In [1]:

    

include("ilmtools.jl")


    

    












    












    
Out[1]:





create_loglikelihood (generic function with 1 method)

In [2]:

    

pop_db1 = create_pop_db_univariates(1000, Uniform(0,25), Uniform(0,25))


    

    
Out[2]:




ind_id
x
y
1
1
5.125011904734533
16.15557099071509
2
2
15.219102687556301
11.972975436325328
3
3
13.046038881472565
10.08328633237483
4
4
20.497525097900482
5.16017648245416
5
5
3.1554191964602794
17.81252802351266
6
6
5.9899691241713295
0.8943337240064242
7
7
7.982536037681726
2.3779127275929293
8
8
1.85648646432508
15.942058418691229
9
9
9.770361786745607
12.757690758824753
10
10
0.930814354254833
19.8055501259083
11
11
18.99200538615375
18.917773388123155
12
12
16.006432133061498
9.964991580137628
13
13
22.72741507921546
3.0429663802547466
14
14
24.192018977177256
17.74396006200777
15
15
15.156022136004704
14.33869263473202
16
16
8.396604637124073
14.45706618253218
17
17
11.94264336635712
2.772734215887762
18
18
7.140670886990852
2.565877600480826
19
19
9.738347679267157
20.864757336620716
20
20
9.223544036116117
23.563271743322467
21
21
0.9399775153126122
20.366049788555486
22
22
15.449084147313325
10.46107982341753
23
23
22.1968643168106
24.67909739676193
24
24
6.937193583422562
16.17759873761288
25
25
5.784281101274614
1.5513642177954812
26
26
23.235034337299332
6.624589564641497
27
27
14.807931134096824
4.256291772566207
28
28
12.795125331898372
24.961266891798985
29
29
22.792475356877517
11.08507152432776
30
30
22.92071835131634
13.440803802865753
&vellip
&vellip
&vellip
&vellip

In [3]:

    

evdb = infect_recover_loop(pop_db1, "continuous", "SIR", 2, 6, 5)


    

    
Out[3]:





edb(1000x4 DataFrame
| Row  | ind_id | s | i       | r       |
|------|--------|---|---------|---------|
| 1    | 1      | 0 | 1.28856 | 3.4151  |
| 2    | 2      | 0 | 1.62554 | 19.733  |
| 3    | 3      | 0 | 1.51886 | 11.458  |
| 4    | 4      | 0 | 1.86001 | 7.42561 |
| 5    | 5      | 0 | 1.26228 | 2.87442 |
| 6    | 6      | 0 | 1.89921 | 8.33897 |
| 7    | 7      | 0 | 1.8136  | 9.21274 |
| 8    | 8      | 0 | 1.3846  | 2.58653 |
| 9    | 9      | 0 | 1.33986 | 4.92792 |
| 10   | 10     | 0 | 1.36897 | 1.65071 |
| 11   | 11     | 0 | 1.61995 | 8.55315 |
⋮
| 989  | 989    | 0 | 1.62452 | 2.30524 |
| 990  | 990    | 0 | 1.58454 | 5.0418  |
| 991  | 991    | 0 | 1.6369  | 33.3878 |
| 992  | 992    | 0 | 1.82507 | 2.37633 |
| 993  | 993    | 0 | 1.95244 | 2.36642 |
| 994  | 994    | 0 | 1.7409  | 5.31333 |
| 995  | 995    | 0 | 1.34308 | 3.70939 |
| 996  | 996    | 0 | 1.74095 | 2.83141 |
| 997  | 997    | 0 | 1.27044 | 6.59653 |
| 998  | 998    | 0 | 1.62528 | 3.00566 |
| 999  | 999    | 0 | 1.69481 | 2.69461 |
| 1000 | 1000   | 0 | 1.87031 | 3.91214 |,[1.0,1.00044,1.00551,1.00563,1.0119,1.01246,1.03406,1.05569,1.05577,1.06241  …  26.6155,27.1867,27.1925,27.3699,27.7745,32.5808,33.3878,35.843,36.7957,38.9848],"continuous")

In [4]:

    

evseries = state_timeseries(evdb)
plot(evseries, x="time", y="S", Geom.line)


    

    
Out[4]:

In [5]:

    

plot(evseries, x="time", y="I", Geom.line)


    

    
Out[5]:

In [6]:

    

plot(evseries, x="time", y="R", Geom.line)


    

    
Out[6]:

In [7]:

    

state_animation(0.1, evdb, pop_db1)


    

    












    
Out[7]:

In [8]: