gprocessingjs: Interface to Processing.js code to create graphics with...

Description Usage Arguments Details Value Author(s) References Examples

View source: R/gprocessingjs.R

Description

This function provides the ability to write to canvas on the browser using somewhat familar graphics commands in R. The processing.js (http://ejohn.org/blog/processingjs) javascript library is used to provide an interface to the canvas web object.

The package also provides gcanvas, for the canvas device, which uses the same technology to display graphics, but using R's plotting commands.

Usage

1
gprocessingjs(width=400, height=400, pointsize= 12, container = NULL, ...)

Arguments

width

width of canvas in pixels

height

height of canvas in pixels

pointsize

size of font in pixels

container

parent container for processing object

...

not used

Details

This package is an interface to the processing.js javascript libraries http://ejohn.org/apps/processing.js/processing.js and http://ejohn.org/apps/processing.js/examples/init.js. These provide the processing API for javascript. (Processing is an API for JAVA-based graphics.

The gcanvas widget is more straightforward to use, but this widget is still included, as it can be used to create relatively interactive graphics with the local server version of gWidgetsWWW. For this use, no installation is required.

This does not work like a typical R device. The constructor returns a proto object, for which several methods are defined, including many familiar graphics primitives. Methods for proto objects are called through the object-oriented notation obj\$methodname(arguments).

The proto object has properties ..margin and ..background that may be changed directly to adjust the defaults.

The main methods have only an abbreviated subset of the graphical parameters available.

The following familiar methods are implemented:

p\$plot.new()

Simply sets the background color to the value in the ..background property

p\$plot.window(xlim, ylim, ...)

Set the user limits for the graphic. The underlying canvas values are in pixels, this allows conversion into x-y coordinates.

p\$title(main=NULL, sub=NULL, xlab=NULL, ylab=NULL, cex=1

Set the titles etc. for the graphic. The ylabel is not rotated.

p\$axis(side)

Draw axis on side given by side. Uses pretty to label axis.

p\$box()

Draw a box around graphic area

p\$lines(x, y=NULL, col=NA, lwd=1, ...

Draw lines between values in x and values in y

p\$points(x,y=NULL, cex=1, col=NA, ...

Draw points centered at x,y. The interior color is adjusted by col

p\$polygon(x, y=NULL, col=NA

Draw polygon using opints in x and y. The col sets the interior fill.

p\$rect(xleft, ybottom, xright, ytop, col=NA, ...)

Draw rectangle(s) filling with the color if given.

p\$abline(a=NULL, b=NULL, v=NULL, h=NULL, coef=NULL, ...)

draws line over the canvas

p\$text(x, y = NULL, labels = seq\_along(x),cex = 1, col = NULL, pos = NULL, ...)

Places text label at x,y position. The value of pos adjusts the text: 1 for below, 2 to left, 3 above, 4 to right, 0 center.

There are also several methods from the processing API that are implemented. The processing API allows for interactive graphics. The example shows how one can use a slider to adjust a histogram.

This can be kind of slow, as the lag between the browser and R can make the interface non-responsive. This isn't so bad with the local version. If one wishes to write some javascript code, the methods "mouseDragged","mouseMoved", "mousePressed", "mouseReleased", "keyPressed","keyReleased","draw","setup" can be set to functions that produce javascript handlers. This way there is not a lag between the browser and the R process.

Value

Returns a proto object with class gProcessing.

Author(s)

John Verzani

References

http://ejohn.org/blog/processingjs

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
## Not run: 
   ## make a histogram with breaks controlled by a slider
   w <- gwindow("processing example")
   g <- ggroup(horizontal=FALSE, cont=w)
   x <- faithful$eruptions
   p <- gprocessingjs(width=500, height = 400, container  = g)
   p$textFont("arial",14)
   p$Hist <- function(.,x, breaks = "Sturges", col = "goldenrod") {
     out <- hist(x, breaks = breaks, plot=FALSE)
     p$plot.new()
     p$plot.window(xlim = range(out$breaks), ylim = c(0, max(out$counts)))
     p$axis(1)
     p$title(main = deparse(substitute(x)))
     nb <- length(out$breaks)
     p$rect(out$breaks[1:(nb-1)], rep(0, length=nb-1), out$breaks[2:nb],
       out$counts, col)
   }
   p$Hist(faithful$eruptions)
   gslider(from = 1, to = length(x), by = 1, cont = g, handler =
   function(h,...) {
     p$Hist(faithful$eruptions, breaks =as.numeric(svalue(h$obj)))
   })


 ## Make regression line that follows mouse clicks
 x <- c(); y <- c()
 glabel("Click in graph to set points", container=g)
 p1 <- gprocessingjs(width=500, height = 400, container  = g)
 p1$..background <- 200
 p1$plot.new()
 p1$plot.window(xlim=c(0,10), ylim=c(0,10))
 addHandlerMouseclick(p1, handler = function(h,...) {
   xy <- p1$pixelsToXY(h$xy)
   assign("x",c(x, xy[1]), envir=.GlobalEnv)
   assign("y",c(y, xy[2]), envir=.GlobalEnv)
   p1$plot.new() # paints background
   p1$points(x, y, cex=2, col="red")
   if(length(x) != 1) {
     res <- lm(y ~ x)
     p$abline(res,col="blue")
   }
 })

   visible(w) <- TRUE

   ## This is really slow!
w <- gwindow("Follow the cursor", cont=g)
w$doLoadingText <- FALSE

f <- gframe("Regression example", horiz=FALSE, cont = w)
glabel("Move mouse through canvas and red ball will follow along", container=f)
p1 = gprocessingjs(width=500, height = 400, container  = f)
p1$..background = 200
p1$plot.new()
p1$plot.window(xlim=c(0,10), ylim=c(0,10))

theta <- seq(0, 2*pi, length=100)
inds <- 2*(0:4) + 1.5
p1$addHandlerMousemove(handler = function(h,...) {
  xy = p1$pixelsToXY(h$xy) ## need to convert to user coordinates
  p1$plot.new()
  for(i in inds) {
    for(j in inds) {
      r <- min(0.5, sqrt((i-xy[1])^2 + (j-xy[2])^2)/5)
      p1$points(i, j, cex=r*10, col="red")
    }
  }
})


gstatusbar("Powered by gWidgetsWWW", cont=w)
visible(w) <- TRUE




## End(Not run)

gWidgetsWWW documentation built on May 31, 2017, 2:08 a.m.