plot.hisse.states {hisse} | R Documentation |
Plotting function hisse.states objects
Description
A plotting function for visualizing changes in states and rates over a phylogeny
Usage
## S3 method for class 'hisse.states'
plot(x, rate.param = "net.div", type = "fan",
show.tip.label = TRUE, fsize = 1.0, legend = "tips", ...)
Arguments
x |
a |
rate.param |
indicates the type of rates to plot. Options include: “turnover”, “net.div”, “speciation”, “extinction”, “extinction.fraction”. The default is “net.div”. |
type |
a character string specifying the type of phylogeny to be drawn. Options are "fan" (default) or "phylogram". |
show.tip.label |
a logical indicating whether tip names should be included. |
fsize |
sets the font size for the tip labels. |
legend |
indicates the type of legend. Options include: “none”, “traditional”, “tips”, “internal”, “all”. |
... |
Additional parameters to control the plot. See “Details”. |
Details
Provides phylogeny that shows a heat map of the diversification rate parameter you specify (which could be turnover, net.div, speciation, extinction, or extinction.fraction). The discrete state reconstruction appears as lines on top of the heat map. If you give a single hisse.state object, it uses that; if you give it a list of them, it will model-average the results (it assumes the trees are the same). Colors can be specified by sending a vector of colors to rate.colors or state.colors (the defaults are red to blue for rate and white to black for state). You can specify two or more colors: c("red", "gray", "blue") for example. By default the visualization uses the minimum rate on the tree for the minimum color, and the maximum rate for the maximum color, but you may want to use the same color scale across models, even if some of them have a smaller range than others. To do this, pass a vector with the minimum and maximum rate across all models to the visualization for all models and they will use the same scale. There are many options for adding a legend. A traditional legend showing what values a color corresponds to is “traditional”, like what plotSimmap will show in phytools. However, we can also use the legend to show the distribution of values, rather than just a key to color. “tips” shows a density plot of states or rates at tips, “internal” a distribution at internal nodes, and “all” at all nodes in the tree. For the density or histogram plots, you can let the package pick the best visualization or choose yourself whether to use a histogram or density plot, and if the latter, what kernel you want. The legend can be moved around the overall tree plot by using “legend.position”: this is a vector that specifies the “fig” argument to “par”: c(x1, x2, y1, y2), where the values are the starting and ending positions as a fraction of the overall plot. By default, the legend starts at the lower left corner and continues up 20 the rest of the plot (c(0, 0.2, 0, 0.2)): by changing values, you can make the legend larger or smaller and change its position. The heatmap code is modified slightly from Liam Revell's phytools package.
Additional parameters to control the plot:
“do.observed.only” is a logical indicating whether just the states should be plotted; for now, only TRUE works.
“rate.colors” sets user specified colors to be used for coloring rates.
“state.colors” sets user specified colors to be used for coloring states.
“edge.width” sets the width of the branches of the phylogeny.
“width.factor” is the factor multiplying the edge.width to get the
width of the branch for the states tree. Needs to be a numeric value
between 0 and 1.
“rate.range” is an optional two element vector. If present, specifies the range of rate values to use for plotting.
“lims.percentage.correction” deals with cases where the limits are slightly smaller than the values due to imprecision issues.
“legend.position” are the coordinates for placing the legend.
“legend.cex” is the text size inside the legend.
“legend.kernel.rates” used for legend=tips, internal, or all, lets you specify the way the density plot or histogram is made for rates. “auto”
chooses what we think is the best option given your data, “hist” makes a histogram, “rectangular”, “gaussian”, and others make a density plot. See ?density
for all non-“hist” options.
“legend.kernel.states” is as above, for states.
“legend.bg” sets the color for the legend background.
“mar” sets the margins for the plot. See more information in 'help(par)'.
“outline” sets whether to plot an outline on the branches of the tree. Choose the color of the outline using the parameter outline.color.
“outline.color” sets the color for the outline. Defaults to "black".
“swap.underscore” defines whether to substitute all "_" with " " on the labels for the tips.
Author(s)
Brian O'Meara and Daniel Caetano
References
Beaulieu, J.M, and B.C. O'Meara. 2016. Detecting hidden diversification shifts in models of trait-dependent speciation and extinction. Syst. Biol. 65:583-601.