Animate a 1d tour path with a density plot or histogram.
display_dist(
method = "density",
center = TRUE,
half_range = NULL,
col = "black",
rug = FALSE,
palette = "Zissou 1",
density_max = 3,
bw = 0.2,
scale_density = FALSE,
...
)
animate_dist(data, tour_path = grand_tour(1), ...)
display method, histogram or density plot
should 1d projection be centered to have mean zero (default: TRUE). This pins the centre of distribution to the same place, and makes it easier to focus on the shape of the distribution.
half range to use when calculating limits of projected. If not set, defaults to maximum distance from origin to each row of data.
color to use for points, can be a vector or hexcolors or a factor. Defaults to "black".
draw rug plot showing position of actual data points?
name of color palette for point colour, used by hcl.colors
, default "Zissou 1"
allow control of the y range for density plot
binwidth for histogram and density, between 0-1, default 0.2
Height of density is scaled at each projection, default FALSE
other arguments passed on to animate
matrix, or data frame containing numeric columns
tour path generator, defaults to 2d grand tour
animate
for options that apply to all animations
animate_dist(flea[, 1:6])
#> Converting input data to the required matrix format.
#> Using half_range 66
# Change inputs, to color by group, fix y axis, change bin width
# and scale bar height or density at each projection
animate_dist(flea[, 1:6], col=flea$species, density_max=5)
#> Converting input data to the required matrix format.
#> Using half_range 66
animate_dist(flea[, 1:6], col=flea$species, density_max=5, bw=0.1)
#> Converting input data to the required matrix format.
#> Using half_range 66
animate_dist(flea[, 1:6], col=flea$species, scale_density=TRUE)
#> Converting input data to the required matrix format.
#> Using half_range 66
# When the distribution is not centred, it tends to wander around in a
# distracting manner
animate_dist(flea[, 1:6], center = FALSE)
#> Converting input data to the required matrix format.
#> Using half_range 323
# Alternatively, you can display the distribution with a histogram
animate_dist(flea[, 1:6], method = "hist")
#> Converting input data to the required matrix format.
#> Using half_range 66