist$date_of_onset class(onset) head(onset)
We compute the weekly incidence:
i <- incidence(onset, interval = 7) i i.sex <- incidence(onset, interval = 7, group = ebola_sim_clean$linelist$gender) i.sex i.hosp <- incidence(onset, interval = 7, group = ebola_sim_clean$linelist$hospital) i.hosp
plot on an incidence object, the function
plot.incidence is implicitly used. To access its documentation, use
?plot.incidence. In this section, we illustrate existing customisations.
By default, the function uses grey for single time series, and colors from the color palette
incidence_pal1 when incidence is computed by groups:
plot(i) plot(i.sex) plot(i.hosp)
However, some of these defaults can be altered through the various arguments of the function:
A color palette is a function which outputs a specified number of colors. By
default, the color used in incidence is called
behaviour is different from usual palettes, in the sense that the first 4
colours are not interpolated:
par(mfrow = c(3, 1), mar = c(4,2,1,1)) barplot(1:2, col = incidence_pal1(2)) barplot(1:4, col = incidence_pal1(4)) barplot(1:20, col = incidence_pal1(20))
This palette also has a light and a dark version:
par(mfrow = c(3,1)) barplot(1:20, col = incidence_pal1_dark(20), main = "palette: incidence_pal1_dark") barplot(1:20, col = incidence_pal1(20), main = "palette: incidence_pal1") barplot(1:20, col = incidence_pal1_light(20), main = "palette: incidence_pal1_light")
Other color palettes can be provided via
col_pal. Various palettes are part of the base R distribution, and many more are provided in additional packages. We provide a couple of examples:
plot(i.hosp, col_pal = rainbow) plot(i.sex, col_pal = cm.colors)
Colors can be specified manually using the argument
color; note that whenever incidence is computed by groups, the number of colors must match the number of groups, otherwise
color is ignored.
plot(i, color = "darkred")
plot(i.sex, color = c(m = "orange2", f = "purple3"))
plot(i.hosp, color = c("#ac3973", "#6666ff", "white", "white", "white", "white"))
Numerous tweaks for ggplot2 are documented online. In the following, we merely provide a few useful tips in the context of incidence.
By default, the dates indicated on the x-axis of an incidence plot may not
have the suitable format.
The package scales can be used to change the way dates are labeled (see
?strptime for possible formats):
library(scales) plot(i, labels_week = FALSE) + scale_x_date(labels = date_format("%d %b %Y"))
Notice how the labels are all situated at the first of the month? If you want to
make sure the labels are situated in a different orientation, you can use the
make_breaks() function to calculate breaks for the plot:
b <- make_breaks(i, labels_week = FALSE) b plot(i) + scale_x_date(breaks = b$breaks, labels = date_format("%d %b %Y"))
And for another example, with a subset of the data (first 50 weeks), using more detailed dates and rotating the annotations:
plot(i[1:50]) + scale_x_date(breaks = b$breaks, labels = date_format("%a %d %B %Y")) + theme(axis.text.x = element_text(angle = 45, hjust = 1, size = 12))
Note that you can save customisations for later use:
rotate.big <- theme(axis.text.x = element_text(angle = 45, hjust = 1, size = 12))
The last example above illustrates that it can be useful to have denser annotations of the x-axis, especially over short time periods. Here, we provide an example where we try to zoom on the peak of the epidemic, using the data by hospital:
Let us look at the data 40 days before and after the 1st of October:
period <- as.Date("2014-10-01") + c(-40, 40) i.zoom <- subset(i.hosp, from = period, to = period) detailed.x <- scale_x_date(labels = date_format("%a %d %B %Y"), date_breaks = "2 weeks", date_minor_breaks = "week") plot(i.zoom, border = "black") + detailed.x + rotate.big
If you have weekly incidence that starts on a day other than monday, then the above solution may produce breaks that fall inside of the bins:
i.sat <- incidence(onset, interval = "1 week: saturday", groups = ebola_sim_clean$linelist$hospital) i.szoom <- subset(i.sat, from = period, to = period) plot(i.szoom, border = "black") + detailed.x + rotate.big
In this case, you may want to either calculate breaks using
scale_x_incidence() function to automatically calculate these for you:
plot(i.szoom, border = "black") + scale_x_incidence(i.szoom, n_breaks = nrow(i.szoom)/2, labels_week = FALSE) + rotate.big
sat_breaks <- make_breaks(i.szoom, n_breaks = nrow(i.szoom)/2) plot(i.szoom, border = "black") + scale_x_date(breaks = sat_breaks$breaks, labels = date_format("%a %d %B %Y")) + rotate.big
Sometimes you may want to label every bin of the incidence object. To do this,
you can simply set
n_breaks to the number of rows in your incidence object:
plot(i.szoom, n_breaks = nrow(i.szoom), border = "black") + rotate.big
The previous plot has a fairly large legend which we may want to move around.
Let us save the plot as a new object
p and customize the legend:
p <- plot(i.zoom, border = "black") + detailed.x + rotate.big p + theme(axis.text.x = element_text(angle = 45, hjust = 1, size = 12), legend.position = "top", legend.direction = "horizontal", legend.title = element_blank())
For small datasets it is convention of EPIET to display individual cases as
rectangles. It can be done by doing two things: first, adding using the option
show_cases = TRUE with a white border and second, setting the background to
white. We also add
coord_equal() which forces each case to be a square.
i.small <- incidence(onset[160:180]) plot(i.small, border = "white", show_cases = TRUE) + theme(panel.background = element_rect(fill = "white")) + rotate.big + coord_equal()
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