Transcript Random numbers in C++

Random numbers in
Python
Nobody knows what’s next...
Deterministic machines
That means that computers do the same
predictable thing every time you give them
the same instructions
 we WANT this – we don't want random
happenings - most of the time
 when would you NOT want this?

 games
of reality – traffic flows, nuclear
explosions, star formation
 Cryptography!
 simulations
What is "random"?
A “real” random number is generated by a
real world event like an atom decaying or
not in a certain time
 Hard to do that in a computer
 Best we can do with a deterministic
machine is make “pseudorandom”
numbers
 They are “good enough”

“good enough”?
A “good” random number is one that is
distributed evenly in its range
 If you were rolling a die, you want
numbers from 1 to 6 to be equally likely to
show up
 This is over the “long run”, not each
individual trial

Lots of research
Lots has been done on random numbers
 Trying to get faster algorithms
 With larger cycles – all algorithms will
eventually start repeating but the best
ones not before a few million numbers at
least
 Very heavy statistics and mathematics in
the latest algorithms

A simple one – “mid square”
Take a number to start with (the “seed”)
 Square it
 Take the “middle” of it – trim off some
digits at front and end
 That’s the random number
 Repeat the process by feeding the number
just generated back in as the starting
number next time

An example
12345 squared = 152399025
 chop it off and get 23990
 23990 squared = 575520100
 chop it off and get 55201
 55201 squared = 3047150401
 chop it off and get 71504
 And so on

Properties of an RNG

Give the algorithm a DIFFERENT seed to
start with and what comes out?

Give the algorithm the SAME seed to start
with and what comes out?
Syntax of random numbers
from random import *
 Use seed(x) to set the initial seed (x is
usually an integer)
 randrange(stop) gets random integer from
0 to stop-1
 randrange(start,stop) to get random
integer number from start to stop-1,
inclusive

Syntax
Use randrange(start, stop, step) to get
random numbers from start to stop-1, with
a step size
 Use random() to get a floating point
number in the range [0.0, 1.0) (meaning
that it may generate 0, it will not generate
1.0) (useful for probabilities, 0 means “will
not happen”, 1 means “certain to happen”)

Seeds to start with
seed(23) will always give you the same
sequence of random numbers – good
when testing!
 Asking the user for a number and then
using it as the seed - works but is a bit
aggravating to the user
 If you don’t set seed at all, will use system
time – different for every run

Examples

choose a random word from a list
words = [“cat”, “hat”, “fox”, “house”, ”red”]
print(words[randrange(len(words))])

roll some dice
for i in range(10):
print (randrange(1,7), randrange(1,7))