README.md
In coolbutuseless/ggdebug: Debug Ggplot Stats
ggdebug
ggdebug is a package for debugging ggplot2 stats.
I created this package to help in developing new ggplot2 stats, and
trying to decipher and understand how existing ones work.
What’s in the box:
get_geom() - New in version 0.1.1 (with help from Brodie
Gaslam’s)
- Get the name of the Geom from within a Stat
create_stat_with_caching()
- Capture arguments and the return values internal to Stat
methods
inject_data_into_stat_function()
- Inject arguments and return values directly into Stat
methods
This package wouldn’t be possible without:
- ggplot2 by Hadley
Wickham
- Brodie Gaslam’s great guide to
ggplot2
internals
- boBRudis’s post on demystifying
ggplot2
Installation
You can install the development version from
GitHub with:
# install.packages("remotes")
remotes::install_github("coolbutuseless/ggdebug")
Determine the Geom from within a Stat
For good reasons(?) within the Grammar of Graphics, the Stat and the
Geom should work independently.
For other reasons, I sometimes want to do weird things within a Stat
depending on which Geom it is being used with.
Finding the name of the Geom is not obvious, so I’ve included
get_geom() which interrogates the frame stack to find the Layer which
contains the Stat, and finds the name of the Geom contained within that
Layer.
If anyone knows of a better way of doing this, please get in
touch!
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create a Stat to test with
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stat_oath_breaker <- function(mapping = NULL, data = NULL,
geom = "point",
position = "identity",
...,
show.legend = NA,
inherit.aes = TRUE) {
layer(
data = data,
mapping = mapping,
stat = StatOathBreaker,
geom = geom,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
na.rm = FALSE,
...
)
)
}
StatOathBreaker <- ggproto(
"StatOathBreaker", Stat,
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Call `get_geom()` from within the Stat
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
setup_params = function(data, params) {
message("StatOathBreaker being used with: ", ggdebug::get_geom())
params
},
compute_layer = function(data, scales, params) {
data
}
)
ggplot(mtcars) +
geom_line(aes(mpg, wt), stat = 'oath_breaker')
#> StatOathBreaker being used with: GeomLine
Debug geom_histogram + StatBin
The following example shows how ggdebug can be used to capture the
data during creation of geom_histogram().
geom_histogram() uses a default Stat of StatBin. Instead we create a
debugging version of this Stat and use it explicitly.
The captured data is available by calling
ggdebug::get_cache_data().
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create a new stat which is identical to StatBin, but captures the
# data for all the methods.
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
StatBinDebug <- ggdebug::create_stat_with_caching(
StatBin
)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create the plot using the new Stat
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
ggplot(mtcars) +
geom_histogram(aes(mpg, fill = as.factor(cyl)), stat = StatBinDebug, bins = 10) +
theme_bw() +
facet_wrap(~cyl)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Get the data we captured from this process
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
cdata <- ggdebug::get_data_cache()
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Interrogate the captured data.
