ggetho (version 0.3.5)

stat_bar_tile_etho: Display a variable of interest either as a colour intensity value or as a bar height

Description

These functions show the temporal trend (time on the x axis) of a variable of interest (z axis) as either colour intensity (stat_tile_etho) or using the hight of the tiles (stat_bar_tile_etho). In both cases, the y axis is a discrete variable such as a treatment or the id of individuals.

Usage

stat_bar_tile_etho(mapping = NULL, data = NULL, geom = "bar_tile",
  position = "identity", ..., method = mean, method.args = list(),
  na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)
stat_tile_etho(mapping = NULL, data = NULL, geom = "raster",
  position = "identity", ..., method = mean, method.args = list(),
  na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)

Arguments

mapping

Set of aesthetic mappings created by aes() or aes_(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

geom

The geometric object to use display the data

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

method

function used to compute the aggregate, when/if grouping several individuals on the same row. The default is fucntion is mean. median, min, max are examples of alternatives.

method.args

List of additional arguments passed on to the modelling function defined by method.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().

Value

A ggplot layer.

• The relevant rethomic tutorial section

See Also

• ggetho to generate a plot object

• stat_pop_etho to show population trend by aggregating individuals over time

• stat_ld_annotations to show light and dark phases on the plot

Other layers: geom_peak, stat_ld_annotations, stat_pop_etho

Examples

# NOT RUN {
# We start by making a to dataset with 20 animals
metadata <- data.frame(id = sprintf("toy_experiment | %02d", 1:20),
                   age = c(1, 5, 10, 20),
                   condition = c("A", "B"))
print(metadata)
dt <- toy_activity_data(metadata, 3)
# We build a plot object
pl <-  ggetho(dt, aes(z = asleep))
# A standard plot one row per animal:
pl + stat_tile_etho()
# We can also group animals per condition and calculate the average sleep
pl <-  ggetho(dt, aes(z = asleep, y = condition))
pl + stat_tile_etho()

# We can sort by adding condition AND id on the y axis:
pl <-  ggetho(dt, aes(z = asleep, y = interaction(id, condition)))
pl + stat_tile_etho()
# Same if we want to sort by age
pl <-  ggetho(dt, aes(z = asleep, y = interaction(id, age)))
pl + stat_tile_etho()

# Instead, of the average, maybe we want to show the highest (max)
# posible value of sleep for any time point
pl + stat_tile_etho(method = max)
# We can also use stat_bar_tile as an alternative
pl + stat_bar_tile_etho()
# }