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config.py
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config.py
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'''
file that contains all configuration related methods and classes
'''
import numpy as np
class config_error(Exception):
pass
class Configuration():
def __init__(self, *args, **kwargs):
#simulation variables
self.verbose = kwargs.get('verbose', True) #whether to print infections, recoveries and fatalities to the terminal
self.simulation_steps = kwargs.get('simulation_steps', 10000) #total simulation steps performed
self.tstep = kwargs.get('tstep', 0) #current simulation timestep
self.save_data = kwargs.get('save_data', False) #whether to dump data at end of simulation
self.save_pop = kwargs.get('save_pop', False) #whether to save population matrix every 'save_pop_freq' timesteps
self.save_pop_freq = kwargs.get('save_pop_freq', 10) #population data will be saved every 'n' timesteps. Default: 10
self.save_pop_folder = kwargs.get('save_pop_folder', 'pop_data/') #folder to write population timestep data to
self.endif_no_infections = kwargs.get('endif_no_infections', True) #whether to stop simulation if no infections remain
self.world_size = kwargs.get('world_size', [2, 2]) #x and y sizes of the world
#scenario flags
self.traveling_infects = kwargs.get('traveling_infects', False)
self.self_isolate = kwargs.get('self_isolate', False)
self.lockdown = kwargs.get('lockdown', False)
self.lockdown_percentage = kwargs.get('lockdown_percentage', 0.1) #after this proportion is infected, lock-down begins
self.lockdown_compliance = kwargs.get('lockdown_compliance', 0.95) #fraction of the population that will obey the lockdown
#visualisation variables
self.visualise = kwargs.get('visualise', True) #whether to visualise the simulation
self.plot_mode = kwargs.get('plot_mode', 'sir') #default or sir
#size of the simulated world in coordinates
self.x_plot = kwargs.get('x_plot', [0, self.world_size[0]])
self.y_plot = kwargs.get('y_plot', [0, self.world_size[1]])
self.save_plot = kwargs.get('save_plot', False)
self.plot_path = kwargs.get('plot_path', 'render/') #folder where plots are saved to
self.plot_style = kwargs.get('plot_style', 'default') #can be default, dark, ...
self.colorblind_mode = kwargs.get('colorblind_mode', False)
#if colorblind is enabled, set type of colorblindness
#available: deuteranopia, protanopia, tritanopia. defauld=deuteranopia
self.colorblind_type = kwargs.get('colorblind_type', 'deuteranopia')
#world variables, defines where population can and cannot roam
self.xbounds = kwargs.get('xbounds', [self.x_plot[0] + 0.02, self.x_plot[1] - 0.02])
self.ybounds = kwargs.get('ybounds', [self.y_plot[0] + 0.02, self.y_plot[1] - 0.02])
#population variables
self.pop_size = kwargs.get('pop_size', 2000)
self.mean_age = kwargs.get('mean_age', 45)
self.max_age = kwargs.get('max_age', 105)
self.age_dependent_risk = kwargs.get('age_dependent_risk', True) #whether risk increases with age
self.risk_age = kwargs.get('risk_age', 55) #age where mortality risk starts increasing
self.critical_age = kwargs.get('critical_age', 75) #age at and beyond which mortality risk reaches maximum
self.critical_mortality_chance = kwargs.get('critical_mortality_chance', 0.1) #maximum mortality risk for older age
self.risk_increase = kwargs.get('risk_increase', 'quadratic') #whether risk between risk and critical age increases 'linear' or 'quadratic'
#movement variables
#mean_speed = 0.01 # the mean speed (defined as heading * speed)
#std_speed = 0.01 / 3 #the standard deviation of the speed parameter
#the proportion of the population that practices social distancing, simulated
#by them standing still
self.proportion_distancing = kwargs.get('proportion_distancing', 0)
self.speed = kwargs.get('speed', 0.01) #average speed of population
#when people have an active destination, the wander range defines the area
#surrounding the destination they will wander upon arriving
self.wander_range = kwargs.get('wander_range', 0.05)
self.wander_factor = kwargs.get('wander_factor', 1)
self.wander_factor_dest = kwargs.get('wander_factor_dest', 1.5) #area around destination
#infection variables
self.infection_range = kwargs.get('infection_range', 0.01) #range surrounding sick patient that infections can take place
self.infection_chance = kwargs.get('infection_chance', 0.03) #chance that an infection spreads to nearby healthy people each tick
self.recovery_duration = kwargs.get('recovery_duration', (200, 500)) #how many ticks it may take to recover from the illness
self.mortality_chance = kwargs.get('mortality_chance', 0.02) #global baseline chance of dying from the disease
#healthcare variables
self.healthcare_capacity = kwargs.get('healthcare_capacity', 300) #capacity of the healthcare system
self.treatment_factor = kwargs.get('treatment_factor', 0.5) #when in treatment, affect risk by this factor
self.no_treatment_factor = kwargs.get('no_treatment_factor', 3) #risk increase factor to use if healthcare system is full
#risk parameters
self.treatment_dependent_risk = kwargs.get('treatment_dependent_risk', True) #whether risk is affected by treatment
#self isolation variables
self.self_isolate_proportion = kwargs.get('self_isolate_proportion', 0.6)
self.isolation_bounds = kwargs.get('isolation_bounds', [0.02, 0.02, 0.1, 0.98])
#lockdown variables
self.lockdown_percentage = kwargs.get('lockdown_percentage', 0.1)
self.lockdown_vector = kwargs.get('lockdown_vector', [])
def get_palette(self):
'''returns appropriate color palette
Uses config.plot_style to determine which palette to pick,
and changes palette to colorblind mode (config.colorblind_mode)
and colorblind type (config.colorblind_type) if required.
