(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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