A simple Python simulation of a Russian Roulette game between 2 players. There are 4 simulations in total.
1 loaded chamber and the cylinder is re-spun every turn
The code provided runs a Russian Roulette Simulation for 2 players (A and B). The code has the function simulation(num, gameTotal) which is used to run the simulation in total of 'num' times (captured from input) and each simulation has 'gameTotal' = 100000 games. In each game, a counter starting from 1 will be initialized and a number in the set {0,1,2,3,4,5} will be randomized. If the random number is not 0, which has the probability of 5/6, the counter will increase by 1 and a new number will be randomized. Only until 0 is randomized, the game will be stopped and the loser will be determined by the parity of the counter (Player A will lose if the counter is odd and vice versa).
# Surviving the deadliest and stupidest game ever: Russian Roulette - The simulations
# Author: Vo-Hoang-Tuan Ngo (26839)
# Rhein-Waal University of Applied Sciences
# Date 03.01.2021
import random
import numpy as np
import matplotlib.pyplot as plt
# Function to run the simulation 'num' times
# Each simulation has 'gameTotal' games
def simulation(num,gameTotal):
gameTotalLost_A = 0
gameTotalLost_B = 0
percentageLostArray_A = np.empty(0,float)
percentageLostArray_B = np.empty(0,float)
for sim in range (0,num):
# Counter for the game lost by each players
gameLost_A = 0
gameLost_B = 0
for game in range (0,gameTotal):
# print ("Game", game, ":")
gameEnd = bool(False)
count = 1
while(gameEnd == False):
# Random the integer 'x' in the set of {0,1,2,3,4,5}
# 'x' has 1/6 chance to be 0, which is chose to be when the weapon discharges
x = random.randint(0,5)
if(x == 0):
if (count % 2 == 0):
# When the integer 'count' is even and 'x' is randomized to equal 0, which means player B lost
# Increment for the counter which B loses
gameLost_B += 1
else:
# Increment for the counter which A loses
gameLost_A += 1
# Boolean to check whether the game is finished
gameEnd = True
else:
# Increment for the integer 'count'
count += 1
#print("\nSimulation", sim+1, ":", "In", gameTotal, "games:")
#print("Player A lost:", gameLost_A, "times, accounting for", round(gameLost_A/gameTotal*100,3), "% of the games.")
#print("Player B lost:", gameLost_B, "times, accounting for", round(gameLost_B/gameTotal*100,3), "% of the games.")
gameTotalLost_A += gameLost_A
gameTotalLost_B += gameLost_B
percentageLostArray_A = np.append(percentageLostArray_A, [round(gameLost_A/gameTotal*100,3)], axis=0)
percentageLostArray_B = np.append(percentageLostArray_B, [round(gameLost_B/gameTotal*100,3)], axis=0)
percentageLostAverage_A = round(gameTotalLost_A/(gameTotal*num)*100,3)
percentageLostAverage_B = round(gameTotalLost_B/(gameTotal*num)*100,3)
print("\nOn average:", sim+1, "simulations of", gameTotal, "games each:")
print(" - Player A lost:", percentageLostAverage_A, "% of the games.")
print(" - Player B lost:", percentageLostAverage_B, "% of the games.")
print("\nPlayer A has lost", round(percentageLostAverage_A - percentageLostAverage_B,3), "% of the games more than player B.")
return percentageLostAverage_A, percentageLostAverage_B, percentageLostArray_A, percentageLostArray_B
# Run the simulation() function
num = int(input("Number of the 1st simulations (1 loaded chamber & the cylinder is re-spun every turn): "))
P_A, P_B, Array_A, Array_B = simulation(num,100000)
import pandas as pd
Array_combined = np.vstack((Array_A, Array_B)).T
fig, ax = plt.subplots(1,1)
column_labels=["A losing (%)", "B losing (%)"]
df = pd.DataFrame(Array_combined, columns=column_labels)
ax.axis('off')
table = ax.table(cellText=df.values,
colLabels=df.columns,
rowLabels=[x+1 for x in range (0,num)],
rowColours =["lightskyblue"] * 10,
colColours =["lightskyblue"] * 2,
colWidths=[.5]*2,
cellLoc="center",
loc="center")
table.set_fontsize(14)
table.scale(0.75, 1.75)
plt.title("Table. Percentage of each player losing in each of the first simulation", y=-0.2)
plt.show()2 adjacent loaded chambers and the cylinder is re-spun every turn
The function simulation(num, gameTotal) is changed into simulation2(num, gameTotal) with 0 and 1 are the two numbers used to determine when the one of the two loaded chamber is triggered. The odds of one of the two numbers being randomized are 2/6 (33.33%).
