Summarise built plot objects — summarise

These functions provide summarised information about built ggplot objects.

summarise_layout(p)

summarise_coord(p)

summarise_layers(p)

Arguments

p: A ggplot_built object.

Details

There are three types of summary that can be obtained: A summary of the plot layout, a summary of the plot coord, and a summary of plot layers.

Layout summary

The function summarise_layout() returns a table that provides information about the plot panel(s) in the built plot. The table has the following columns:

panel: A factor indicating the individual plot panels.
row: Row number in the grid of panels.
col: Column number in the grid of panels.
vars: A list of lists. For each panel, the respective list provides the variables and their values that specify the panel.
xmin, xmax: The minimum and maximum values of the variable mapped to the x aesthetic, in transformed coordinates.
ymin, ymax: The minimum and maximum values of the variable mapped to the y aesthetic, in transformed coordinates.
xscale: The scale object applied to the x aesthetic.
yscale: The scale object applied to the y aesthetic.

Importantly, the values for xmin, xmax, ymin, ymax, xscale, and yscale are determined by the variables that are mapped to x and y in the aes() call. So even if a coord changes how x and y are shown in the final plot (as is the case for coord_flip() or coord_polar()), these changes have no effect on the results returned by summarise_plot().

Coord summary

The function summarise_coord() returns information about the log base for coordinates that are log-transformed in coord_trans(), and it also indicates whether the coord has flipped the x and y axes.

Layer summary

The function summarise_layers() returns a table with a single column, mapping, which contains information about aesthetic mapping for each layer.

Examples

p <-
  ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  facet_wrap(~class)
b <- ggplot_build(p)

summarise_layout(b)
#> # A tibble: 7 × 10
#>   panel   row   col vars          xmin  xmax  ymin  ymax xscale     yscale    
#>   <fct> <int> <int> <list>       <dbl> <dbl> <dbl> <dbl> <list>     <list>    
#> 1 1         1     1 <named list>  1.33  7.27  10.4  45.6 <SclCntnP> <SclCntnP>
#> 2 2         1     2 <named list>  1.33  7.27  10.4  45.6 <SclCntnP> <SclCntnP>
#> 3 3         1     3 <named list>  1.33  7.27  10.4  45.6 <SclCntnP> <SclCntnP>
#> 4 4         2     1 <named list>  1.33  7.27  10.4  45.6 <SclCntnP> <SclCntnP>
#> 5 5         2     2 <named list>  1.33  7.27  10.4  45.6 <SclCntnP> <SclCntnP>
#> 6 6         2     3 <named list>  1.33  7.27  10.4  45.6 <SclCntnP> <SclCntnP>
#> 7 7         3     1 <named list>  1.33  7.27  10.4  45.6 <SclCntnP> <SclCntnP>
summarise_coord(b)
#> $xlog
#> [1] NA
#> 
#> $ylog
#> [1] NA
#> 
#> $flip
#> [1] FALSE
#> 
summarise_layers(b)
#> # A tibble: 1 × 1
#>   mapping         
#>   <list>          
#> 1 <named list [2]>