update way population speeds are set and maintained

to make room for reduced interaction scenario and custom speeds

Author: paulvangentcom

config.py

@@ -53,12 +53,12 @@ def __init__(self, *args, **kwargs):
  self.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
+ #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
  proportion_distancing = 0
- self.speed = 0.01 #TODO: look up wth this is
+ self.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 = 0.05
@@ -160,4 +160,4 @@ def set_self_isolation(self, self_isolate_proportion=0.9,
  self.x_plot = [0, 1.1]
  self.y_plot = [0, 1]
  #update whether traveling agents also infect
- self.traveling_infects = traveling_infects
+ self.traveling_infects = traveling_infects

motion.py

@@ -80,9 +80,9 @@ def out_of_bounds(population, xbounds, ybounds):
  return population
 
 
-def update_randoms(population, pop_size, heading_update_chance=0.02, 
+def update_randoms(population, Config, heading_update_chance=0.02, 
  speed_update_chance=0.02, heading_multiplication=1,
- speed_multiplication=1, speed=0.01):
+ speed_multiplication=1):
  '''updates random states such as heading and speed
  
  Function that randomized the headings and speeds for population members
@@ -115,22 +115,22 @@ def update_randoms(population, pop_size, heading_update_chance=0.02,
 
  #randomly update heading
  #x
- update = np.random.random(size=(pop_size,))
+ update = np.random.random(size=(Config.pop_size,))
  shp = update[update <= heading_update_chance].shape
  population[:,3][update <= heading_update_chance] = np.random.normal(loc = 0, 
  scale = 1/3,
  size = shp) * heading_multiplication
  #y
- update = np.random.random(size=(pop_size,))
+ update = np.random.random(size=(Config.pop_size,))
  shp = update[update <= heading_update_chance].shape
  population[:,4][update <= heading_update_chance] = np.random.normal(loc = 0, 
  scale = 1/3,
  size = shp) * heading_multiplication
  #randomize speeds
- update = np.random.random(size=(pop_size,))
+ update = np.random.random(size=(Config.pop_size,))
  shp = update[update <= heading_update_chance].shape
- population[:,5][update <= heading_update_chance] = np.random.normal(loc = speed, 
- scale = speed / 3,
+ population[:,5][update <= heading_update_chance] = np.random.normal(loc = Config.speed, 
+ scale = Config.speed / 3,
  size = shp) * speed_multiplication
 
  population[:,5] = np.clip(population[:,5], a_min=0.0001, a_max=0.05)

population.py

@@ -10,9 +10,8 @@
 
 from motion import get_motion_parameters
 
-def initialize_population(pop_size, mean_age=45, max_age=105,
- xbounds=[0, 1], ybounds=[0, 1],
- speed=0.01):
+def initialize_population(Config, mean_age=45, max_age=105,
+ xbounds=[0, 1], ybounds=[0, 1]):
  '''initialized the population for the simulation
 
  the population matrix for this simulation has the following columns:
@@ -52,37 +51,37 @@ def initialize_population(pop_size, mean_age=45, max_age=105,
  '''
 
  #initialize population matrix
- population = np.zeros((pop_size, 15))
+ population = np.zeros((Config.pop_size, 15))
 
  #initalize unique IDs
- population[:,0] = [x for x in range(pop_size)]
+ population[:,0] = [x for x in range(Config.pop_size)]
 
  #initialize random coordinates
  population[:,1] = np.random.uniform(low = xbounds[0] + 0.05, high = xbounds[1] - 0.05, 
- size = (pop_size,))
+ size = (Config.pop_size,))
  population[:,2] = np.random.uniform(low = ybounds[0] + 0.05, high = ybounds[1] - 0.05, 
- size=(pop_size,))
+ size=(Config.pop_size,))
 
  #initialize random headings -1 to 1
  population[:,3] = np.random.normal(loc = 0, scale = 1/3, 
- size=(pop_size,))
+ size=(Config.pop_size,))
  population[:,4] = np.random.normal(loc = 0, scale = 1/3, 
- size=(pop_size,))
+ size=(Config.pop_size,))
 
  #initialize random speeds
- population[:,5] = np.random.normal(speed, speed / 3)
+ population[:,5] = np.random.normal(Config.speed, Config.speed / 3)
 
  #initalize ages
  std_age = (max_age - mean_age) / 3
  population[:,7] = np.int32(np.random.normal(loc = mean_age, 
  scale = std_age, 
- size=(pop_size,)))
+ size=(Config.pop_size,)))
 
  population[:,7] = np.clip(population[:,7], a_min = 0, 
  a_max = max_age) #clip those younger than 0 years
 
  #build recovery_vector
- population[:,9] = np.random.normal(loc = 0.5, scale = 0.5 / 3, size=(pop_size,))
+ population[:,9] = np.random.normal(loc = 0.5, scale = 0.5 / 3, size=(Config.pop_size,))
 
  return population
 

simulation.py

@@ -18,7 +18,7 @@
 from visualiser import build_fig, draw_tstep, set_style
 
 #set seed for reproducibility
-np.random.seed(100)
+#np.random.seed(100)
 
 class Simulation():
  #TODO: if lockdown or otherwise stopped: destination -1 means no motion
@@ -42,7 +42,7 @@ def __init__(self, *args, **kwargs):
 
  def population_init(self):
  '''(re-)initializes population'''
- self.population = initialize_population(self.Config.pop_size, self.Config.mean_age, 
+ self.population = initialize_population(self.Config, self.Config.mean_age, 
  self.Config.max_age, self.Config.xbounds, 
  self.Config.ybounds)
 
@@ -88,10 +88,10 @@ def tstep(self):
  self.population[:,5][self.Config.lockdown_vector == 0] = 0
  else:
  #update randoms
- self.population = update_randoms(self.population, self.Config.pop_size, self.Config.speed)
+ self.population = update_randoms(self.population, self.Config)
  else:
  #update randoms
- self.population = update_randoms(self.population, self.Config.pop_size, self.Config.speed)
+ self.population = update_randoms(self.population, self.Config)
 
  #for dead ones: set speed and heading to 0
  self.population[:,3:5][self.population[:,6] == 3] = 0