ternary_density | R Documentation |
Computes and draws density contour lines.
ternary_density(x, y, z, ...)
## S4 method for signature 'numeric,numeric,numeric'
ternary_density(
x,
y,
z,
h = NULL,
n = 25,
nlevels = 10,
levels = NULL,
palette = function(i) grDevices::hcl.colors(i, "YlOrRd", rev = TRUE),
...
)
## S4 method for signature 'ANY,missing,missing'
ternary_density(
x,
h = NULL,
n = 25,
nlevels = 10,
levels = NULL,
palette = function(i) grDevices::hcl.colors(i, "YlOrRd", rev = TRUE),
...
)
x , y , z |
A |
... |
Further arguments to be passed to |
h |
A length-one |
n |
A length-one |
nlevels |
A length-one |
levels |
A |
palette |
A color palette |
Two-dimensional kernel density estimation with an axis-aligned bivariate normal kernel. Normal kernel is evaluated on a square grid, after an isometric log ratio transformation of the original data.
ternary_density()
is called it for its side-effects.
Invisibly returns a list
with elements levels
(the contour levels) and
colors
(the contour colors) that can be used for a legend.
This must be considered as experimental and subject to major changes in a future release.
N. Frerebeau
Two-dimensional kernel density estimation is adapted from MASS::kde2d()
.
grDevices::contourLines()
Other statistics:
ternary_contour()
,
ternary_ellipse()
,
ternary_hull()
,
ternary_mean()
,
ternary_pca()
## Add density
## Data from Aitchison 1986
ternary_plot(lava, panel.first = ternary_grid())
levels <- ternary_density(lava, n = 500, nlevels = 10)
## Add a legend
legend_image <- grDevices::as.raster(rev(levels$colors))
graphics::rasterImage(legend_image, 0.85, 0.75, 0.9, 1)
graphics::text(x = 0.9, y = c(0.75, 1), labels = range(levels$levels), pos = 4)
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