219 lines
6.9 KiB
Python
219 lines
6.9 KiB
Python
import matplotlib.pyplot as plt
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import matplotlib.colors
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import numpy as np
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import random
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from enum import IntEnum
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class Model:
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def __init__(self, width=32, height=32, humandens=0.15, mosquitodens=0.10,
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immunepct=0.1, mosqinfpct=0.1, hm_infpct=0.5, mh_infpct=0.5,
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hinfdiepct=0.01, mhungrypct=0.1, humandiepct=10**-3,
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mosqdiepct=10**-3, mosqnetdens=0.05, time_steps=2000):
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plt.ion()
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self.width = width
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self.height = height
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# The percentage of tiles that start as humans
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self.humandens = humandens
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# The percentage of tiles that contain mosquitos
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self.mosquitodens = mosquitodens
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# Percentage of humans that are immune
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self.immunepct = immunepct
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# Chance for a mosquito to be infectuous
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self.mosqinfpct = mosqinfpct
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# Chance for a human to be infected by a mosquito bite
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self.hm_infpct = hm_infpct
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# Chance for a mosquito to be infected from biting an infected human
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self.mh_infpct = mh_infpct
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# Chance that an infected human dies
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self.hinfdiepct = hinfdiepct
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# Chance for a mosquito to be hungry
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self.mhungrypct = mhungrypct
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# Chance for human to die from random causes
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self.humandiepct = humandiepct
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# Chance for a mosquito to die
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self.mosqdiepct = mosqdiepct
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# Percentage of tiles that contain mosquito nets
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self.mosqnetdens = mosqnetdens
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# The number of timesteps to run te simulation for
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self.time_steps = time_steps
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self.grid = self.gen_humans()
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self.mosquitos = self.gen_mosquitos()
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self.init_draw()
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def init_draw(self):
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self.colors = matplotlib.colors.ListedColormap(
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["black", "green", "red", "yellow"])
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bounds = [Human.DEAD, Human.HEALTHY, Human.INFECTED, Human.IMMUNE]
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self.norm = matplotlib.colors.BoundaryNorm(bounds, self.colors.N)
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def recycle_human(self):
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# Get all living humans
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humans = np.transpose(np.where(self.grid != Human.DEAD))
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# Get a mask of humans to kill
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deaths = np.random.rand(len(humans)) < self.humandiepct
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# Kill them.
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self.grid[humans[deaths][:, 0], humans[deaths][:, 1]] = Human.DEAD
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# get num humans after killing
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humans_survive = len(np.transpose(np.where(self.grid != Human.DEAD)))
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death_count = len(humans) - humans_survive
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# Pick a random, unpopulated spot
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births = np.array(random.sample(list(np.transpose(np.where(self.grid == Human.DEAD))),
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death_count))
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# Deliver the newborns
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for birth in births:
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self.grid[birth[0]][birth[1]] = np.random.choice([Human.HEALTHY, Human.IMMUNE],
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p=[1-self.immunepct, self.immunepct])
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def do_malaria(self):
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"""
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This function determines who of the infected dies from their illness
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"""
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# Get all infected humans
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infected = np.transpose(np.where(self.grid == Human.INFECTED))
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# Decide which infected people die
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deaths = np.random.rand(len(infected)) < self.hinfdiepct
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# Now let's kill them
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self.grid[infected[deaths][:, 0], infected[deaths][:, 1]] = Human.DEAD
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def get_movementbox(self, x, y):
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"""
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Returns indices of a moore neighbourhood around the given index
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"""
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x_min = (x - 1)
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x_max = (x + 1)
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y_min = (y - 1)
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y_max = (y + 1)
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indices = [(i % self.width, j % self.height) for i in range(x_min, x_max + 1)
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for j in range(y_min, y_max + 1)]
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# remove current location from the indices
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indices.remove((x, y))
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return indices
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def move_mosquitos(self):
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for mosq in self.mosquitos:
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# get the movement box for every mosquito
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movement = self.get_movementbox(mosq.x, mosq.y)
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# choose random new position
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new_pos = random.choice(movement)
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mosq.x = new_pos[0]
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mosq.y = new_pos[1]
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def gen_humans(self):
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"""
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Fill the grid with humans that can either be healthy or infected
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"""
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# Calculate the probabilities
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p_dead = 1 - self.humandens
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p_immune = self.humandens * self.immunepct
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p_healthy = self.humandens - p_immune
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# Create the grid with humans.
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return np.random.choice((Human.DEAD, Human.HEALTHY, Human.IMMUNE),
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size=(self.width, self.height),
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p=(p_dead, p_healthy, p_immune))
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def gen_mosquitos(self):
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"""
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Generate the list of mosquitos
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"""
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mosquitos = []
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count = int(self.width * self.height * self.mosquitodens)
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# generate random x and y coordinates
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xs = np.random.randint(0, self.width, count)
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ys = np.random.randint(0, self.height, count)
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coords = list(zip(xs, ys))
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# generate the mosquitos
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for coord in coords:
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# determine if the mosquito is infected
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infected = random.uniform(0, 1) < self.mosqinfpct
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# determine if the mosquito starts out hungry
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hungry = random.uniform(0, 1) < self.mhungrypct
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mosquitos.append(Mosquito(coord[0], coord[1], infected, hungry))
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return mosquitos
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def run(self):
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"""
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This functions runs the simulation
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"""
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for t in range(self.time_steps):
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self.step()
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self.draw(t)
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def step(self):
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"""
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Step through a timestep of the simulation
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"""
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# check who dies from malaria
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self.do_malaria()
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# check if people die from other causes
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self.recycle_human()
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# move mosquitos
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self.move_mosquitos()
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def draw(self, t: int):
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# this function draws the humans
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plt.title("t={}".format(t))
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# draw the grid
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plt.imshow(self.grid, cmap=self.colors, norm=self.norm)
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# draw mosquitos
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for mos in self.mosquitos:
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plt.plot(mos.x, mos.y, mos.get_color()+mos.get_shape())
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plt.pause(0.0001)
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plt.clf()
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class Mosquito:
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def __init__(self, x: int, y: int, infected: bool, hungry: bool):
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self.x = x
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self.y = y
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self.infected = infected
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self.hungry = hungry
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def get_color(self):
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# returns the color for drawing, red if infected blue otherwise
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return "r" if self.infected else "b"
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def get_shape(self):
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# return the shape for drawing, o if hungry + otherwise
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return "o" if self.hungry else "+"
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class Human(IntEnum):
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DEAD = 0
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HEALTHY = 1
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INFECTED = 2
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IMMUNE = 3
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if __name__ == "__main__":
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model = Model()
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model.run()
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