#!/bin/bash
# cannon.sh: Approximating PI by firing cannonballs.
# This is a very simple instance of a "Monte Carlo" simulation:
#+ a mathematical model of a real-life event,
#+ using pseudorandom numbers to emulate random chance.
# Consider a perfectly square plot of land, 10000 units on a side.
# This land has a perfectly circular lake in its center,
#+ with a diameter of 10000 units.
# The plot is actually mostly water, except for land in the four corners.
# (Think of it as a square with an inscribed circle.)
#
# We will fire iron cannonballs from an old-style cannon
#+ at the square.
# All the shots impact somewhere on the square,
#+ either in the lake or on the dry corners.
# Since the lake takes up most of the area,
#+ most of the shots will SPLASH! into the water.
# Just a few shots will THUD! into solid ground
#+ in the four corners of the square.
#
# If we take enough random, unaimed shots at the square,
#+ Then the ratio of SPLASHES to total shots will approximate
#+ the value of PI/4.
#
# The reason for this is that the cannon is actually shooting
#+ only at the upper right-hand quadrant of the square,
#+ i.e., Quadrant I of the Cartesian coordinate plane.
# (The previous explanation was a simplification.)
#
# Theoretically, the more shots taken, the better the fit.
# However, a shell script, as opposed to a compiled language
#+ with floating-point math built in, requires a few compromises.
# This tends to lower the accuracy of the simulation, of course.
DIMENSION=10000 # Length of each side of the plot.
# Also sets ceiling for random integers generated.
MAXSHOTS=1000 # Fire this many shots.
# 10000 or more would be better, but would take too long.
PMULTIPLIER=4.0 # Scaling factor to approximate PI.
get_random ()
{
SEED=$(head -n 1 /dev/urandom | od -N 1 | awk '{ print $2 }')
RANDOM=$SEED # From "seeding-random.sh"
#+ example script.
let "rnum = $RANDOM % $DIMENSION" # Range less than 10000.
echo $rnum
}
distance= # Declare global variable.
hypotenuse () # Calculate hypotenuse of a right triangle.
{ # From "alt-bc.sh" example.
distance=$(bc -l << EOF
scale = 0
sqrt ( $1 * $1 + $2 * $2 )
EOF
)
# Setting "scale" to zero rounds down result to integer value,
#+ a necessary compromise in this script.
# This diminshes the accuracy of the simulation, unfortunately.
}
# main() {
# Initialize variables.
shots=0
splashes=0
thuds=0
Pi=0
while [ "$shots" -lt "$MAXSHOTS" ] # Main loop.
do
xCoord=$(get_random) # Get random X and Y coords.
yCoord=$(get_random)
hypotenuse $xCoord $yCoord # Hypotenuse of right-triangle =
#+ distance.
((shots++))
printf "#%4d " $shots
printf "Xc = %4d " $xCoord
printf "Yc = %4d " $yCoord
printf "Distance = %5d " $distance # Distance from
#+ center of lake --
# the "origin" --
#+ coordinate (0,0).
if [ "$distance" -le "$DIMENSION" ]
then
echo -n "SPLASH! "
((splashes++))
else
echo -n "THUD! "
((thuds++))
fi
Pi=$(echo "scale=9; $PMULTIPLIER*$splashes/$shots" | bc)
# Multiply ratio by 4.0.
echo -n "PI ~ $Pi"
echo
done
echo
echo "After $shots shots, PI looks like approximately $Pi."
# Tends to run a bit high . . .
# Probably due to round-off error and imperfect randomness of $RANDOM.
echo
# }
exit 0
# One might well wonder whether a shell script is appropriate for
#+ an application as complex and computation-intensive as a simulation.
#
# There are at least two justifications.
# 1) As a proof of concept: to show it can be done.
# 2) To prototype and test the algorithms before rewriting
#+ it in a compiled high-level language.