import random
import numpy as np
import matplotlib.pyplot as plt
def simulation2(num,gameTotal):
gameTotalLost_A = 0
gameTotalLost_B = 0
percentageLostArray_A = np.empty(0,float)
percentageLostArray_B = np.empty(0,float)
for sim in range (0,num):
# Counter for the game lost by each players
gameLost_A = 0
gameLost_B = 0
for game in range (0,gameTotal):
# print ("Game", game, ":")
gameEnd = bool(False)
count = 1
while(gameEnd == False):
# Random the integer 'x' in the set of {0,1,2,3,4,5}
# 'x' has 2/6 chance to be 0 or 1, which is chose to be when the weapon discharges
x = random.randint(0,5)
if((x == 0) or (x == 1)):
if (count % 2 == 0):
# When the integer 'count' is even and 'x' is randomized to equal 0, which means player B lost
# Increment for the counter which B loses
gameLost_B += 1
else:
# Increment for the counter which A loses
gameLost_A += 1
# Boolean to check whether the game is finished
gameEnd = True
else:
# Increment for the integer 'count'
count += 1
#print("\nSimulation", sim+1, ":", "In", gameTotal, "games:")
#print("Player A lost:", gameLost_A, "times, accounting for", round(gameLost_A/gameTotal*100,3), "% of the games.")
#print("Player B lost:", gameLost_B, "times, accounting for", round(gameLost_B/gameTotal*100,3), "% of the games.")
gameTotalLost_A += gameLost_A
gameTotalLost_B += gameLost_B
percentageLostArray_A = np.append(percentageLostArray_A, [round(gameLost_A/gameTotal*100,3)], axis=0)
percentageLostArray_B = np.append(percentageLostArray_B, [round(gameLost_B/gameTotal*100,3)], axis=0)
percentageLostAverage_A = round(gameTotalLost_A/(gameTotal*num)*100,3)
percentageLostAverage_B = round(gameTotalLost_B/(gameTotal*num)*100,3)
print("\nOn average:", sim+1, "simulations of", gameTotal, "games each:")
print(" - Player A lost:", percentageLostAverage_A, "% of the games.")
print(" - Player B lost:", percentageLostAverage_B, "% of the games.")
print("\nPlayer A has lost", round(percentageLostAverage_A - percentageLostAverage_B,3), "% of the games more than player B.")
return percentageLostAverage_A, percentageLostAverage_B, percentageLostArray_A, percentageLostArray_B
# Run the simulation() function
num = int(input("Number of the 2nd simulations (2 adjacent loaded chambers & the cylinder is re-spun every turn): "))
P_A, P_B, Array_A, Array_B = simulation2(num,100000)
import pandas as pd
Array_combined = np.vstack((Array_A, Array_B)).T
fig, ax = plt.subplots(1,1)
column_labels=["A losing (%)", "B losing (%)"]
df = pd.DataFrame(Array_combined, columns=column_labels)
ax.axis('off')
table = ax.table(cellText=df.values,
colLabels=df.columns,
rowLabels=[x+1 for x in range (0,num)],
rowColours =["lightskyblue"] * 10,
colColours =["lightskyblue"] * 2,
colWidths=[.5]*2,
cellLoc="center",
loc="center")
table.set_fontsize(14)
table.scale(0.75, 1.75)
plt.title("Table. Percentage of each player losing in each of the second simulation", y=-0.2)
plt.show()2 adjacent loaded chambers and the cylinder NOT is re-spun every turn
The function is one more time changed into simulation3(num, gameTotal) with 2 adjacent randomized numbers for the two loaded chambers (if the first number is 5 then the second number will be 0). A new number, the starting chamber, is randomized, and this number increases by 1 every turn. If this number gets to 5, the last chamber, and the game still doesn't end, the number is looped back to 0.
