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September 19, 2019 21:33
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CS166 Assignment 1
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"\"\"\"\n", | |
"Strategy One:\n", | |
"A simple one-shot elevator.\n", | |
"It starts at a random floor, chooses the nearest passenger to it, picks them up and drops them off. Afterwards, looks\n", | |
"again for nearest passenger and so on.\n", | |
"\n", | |
"Attributes:\n", | |
"CurrentFloor is the elevator's current floor.\n", | |
"DesiredFloor is where the elevator is heading.\n", | |
"PassengerNumber is how many passengers are on the elevator (In this scenario, it's either 0 or 1).\n", | |
"Counter is a list which is going to be used to keep track of how many steps the elevator takes. This is going to be\n", | |
"used as a measure of how efficient the elevator is. It starts counting from when the first passenger requests the \n", | |
"elevator until the last passenger is dropped off.\n", | |
"\n", | |
"Methods:\n", | |
"FindMin is where the bulk of the work is. It acccepts a parameter \"Passenger\" which is an array with dimensions m*3\n", | |
"where m is the number of passengers in the simulation. The columns represent Passenger ID, current floor, and desired\n", | |
"floor respectively. It starts by passing through the list of random passengers to find the nearest passenger.\n", | |
"It records the index of that passenger, and uses the index to record the passenger's current and desired floors. It then\n", | |
"deletes the passenger from the passenger list so it doesn't pick them up again.\n", | |
"\n", | |
"MoveToPassenger is a simple while loop. It starts by computing the difference between the elevator's current floor\n", | |
"and destination floors to see if it's going up or down, and then iteratively moves between floors.\n", | |
"\n", | |
"AddPassenger simply converts the value of PassengerNumber to reflect that a passenger is in the elevator.\n", | |
"\n", | |
"MoveToLocation is the same as MoveToPassenger, except it moves to the passenger's desired location rather than\n", | |
"their current location.\n", | |
"\n", | |
"Run is the simulation starter.\n", | |
"\n", | |
"The Building and Passenger classes were formed to be kept at a complete minimum.\n", | |
"\n", | |
"The simulation is initiated by creating a randomized array of passengers. The list is then cleaned to make sure\n", | |
"no passenger has the same current location as their desired location. The simulation is then run and the values\n", | |
"of the resulting counters are stored for efficiency evaluation.\n", | |
"\n", | |
"The final chosen efficiency measure is average elevator steps taken. This is going to be plotted against number of passengers\n", | |
"in the system. So, each simulation will be repeated several times and at different numbers of passengers in the system\n", | |
"in order to store and present the final data.\n", | |
"\"\"\"" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 22, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"import numpy as np #Importing Libraries\n", | |
"import random\n", | |
"import matplotlib.pyplot as plt\n", | |
"import matplotlib.style as style\n", | |
"class Elevator:\n", | |
" def __init__(self, Building, DesiredFloor = 0, PassengerNumber = 0):\n", | |
" self.CurrentFloor = random.randint(Building.MinFloor,Building.MaxFloor)\n", | |
" self.DesiredFloor = DesiredFloor\n", | |
" self.DesiredFloor2 = 0\n", | |
" self.PassengerNumber = 0\n", | |
" self.Counter = []\n", | |
" \n", | |
" def FindMin(self, Passenger):\n", | |
" MinList=[]\n", | |
" for i in Passenger[1:,1]:\n", | |
" MinList.append(abs(i-self.CurrentFloor)) #Appending differences with each passenger location\n", | |
" Minimum = min(MinList) #Finding the minimum\n", | |
" '''\n", | |
" Here, I added a couple of lines of code that gives the elevator the ability to scan the passengers \n", | |
" in that particular floor and determine the one whose destination floor is the closest. \n", | |
" \n", | |
" '''\n", | |
" minpeople = [] #Iterating through the list to find the index for people in that particular floor\n", | |
" minpeople = [i for i, x in enumerate(MinList) if x == Minimum]\n", | |
" MinDesiredFloor = [] \n", | |
" for i in Passenger[minpeople, 2]: #Iterate across the index of people to find the difference between \n", | |
" #their destination and them\n", | |
" MinDesiredFloor.append(abs(i-MinList.index(Minimum))) #Add those differences to a list\n", | |
" MinimumDesiredFloor = min(MinDesiredFloor) #Find the minimum difference in floors\n", | |