# Each method has its only entry in the data cache, and
# within each entry there are both the `args` and the `return` value
# for this method
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
names(cdata)
#> [1] "parameters" "compute_group" "compute_panel" "compute_layer"
#> [5] "finish_layer"
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# arguments and the return value for the 'parameters()' method
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
cdata$parameters
#> $args
#> $args$extra
#> [1] FALSE
#>
#>
#> $return
#> [1] "binwidth" "bins" "center" "boundary" "closed" "pad"
#> [7] "breaks" "origin" "right" "drop" "width"
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# The 'data' argument passed in to the 'compute_layer()' method
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
head(cdata$compute_layer$args$data)
#> x fill PANEL group
#> 1 21.0 6 2 2
#> 2 21.0 6 2 2
#> 3 22.8 4 1 1
#> 4 21.4 6 2 2
#> 5 18.7 8 3 3
#> 6 18.1 6 2 2
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# The return value from the 'finish_layer()' method
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
head(cdata$finish_layer$return)
#> fill y count x xmin xmax density ncount
#> 1 #F8766D 0 0 10.44444 9.138889 11.75000 0.0000000 0.0000000
#> 2 #F8766D 0 0 13.05556 11.750000 14.36111 0.0000000 0.0000000
#> 3 #F8766D 0 0 15.66667 14.361111 16.97222 0.0000000 0.0000000
#> 4 #F8766D 0 0 18.27778 16.972222 19.58333 0.0000000 0.0000000
#> 5 #F8766D 2 2 20.88889 19.583333 22.19444 0.0696325 0.6666667
#> 6 #F8766D 3 3 23.50000 22.194444 24.80556 0.1044487 1.0000000
#> ndensity PANEL group ymin ymax colour size linetype alpha
#> 1 0.0000000 1 1 0 0 NA 0.5 1 NA
#> 2 0.0000000 1 1 0 0 NA 0.5 1 NA
#> 3 0.0000000 1 1 0 0 NA 0.5 1 NA
#> 4 0.0000000 1 1 0 0 NA 0.5 1 NA
#> 5 0.6666667 1 1 0 2 NA 0.5 1 NA
#> 6 1.0000000 1 1 0 3 NA 0.5 1 NA
Inject data into geom_histogram + StatBin
ggdebug also allows you to inject arguments and override return values
within methods inside a Stat.
In this example, we take the above histogram, and at the last stage
(finish_layer) we inject a modified return value to override the real
one.
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# From the above debugging example, grab the return value from `finish_layer`
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
finish_layer_return_value <- cdata$finish_layer$return
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Change the visual properties for the bar with the greatest height
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
finish_layer_return_value <- finish_layer_return_value %>%
group_by(group) %>%
mutate(
fill = ifelse(count == max(count), '#000000', fill ),
colour = ifelse(count == max(count), '#ff0000', colour),
size = ifelse(count == max(count), 1 , size )
) %>%
ungroup()
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create a modified version of StatBin which only returns our version of the
# dataset from `finishlayer`
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
StatBinInject <- inject_data_into_stat_function(
StatBin, 'finish_layer',
return_value = finish_layer_return_value
)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Recreate the plot using the injected data as the return from `finish_layer`
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
ggplot(mtcars) +
geom_histogram(aes(mpg, fill = as.factor(cyl)), stat = StatBinInject, bins = 5) +
theme_bw() +
facet_wrap(~cyl) +
labs(title = "Use injected data to highlight the maximum bar within each group")
Inject tetris pieces into geom_histogram + StatBin
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create 3 tetris pieces
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
tetris <- tribble(
~fill , ~xmin, ~xmax, ~ymin, ~ymax,
'#ff0000', 10, 19, 6, 7,
'#ff0000', 13, 16, 6, 8,
'#00ff00', 25, 28, 6, 8,
'#00ff00', 28, 31, 7, 9,
'#0000ff', 25, 34, 6, 7,
'#0000ff', 28, 31, 6, 8
)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Assign each piece to a different panel
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
tetris <- tetris %>% mutate(
PANEL = factor(c(1, 1, 2, 2, 3, 3), levels = 1:3),
group = 1,
linetype = 1,
x = xmax,
y = ymax
)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Add the tetris data to the original data returned by `finish_layer`
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
finish_layer_return_value <- bind_rows(
tetris,
cdata$finish_layer$return
)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create a StatBin that only returns this modified data from `finish_layer`
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
StatBinInject <- inject_data_into_stat_function(
StatBin, 'finish_layer',
return_value = finish_layer_return_value
)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create the plot to generate tetris pieces injected into the data
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
ggplot(mtcars) +
geom_histogram(aes(mpg, fill = as.factor(cyl)), stat = StatBinInject, bins = 5) +
theme_bw() +
facet_wrap(~cyl) +
labs(title = "Use injected data to create tetris pieces")
coolbutuseless/ggdebug documentation built on May 13, 2019, 11:25 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
ggdebug
ggdebug is a package for debugging ggplot2 stats.
