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simulation.jl
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simulation.jl
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### A Pluto.jl notebook ###
# v0.16.1
using Markdown
using InteractiveUtils
# This Pluto notebook uses @bind for interactivity. When running this notebook outside of Pluto, the following 'mock version' of @bind gives bound variables a default value (instead of an error).
macro bind(def, element)
quote
local el = $(esc(element))
global $(esc(def)) = Core.applicable(Base.get, el) ? Base.get(el) : missing
el
end
end
# ╔═╡ 450adc07-0529-451c-a897-f1bb2f5394a3
using GLMakie,PlutoUI, StatsBase, Statistics
# ╔═╡ 787a80fc-e7f9-4108-a5ed-e4f458356ca0
md"""
# 🐙 Squid Game: Hopscotch
A special game of hopscotch is devised wherein $n$ players sequentially attempt to traverse a path of length $n$.
At each step of the path, the player must choose how to proceed: on the left, or on the right.
Each choice is a 50/50 gamble on whether the player hits a dead end and is eliminated from the game.
!!! note
this would be a good place for a figure
What is the probability of a given player traversing the path?
Assume that each player will make guesses until either reaching the end of the playing field or making an incorrect guess and players will proceed in their assigned order.
Also assume no mistakes are made (each player follows the solved path as far as it is known).
We can solve this problem via Monte-Carlo simulation.
## The Playing Field
We define a `struct Field` to track the state of the game.
Its `path` attribute encodes the safe/unsafe spaces as true/false.
The path is as long as `length` (number of steps to cross) and as wide as `width` (number of options at each step).
The `state` attribute encodes the players' knowledge of the game's state; `missing` values show which guesses haven't been made yet.
The `solved` attribute tracks how many steps along the path have been solved (meaning there is a safe choice known for that step).
We initialize a `Field` by passing it a length, width, and number of safe choices per step.
"""
# ╔═╡ c826a0a0-c034-4b33-aaee-2fc26a361e67
begin
# data type for tracking the state of the playing field
mutable struct Field
path::Array{Bool} # True = part of correct path
length::Int # how long the path is
width::Int # how many "lanes" wide the field is
solved::Int # how many steps of the correct path are known
state::Array{Union{Bool, Missing}} # state of the game as known to players
end
# constructor
function Field(steps::Int, lanes::Int, safe::Int)
@assert safe ≥ 1 "there must be at least one safe choice per step"
@assert safe < lanes "there must be at least one wrong choice per step"
@assert steps ≥ 1 "the board must have at least one step"
@assert lanes ≥ 2 "there must be actual choices at each step"
# build the path
path = falses(steps, lanes)
for step in 1:steps # loop over steps along path
# label the safe spots
safe_lanes = Int.(sample(1:lanes, safe, replace=false))
path[step, safe_lanes] .= true
end
# initialize the players' view of the game's state
state = reshape([missing for _ in 1:length(path)], (steps, lanes))
return Field(path, steps, lanes, 0, state)
end
end;
# ╔═╡ 836e2445-9178-4947-9f68-604d385c95e6
md"""
## Simulation Code
"""
# ╔═╡ 1cb34a0d-bc2a-47da-b4eb-3fd1f07cdd81
"""
is_solved = solved(field)
Checks to see if a complete path has been found for `field`.
"""
function solved(field::Field)::Bool
return field.length == field.solved
end;
# ╔═╡ 0acf160e-3132-4b7c-ab03-a071ea017dff
"""
Simulate a single player's attempt at crossing the `field` in its current state.
"""
function attempt_crossing!(field::Field)
# make guesses until guess returns false or the last step is solved
while !solved(field)
# start from the first step w/o a known safe spot
position = field.solved + 1
# get the possible choices at this step
options = [i for i in 1:field.width if ismissing(field.state[position, i])]
# make a selection
guess = sample(options)
if field.path[position, guess]
# good guess -- mark the correct step and move on
field.state[position, guess] = true
field.solved += 1
else
# bad guess -- mark the incorrect step and end this player's turn
field.state[position, guess] = false
break
end
end
end;
# ╔═╡ d1fec284-c381-40ad-9667-c236598702a2
"""
crossed = simulate_hopscotch(players, steps, lanes, safe)
Simulate one slate of players in a hopscotch game.
Returns the number of players that got all the way across.