" index=MinDesiredFloor.index(MinimumDesiredFloor) \n", | |
" ''' \n", | |
" End of additional code.\n", | |
" \n", | |
" '''\n", | |
" self.DesiredFloor=Passenger[index,1] #Setting the desired floor to pick up the passenger\n", | |
" self.DesiredFloor2 = Passenger[index,2] #Setting the desired floor to drop off the passenger\n", | |
" Passenger = np.delete(Passenger, index, 0) #removing the passenger from the pool of possible pick-ups.\n", | |
" return(Passenger)\n", | |
"\n", | |
" def MoveToPassenger(self, Passenger, Building):\n", | |
" if self.CurrentFloor - self.DesiredFloor < 0: #If direction is positive\n", | |
" while self.CurrentFloor<self.DesiredFloor and self.CurrentFloor < Building.MaxFloor:\n", | |
" self.CurrentFloor+=1 #Keep increasing the current floor until you reach the passenger (or max floor).\n", | |
" self.Counter.append(1)\n", | |
" \n", | |
" elif self.CurrentFloor - self.DesiredFloor > 0:\n", | |
" while self.CurrentFloor>self.DesiredFloor and self.CurrentFloor > Building.MinFloor:\n", | |
" self.CurrentFloor-=1\n", | |
" self.Counter.append(1)\n", | |
" \n", | |
" def AddPassenger(self,Passenger):\n", | |
" self.PassengerNumber = 1\n", | |
"\n", | |
" def MoveToLocation(self, Building):\n", | |
" if self.CurrentFloor - self.DesiredFloor2 < 0:\n", | |
" while self.CurrentFloor<self.DesiredFloor2 and self.CurrentFloor < Building.MaxFloor:\n", | |
" self.CurrentFloor+=1\n", | |
" self.Counter.append(1)\n", | |
" \n", | |
" elif self.CurrentFloor - self.DesiredFloor2 >0:\n", | |
" while self.CurrentFloor>self.DesiredFloor2 and self.CurrentFloor > Building.MinFloor:\n", | |
" self.CurrentFloor-=1\n", | |
" self.Counter.append(1)\n", | |
" \n", | |
" def DeliverPassenger(self):\n", | |
" if self.CurrentFloor==self.DesiredFloor2:\n", | |
" self.PassengerNumber=0\n", | |
" \n", | |
" \n", | |
" def Run(self, Passenger, Building):\n", | |
" for i in range(len(Passenger[1:,:])):\n", | |
" Passenger = self.FindMin(Passenger)\n", | |
" self.MoveToPassenger(Passenger, Building)\n", | |
" self.AddPassenger(Passenger)\n", | |
" self.MoveToLocation(Building)\n", | |
" self.DeliverPassenger()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 23, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"class Building:\n", | |
" def __init__(self, MaxFloor, MinFloor):\n", | |
" self.MaxFloor = MaxFloor\n", | |
" self.MinFloor = MinFloor" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 24, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"class Passenger:\n", | |
" def __init__(self, CurrentFloor, DesiredFloor):\n", | |
" self.CurrentFloor = CurrentFloor\n", | |
" self.DesiredFloor = DesiredFloor" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 25, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"'\\nThe Simulation function has two parameters, n and m. n denotes how many times the simulation will be repeated, while\\nm is the number of passengers per simulation.\\nOnce those parameters are chosen, the function returns the average steps taken for the simulation to complete.\\n'" | |
] | |
}, | |
"execution_count": 25, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"\"\"\"\n", | |
"The Simulation function has two parameters, n and m. n denotes how many times the simulation will be repeated, while\n", | |
"m is the number of passengers per simulation.\n", | |
"Once those parameters are chosen, the function returns the average steps taken for the simulation to complete.\n", | |
"\"\"\"" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 26, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"def Simulation(n,m):\n", | |
" CountStorage = [] #an empty list to store the counters from the simulation\n", | |
" for i in range(n):\n", | |
" PassengerList = [] #List to store the passenger classes\n", | |
" for i in range(m):\n", | |
" PassengerList.append(Passenger(random.randint(0,20),random.randint(0,20))) #Append passenger classes\n", | |
" PassengerList #With randomized current and desired drop offs.\n", | |
" PassengerArray = np.array([0,0,0],ndmin=2) #Now, we append the information in an array for easier access.\n", | |
" for i in PassengerList:\n", | |
" PassengerArray = np.vstack([PassengerArray, [i, i.CurrentFloor, i.DesiredFloor]]) #Stack information in array.\n", | |
"\n", | |
" for i in PassengerArray[1:,2]: #This loop deletes any row where the passenger's current floor is equal to their\n", | |
" if PassengerArray[i,1] == PassengerArray[i,2]: #Desired drop off.\n", | |
" PassengerArrayFinal = np.delete(PassengerArray,i,0)\n", | |
" \n", | |