Palette colors are based on
https://venngage.com/blog/color-blind-friendly-palette/
'''
#palette colors are: [healthy, infected, immune, dead]
palettes = {'regular': {'default': ['gray', 'red', 'green', 'black'],
'dark': ['#404040', '#ff0000', '#00ff00', '#000000']},
'deuteranopia': {'default': ['gray', '#a50f15', '#08519c', 'black'],
'dark': ['#404040', '#fcae91', '#6baed6', '#000000']},
'protanopia': {'default': ['gray', '#a50f15', '08519c', 'black'],
'dark': ['#404040', '#fcae91', '#6baed6', '#000000']},
'tritanopia': {'default': ['gray', '#a50f15', '08519c', 'black'],
'dark': ['#404040', '#fcae91', '#6baed6', '#000000']}
}
if self.colorblind_mode:
return palettes[self.colorblind_type.lower()][self.plot_style]
else:
return palettes['regular'][self.plot_style]
def get(self, key):
'''gets key value from config'''
try:
return self.__dict__[key]
except:
raise config_error('key %s not present in config' %key)
def set(self, key, value):
'''sets key value in config'''
self.__dict__[key] = value
def read_from_file(self, path):
'''reads config from filename'''
#TODO: implement
pass
def set_lockdown(self, lockdown_percentage=0.1, lockdown_compliance=0.9):
'''sets lockdown to active'''
self.lockdown = True
#fraction of the population that will obey the lockdown
self.lockdown_percentage = lockdown_percentage
self.lockdown_vector = np.zeros((self.pop_size,))
#lockdown vector is 1 for those not complying
self.lockdown_vector[np.random.uniform(size=(self.pop_size,)) >= lockdown_compliance] = 1
def set_self_isolation(self, self_isolate_proportion=0.9,
isolation_bounds = [0.02, 0.02, 0.09, 0.98],
traveling_infects=False):
'''sets self-isolation scenario to active'''
self.self_isolate = True
self.isolation_bounds = isolation_bounds
self.self_isolate_proportion = self_isolate_proportion
#set roaming bounds to outside isolated area
self.xbounds = [0.1, 1.1]
self.ybounds = [0.02, 0.98]
#update plot bounds everything is shown
self.x_plot = [0, 1.1]
self.y_plot = [0, 1]
#update whether traveling agents also infect
self.traveling_infects = traveling_infects
def set_reduced_interaction(self, speed = 0.001):
'''sets reduced interaction scenario to active'''
self.speed = speed
def set_demo(self, destinations, population):
#make C
#first leg
destinations[:,0][0:100] = 0.05
destinations[:,1][0:100] = 0.7
population[:,13][0:100] = 0.01
population[:,14][0:100] = 0.05
#Top
destinations[:,0][100:200] = 0.1
destinations[:,1][100:200] = 0.75
population[:,13][100:200] = 0.05
population[:,14][100:200] = 0.01
#Bottom
destinations[:,0][200:300] = 0.1
destinations[:,1][200:300] = 0.65
population[:,13][200:300] = 0.05
population[:,14][200:300] = 0.01
#make O
#first leg
destinations[:,0][300:400] = 0.2
destinations[:,1][300:400] = 0.7
population[:,13][300:400] = 0.01
population[:,14][300:400] = 0.05
#Top
destinations[:,0][400:500] = 0.25
destinations[:,1][400:500] = 0.75
population[:,13][400:500] = 0.05
population[:,14][400:500] = 0.01
#Bottom
destinations[:,0][500:600] = 0.25
destinations[:,1][500:600] = 0.65
population[:,13][500:600] = 0.05
population[:,14][500:600] = 0.01
#second leg
destinations[:,0][600:700] = 0.3
destinations[:,1][600:700] = 0.7
population[:,13][600:700] = 0.01
population[:,14][600:700] = 0.05
#make V
#First leg
destinations[:,0][700:800] = 0.35
destinations[:,1][700:800] = 0.7
population[:,13][700:800] = 0.01
population[:,14][700:800] = 0.05
#Bottom
destinations[:,0][800:900] = 0.4
destinations[:,1][800:900] = 0.65
population[:,13][800:900] = 0.05
population[:,14][800:900] = 0.01
#second leg
destinations[:,0][900:1000] = 0.45
destinations[:,1][900:1000] = 0.7
population[:,13][900:1000] = 0.01