import random
import numpy as np
import matplotlib.pyplot as plt
def simulation3(num,gameTotal):
gameTotalLost_A = 0
gameTotalLost_B = 0
percentageLostArray_A = np.empty(0,float)
percentageLostArray_B = np.empty(0,float)
for sim in range (0,num):
# Counter for the game lost by each players
gameLost_A = 0
gameLost_B = 0
for game in range (0,gameTotal):
# print ("Game", game, ":")
gameEnd = bool(False)
count = 1
# Random two loaded chambers
chamber_1 = random.randint(0,5)
chamber_2 = chamber_1 + 1
# Checking whether the second chamber is out of the range {0,5}
if (chamber_2 > 5):
chamber_2 = 0
# Initialize the starting chamber
x = random.randint(0,5)
while(gameEnd == False):
if((x == chamber_1) or (x == chamber_2)):
if (count % 2 == 0):
# When the integer 'count' is even and 'x' is randomized to equal 0, which means player B lost
# Increment for the counter which B loses
gameLost_B += 1
else:
# Increment for the counter which A loses
gameLost_A += 1
# Boolean to check whether the game is finished
gameEnd = True
else:
# Increment for the integer 'count'
count += 1
# If x=5 and game still doesn't end, loop back to x=0. Else increase x by 1
if (x == 5):
x = 0
else:
x += 1
#print("\nSimulation", sim+1, ":", "In", gameTotal, "games:")
#print("Player A lost:", gameLost_A, "times, accounting for", round(gameLost_A/gameTotal*100,3), "% of the games.")
#print("Player B lost:", gameLost_B, "times, accounting for", round(gameLost_B/gameTotal*100,3), "% of the games.")
gameTotalLost_A += gameLost_A
gameTotalLost_B += gameLost_B
percentageLostArray_A = np.append(percentageLostArray_A, [round(gameLost_A/gameTotal*100,3)], axis=0)
percentageLostArray_B = np.append(percentageLostArray_B, [round(gameLost_B/gameTotal*100,3)], axis=0)
percentageLostAverage_A = round(gameTotalLost_A/(gameTotal*num)*100,3)
percentageLostAverage_B = round(gameTotalLost_B/(gameTotal*num)*100,3)
print("\nOn average:", sim+1, "simulations of", gameTotal, "games each:")
print(" - Player A lost:", percentageLostAverage_A, "% of the games.")
print(" - Player B lost:", percentageLostAverage_B, "% of the games.")
print("\nPlayer A has lost", round(percentageLostAverage_A - percentageLostAverage_B,3), "% of the games more than player B.")
return percentageLostAverage_A, percentageLostAverage_B, percentageLostArray_A, percentageLostArray_B
# Run the simulation() function
num = int(input("Number of the 3rd simulations (2 adjacent loaded chambers & the cylinder NOT is re-spun every turn): "))
P_A, P_B, Array_A, Array_B = simulation3(num,100000)
import pandas as pd
Array_combined = np.vstack((Array_A, Array_B)).T
fig, ax = plt.subplots(1,1)
column_labels=["A losing (%)", "B losing (%)"]
df = pd.DataFrame(Array_combined, columns=column_labels)
ax.axis('off')
table = ax.table(cellText=df.values,
colLabels=df.columns,
rowLabels=[x+1 for x in range (0,num)],
rowColours =["lightskyblue"] * 10,
colColours =["lightskyblue"] * 2,
colWidths=[.5]*2,
cellLoc="center",
loc="center")
table.set_fontsize(14)
table.scale(0.75, 1.75)
plt.title("Table. Percentage of each player losing in each of the third simulation", y=-0.2)
plt.show()2 random loaded chambers and the cylinder NOT is re-spun every turn
The function simulation3(num, gameTotal) is changed into simulation4(num, gameTotal) with a little tweak this time. Instead of 2 adjacent randomized numbers, this time 2 different numbers are chosen to be the 2 loaded chambers.
