我试图从eon包中修改SIR模型,并对其进行了一些更改。它附加了一个新的疫苗接种参数,还有新的参数beta,omega和Vl,我的代码是-
def test_transmission(u, v, p):
return random.random()<p
def discrete_SIR(G,
initial_infecteds,beta,
w,Vl,return_full_data=True):
if G.has_node(initial_infecteds):
initial_infecteds=[initial_infecteds]
if return_full_data:
node_history = defaultdict(lambda : ([tmin], ['S']))
transmissions = []
for node in initial_infecteds:
node_history[node] = ([tmin], ['I'])
transmissions.append((tmin-1, None, node))
node_history = defaultdict(lambda : ([tmin], ['S']))
# transmissions = []
for node in initial_infecteds:
node_history[node] = ([tmin], ['I'])
#transmissions.append((tmin-1, None, node))
N=G.order()
t = [tmin]
S = [N-len(initial_infecteds)]
I = [len(initial_infecteds)]
R = [0]
V = [0]
susceptible = defaultdict(lambda: True)
#above line is equivalent to u.susceptible=True for all nodes.
for u in initial_infecteds:
susceptible[u] = False
infecteds = set(initial_infecteds)
while infecteds and t[-1]<tmax :
new_infecteds = set()
vaccinated= set()
infector = {} #used for returning full data. a waste of time otherwise
for u in infecteds:
# print('u-->' +str(u))
for v in G.neighbors(u):
# print('v --> '+ str(v))
##vaccination
if len(vaccinated)+V[-1]< (Vl*N) : #check if vaccination over or not
#print(len(vaccinated),Vl*N)
#print("HI")
if susceptible[v] and test_transmission(u, v, w):
vaccinated.add(v)
susceptible[v] = False
# print('transmitting vaccination')
elif susceptible[v] and test_transmission(u,v,beta):
new_infecteds.add(v)
susceptible[v]=False
infector[v] = [u]
# print('transmitting infection')
else:
# print("BYE")
if susceptible[v] and test_transmission(u, v,beta):
new_infecteds.add(v)
susceptible[v] = False
infector[v] = [u]
#infector[v] = [u]
if return_full_data:
for v in infector.keys():
transmissions.append((t[-1], random.choice(infector[v]), v))
next_time = t[-1]+1
if next_time <= tmax:
for u in infecteds:
node_history[u][0].append(next_time)
node_history[u][1].append('R')
for v in new_infecteds:
node_history[v][0].append(next_time)
node_history[v][1].append('I')
infecteds = new_infecteds
R.append(R[-1]+I[-1])
V.append(len(vaccinated)+V[-1])
I.append(len(infecteds))
S.append(N-V[-1]-I[-1]-R[-1])
#S.append(S[-1]-V[-1]-I[-1])
t.append(t[-1]+1)
print(str(R[-1])+','+str(V[-1])+','+str(I[-1])+','+str(S[-1]))
if not return_full_data:
return scipy.array(t), scipy.array(S), scipy.array(I), \
scipy.array(R)
else:
return EoN.Simulation_Investigation(G, node_history, transmissions)
现在我想在它上面运行可视化,就像在包中一样-
m=5
G=nx.grid_2d_graph(m,m,periodic=True)
initial_infections = [(u,v) for (u,v) in G if u==int(m/2) and v==int(m/2)]
sim = EoN.basic_discrete_SIR(G,0.5,initial_infecteds = initial_infections,
return_full_data=True, tmax = 25)
pos = {node:node for node in G}
sim.set_pos(pos)
sim.display(0, node_size = 40) #display time 6
plt.show()
plt.savefig('SIR_2dgrid.png')
我需要在代码中做什么更改才能使显示功能正常工作,还是也需要对显示功能进行更改?你知道吗
下面是我现在得到的输出:
您必须安装EoN版本
1.0.8rc3
或更高版本,该版本可以在github页面上找到(请参见installation instructions)。目前pip
无法安装它。我想确保我没有破坏任何东西之前,我把它作为默认安装的pip
。你知道吗这是基于你的密码。你应该看看我所做的改变。同样值得一看的是the examples I've put in the documentation(包括SIRV模型,其中疫苗接种规则与您的不同)。你知道吗
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