plotFun: Plotting mathematical expressions

Description

Plots mathematical expressions in one and two variables.

Usage

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", alpha = NULL, discontinuities = NULL, discontinuity = 1)

Arguments

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 xyplot, levelplot or their panel functions. Frequently

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)

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 cr

Value

a trellis object

Details

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.

Examples

Run this code

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) )
## 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)
plotFun(fitted.length(width, sex="G") ~ width, add=TRUE, col=2)