I created this package to help in developing new ggplot2 stats, and
trying to decipher and understand how existing ones work.
What’s in the box:
get_geom()- New in version 0.1.1 (with help from Brodie Gaslam’s)- Get the name of the Geom from within a Stat
create_stat_with_caching()- Capture arguments and the return values internal to Stat methods
inject_data_into_stat_function()- Inject arguments and return values directly into Stat methods
This package wouldn’t be possible without:
- ggplot2 by Hadley Wickham
- Brodie Gaslam’s great guide to ggplot2 internals
- boBRudis’s post on demystifying ggplot2
Installation
You can install the development version from GitHub with:
# install.packages("remotes")
remotes::install_github("coolbutuseless/ggdebug")
Determine the Geom from within a Stat
For good reasons(?) within the Grammar of Graphics, the Stat and the Geom should work independently.
For other reasons, I sometimes want to do weird things within a Stat depending on which Geom it is being used with.
Finding the name of the Geom is not obvious, so I’ve included
get_geom() which interrogates the frame stack to find the Layer which
contains the Stat, and finds the name of the Geom contained within that
Layer.
If anyone knows of a better way of doing this, please get in touch!
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create a Stat to test with
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stat_oath_breaker <- function(mapping = NULL, data = NULL,
geom = "point",
position = "identity",
...,
show.legend = NA,
inherit.aes = TRUE) {
layer(
data = data,
mapping = mapping,
stat = StatOathBreaker,
geom = geom,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
na.rm = FALSE,
...
)
)
}
StatOathBreaker <- ggproto(
"StatOathBreaker", Stat,
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Call `get_geom()` from within the Stat
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
setup_params = function(data, params) {
message("StatOathBreaker being used with: ", ggdebug::get_geom())
params
},
compute_layer = function(data, scales, params) {
data
}
)
ggplot(mtcars) +
geom_line(aes(mpg, wt), stat = 'oath_breaker')
#> StatOathBreaker being used with: GeomLine
Debug geom_histogram + StatBin
The following example shows how ggdebug can be used to capture the
data during creation of geom_histogram().
geom_histogram() uses a default Stat of StatBin. Instead we create a
debugging version of this Stat and use it explicitly.
The captured data is available by calling
ggdebug::get_cache_data().
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create a new stat which is identical to StatBin, but captures the
# data for all the methods.
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
StatBinDebug <- ggdebug::create_stat_with_caching(
StatBin
)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create the plot using the new Stat
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
ggplot(mtcars) +
geom_histogram(aes(mpg, fill = as.factor(cyl)), stat = StatBinDebug, bins = 10) +
theme_bw() +
facet_wrap(~cyl)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Get the data we captured from this process
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
cdata <- ggdebug::get_data_cache()
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Interrogate the captured data.
