people now die randomly

malaria.py

@@ -8,7 +8,7 @@ from enum import IntEnum
 class Model:
     def __init__(self, width=32, height=32, humandens=0.15, mosquitodens=0.10,
                  immunepct=0.1, mosqinfpct=0.1, hm_infpct=0.5, mh_infpct=0.5,
-                 hinfdiepct=0.01, mhungrypct=0.1, humandiepct=10**-6,
+                 hinfdiepct=0.01, mhungrypct=0.1, humandiepct=10**-3,
                  mosqdiepct=10**-3, mosqnetdens=0.05, time_steps=2000):
         
         plt.ion()
@@ -40,7 +40,7 @@ class Model:
         # The number of timesteps to run te simulation for
         self.time_steps = time_steps
 
-        self.humans = self.gen_humans()
+        self.grid = self.gen_humans()
         self.mosquitos = self.gen_mosquitos()
         self.init_draw()
        
@@ -52,31 +52,41 @@ class Model:
 
     def recycle_human(self):
         # Get all living humans
-        humans = np.transpose(np.where(self.humans != Human.DEAD))
+        humans = np.transpose(np.where(self.grid != Human.DEAD))
 
         # Get a mask of humans to kill
         deaths = np.random.rand(len(humans)) < self.humandiepct
 
         # Kill them.
-        self.humans[humans[deaths][:, 0], humans[deaths][:, 1]] = Human.DEAD
+        self.grid[humans[deaths][:, 0], humans[deaths][:, 1]] = Human.DEAD
+
+        # get num humans after killing
+        humans_survive = len(np.transpose(np.where(self.grid != Human.DEAD)))
+
+        death_count = len(humans) - humans_survive
+
 
         # Pick a random, unpopulated spot
-        x, y = random.choice(np.transpose(np.where(self.humans == Human.DEAD)),
-                             size=np.count_nonzero(deaths))
+        births = np.array(random.sample(list(np.transpose(np.where(self.grid == Human.DEAD))),
+                                        death_count))
 
+        # Deliver the newborns
+        for birth in births:
+            self.grid[birth[0]][birth[1]] = np.random.choice([Human.HEALTHY, Human.IMMUNE], 
+                                                                p=[1-self.immunepct, self.immunepct])
 
     def do_malaria(self):
         """
         This function determines who of the infected dies from their illness
         """
         # Get all infected humans
-        infected = np.transpose(np.where(self.humans == Human.INFECTED))
+        infected = np.transpose(np.where(self.grid == Human.INFECTED))
 
         # Decide which infected people die
         deaths = np.random.rand(len(infected)) < self.hinfdiepct
 
         # Now let's kill them
-        self.humans[infected[deaths][:, 0], infected[deaths][:, 1]] = Human.DEAD
+        self.grid[infected[deaths][:, 0], infected[deaths][:, 1]] = Human.DEAD
 
     def gen_humans(self):
         # Calculate the probabilities
@@ -98,12 +108,13 @@ class Model:
             self.draw(t)
 
     def step(self):
-        self.do_malaria()
+        # self.do_malaria()
+        self.recycle_human()
 
     def draw(self, t):
         # this function draws the humans
         plt.title("t={}".format(t))
-        plt.imshow(self.humans, cmap=self.colors, norm=self.norm)
+        plt.imshow(self.grid, cmap=self.colors, norm=self.norm)
 
         plt.pause(0.0001)
         plt.clf()