" Building1 = Building(20, 0) #Generate a building object with 20 floors (from 0 to 20)\n", | |
" Elevator1 = Elevator(Building1) #Generate the elevator object\n", | |
" Elevator1.Run(PassengerArray, Building1) #Run the simulation\n", | |
" CountStorage.append(Elevator1.Counter.count(1)) #Store the counts\n", | |
" \n", | |
" Average = (sum(CountStorage)/n)/m #Compute the average count per simulation.\n", | |
" return Average" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 27, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"'\\nSide note:\\nFor some reason, the code breaks down when using a value less than 20 in the range.\\n'" | |
] | |
}, | |
"execution_count": 27, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"AverageData = [] #Repeat the simulation 100 times, varying the number of passengers from 20 to 200 each time.\n", | |
"for j in range(20,200):\n", | |
" AverageData.append(Simulation(100,j))\n", | |
" \n", | |
"\n", | |
"\"\"\"\n", | |
"Side note:\n", | |
"For some reason, the code breaks down when using a value less than 20 in the range.\n", | |
"\"\"\"" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 28, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"Text(0, 0.5, 'Average Steps Taken by Elevator Per Passenger')" | |
] | |
}, | |
"execution_count": 28, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
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\n", | |
"text/plain": [ | |
"<Figure size 921.6x633.6 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"style.use('seaborn-poster')\n", | |
"style.use('ggplot')\n", | |
"plt.plot(range(20,200), AverageData)\n", | |
"plt.title('Average Steps Taken by Elevator pesr Passenger vs. # of Passengers')\n", | |
"plt.xlabel('# of Passengers')\n", | |
"plt.ylabel('Average Steps Taken by Elevator Per Passenger')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 29, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"def Simulation2(n,m):\n", | |
" CountStorage = [] #an empty list to store the counters from the simulation\n", | |
" for i in range(n):\n", | |
" PassengerList = [] #List to store the passenger classes\n", | |
" for i in range(m):\n", | |
" PassengerList.append(Passenger(random.randint(0,20),random.randint(0,20))) #Append passenger classes\n", | |
" PassengerList #With randomized current and desired drop offs.\n", | |
" PassengerArray = np.array([0,0,0],ndmin=2) #Now, we append the information in an array for easier access.\n", | |
" for i in PassengerList:\n", | |
" PassengerArray = np.vstack([PassengerArray, [i, i.CurrentFloor, i.DesiredFloor]]) #Stack information in array.\n", | |
"\n", | |
" for i in PassengerArray[1:,2]: #This loop deletes any row where the passenger's current floor is equal to their\n", | |
" if PassengerArray[i,1] == PassengerArray[i,2]: #Desired drop off.\n", | |
" PassengerArrayFinal = np.delete(PassengerArray,i,0)\n", | |
" \n", | |
" Building1 = Building(20, 0) #Generate a building object with 20 floors (from 0 to 20)\n", | |
" Elevator1 = Elevator(Building1) #Generate the elevator object\n", | |
" Elevator1.Run(PassengerArray, Building1) #Run the simulation\n", | |
" CountStorage.append(Elevator1.Counter.count(1)) #Store the counts\n", | |
" \n", | |
" Average = (sum(CountStorage)/n) #Compute the average count per simulation.\n", | |
" return Average\n", | |
"\n", | |
"AverageData1 = [] #Repeat the simulation 100 times, varying the number of passengers from 20 to 200 each time.\n", | |
"for j in range(20,200):\n", | |
" AverageData1.append(Simulation2(100,j))\n", | |
" " | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 30, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"Text(0, 0.5, 'Average Steps Taken by Elevator')" | |
] | |
}, | |
"execution_count": 30, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 921.6x633.6 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"plt.plot(range(20,200), AverageData1)\n", | |
"plt.title('Average Steps Taken by Elevator vs. # of Passengers')\n", | |
"plt.xlabel('# of Passengers')\n", | |
"plt.ylabel('Average Steps Taken by Elevator')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"\"\"\"\n", | |
"We notice slight noise in the line due to the randomness of the data. The noise is expected to decrease after\n", | |
"increasing the number of samples we average over.\n", | |
"The final trend seems to be a curve that decreases at a decreasing rate, and finally tends to a fixed value.\n", | |
"\"\"\"" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.7.3" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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