another experiment
Evangeline Reynolds
2025-01-20
Intro Thoughts
Status Quo
library(tidyverse)Experiment
library(ggplot2)
data_filter <- function(.keep, .by) {
structure(list(keep_specification = rlang::enquo(.keep),
by_specification = rlang::enquo(.by)),
class = "filterobs")
}
ggplot_add.filterobs <- function(object, plot, object_name) {
new_data <- dplyr::filter(plot$data,
!!object$keep_specification,
.by = !!object$by_specification)
plot$data <- new_data
plot
}
mtcars## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
## Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
## Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2plot(mtcars)
ggplot(mtcars) +
aes(factor(cyl), fill = factor(cyl)) +
geom_bar() -> p1;p1
ggplot(mtcars) +
aes(id = cyl, fill = factor(cyl)) +
ggcirclepack::geom_circlepack() +
coord_equal() -> p2
ggplot(mtcars) +
aes(wt, mpg, color = factor(cyl)) +
geom_point(size = 4) -> p3
library(patchwork)
p1 + p2 + p3
(p1 + p2 + p3) * data_filter(cyl != 4)
(p1 + p2 + p3) * aes(alpha = cyl != 4)
However, w/ / some repetition is required.
(p1 + p2) * aes(alpha = cyl != 4) / p3 * aes(alpha = cyl != 4)
(p1 + p2) * data_filter(cyl != 4) / p3 * data_filter(cyl != 4)
p1 * data_filter(cyl != 4) / ((p2 + p3) * data_filter(cyl != 4))
This can be shorted by naming specification.
cyl4spotlight <- aes(alpha = cyl == 4)
(p1 + p2) * cyl4spotlight / p3 * cyl4spotlight
rm4 <- data_filter(cyl != 4)
(p1 + p2) * rm4 / p3 * rm4
There is an & operator, that is demonstrated with
‘theme’ in the documentation.
& will add the element to all subplots in the patchwork, and * will add the element to all the subplots in the current nesting level. As with | and /, be aware that operator precedence must be kept in mind.
Which sounds promising, but isn’t working with data_filter() as written but does work with the opaqueness spotlighting. Exciting!
patchwork <- p3 / (p1 | p2)
patchwork & theme_minimal()
patchwork & aes(alpha = cyl == 4) & guides(alpha = "none")
patchwork & data_filter(cyl != 4)## Error in UseMethod("filter"): no applicable method for 'filter' applied to an object of class "waiver"file.info("programmatic-crosstalk.Rmd")$ctime -
Sys.time()## Time difference of -1.129331 days