Plot function for incidence objects

Source: R/plot.R, R/scale_x_incidence.R

This function is used to visualise the output of the incidence() function using the package ggplot2. #'

# S3 method for class 'incidence'
plot(
  x,
  ...,
  fit = NULL,
  stack = is.null(fit),
  color = "black",
  border = NA,
  col_pal = incidence_pal1,
  alpha = 0.7,
  xlab = "",
  ylab = NULL,
  labels_week = !is.null(x$weeks),
  labels_iso = !is.null(x$isoweeks),
  show_cases = FALSE,
  n_breaks = 6
)

add_incidence_fit(p, x, col_pal = incidence_pal1)

# S3 method for class 'incidence_fit'
plot(x, ...)

# S3 method for class 'incidence_fit_list'
plot(x, ...)

scale_x_incidence(x, n_breaks = 6, labels_week = TRUE, ...)

make_breaks(x, n_breaks = 6L, labels_week = TRUE)

Arguments

x

An incidence object, generated by the function incidence().

...

arguments passed to ggplot2::scale_x_date(), ggplot2::scale_x_datetime(), or ggplot2::scale_x_continuous(), depending on how the $date element is stored in the incidence object.

fit

An 'incidence_fit' object as returned by fit().

stack

A logical indicating if bars of multiple groups should be stacked, or displayed side-by-side.

color

The color to be used for the filling of the bars; NA for invisible bars; defaults to "black".

border

The color to be used for the borders of the bars; NA for invisible borders; defaults to NA.

col_pal

The color palette to be used for the groups; defaults to incidence_pal1. See incidence_pal1() for other palettes implemented in incidence.

alpha

The alpha level for color transparency, with 1 being fully opaque and 0 fully transparent; defaults to 0.7.

xlab

The label to be used for the x-axis; empty by default.

ylab

The label to be used for the y-axis; by default, a label will be generated automatically according to the time interval used in incidence computation.

labels_week

a logical value indicating whether labels x axis tick marks are in week format YYYY-Www when plotting weekly incidence; defaults to TRUE.

labels_iso

(deprecated) This has been superceded by labels_iso. Previously:a logical value indicating whether labels x axis tick marks are in ISO 8601 week format yyyy-Www when plotting ISO week-based weekly incidence; defaults to be TRUE.

show_cases

if TRUE (default: FALSE), then each observation will be colored by a border. The border defaults to a white border unless specified otherwise. This is normally used outbreaks with a small number of cases. Note: this can only be used if stack = TRUE

n_breaks

the ideal number of breaks to be used for the x-axis labeling

p

An existing incidence plot.

Value

  • plot() a ggplot2::ggplot() object.

  • make_breaks() a two-element list. The "breaks" element will contain the evenly-spaced breaks as either dates or numbers and the "labels" element will contain either a vector of weeks OR a ggplot2::waiver() object.

  • scale_x_incidence() a ggplot2 "ScaleContinuous" object.

Details

  • plot() will visualise an incidence object using ggplot2

  • make_breaks() calculates breaks from an incidence object that always align with the bins and start on the first observed incidence.

  • scale_x_incidence() produces and appropriate ggplot2 scale based on an incidence object.

See also

The incidence() function to generate the 'incidence' objects.

Author

Thibaut Jombart thibautjombart@gmail.com Zhian N. Kamvar zkamvar@gmail.com

Examples


if(require(outbreaks) && require(ggplot2)) { withAutoprint({
  onset <- outbreaks::ebola_sim$linelist$date_of_onset

  ## daily incidence
  inc <- incidence(onset)
  inc
  plot(inc)

  ## weekly incidence
  inc.week <- incidence(onset, interval = 7)
  inc.week
  plot(inc.week) # default to label x axis tick marks with isoweeks
  plot(inc.week, labels_week = FALSE) # label x axis tick marks with dates
  plot(inc.week, border = "white") # with visible border

  ## use group information
  sex <- outbreaks::ebola_sim$linelist$gender
  inc.week.gender <- incidence(onset, interval = "1 epiweek", groups = sex)
  plot(inc.week.gender)
  plot(inc.week.gender, labels_week = FALSE)

  ## show individual cases at the beginning of the epidemic
  inc.week.8 <- subset(inc.week.gender, to = "2014-06-01")
  p <- plot(inc.week.8, show_cases = TRUE, border = "black")
  p

  ## update the range of the scale
  lim <- c(min(get_dates(inc.week.8)) - 7*5,
           aweek::week2date("2014-W50", "Sunday"))
  lim
  p + scale_x_incidence(inc.week.gender, limits = lim)

  ## customize plot with ggplot2
  plot(inc.week.8, show_cases = TRUE, border = "black") +
    theme_classic(base_size = 16) +
    theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5))

  ## adding fit
  fit <- fit_optim_split(inc.week.gender)$fit
  plot(inc.week.gender, fit = fit)
  plot(inc.week.gender, fit = fit, labels_week = FALSE)

})}
#> > onset <- outbreaks::ebola_sim$linelist$date_of_onset
#> > inc <- incidence(onset)
#> > inc
#> <incidence object>
#> [5888 cases from days 2014-04-07 to 2015-04-30]
#> 
#> $counts: matrix with 389 rows and 1 columns
#> $n: 5888 cases in total
#> $dates: 389 dates marking the left-side of bins
#> $interval: 1 day
#> $timespan: 389 days
#> $cumulative: FALSE
#> 
#> > plot(inc)

#> > inc.week <- incidence(onset, interval = 7)
#> > inc.week
#> <incidence object>
#> [5888 cases from days 2014-04-07 to 2015-04-27]
#> [5888 cases from ISO weeks 2014-W15 to 2015-W18]
#> 
#> $counts: matrix with 56 rows and 1 columns
#> $n: 5888 cases in total
#> $dates: 56 dates marking the left-side of bins
#> $interval: 7 days
#> $timespan: 386 days
#> $cumulative: FALSE
#> 
#> > plot(inc.week)

#> > plot(inc.week, labels_week = FALSE)

#> > plot(inc.week, border = "white")

#> > sex <- outbreaks::ebola_sim$linelist$gender
#> > inc.week.gender <- incidence(onset, interval = "1 epiweek", groups = sex)
#> > plot(inc.week.gender)

#> > plot(inc.week.gender, labels_week = FALSE)

#> > inc.week.8 <- subset(inc.week.gender, to = "2014-06-01")
#> > p <- plot(inc.week.8, show_cases = TRUE, border = "black")
#> > p

#> > lim <- c(min(get_dates(inc.week.8)) - 7 * 5, aweek::week2date("2014-W50", 
#> +     "Sunday"))
#> > lim
#> [1] "2014-03-02" "2014-12-07"
#> > p + scale_x_incidence(inc.week.gender, limits = lim)
#> Scale for x is already present.
#> Adding another scale for x, which will replace the existing scale.

#> > plot(inc.week.8, show_cases = TRUE, border = "black") + theme_classic(base_size = 16) + 
#> +     theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5))

#> > fit <- fit_optim_split(inc.week.gender)$fit
#> > plot(inc.week.gender, fit = fit)
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.

#> > plot(inc.week.gender, fit = fit, labels_week = FALSE)
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.