gg_doubleplot: Double Plots

In LightLogR: Process Data from Wearable Light Loggers and Optical Radiation Dosimeters

Double Plots

Description

The function is by default opinionated, and will automatically select the best way to display the double date plot. However, the user can also manually select the type of double date plot to be displayed: repeating each day (default when there is only one day in all of the groups), or displaying consecutive days (default when there are multiple days in the groups).

Usage

gg_doubleplot(
  dataset,
  Datetime.colname = Datetime,
  type = c("auto", "repeat", "next"),
  geom = "ribbon",
  alpha = 0.5,
  col = "grey40",
  fill = "#EFC000FF",
  linewidth = 0.4,
  x.axis.breaks.next = Datetime_breaks,
  x.axis.format.next = "%a %D",
  x.axis.breaks.repeat = ~Datetime_breaks(.x, by = "6 hours", shift =
    lubridate::duration(0, "hours")),
  x.axis.format.repeat = "%H:%M",
  ...
)

Arguments

dataset	A light logger dataset. Expects a dataframe. If not imported by LightLogR, take care to choose a sensible variable for the Datetime.colname.
Datetime.colname	column name that contains the datetime. Defaults to "Datetime" which is automatically correct for data imported with LightLogR. Expects a symbol. Needs to be part of the dataset. Must be of type POSIXct.
type	One of "auto", "repeat", or "next". The default is "auto", which will automatically select the best way to display the double date plot based on the amount of days in the dataset (⁠all = 1 >> "repeat", else "next⁠). "repeat" will repeat each day in the plot, and "next" will display consecutive days.
geom	The type of geom to be used in the plot. The default is "ribbon".
alpha, linewidth	The alpha and linewidth setting of the geom. The default is 0.5 and 0.4, respectively.
col, fill	The color and fill of the geom. The default is "#EFC000FF". If the parameters aes_col or aes_fill are used through ..., these will override the respective col and fill parameters.
x.axis.breaks.next, x.axis.breaks.repeat	Datetime breaks when consecutive days are displayed (type = "next") or days are repeated (type = "repeat"). Must be a function. The default for next is a label at 12:00 am of each day, and for repeat is a label every 6 hours.
x.axis.format.next, x.axis.format.repeat	Datetime label format when consecutive days are displayed (type = "next") or days are repeated (type = "repeat"). The default for next is "%a %D", showing the date, and for repeat ist "%H:%M", showing hours and minutes. See base::strptime() for more options.
...	Arguments passed to gg_days(). When the arguments aes_col and aes_fill are used, they will invalidate the col and fill parameters.

Details

gg_doubleplot() is a wrapper function for gg_days(), combined with an internal function to duplicate and reorganize dates in a dataset for a double plot view. This means that the same day is displayed multiple times within the plot in order to reveal pattern across days.

Value

a ggplot object

Examples

#take only the Participant data from sample data, and three days
library(dplyr)
library(lubridate)
library(ggplot2)
sample.data <- 
sample.data.environment %>% 
dplyr::filter(Id == "Participant") %>% 
filter_Date(length = ddays(3))

#create a double plot with the default settings
sample.data %>% gg_doubleplot()

#repeat the same day in the plot
sample.data %>% gg_doubleplot(type = "repeat")

#more examples that are not executed for computation time:

#use the function with more than one Id
sample.data.environment %>% 
filter_Date(length = ddays(3)) %>% 
gg_doubleplot(aes_fill = Id, aes_col = Id) +
facet_wrap(~ Date.data, ncol = 1, scales = "free_x", strip.position = "left")

#if data is already grouped by days, type = "repeat" will be automatic
sample.data.environment %>% 
dplyr::group_by(Date = date(Datetime), .add = TRUE) %>% 
filter_Date(length = ddays(3)) %>% 
gg_doubleplot(aes_fill = Id, aes_col = Id) + 
guides(fill = "none", col = "none") + #remove the legend
facet_wrap(~ Date.data, ncol = 1, scales = "free_x", strip.position = "left")

#combining `aggregate_Date()` with `gg_doubleplot()` easily creates a good
#overview of the data
sample.data.environment %>%
aggregate_Date() %>%
gg_doubleplot()

LightLogR documentation built on April 3, 2025, 10:10 p.m.