plot_asr {cauphy}  R Documentation 
Plot Ancestral States Reconstructions
Description
Plot the ancestral states reconstructions from a fitted Cauchy model.
Usage
plot_asr(
x,
anc = NULL,
inc = NULL,
common_colorscale = FALSE,
x.legend = "topleft",
y.legend = NULL,
adj = c(0.5, 0.5),
piecol = NULL,
width.node = NULL,
height.node = NULL,
width.edge = NULL,
height.edge = NULL,
style = "bars",
offset = 1,
scaling = 1,
x.lim = NULL,
x.intersp = NULL,
...
)
Arguments
x 

anc 
(optional) an object of class 
inc 
(optional) an object of class 
common_colorscale 
If both plotted, should the ancestral states and the increment be represented by the same color scale ? Default to 
x.legend , y.legend 
the x and y coordinates to be used to position the legend. They can be specified by keyword or in any way which is accepted by 
adj 
one or two numeric values specifying the horizontal and vertical, respectively, justification of the text or symbols. By default, the text is centered horizontally and vertically. If a single value is given, this alters only the horizontal position of the text. 
piecol 
a list of colours (given as a character vector) to be
used by 
width.node , height.node , width.edge , height.edge 
parameters controlling the aspect of thermometers for the nodes and the edges; by default, their width and height are determined automatically. 
style 
a character string specifying the type of graphics; can be abbreviated (see details). 
offset 
offset of the tip labels (can be negative). 
scaling 
the scaling factor to apply to the data. 
x.lim 
a numeric vector of length one or two giving the limit(s)
of the xaxis. If 
x.intersp 
character interspacing factor for horizontal (x) spacing between symbol and legend text (see 
... 
other parameters to be passed on to 
Details
The main plot is done with plot.phylo
,
the node annotation use nodelabels
, and the
tip data plot use phydataplot
.
Please refer to these functions for the details of the parameters.
The width of each color in the thermo plots approximately represents the
weight of each node of the distribution, that is estimated by numerically
integrating the density function around each mode.
Function findpeaks
is first used to find the modes and
estimate their starting and ending points.
Then function trapz
estimates the integral of the density
around the mode.
For an exact representation of a node posterior density, please plot it separately,
using function plot.ancestralCauchy
.
Value
None.
See Also
cauphylm
, fitCauchy
, ancestral
, increment
,
plot.phylo
, phydataplot
, nodelabels
Examples
set.seed(1289)
# Simulate tree and data
phy < ape::rphylo(10, 0.1, 0)
dat < rTraitCauchy(n = 1, phy = phy, model = "cauchy",
parameters = list(root.value = 10, disp = 0.1))
# Fit the data
fit < fitCauchy(phy, dat, model = "cauchy", method = "reml")
# Reconstruct the ancestral states and increments
inc < increment(fit, n_values = 100)
anc < ancestral(fit, n_values = 100)
plot_asr(fit, inc = inc, anc = anc, offset = 3,
width.node = 0.8, height.node = 0.5,
width.edge = 1.5, height.edge = 0.2,
x.legend = "topright")