population[:,14][900:1000] = 0.05
#Make I
#leg
destinations[:,0][1000:1100] = 0.5
destinations[:,1][1000:1100] = 0.7
population[:,13][1000:1100] = 0.01
population[:,14][1000:1100] = 0.05
#I dot
destinations[:,0][1100:1200] = 0.5
destinations[:,1][1100:1200] = 0.8
population[:,13][1100:1200] = 0.01
population[:,14][1100:1200] = 0.01
#make D
#first leg
destinations[:,0][1200:1300] = 0.55
destinations[:,1][1200:1300] = 0.67
population[:,13][1200:1300] = 0.01
population[:,14][1200:1300] = 0.03
#Top
destinations[:,0][1300:1400] = 0.6
destinations[:,1][1300:1400] = 0.75
population[:,13][1300:1400] = 0.05
population[:,14][1300:1400] = 0.01
#Bottom
destinations[:,0][1400:1500] = 0.6
destinations[:,1][1400:1500] = 0.65
population[:,13][1400:1500] = 0.05
population[:,14][1400:1500] = 0.01
#second leg
destinations[:,0][1500:1600] = 0.65
destinations[:,1][1500:1600] = 0.7
population[:,13][1500:1600] = 0.01
population[:,14][1500:1600] = 0.05
#dash
destinations[:,0][1600:1700] = 0.725
destinations[:,1][1600:1700] = 0.7
population[:,13][1600:1700] = 0.03
population[:,14][1600:1700] = 0.01
#Make 1
destinations[:,0][1700:1800] = 0.8
destinations[:,1][1700:1800] = 0.7
population[:,13][1700:1800] = 0.01
population[:,14][1700:1800] = 0.05
#Make 9
#right leg
destinations[:,0][1800:1900] = 0.91
destinations[:,1][1800:1900] = 0.675
population[:,13][1800:1900] = 0.01
population[:,14][1800:1900] = 0.08
#roof
destinations[:,0][1900:2000] = 0.88
destinations[:,1][1900:2000] = 0.75
population[:,13][1900:2000] = 0.035
population[:,14][1900:2000] = 0.01
#middle
destinations[:,0][2000:2100] = 0.88
destinations[:,1][2000:2100] = 0.7
population[:,13][2000:2100] = 0.035
population[:,14][2000:2100] = 0.01
#left vertical leg
destinations[:,0][2100:2200] = 0.86
destinations[:,1][2100:2200] = 0.72
population[:,13][2100:2200] = 0.01
population[:,14][2100:2200] = 0.01
###################
##### ROW TWO #####
###################
#S
#first leg
destinations[:,0][2200:2300] = 0.115
destinations[:,1][2200:2300] = 0.5
population[:,13][2200:2300] = 0.01
population[:,14][2200:2300] = 0.03
#Top
destinations[:,0][2300:2400] = 0.15
destinations[:,1][2300:2400] = 0.55
population[:,13][2300:2400] = 0.05
population[:,14][2300:2400] = 0.01
#second leg
destinations[:,0][2400:2500] = 0.2
destinations[:,1][2400:2500] = 0.45
population[:,13][2400:2500] = 0.01
population[:,14][2400:2500] = 0.03
#middle
destinations[:,0][2500:2600] = 0.15
destinations[:,1][2500:2600] = 0.48
population[:,13][2500:2600] = 0.05
population[:,14][2500:2600] = 0.01
#bottom
destinations[:,0][2600:2700] = 0.15
destinations[:,1][2600:2700] = 0.41
population[:,13][2600:2700] = 0.05
population[:,14][2600:2700] = 0.01
#Make I
#leg
destinations[:,0][2700:2800] = 0.25
destinations[:,1][2700:2800] = 0.45
population[:,13][2700:2800] = 0.01
population[:,14][2700:2800] = 0.05
#I dot
destinations[:,0][2800:2900] = 0.25
destinations[:,1][2800:2900] = 0.55
population[:,13][2800:2900] = 0.01
population[:,14][2800:2900] = 0.01
#M
#Top
destinations[:,0][2900:3000] = 0.37
destinations[:,1][2900:3000] = 0.5
population[:,13][2900:3000] = 0.07
population[:,14][2900:3000] = 0.01
#Left leg
destinations[:,0][3000:3100] = 0.31
destinations[:,1][3000:3100] = 0.45
population[:,13][3000:3100] = 0.01
population[:,14][3000:3100] = 0.05
#Middle leg
destinations[:,0][3100:3200] = 0.37
destinations[:,1][3100:3200] = 0.45
population[:,13][3100:3200] = 0.01
population[:,14][3100:3200] = 0.05
#Right leg
destinations[:,0][3200:3300] = 0.43
destinations[:,1][3200:3300] = 0.45
population[:,13][3200:3300] = 0.01
population[:,14][3200:3300] = 0.05
#set all destinations active
population[:,11] = 1