# Doodling in R!

August 21, 2013
By

(This article was first published on Econometrics by Simulation, and kindly contributed to R-bloggers)

# I am working on creating some functions that will be capable of creating shapes and plots that look hand drawn.

# I have made some progress in this goal.

# In that process I have also discovered that I can make some doodles that look hand drawn as well.

# In order to accomplish the goal of simulating hand drawing I want to simulate the momentum of hand writing.

# In order to do that I will break the task down into a goal oriented system where each end point is a target.

doodle <- function(
start=c(0,0),
targets = rbind(c(0,10),c(10,10), c(10,0), c(0,0)) ,
tdist = .25,
speed = c(0,0),
accel = .1,
resis = .005,
jitter = .0005,
chncStp = 0) {
# start - We start with the starting position
# targ - Points that will be pursued (initially just a square)
# tdist - How close we need to get to each point before moving on
# speed - Initial speed
# accel - How fast does the drawer accelerate towards that point
# resis - What percentage of speed is lost each round
# jitter - A normal draw random jitter that moves the writing tool in an unexpected direction.
# chncStp - There is some chance that the drawing tool will kill all momentum and stop.

# First off I define a function uvect to convert any two sets of points
# into a unit vector and measure the distance between the two points.

uvect <- function(p1,p2=NULL) {
if (is.null(p2)) {
p2 <- p1[[2]]
p1 <- p1[[1]]
}
list(vect=(p2-p1)/sqrt(sum((p1-p2)^2)), dist=sqrt(sum((p1-p2)^2)))
}

# Starup parameters
i <- 1
plist <- position <- start # plist saves all of the points that the drawing tool has passed through
vect <- uvect(position,targets[i,])

while(i<=nrow(targets)) {
# Calculate the appropriate unit vector and distance from end point
vect <- uvect(position,targets[i,])
# Remove some amount of speed from previous velocity
speed <- speed*(1-resis)
# IF drawer randomly stops remove all speed
if (rbinom(1,1,chncStp)) speed<-0
#
speed <- speed + accel*vect[[1]] + rnorm(2)*jitter
position <- position + speed
plist <- rbind(plist,position)
vect <- uvect(position,targets[i,])
if (vect[[2]]<tdist) i <- i+1
}
plist
}

plist <- doodle()

plot(plist, type="n", lwd=3)
lcol <- rainbow(nrow(plist-1))
for (i in 1:(nrow(plist)-1)) lines(plist[c(i:(i+1)),], type="l", lwd=3, col=lcol[i])

# However this was not the primary intention of this function.

# The main intention is to be able to make plots that look hand drawn.
shape1 <- doodle(cbind(c(0,10,10,0),c(10,10,0,0)),resis=.25)

plot(shape1, type="l", lwd=1)

#
shape2 <- doodle(cbind(c(0,-2,5,15,10,0),c(5,9,10,5,2,0)),resis=.25)

plot(shape2, type="l", lwd=1)

Created by Pretty R at inside-R.org

# To tell you the truth.  I don't know what is going on some I am going to have to debug this function for a while.  In the mean time it is making unexpected shapes which look pretty crazy.

https://gist.github.com/EconometricsBySimulation/6296678

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