जुड़े हुए ढांचे का ह्रास

#   /
w_size = 1024 * 32

#  ,        max_conn 
max_conn = 6

#    ,  ,    .. 
#            
infection_probably = 0.9

#    ,  ,
#     ..    
pr_recover = 0.75

#       .
#       
# ..  /,         
#    
quarantine = 5

#        -  
dead = 14

import numpy as np
from tqdm import tqdm
import matplotlib
import matplotlib.pyplot as plt
from termcolor import colored

l_immun = []
l_quar = []
l_died =[]
l_infl = []

map_conn = []

#    . =0 , >0   <quarantine  
#   , >quarantine  , >dead - 
# <0 -    / 
map_stat = np.zeros((w_size), dtype="int16")

#        .
# .. map_conn[i] -        i
for i in range(w_size):
    map_conn.append([])
    
for i in tqdm(range(w_size)):
    t = np.random.randint(0, max_conn//2)
    tt = np.random.randint(0, w_size, (t))
    for j in tt:
        map_conn[i].append(j)
        map_conn[j].append(i)

for i in range(w_size):
    map_conn[i] = list(set(map_conn[i]))    

# ,     max_conn .
#       max_conn//2 ,
#   .

#  .  0  ,  <0 ,   
#    
#  >0  /,  >quarantine,   
#  >dead  , .
map_stat[:] = 0
#    

map_stat[np.random.randint(1, w_size)] = 1
#   ,   .

day = 1

while True:

    tmp_map_conn = map_conn.copy()
    tmp_map_stat = map_stat.copy()
#        
#    

    for i in range(w_size):
#      ,  -  - 
        if tmp_map_stat[i] < 0:
            map_stat[i] = tmp_map_stat[i]
            continue

#        quarantine  /
#     1
        if tmp_map_stat[i] >= quarantine:
            map_stat[i] = tmp_map_stat[i] + 1
            continue

#        quarantine  /
#      pr_recover
#       
        if tmp_map_stat[i] > 0:
            if np.random.rand() < pr_recover:
                map_stat[i] = -tmp_map_stat[i]
            else:
                map_stat[i] = tmp_map_stat[i] + 1
#      quarantine ,
#          
#          
                if map_stat[i] >= quarantine:
                    for j in tmp_map_conn[i]:
                        if i in map_conn[j]:
                            map_conn[j].remove(i)
                    map_conn[i] = []
            continue

#   ,       
#    infection_probably
        if tmp_map_stat[i] == 0:
            map_stat[i] = 0
            for j in tmp_map_conn[i]:
                t = np.random.rand()
                if (
                    t < infection_probably
                    and tmp_map_stat[j] > 0
                    and tmp_map_stat[j] < quarantine
                ):
                    map_stat[i] = 1
                    break

#     0,  0  quarantine
#  quarantine  dead 
    immun = np.count_nonzero(map_stat < 0)
    quar = np.count_nonzero((map_stat >= quarantine) & (map_stat < dead))
    died = np.count_nonzero(map_stat >= dead)
    infl = np.sum((map_stat > 0) & (map_stat < dead))
    print(
        "day {0:3d}   infected {1:6d}   recovered {2:6d}   quarantine {3:6d} died {4:6d}".format(
            day, infl, immun, quar, died
        )
    )
    l_immun.append(immun)
    l_quar.append(quar)
    l_died.append(died)
    l_infl.append(infl)
    
#   ,  
    if infl == 0:
        break
#   
    day += 1

print ("\n{:6d} point number ".format(w_size))
print ("{:4d} maximum number of links ".format(max_conn))
print ("{:3.2f} the probability of infection in a single contact ".format(infection_probably))
print ("{:3.2f} chance to recover in one day ".format(pr_recover))
print ("{:4d} the number of days before the detection of the disease and the beginning of quarantine".format(quarantine))
print ("{:4d} number of treatment days to death".format(dead))

t = np.arange(0, day, 1.)
print (colored("the number of recovered ", "red"))
print (colored("the number in quarantine ", "green"))
print ("the number of died ")
print (colored("the number of infected ", "blue"))

fig, ax = plt.subplots()
ax.plot(t, l_immun, color='red')
ax.plot(t, l_quar, color='green')
ax.plot(t, l_died, color='black')
ax.plot(t, l_infl, color='blue')

ax.set(xlabel='time (days)', ylabel='number',
       title='virus behavior')
ax.grid()

fig.savefig("test.png")
plt.show()

day   1   infected      2   recovered      1   quarantine      0 died      0
day   2   infected      4   recovered      2   quarantine      0 died      0
day   3   infected     10   recovered      4   quarantine      0 died      0
day   4   infected     12   recovered      9   quarantine      0 died      0
day   5   infected     11   recovered     20   quarantine      0 died      0
day   6   infected     21   recovered     28   quarantine      0 died      0
day   7   infected     39   recovered     43   quarantine      0 died      0
day   8   infected     66   recovered     72   quarantine      0 died      0
day   9   infected     92   recovered    120   quarantine      0 died      0
day  10   infected    127   recovered    197   quarantine      0 died      0
day  11   infected    211   recovered    292   quarantine      1 died      0
day  12   infected    352   recovered    446   quarantine      1 died      0
day  13   infected    578   recovered    714   quarantine      1 died      0
day  14   infected    949   recovered   1151   quarantine      1 died      0
day  15   infected   1492   recovered   1841   quarantine      1 died      0
day  16   infected   2192   recovered   2954   quarantine      2 died      0
day  17   infected   3045   recovered   4612   quarantine      3 died      0
day  18   infected   3995   recovered   6902   quarantine      8 died      0
day  19   infected   4617   recovered   9889   quarantine     14 died      0
day  20   infected   4595   recovered  13385   quarantine     16 died      1
day  21   infected   3880   recovered  16847   quarantine     26 died      1
day  22   infected   2887   recovered  19722   quarantine     41 died      1
day  23   infected   1834   recovered  21859   quarantine     58 died      1
day  24   infected   1106   recovered  23203   quarantine     67 died      1
day  25   infected    688   recovered  23977   quarantine     75 died      2
day  26   infected    412   recovered  24422   quarantine     85 died      3
day  27   infected    249   recovered  24679   quarantine     83 died      8
day  28   infected    174   recovered  24796   quarantine     80 died     14
day  29   infected    112   recovered  24873   quarantine     81 died     17
day  30   infected     86   recovered  24894   quarantine     71 died     27
day  31   infected     60   recovered  24906   quarantine     58 died     42
day  32   infected     42   recovered  24908   quarantine     41 died     59
day  33   infected     33   recovered  24909   quarantine     32 died     68
day  34   infected     23   recovered  24910   quarantine     23 died     77
day  35   infected     12   recovered  24910   quarantine     12 died     88
day  36   infected      9   recovered  24910   quarantine      9 died     91
day  37   infected      6   recovered  24910   quarantine      6 died     94
day  38   infected      2   recovered  24910   quarantine      2 died     98
day  39   infected      2   recovered  24910   quarantine      2 died     98
day  40   infected      0   recovered  24910   quarantine      0 died    100

32768 point number 
   6 maximum number of links 
0.90 the probability of infection in a single contact 
0.75 chance to recover in one day 
   5 the number of days before the detection of the disease and the beginning of quarantine
  14 number of treatment days to death