# Each method has its only entry in the data cache, and
# within each entry there are both the `args` and the `return` value
# for this method
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
names(cdata)
#> [1] "parameters" "compute_group" "compute_panel" "compute_layer"
#> [5] "finish_layer"
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# arguments and the return value for the 'parameters()' method
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
cdata$parameters
#> $args
#> $args$extra
#> [1] FALSE
#>
#>
#> $return
#> [1] "binwidth" "bins" "center" "boundary" "closed" "pad"
#> [7] "breaks" "origin" "right" "drop" "width"
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# The 'data' argument passed in to the 'compute_layer()' method
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
head(cdata$compute_layer$args$data)
#> x fill PANEL group
#> 1 21.0 6 2 2
#> 2 21.0 6 2 2
#> 3 22.8 4 1 1
#> 4 21.4 6 2 2
#> 5 18.7 8 3 3
#> 6 18.1 6 2 2
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# The return value from the 'finish_layer()' method
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
head(cdata$finish_layer$return)
#> fill y count x xmin xmax density ncount
#> 1 #F8766D 0 0 10.44444 9.138889 11.75000 0.0000000 0.0000000
#> 2 #F8766D 0 0 13.05556 11.750000 14.36111 0.0000000 0.0000000
#> 3 #F8766D 0 0 15.66667 14.361111 16.97222 0.0000000 0.0000000
#> 4 #F8766D 0 0 18.27778 16.972222 19.58333 0.0000000 0.0000000
#> 5 #F8766D 2 2 20.88889 19.583333 22.19444 0.0696325 0.6666667
#> 6 #F8766D 3 3 23.50000 22.194444 24.80556 0.1044487 1.0000000
#> ndensity PANEL group ymin ymax colour size linetype alpha
#> 1 0.0000000 1 1 0 0 NA 0.5 1 NA
#> 2 0.0000000 1 1 0 0 NA 0.5 1 NA
#> 3 0.0000000 1 1 0 0 NA 0.5 1 NA
#> 4 0.0000000 1 1 0 0 NA 0.5 1 NA
#> 5 0.6666667 1 1 0 2 NA 0.5 1 NA
#> 6 1.0000000 1 1 0 3 NA 0.5 1 NA
Inject data into geom_histogram + StatBin
ggdebug also allows you to inject arguments and override return values
within methods inside a Stat.
In this example, we take the above histogram, and at the last stage
(finish_layer) we inject a modified return value to override the real
one.
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# From the above debugging example, grab the return value from `finish_layer`
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
finish_layer_return_value <- cdata$finish_layer$return
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Change the visual properties for the bar with the greatest height
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
finish_layer_return_value <- finish_layer_return_value %>%
group_by(group) %>%
mutate(
fill = ifelse(count == max(count), '#000000', fill ),
colour = ifelse(count == max(count), '#ff0000', colour),
size = ifelse(count == max(count), 1 , size )
) %>%
ungroup()
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create a modified version of StatBin which only returns our version of the
# dataset from `finishlayer`
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
StatBinInject <- inject_data_into_stat_function(
StatBin, 'finish_layer',
return_value = finish_layer_return_value
)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Recreate the plot using the injected data as the return from `finish_layer`
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
ggplot(mtcars) +
geom_histogram(aes(mpg, fill = as.factor(cyl)), stat = StatBinInject, bins = 5) +
theme_bw() +
facet_wrap(~cyl) +
labs(title = "Use injected data to highlight the maximum bar within each group")
Inject tetris pieces into geom_histogram + StatBin
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create 3 tetris pieces
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
tetris <- tribble(
~fill , ~xmin, ~xmax, ~ymin, ~ymax,
'#ff0000', 10, 19, 6, 7,
'#ff0000', 13, 16, 6, 8,
'#00ff00', 25, 28, 6, 8,
'#00ff00', 28, 31, 7, 9,
'#0000ff', 25, 34, 6, 7,
'#0000ff', 28, 31, 6, 8
)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Assign each piece to a different panel
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
tetris <- tetris %>% mutate(
PANEL = factor(c(1, 1, 2, 2, 3, 3), levels = 1:3),
group = 1,
linetype = 1,
x = xmax,
y = ymax
)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Add the tetris data to the original data returned by `finish_layer`
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
finish_layer_return_value <- bind_rows(
tetris,
cdata$finish_layer$return
)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create a StatBin that only returns this modified data from `finish_layer`
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
StatBinInject <- inject_data_into_stat_function(
StatBin, 'finish_layer',
return_value = finish_layer_return_value
)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Create the plot to generate tetris pieces injected into the data
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
ggplot(mtcars) +
geom_histogram(aes(mpg, fill = as.factor(cyl)), stat = StatBinInject, bins = 5) +
theme_bw() +
facet_wrap(~cyl) +
labs(title = "Use injected data to create tetris pieces")
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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