import random
import numpy as np
import matplotlib.pyplot as plt
def simulation4(num,gameTotal):
gameTotalLost_A = 0
gameTotalLost_B = 0
percentageLostArray_A = np.empty(0,float)
percentageLostArray_B = np.empty(0,float)
for sim in range (0,num):
# Counter for the game lost by each players
gameLost_A = 0
gameLost_B = 0
for game in range (0,gameTotal):
# print ("Game", game, ":")
gameEnd = bool(False)
count = 1
# Random two loaded chambers
chamber_1 = random.randint(0,5)
chamber_2 = random.randint(0,5)
# Checking whether the two random numbers are different
while (chamber_2 == chamber_1):
chamber_2 = random.randint(0,5)
# Initialize the starting chamber
x = random.randint(0,5)
while(gameEnd == False):
if((x == chamber_1) or (x == chamber_2)):
if (count % 2 == 0):
# When the integer 'count' is even and 'x' is randomized to equal 0, which means player B lost
# Increment for the counter which B loses
gameLost_B += 1
else:
# Increment for the counter which A loses
gameLost_A += 1
# Boolean to check whether the game is finished
gameEnd = True
else:
# Increment for the integer 'count'
count += 1
# If x=5 and game still doesn't end, loop back to x=0. Else increase x by 1
if (x == 5):
x = 0
else:
x += 1
#print("\nSimulation", sim+1, ":", "In", gameTotal, "games:")
#print("Player A lost:", gameLost_A, "times, accounting for", round(gameLost_A/gameTotal*100,3), "% of the games.")
#print("Player B lost:", gameLost_B, "times, accounting for", round(gameLost_B/gameTotal*100,3), "% of the games.")
gameTotalLost_A += gameLost_A
gameTotalLost_B += gameLost_B
percentageLostArray_A = np.append(percentageLostArray_A, [round(gameLost_A/gameTotal*100,3)], axis=0)
percentageLostArray_B = np.append(percentageLostArray_B, [round(gameLost_B/gameTotal*100,3)], axis=0)
percentageLostAverage_A = round(gameTotalLost_A/(gameTotal*num)*100,3)
percentageLostAverage_B = round(gameTotalLost_B/(gameTotal*num)*100,3)
print("\nOn average:", sim+1, "simulations of", gameTotal, "games each:")
print(" - Player A lost:", percentageLostAverage_A, "% of the games.")
print(" - Player B lost:", percentageLostAverage_B, "% of the games.")
print("\nPlayer A has lost", round(percentageLostAverage_A - percentageLostAverage_B,3), "% of the games more than player B.")
return percentageLostAverage_A, percentageLostAverage_B, percentageLostArray_A, percentageLostArray_B
# Run the simulation() function
num = int(input("Number of the 4th simulations (2 random loaded chambers & the cylinder NOT is re-spun every turn): "))
P_A, P_B, Array_A, Array_B = simulation4(num,100000)
import pandas as pd
Array_combined = np.vstack((Array_A, Array_B)).T
fig, ax = plt.subplots(1,1)
column_labels=["A losing (%)", "B losing (%)"]
df = pd.DataFrame(Array_combined, columns=column_labels)
ax.axis('off')
table = ax.table(cellText=df.values,
colLabels=df.columns,
rowLabels=[x+1 for x in range (0,num)],
rowColours =["lightskyblue"] * 10,
colColours =["lightskyblue"] * 2,
colWidths=[.5]*2,
cellLoc="center",
loc="center")
table.set_fontsize(14)
table.scale(0.75, 1.75)
plt.title("Table. Percentage of each player losing in each of the fourth simulation", y=-0.2)
plt.show()