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MLITTELPWNES.nlogo
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extensions [ gis ]
globals [ population-dataset
headquarters-dataset
all_data-dataset
city-dataset
road-dataset
citycost-dataset
m-attacks
]
breed [bhturtles bhturtle]
breed [attacks attack]
bhturtles-own [goal jerk]
attacks-own [maidu]
patches-own [Dist_City Dist_Cap Dist_HQs Grid_Pop Is_Major_City Is_HQ Is_Capital City_ID City00 City01 City02 City03 City04 City05 City06 City07 City08 City09 City10 City11 City12
City13 City14 City15 City16 City17 City18 City19 City20 City21 City22 City23 City24 City25 City26
]
;;----------------------------------------------------SETUP------------------------------------------------------------------------------
to setup
ca
; Load all of the datasets
set population-dataset gis:load-dataset "Data/Full_Pop_final.shp"
set headquarters-dataset gis:load-dataset "Data/Turtle_Area_Start.shp"
set all_data-dataset gis:load-dataset "Data/Grid_all_data.shp"
set city-dataset gis:load-dataset "Data/MajorCityPt.shp"
set road-dataset gis:load-dataset "Data/Roads_Simple.shp"
set citycost-dataset gis:load-dataset "Data/City_Costs_buff.shp"
; Set the world envelope to extent
gis:set-world-envelope (gis:envelope-of population-dataset)
;Visualizing a map of sorts
;set visual for grid
gis:set-drawing-color white
gis:fill population-dataset 2
gis:draw population-dataset 1
; just to see hq area for turtles if i use that
gis:set-drawing-color brown + 2
gis:draw headquarters-dataset 10
;visualize roads
gis:set-drawing-color black
gis:draw road-dataset 1
;visualize cities
gis:set-drawing-color blue
gis:fill city-dataset 3
gis:draw city-dataset 3
;;Read cost attributes from dataset & patchify
gis:apply-coverage all_data-dataset "MC_CD" Dist_City ; used it identify where the major cities are
gis:apply-coverage all_data-dataset "CITY_ID" City_ID ; used to call the cost surface for the goal city chosen
gis:apply-coverage all_data-dataset "BHHQ_CD" Dist_HQs ; used to set up bhturtles
gis:apply-coverage population-dataset "FULLPOP" Grid_Pop ;population data
gis:apply-coverage citycost-dataset "MAX_CITY00" City00 gis:apply-coverage citycost-dataset "MAX_CITY13" City13
gis:apply-coverage citycost-dataset "MAX_CITY01" City01 gis:apply-coverage citycost-dataset "MAX_CITY14" City14
gis:apply-coverage citycost-dataset "MAX_CITY02" City02 gis:apply-coverage citycost-dataset "MAX_CITY15" City15
gis:apply-coverage citycost-dataset "MAX_CITY03" City03 gis:apply-coverage citycost-dataset "MAX_CITY16" City16
gis:apply-coverage citycost-dataset "MAX_CITY04" City04 gis:apply-coverage citycost-dataset "MAX_CITY17" City17
gis:apply-coverage citycost-dataset "MAX_CITY05" City05 gis:apply-coverage citycost-dataset "MAX_CITY18" City18
gis:apply-coverage citycost-dataset "MAX_CITY06" City06 gis:apply-coverage citycost-dataset "MAX_CITY19" City19
gis:apply-coverage citycost-dataset "MAX_CITY07" City07 gis:apply-coverage citycost-dataset "MAX_CITY20" City20
gis:apply-coverage citycost-dataset "MAX_CITY08" City08 gis:apply-coverage citycost-dataset "MAX_CITY21" City21
gis:apply-coverage citycost-dataset "MAX_CITY09" City09 gis:apply-coverage citycost-dataset "MAX_CITY22" City22
gis:apply-coverage citycost-dataset "MAX_CITY10" City10 gis:apply-coverage citycost-dataset "MAX_CITY23" City23
