我有一个任务，我们必须模拟疾病的传播，它几乎可以正常工作，除非被感染的人死亡时它会删除2个被感染的人，并且只会增加1个死亡，我添加了fixInfected模块来尝试解决它，但这也没有用达到预期的效果（最终我获得的人数基本上比开始时多了100人）
import numpy as np
import random
#Inputs
#Option for using Moore or Von Neumann neighbourhoods (Von Neumann is default)
moore = input("Use Moore Neighbourhoods? (Y/N): ")
#Input for probability of an uninfected person getting infected
probInfect = input("Enter the probability of an uninfected becoming infected: ")
#Make sure input is a float
try:
probInfect = float(probInfect)
except:
probInfect = float(0.5)
#Make sure probability is < 1
if probInfect > 1:
probInfect = probInfect/10
#Input for probability of an infected person recovering (if they don't recover they die)
probRecover = input("Enter the probability of an infected person recovering: ")
#Make sure input is a float
try:
probRecover = float(probRecover)
except:
probRecover = float(0.5)
#Make sure probability is < 1
if probRecover > 1:
probRecover = probRecover/10
#Input the probability of an infected person dying
probDie = input("Enter the probability of an infected person dying: ")
#Make sure input is a float
try:
probDie = float(probDie)
except:
probDie = float(0.5)
#Make sure probability is < 1
if probDie > 1:
probDie = probDie/10
#Input the person of a recovering person to become immune
probImmune = input("Enter the probability of a recovering person becoming immune: ")
#Make sure input is a float
try:
probImmune = float(probImmune)
except:
probImmune = float(0.5)
#Make sure probability is < 1
if probImmune > 1:
probImmune = probImmune/10
#Initialize
INIT_POP = 100
INIT_INFECTED = 5
NUM_COLS = 15
NUM_ROWS = 10
NUM_STEPS = 10
infected = np.zeros((NUM_ROWS, NUM_COLS), dtype=np.int)
uninfected = np.zeros((NUM_ROWS, NUM_COLS), dtype=np.int)
dead = np.zeros((NUM_ROWS, NUM_COLS), dtype=np.int)
recovering = np.zeros((NUM_ROWS, NUM_COLS), dtype=np.int)
immune = np.zeros((NUM_ROWS, NUM_COLS), dtype=np.int)
#Defining Modules
def distribute(grid, num_r, num_c, numpeep):
for i in range(numpeep):
rpos = random.randint(0, num_r-1)
cpos = random.randint(0, num_c-1)
grid[rpos, cpos] += 1
def makeScatter(grid, num_r, num_c):
r_values = []
c_values = []
count_values = []
for row in range(num_r):
for col in range(num_c):
if grid[row,col] > 0:
r_values.append(row)
c_values.append(col)
count_values.append(grid[row,col]*100)
return(r_values, c_values, count_values)
def displayGrid(grid, num_r, num_c):
for row in range(num_r-1, -1, -1):
for col in range(num_c):
print(grid[row,col], end=" ")
print()
def movePeeps(cur, next, r, c, dead):
for peep in range(cur[r,c]):
if moore == "Y":
rMove = random.randint(-1,1)
cMove = random.randint(-1,1)
else:
direction = random.randint(1,4)
if direction%2 == 1:
rMove = random.randint(-1,1)
cMove = 0
else:
cMove = random.randint(-1,1)
rMove = 0
if (r + rMove) > (NUM_ROWS-1) or (r + rMove) < 0:
rMove = 0
if (c + cMove) > (NUM_COLS-1) or (c + cMove) < 0:
cMove = 0
if dead == 0:
next[r + rMove, c + cMove] +=1
else:
next[r,c] +=1
def infect(inf, notinf, r, c, prob):
prob = prob * inf[r,c]
if prob:
for peep in range(notinf[r,c]):
if random.random() < prob:
inf[r, c] +=1
notinf[r, c] -=1
print("***** New infection (", r, ",", c, ")")
def fixInfected(infected, uninfected, dead, recovering, immune, INIT_POP, INIT_INFECTED, r, c):
