This is the heavily requested geometry for interpolating between ternary values, results being rendered using contours on a ternary mesh.
geom_interpolate_tern(
mapping = NULL,
data = NULL,
stat = "InterpolateTern",
position = "identity",
...,
method = "auto",
formula = value ~ poly(x, y, degree = 1),
lineend = "butt",
linejoin = "round",
linemitre = 1,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)stat_interpolate_tern(
mapping = NULL,
data = NULL,
geom = "interpolate_tern",
position = "identity",
...,
method = "auto",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
n = 80,
formula = value ~ poly(x, y, degree = 1),
base = "ilr"
)
Set of aesthetic mappings created by aes()
. If specified and
inherit.aes = TRUE
(the default), it is combined with the default mapping
at the top level of the plot. You must supply mapping
if there is no plot
mapping.
The data to be displayed in this layer. There are three options:
If NULL
, the default, the data is inherited from the plot
data as specified in the call to ggplot()
.
A data.frame
, or other object, will override the plot
data. All objects will be fortified to produce a data frame. See
fortify()
for which variables will be created.
A function
will be called with a single argument,
the plot data. The return value must be a data.frame
, and
will be used as the layer data. A function
can be created
from a formula
(e.g. ~ head(.x, 10)
).
Position adjustment, either as a string naming the adjustment
(e.g. "jitter"
to use position_jitter
), or the result of a call to a
position adjustment function. Use the latter if you need to change the
settings of the adjustment.
Other arguments passed on to layer()
. These are
often aesthetics, used to set an aesthetic to a fixed value, like
colour = "red"
or size = 3
. They may also be parameters
to the paired geom/stat.
Smoothing method (function) to use, accepts either
NULL
or a character vector, e.g. "lm"
, "glm"
, "gam"
, "loess"
or a function, e.g. MASS::rlm
or mgcv::gam
, stats::lm
, or stats::loess
.
"auto"
is also accepted for backwards compatibility. It is equivalent to
NULL
.
For method = NULL
the smoothing method is chosen based on the
size of the largest group (across all panels). stats::loess()
is
used for less than 1,000 observations; otherwise mgcv::gam()
is
used with formula = y ~ s(x, bs = "cs")
with method = "REML"
. Somewhat anecdotally,
loess
gives a better appearance, but is \(O(N^{2})\) in memory,
so does not work for larger datasets.
If you have fewer than 1,000 observations but want to use the same gam()
model that method = NULL
would use, then set
method = "gam", formula = y ~ s(x, bs = "cs")
.
Formula to use in smoothing function, eg. y ~ x
,
y ~ poly(x, 2)
, y ~ log(x)
. NULL
by default, in which case
method = NULL
implies formula = y ~ x
when there are fewer than 1,000
observations and formula = y ~ s(x, bs = "cs")
otherwise.
Line end style (round, butt, square).
Line join style (round, mitre, bevel).
Line mitre limit (number greater than 1).
If FALSE
, the default, missing values are removed with
a warning. If TRUE
, missing values are silently removed.
logical. Should this layer be included in the legends?
NA
, the default, includes if any aesthetics are mapped.
FALSE
never includes, and TRUE
always includes.
It can also be a named logical vector to finely select the aesthetics to
display.
If FALSE
, overrides the default aesthetics,
rather than combining with them. This is most useful for helper functions
that define both data and aesthetics and shouldn't inherit behaviour from
the default plot specification, e.g. borders()
.
Use to override the default connection between
geom_smooth()
and stat_smooth()
.
number of grid points in each direction
the base transformation of the data, options include 'identity' (ie direct on the cartesian space), or 'ilr' which means to use the isometric log ratio transformation.
ggtern:::rd_aesthetics("geom", "InterpolateTern")
Nicholas Hamilton
data(Feldspar)
ggtern(Feldspar,aes(Ab,An,Or,value=T.C)) +
stat_interpolate_tern(geom="polygon",
formula=value~x+y,
method=lm,n=100,
breaks=seq(0,1000,by=100),
aes(fill=..level..),expand=1) +
geom_point()
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