gis:apply-coverage citycost-dataset "MAX_CITY11" City11 gis:apply-coverage citycost-dataset "MAX_CITY24" City24
gis:apply-coverage citycost-dataset "MAX_CITY12" City12 gis:apply-coverage citycost-dataset "MAX_CITY25" City25
gis:apply-coverage citycost-dataset "MAX_CITY26" City26
ask patches with [Dist_City = 0][set Is_Major_City 1] ;;set patch variable Is_Major_City to 1 if there is a city here
ask patches with [Dist_HQs = 0][set Is_HQ 1] ;;set patch variable Is_HQ to 1 if there is a HQ here
ask patches with [City12 < 3000] [set Is_Capital 1];;set capital Maiduguri
make-bhturtles
reset-ticks
end
;;----------------------------------------------------TO DOs------------------------------------------------------------------------------
to make-bhturtles
ask bhturtles [die]
create-bhturtles 3 [set shape "person soldier" set size 9]
ask bhturtles [
move-to one-of patches with [Is_HQ = 1]
set goal one-of patches with [Is_Major_City = 1] ]
end
to go
move-turtles
tick
end
to move-turtles
ask bhturtles [
ifelse patch-here = goal ;;arriving at goal
[ set goal one-of patches with [Is_Major_City = 1] be-a-jerk ] ;;choose a new city as goal randomly
[walk-towards-goal]]
end
to walk-towards-goal ;; Walk across the cost surface based on goal choice
if [City_ID] of goal = 0 [walk-across-cost0]
if [City_ID] of goal = 1 [walk-across-cost1]
if [City_ID] of goal = 2 [walk-across-cost2]
if [City_ID] of goal = 3 [walk-across-cost3]
if [City_ID] of goal = 4 [walk-across-cost4]
if [City_ID] of goal = 5 [walk-across-cost5]
if [City_ID] of goal = 6 [walk-across-cost6]
if [City_ID] of goal = 7 [walk-across-cost7]
if [City_ID] of goal = 8 [walk-across-cost8]
if [City_ID] of goal = 9 [walk-across-cost9]
if [City_ID] of goal = 10 [walk-across-cost10]
if [City_ID] of goal = 11 [walk-across-cost11]
if [City_ID] of goal = 12 [walk-across-cost12]
if [City_ID] of goal = 13 [walk-across-cost13]
if [City_ID] of goal = 14 [walk-across-cost14]
if [City_ID] of goal = 15 [walk-across-cost15]
if [City_ID] of goal = 16 [walk-across-cost16]
if [City_ID] of goal = 17 [walk-across-cost17]
if [City_ID] of goal = 18 [walk-across-cost18]
if [City_ID] of goal = 19 [walk-across-cost19]
if [City_ID] of goal = 20 [walk-across-cost20]
if [City_ID] of goal = 21 [walk-across-cost21]
if [City_ID] of goal = 22 [walk-across-cost22]
if [City_ID] of goal = 23 [walk-across-cost23]
if [City_ID] of goal = 24 [walk-across-cost24]
if [City_ID] of goal = 25 [walk-across-cost25]
if [City_ID] of goal = 26 [walk-across-cost26]
end
to be-a-jerk ;; Attack a city
if random aggressive-1-in-n-chance = 0 [hatch-attacks 1 [set color red set shape "face sad" set size 7]]
end
;;----------------------------------------------------WALK ON COSTS------------------------------------------------------------------------------
to walk-across-cost0
fd 1 pen-down
let p min-one-of neighbors [City00] ;find the least cost to travel to next big city
if [City00] of p < City00 [
face p
move-to p]
end
to walk-across-cost1
fd 1 pen-down
let p min-one-of neighbors [City01] ;find the least cost to travel to next big city
if [City01] of p < City01 [
face p
move-to p]
end
to walk-across-cost2
fd 1 pen-down
let p min-one-of neighbors [City02] ;find the least cost to travel to next big city
if [City02] of p < City02 [
face p
move-to p]
end
to walk-across-cost3
fd 1 pen-down
let p min-one-of neighbors [City03] ;find the least cost to travel to next big city
