Plots mathematical expressions in one and two variables.

```
plotFun(
object,
...,
plot = trellis.last.object(),
add = NULL,
under = FALSE,
xlim = NULL,
ylim = NULL,
npts = NULL,
ylab = NULL,
xlab = NULL,
zlab = NULL,
filled = TRUE,
levels = NULL,
nlevels = 10,
labels = TRUE,
surface = FALSE,
groups = NULL,
col = trellis.par.get("superpose.line")$col,
col.regions = topo.colors,
type = "l",
lwd = trellis.par.get("superpose.line")$lwd,
lty = trellis.par.get("superpose.line")$lty,
alpha = NULL,
discontinuities = NULL,
discontinuity = 1,
interactive = rstudio_is_available()
)
```

- object
a mathematical expression or a function "of one variable" which will converted to something intuitively equivalent to

`object(x) ~ x`

. (See examples)- ...
additional parameters, typically processed by

`lattice`

functions such as`lattice::xyplot()`

,`lattice::levelplot()`

or their panel functions. Frequently used parameters include`main`

main title for plot

`sub`

subtitle for plot

`lwd`

line width

`lty`

line type

`col`

a color or a (small) integer indicating which color in the current color scheme is desired.

Additionally, these arguments can be used to specify parameters for the function being plotted and to specify the plotting window with natural names. See the examples for such usage.

- plot
a trellis object; by default, the most recently created trellis plot. When

`add`

is`TRUE`

, the new function will be plotted into a layer added to this object.- add
if

`TRUE`

, then add a layer to an existing plot rather than creating a new plot. If`NULL`

, this will be determined by the value of`under`

.- under
if

`TRUE`

, then new layer is added beneath existing layers- xlim
limits for x axis (or use variable names, see examples)

- ylim
limits for y axis (or use variable names, see examples)

- npts
number of points for plotting.

- ylab
label for y axis

- xlab
label for x axis

- zlab
label for z axis (when in surface-plot mode)

- filled
fill with color between the contours (

`TRUE`

by default)- levels
levels at which to draw contours

- nlevels
number of contours to draw (if

`levels`

not specified)- labels
if

`FALSE`

, don't label contours- surface
draw a surface plot rather than a contour plot

- groups
grouping argument ala lattice graphics

- col
vector of colors for line graphs and contours

- col.regions
a vector of colors or a function (

`topo.colors`

by default) for generating such- type
type of plot (

`"l"`

by default)- lwd
vector of line widths for line graphs

- lty
vector of line types for line graphs

- alpha
number from 0 (transparent) to 1 (opaque) for the fill colors

- discontinuities
a vector of input values at which a function is discontinuous or

`NULL`

to use a heuristic to auto-detect.- discontinuity
a positive number determining how sensitive the plot is to potential discontinuity. Larger values result in less sensitivity. The default is 1. Use

`discontinuity = Inf`

to disable discontinuity detection. Discontinuity detection uses a crude numerical heuristic and may not give the desired results in all cases.- interactive
a logical indicating whether the surface plot should be interactive.

a `trellis`

object

makes plots of mathematical expressions using the formula syntax. Will
draw both line plots and contour/surface plots (for functions of two variables).
In RStudio, the surface plot comes with sliders to set orientation.
If the colors in filled surface plots are too blocky, increase `npts`

beyond the default of 50, though `npts=300`

is as much as you're likely to ever need.
See examples for overplotting a constraint function on an objective function.

```
plotFun( a*sin(x^2)~x, xlim=range(-5,5), a=2 ) # setting parameter value
plotFun( u^2 ~ u, ulim=c(-4,4) ) # limits in terms of u
# Note roles of ylim and y.lim in this example
plotFun( y^2 ~ y, ylim=c(-2,20), y.lim=c(-4,4) )
# Combining plot elements to show the solution to an inequality
plotFun( x^2 -3 ~ x, xlim=c(-4,4), grid=TRUE )
ladd( panel.abline(h=0,v=0,col='gray50') )
plotFun( (x^2 -3) * (x^2 > 3) ~ x, type='h', alpha=.1, lwd=4, col='lightblue', add=TRUE )
plotFun( sin(x) ~ x,
groups=cut(x, findZeros(sin(x) ~ x, within=10)$x),
col=c('blue','green'), lty=2, lwd=3, xlim=c(-10,10) )
plotFun( sin(x) ~ x,
groups=cut(x, findZeros(sin(x) ~ x, within=10)$x),
col=c(1,2), lty=2, lwd=3, xlim=c(-10,10) )
#> converting numerical color value into a color using lattice settings
## plotFun( sin(2*pi*x/P)*exp(-k*t)~x+t, k=2, P=.3)
f <- rfun( ~ u & v )
plotFun( f(u=u,v=v) ~ u & v, u.lim=range(-3,3), v.lim=range(-3,3) )
plotFun( u^2 + v < 3 ~ u & v, add=TRUE, npts=200 )
if (require(mosaicData)) {
# display a linear model using a formula interface
model <- lm(wage ~ poly(exper,degree=2), data=CPS85)
fit <- makeFun(model)
xyplot(wage ~ exper, data=CPS85)
plotFun(fit(exper) ~ exper, add=TRUE, lwd=3, col="red")
# Can also just give fit since it is a "function of one variable"
plotFun(fit, add=TRUE, lwd=2, col='white')
}
# Attempts to find sensible axis limits by default
plotFun( sin(k*x)~x, k=0.01 )
# Plotting a linear model with multiple predictors.
mod <- lm(length ~ width * sex, data=KidsFeet)
fitted.length <- makeFun(mod)
xyplot(length ~ width, groups=sex, data=KidsFeet, auto.key=TRUE)
plotFun(fitted.length(width, sex="B") ~ width, add=TRUE, col=1)
#> converting numerical color value into a color using lattice settings
plotFun(fitted.length(width, sex="G") ~ width, add=TRUE, col=2)
#> converting numerical color value into a color using lattice settings
#> converting numerical color value into a color using lattice settings
```