One a Day One Liners with Python — Week 6

Patterns in the Noise

Photo by Nick Fewings on Unsplash

This week we explore patterns in the noise. No promises about what comes next…

GitHub - jeremyfromearth/one-a-day-one-liners-python: Every day I add a new Python One Liner

Feb 11, 2023

A random walk in a 2D plane with a One Liner 🤔 🚶🏻

from itertools import accumulate
from random import randint as rand

steps = 100000
walk = accumulate(
  [[rand(-1, 1), rand(-1, 1)] for x in range(steps)], 
  lambda p, c: (p[0] + c[0], p[1] + c[1]),
  initial=[0, 0]
)

Feb 10, 2023

Let’s make some noise 🎧

The noise data saved to an image

from math import cos, sin
from random import randint

w = 512
h = 512
noise = [[cos(x*8/w) * sin(y*8/h) * randint(0, 255) for x in range(w)] for y in range(h)]

Feb 09, 2023

Calculate the probability of rolling 8, twice in 10 rolls of a 20 sided die 🎲

Photo by Trnava University on Unsplash

from random import choices

rolls = 10
match = 8
matches = 2
sides = 20
sims = 10000

prob = sum([
  choices([i for i in range(sides)], k=rolls)
    .count(match) >= matches for i in range(sims)
]) / sims

Discussion

random.choices returns k random selections from a given iterable object. We then count the number of eights and store a value of True if there are 2 or more and False otherwise. Calling sum on a list of booleans will return the number of True values. Lastly, we divide the number of True values by the total number of simulations, resulting in the probability we are looking for!

Feb 08, 2023

Never make a choice on your own again, with a Magic 8 Ball One Liner 🎱

from random import choice
q = input('Ask the Magic Eight Ball for advice...\n')
print(choice(open('./data/text/eightball.txt').readlines()))

Discussion

Move over ChatGPT, you’re 5 billion parameter neural nets are no match for random.choice!

Feb 07, 2023

Create a year of mock weather data ❄️🌿☀️🍂📈

from math import cos
from random import uniform

celsius = [(1-cos(d / 60)) * 16 + uniform(-1.5, 1.5) for d in range(365)]

Feb 06, 2023

Generate a variable length pseudo random key 🗝️

from random import randint, seed
from string import ascii_letters, digits

n = 64
seed(0)
chars = ascii_letters + digits
key = ''.join([chars[randint(0, len(chars)-1)] for _ in range(n)])

Discussion

There is something very satisfying about the concept of a pseudo randomness. It’s at once random and completely predictable.

Resources

random - Generate pseudo-random numbers

Feb 05, 2023

Create a Poisson distribution 🔔

from functools import reduce
from math import exp

m = 15
k = m * 2
poisson = [((m**x) * exp(-m)) / reduce(lambda x, y: x*y, range(1, x+1)) for x in range(1, k)]

Resources

Poisson distribution - Wikipedia

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