if [City03] of p < City03 [
face p
move-to p]
end
to walk-across-cost4
fd 1 pen-down
let p min-one-of neighbors [City04] ;find the least cost to travel to next big city
if [City04] of p < City04 [
face p
move-to p]
end
to walk-across-cost5
fd 1 pen-down
let p min-one-of neighbors [City05] ;find the least cost to travel to next big city
if [City05] of p < City05 [
face p
move-to p]
end
to walk-across-cost6
fd 1 pen-down
let p min-one-of neighbors [City06] ;find the least cost to travel to next big city
if [City06] of p < City06 [
face p
move-to p]
end
to walk-across-cost7
fd 1 pen-down
let p min-one-of neighbors [City07] ;find the least cost to travel to next big city
if [City07] of p < City07 [
face p
move-to p]
end
to walk-across-cost8
fd 1 pen-down
let p min-one-of neighbors [City08] ;find the least cost to travel to next big city
if [City08] of p < City08 [
face p
move-to p]
end
to walk-across-cost9
fd 1 pen-down
let p min-one-of neighbors [City09] ;find the least cost to travel to next big city
if [City09] of p < City09 [
face p
move-to p]
end
to walk-across-cost10
fd 1 pen-down
let p min-one-of neighbors [City10] ;find the least cost to travel to next big city
if [City10] of p < City10 [
face p
move-to p]
end
to walk-across-cost11
fd 1 pen-down
let p min-one-of neighbors [City11] ;find the least cost to travel to next big city
if [City11] of p < City11 [
face p
move-to p]
end
to walk-across-cost12
fd 1 pen-down
let p min-one-of neighbors [City12] ;find the least cost to travel to next big city
if [City12] of p < City12 [
face p
move-to p]
end
to walk-across-cost13
fd 1 pen-down
let p min-one-of neighbors [City13] ;find the least cost to travel to next big city
if [City13] of p < City13 [
face p
move-to p]
end
to walk-across-cost14
fd 1 pen-down
let p min-one-of neighbors [City14] ;find the least cost to travel to next big city
if [City14] of p < City14 [
face p
move-to p]
end
to walk-across-cost15
fd 1 pen-down
let p min-one-of neighbors [City15] ;find the least cost to travel to next big city
if [City15] of p < City15 [
face p
move-to p]
end
to walk-across-cost16
fd 1 pen-down
let p min-one-of neighbors [City16] ;find the least cost to travel to next big city
if [City16] of p < City16 [
face p
move-to p]
end
to walk-across-cost17
fd 1 pen-down
let p min-one-of neighbors [City17] ;find the least cost to travel to next big city
if [City17] of p < City17 [
face p
move-to p]
end
to walk-across-cost18
fd 1 pen-down
let p min-one-of neighbors [City18] ;find the least cost to travel to next big city
if [City18] of p < City18 [
face p
move-to p]
end
to walk-across-cost19
fd 1 pen-down
let p min-one-of neighbors [City19] ;find the least cost to travel to next big city
if [City19] of p < City19 [
face p
move-to p]
end
to walk-across-cost20
fd 1 pen-down
let p min-one-of neighbors [City20] ;find the least cost to travel to next big city
if [City20] of p < City20 [
face p
move-to p]
end
to walk-across-cost21
fd 1 pen-down
let p min-one-of neighbors [City21] ;find the least cost to travel to next big city
if [City21] of p < City21 [
face p
move-to p]
end
to walk-across-cost22
fd 1 pen-down
let p min-one-of neighbors [City22] ;find the least cost to travel to next big city
if [City22] of p < City22 [
face p
move-to p]
end
to walk-across-cost23
fd 1 pen-down
let p min-one-of neighbors [City23] ;find the least cost to travel to next big city