#Replaces infected that were removed and not added due to error
if sum(sum(infected))+sum(sum(uninfected))+sum(sum(dead))+sum(sum(recovering))+sum(sum(immune)) != INIT_POP + INIT_INFECTED:
Sum = (sum(sum(infected))+sum(sum(uninfected))+sum(sum(dead))+sum(sum(recovering))+sum(sum(immune)))
errDif = (INIT_POP+INIT_INFECTED)-Sum
print("errDif is: ", errDif)
infected[r, c] =+ errDif
def failedRecovery(inf, recovering, r, c, prob):
prob = prob * inf[r,c]
if prob:
for peep in range(recovering[r,c]):
if random.random() < prob:
inf[r, c] +=1
recovering[r, c] -= 1
print("***** New infection (", r, ",", c, ")")
def recover(inf, recover, r, c, prob):
prob = prob * inf[r,c]
if prob:
for peep in range(inf[r,c]):
if random.random() < prob:
recover[r,c] +=1
inf[r,c] =-1
print("***** New Recovery (", r, ",", c, ")")
def die(inf, dead, r, c, prob):
prob = prob * inf[r,c]
if prob:
for peep in range(inf[r,c]):
if random.random() < prob:
dead[r,c] +=1
inf[r,c] =-1
print("***** New Death (", r, ",", c, ")")
def immunity(recover, immune, r, c, prob):
prob = prob * recover[r,c]
if prob:
for peep in range(recover[r,c]):
if random.random() < probImmune:
immune[r,c] +=1
recovering[r,c] -=1
print("***** New Immunity (", r,",", c, ")")
distribute(infected, NUM_ROWS, NUM_COLS, INIT_INFECTED)
distribute(uninfected, NUM_ROWS, NUM_COLS, INIT_POP)
for timestep in range(NUM_STEPS):
print("\n###################### TIMESTEP", timestep, "#####################\n")
print("Sim Report: ")
print("Number of infected: ", sum(sum(infected)))
print("Number of uninfected: ", sum(sum(uninfected)))
print("Number of deaths: ", sum(sum(dead)))
print("Number of recovering:", sum(sum(recovering)))
print("Number of immune:", sum(sum(immune)))
infected2 = np.zeros((NUM_ROWS, NUM_COLS), dtype=np.int)
uninfected2 = np.zeros((NUM_ROWS, NUM_COLS), dtype=np.int)
dead2 = np.zeros((NUM_ROWS, NUM_COLS), dtype=np.int)
recovering2 = np.zeros((NUM_ROWS, NUM_COLS), dtype=np.int)
immune2 = np.zeros((NUM_ROWS, NUM_COLS), dtype=np.int)
for row in range(NUM_ROWS):
for col in range(NUM_COLS):
infect(infected, uninfected, row, col, probInfect)
recover(infected, recovering, row, col, probRecover)
die(infected, dead, row, col, probDie)
immunity(recovering, immune, row, col, probImmune)
failedRecovery(infected, recovering, row, col, (1 - probRecover))
fixInfected(infected, uninfected, dead, recovering, immune, INIT_POP, INIT_INFECTED, row, col)
movePeeps(infected, infected2, row, col, 0)
movePeeps(uninfected, uninfected2, row, col, 0)
movePeeps(recovering, recovering2, row, col, 0)
movePeeps(immune, immune2, row, col, 0)
movePeeps(dead, dead2, row, col, 1)
infected = infected2
uninfected = uninfected2
dead = dead2
recovering = recovering2
immune = immune2
print("Sim Report: ")
print("Number of infected: ", np.sum(infected))
print("Number of uninfected: ", np.sum(uninfected))
print("Number of deaths: ", np.sum(dead))
print("Number of recovering:", np.sum(recovering))
print("Number of immune:", np.sum(immune))
print("Done")
答案 0 :(得分：1)
在不花太多时间研究代码的情况下，我认为第149和158行有错别字。他们应该说：
inf[r,c] -= 1
答案 1 :(得分：0)
inf[r,c] =-1
应该是
inf[r,c] -= 1
和
#Make sure probability is < 1
if probDie > 1:
probDie = probDie/10
应该是
#Make sure probability is < 1
if probDie > 1:
probDie = probDie/100
如果要处理以百分比形式给出的值