Skip to content
This repository has been archived by the owner on Mar 28, 2022. It is now read-only.

Latest commit

 

History

History
104 lines (58 loc) · 2.01 KB

PLAN.md

File metadata and controls

104 lines (58 loc) · 2.01 KB

Overview

File Structure

MAIN.py

SIMULATION.py

PLOT.py

ANIMATION.py

Classes

SubPopulationSim(W, H, Pdeath, Precovery, Preinfiction, Ptravel, Pquarantine, cityname):
"The grid of people with SIR, location and probability states"	

	__init__(grid size, initial infected, inital vaccinated, initial empty):
	
	self.size = grid size
	self.grid = Initialise grid with all Susceptible (np.zeros)
	self.day = 0
	- probability of someone 'leaving the grid' and infecting another grid
	self.vaccinated = ??
    
    initialinfection(self, num):
    
    
    emptyspace():
    'randomly select grid points to be empty'
    
    vaccinate():
    'randomly vaccinate num of people'
    - V for vaccinated
    
	updatePopulation():
	'determines SIR states after t+=1 day'
	- loops through every point on grid, and changes SIR status based on
    	 adjacent points, using updatePerson()
	
	
	updatePerson():
	'updates a single grid point'
	- if infected, either recover, else: die, or stay infected
	- if susceptible, probability of being infected depends on adjacent points, and other population
        - use indexing to determine status of adjacent point 
    - the grid point takes new value S,I,R,D,Q
    
    updateProbability:
        - To index and find probability of infection for partcular point

PopulationSim(cityNum, cityNames):


GridPlot()


LinePlot()


Animation():
'combines different animations together'
    __init__:
    self.fig = create figure
    self.axes = create axes
    
    


GridAnimation(SubPopulationSim)

    __init__:
    self.size = SubPopulationSim.size
    self.grid = SubPopulationSim.grid
    self.day = 


LineAnimation()

Functions

Arguments

import argsparse

define all our arguments: size (NxN) probabilities