if [City23] of p < City23 [
face p
move-to p]
end
to walk-across-cost24
fd 1 pen-down
let p min-one-of neighbors [City24] ;find the least cost to travel to next big city
if [City24] of p < City24 [
face p
move-to p]
end
to walk-across-cost25
fd 1 pen-down
let p min-one-of neighbors [City25] ;find the least cost to travel to next big city
if [City25] of p < City25 [
face p
move-to p]
end
to walk-across-cost26
fd 1 pen-down
let p min-one-of neighbors [City26] ;find the least cost to travel to next big city
if [City26] of p < City26 [
face p
move-to p]
end
@#$#@#$#@
GRAPHICS-WINDOW
210
10
664
565
-1
-1
2.0
1
10
1
1
1
0
0
0
1
0
222
0
272
0
0
1
ticks
30.0
BUTTON
20
17
76
51
NIL
setup
NIL
1
T
OBSERVER
NIL
NIL
NIL
NIL
1
BUTTON
127
17
190
50
go
go
T
1
T
OBSERVER
NIL
NIL
NIL
NIL
0
PLOT
683
407
1165
564
Susceptible Population
Time
Max Susceptible
0.0
10.0
0.0
10.0
true
false
"" ""
PENS
"Pop" 1.0 0 -955883 true "" "plot sum [Grid_Pop] of bhturtles"
PLOT
684
201
1165
383
Susceptible Population by Terror Turtle
NIL
NIL
0.0
10.0
0.0
10.0
true
false
"" ""
PENS
"default" 1.0 0 -6459832 true "" "plot [Grid_Pop] of turtle 0"
"pen-1" 1.0 0 -8630108 true "" "plot [Grid_Pop] of turtle 1"
"pen-2" 1.0 0 -11221820 true "" "plot [Grid_Pop] of turtle 2"
MONITOR
27
243
182
288
Est. Population near TT 2
[Grid_Pop] of turtle 2
17
1
11
MONITOR
27
192
182
237
Est. Population near TT 1
[Grid_Pop] of turtle 1
17
1
11
MONITOR
40
431
184
476
TT 2 Distance from Goal
[Dist_City] of turtle 2
17
1
11
MONITOR
40
379
184
424
TT 1 Distance from Goal
[Dist_City] of turtle 1
17
1
11
MONITOR
39
327
183
372
TT 0 Distance from Goal
[Dist_City] of turtle 0
17
1
11
MONITOR
1054
13
1142
58
NIL
count attacks
17
1
11
PLOT
685
12
1039
178
Max Potential Affected By Attack
Time
Population
0.0
10.0
0.0
10.0
true
false
"" ""
PENS
"default" 1.0 0 -2674135 true "" "plot sum [Grid_Pop] of attacks"
SLIDER
19
70
203
103
aggressive-1-in-n-chance
aggressive-1-in-n-chance
1
10
2.0
1
1
NIL
HORIZONTAL
MONITOR
28
139
180
184
Est. Population near TT 0
[Grid_Pop] of turtle 0
17
1
11
MONITOR
1055
75
1179
120
Attacks in Maiduguri
count attacks with [Is_Capital = 1]
17
1
11
@#$#@#$#@
## WHAT IS IT?
This model is designed on the Boko Haram terrorist group based in Borno State, Nigeria. The model is a simple exploration of estimating population at risk to when a Boko Haram group (Terror Turtle) is near as well as counting the max potential affected by an attack by Boko Haram.
MWLITTELPWNES: Modeling likely indicators tempting turtle events linking population weights in estimating susceptibility
## HOW IT WORKS
Terror Turtle randomly chooses a city and walks across cost surface to the city. User defines how aggresive the terror turtle is. Based on the user definition of Aggression, the terror turtle will attack.
## HOW TO USE IT
Choose a level of aggression. If 2 is chosen, there is a 1-in-2 chance an attack will occur.
## THINGS TO NOTICE
Counts of population and routes taken
## THINGS TO TRY
## EXTENDING THE MODEL
1) Weighting the city choice by population instead of random choice
2) Specify likely routes
3) Introduce behaviors
4) Memory of where prior attacks occured
5) Add in peace keeping soldiers affecting terror turtle decisions
## NETLOGO FEATURES
Buffer was added around the dataset to prevent turtles from falling off the layer
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