"""
function simulate_hopscotch(players::Int, steps::Int, lanes::Int, safe::Int)::Int
# initialize the playing field
field = Field(steps, lanes, safe)
# loop over players and have each one make guesses
for player in 1:players
attempt_crossing!(field) # make guesses until a stopping condition is met
if solved(field)
# if player m made it, then n - m + 1 players made it
return players - player + 1
end
end
# if final player didn't make it, no one did
return 0
end;
# ╔═╡ e146d512-c841-4535-8c7d-d12b8aec3fb1
md"""
## Simulations
"""
# ╔═╡ 91631440-0d9e-4dfd-b0b2-183a3c63213c
md"""
!!! parameters
Use the fields below to run batches of game simulations with different versions of the rules.
Number of Players: $(@bind players NumberField(1:1:128, default=16))
Path Length (Steps): $(@bind steps NumberField(1:1:128, default=16))
Path Width (Lanes): $(@bind lanes NumberField(2:1:32, default=2))
Safe Spots per Step: $(@bind safe_lanes NumberField(1:1:32, default=1))
Simulations to Run: $(@bind simulations NumberField(100:100000, default=1000))
"""
# ╔═╡ d4cc0e2a-f9ed-4519-a9e9-5a96471a0cb8
md"""
## Calculations
For each game, how many players got across?
"""
# ╔═╡ e1dd9af4-df1f-4506-b1fc-98d467a371cf
results =
[simulate_hopscotch(players, steps, lanes, safe_lanes) for _ in 1:simulations]
# ╔═╡ 31ea2b98-c87e-42c2-8ee9-72f354be6a09
md"""
Minimum: $(minimum(results))
Maximum: $(maximum(results))
Median: $(Int(round(median(results))))
"""
# ╔═╡ bce5ea0b-2611-4de2-a42d-12ded0d928a6
md"""
How often does a certain number of players get through?
"""
# ╔═╡ acced147-f3a2-4c51-ad97-f2ae638b4e24
"""
frequencies = calculate_frequencies(results)
Calculates the frequency
"""
function calculate_frequencies(results::Vector{Int}, players::Int)
return [count(y -> y == x, results) for x in 0:players] ./ length(results)
end;
# ╔═╡ 0267b4c6-cc36-4e0a-b144-ed4136aea89e
frequencies = calculate_frequencies(results, players)
# ╔═╡ 41dfe76f-5875-4840-a798-2b572c98ec4a
freq_err = 2 * sqrt.([p*(1-p)/simulations for p in frequencies])
# ╔═╡ f423c5bf-30c2-494d-9ff3-095c47386116
md"""
How likely is player $n$ to cross successfully?
"""
# ╔═╡ 038d6b7c-3311-4912-bc67-754570b1dfa3
"""
simulated_odds = calculate_odds(results, players)
"""
function calculate_odds(results::Vector{Int}, players::Int)
return [count(result -> result > players-i, results)
for i in 1:players] ./ length(results)
end;
# ╔═╡ 7409d3ff-dda3-4e09-bcd1-78c4411baed1
simulated_odds = calculate_odds(results, players)
# ╔═╡ c79df27e-d70b-49ad-91ac-2929ddb89c9b
odds_err = 2 * sqrt.([p*(1-p)/simulations for p in simulated_odds])
# ╔═╡ 001c77da-2e78-4075-a5d5-813c3dfdd815
begin
# create the figure
local fig = Figure()
# first plot - frequency distribution
local ax1 = Axis(
fig[1, 1],
title="$players Players, $steps Steps, $lanes Lanes, $safe_lanes Safe",
xlabel="Players Crossed",
ylabel="Frequency",
)
local p1 = plot!(0:players, frequencies)
barplot!(0:players, frequencies)
local e1 = errorbars!(0:players, frequencies, freq_err, freq_err, color=:red)
# second plot - cumulative probability
local ax2 = Axis(
fig[2, 1],
title="$players Players, $steps Steps, $lanes Lanes, $safe_lanes Safe",
xlabel="Player Number",
ylabel="Probability of Crossing",
)
local p2 = plot!(1:players, simulated_odds)
local e2 = errorbars!(1:players, simulated_odds, odds_err, odds_err, color=:red)
Legend(fig[1,2], [p1, e1], ["mean", "95 % CI"])
current_figure()
end
# ╔═╡ 00000000-0000-0000-0000-000000000001
PLUTO_PROJECT_TOML_CONTENTS = """
[deps]
GLMakie = "e9467ef8-e4e7-5192-8a1a-b1aee30e663a"
PlutoUI = "7f904dfe-b85e-4ff6-b463-dae2292396a8"
Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
[compat]
GLMakie = "~0.4.6"
PlutoUI = "~0.7.16"
StatsBase = "~0.33.11"
"""
# ╔═╡ 00000000-0000-0000-0000-000000000002
PLUTO_MANIFEST_TOML_CONTENTS = """
# This file is machine-generated - editing it directly is not advised
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