<jupyter_start><jupyter_text>emm目前跑出来是可以跑？可视化来检查一下结果<jupyter_code>testfuninfo
maxinfo = {}
for keys in tfuninfo4:
    
    thiso = tfuninfo4[keys][1][40]
    maxinfo[keys] = thiso
maxinfo
testfuninfo['l.crin.s']

singleGenerated
nowis_ = singleGenerated[singleGenerated['Climate']=='arid']
nowis_.sort_values(by='Means',inplace=True)
nowis_
namelist = ['m.trem.s','p.flav.s','p.rufa.acer.s']

tfuninfo1,tdecomposition1 = LotkaVolterra(BS,D_t,[namelist[0]])
tfuninfo2,tdecomposition2 = LotkaVolterra(BS,D_t,[namelist[1]])
tfuninfo3,tdecomposition3 = LotkaVolterra(BS,D_t,[namelist[2]])
plt.plot(time1,tdecomposition1,label='p.flav.n')
plt.plot(time1,tdecomposition2,label='l.crin.s')
plt.plot(time1,tdecomposition3,label='m.trem.n')
#plt.plot(time1,tdecomposition4,label='combination')
plt.show()





#subnames = names[0:34].tolist()
subnames = ['p.flav.s','p.flav.n','m.trem.s','m.trem.n','p.rufa.acer.s']
#Afjuanwang = ['p.flav.s','p.flav.n','m.trem.s','m.trem.n','p.rufa.acer.s']
tfuninfo4,tdecomposition4 = LotkaVolterra(BS,D_t,subnames)
fig = plt.figure(figsize=(15,5),facecolor='white')

ax1 = fig.add_subplot(121)
for item in subnames:
    N = tfuninfo4[item][1]
    plt.plot(time,N,label=item)
plt.title('Arid')
plt.xlabel("Days")
plt.ylabel("Population")
plt.legend(frameon = False)

ax2 = fig.add_subplot(122)
plt.plot(time1,tdecomposition1,color = 'lightgreen',label=namelist[0])
plt.plot(time1,tdecomposition2,color = 'thistle',label=namelist[1])
plt.plot(time1,tdecomposition3,color = 'lightblue',label=namelist[2])
plt.plot(time1,tdecomposition4,color = 'r',label='combination')
plt.legend(frameon = False)
plt.xlabel("Days")
plt.ylabel("Decomposition Rate")
plt.title('Comparision between Single and Multiple Species')

plt.savefig('Arid_t4.jpg')<jupyter_output><empty_output>
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