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MC2B-RandomTies.nlogo
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;;By m6f, any comment please write me at hellypoch@gmail.com
;GLOBALES VARIABLES
;------------------
;Global Variables
globals[contadorAct contadorActNull i j tduni1 tduni2 tduni3 tduni4 blacks
N propini propfin propiniab propt0 personas Caux sum-color1 sum-color2
sum-color3 sum-color4 npixel z pc nlist nlist1
t0party_1 t0party_2 t0party_3 t0party_4 t0party_5
contempate-mr contempate-ab menorav mayorav colorempate2rm
c1 c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12
]
;PATCH VARIABLES
patches-own [partido influencia]
;---------------
;SETUP PROCEDURE. System initializatioin, by distributing opinions A,B,C,0
;Opinions A, B, C, 0 are drawed with black respectively.
;------------------------------------------------------------------------
to setup
;Resize the work according to netorder value
resize-world 0 netorder 0 netorder
;tparty_1 is the variable associated with entry buttom, also variables tparty_2, tparty_3, tparty_4, tparty_5 has an entry buttom
;this variables serves to initialize the world, at the beginning must be 0, and at final inizialitation must be equal to persons_party's variables.
set tparty_1 0
set tparty_2 0
set tparty_3 0
set tparty_4 0
set tparty_5 0
;porcentA, porcentB and porcentC sets percents for party, i.e., numbers in [0,1] s.t. porcentA + porcentB = 1 - pocentC and porcentC <= 1
ifelse (porcentC <= 1)
[
;Setting porcentC to 0.5 party C has the half of nodes and AB has the other half
set porcentB (precision (1 - porcentC - porcentA) 3) ;precision predicate sets the number of decimal digits to use.
]
[ stop ]
;Setting number of nodes in totaladistribuir variable
;Fixing totaladistribuir, in general it could be variable
;set totaladistribuir (netorder + 1) * (netorder + 1)
set nnodos (netorder + 1) * (netorder + 1)
;First erase our world
clear-all
;To each patche we set its party to null party, influencia to 0, color to black
ask patches [set partido 4 set influencia 0 set pcolor black]
;To assign the number of nodes we use porcent variables and totaladistribuir variable.
set persons_party1 floor (porcentA * totaladistribuir)
set persons_party2 floor (porcentB * totaladistribuir)
set persons_party3 floor (porcentC * totaladistribuir)
set persons_party4 nnodos - persons_party1 - persons_party2 - persons_party3
;To have an ordered list of patches
set npixel []
set i 0
set j 0
repeat netorder + 1 ; Run r times the inner repeat
[
repeat netorder + 1 ; Run r times set npixel...
[
set npixel sentence npixel patch i j
set j j + 1 ; Increases j from 0 to 99
]
set i i + 1 ; Increases i from 0 to 99
set j 0
]
;Here npixel is an ordered list o patches pairs, length(npixel)=10000
set Caux npixel
;10000 = N
set N nnodos
;It is distributed patches according to persons_party1, persons_party2, and persons_party3
;List to be filled with the patche distribution per party. Initialized to empty list
set tduni1 []
set tduni2 []
set tduni3 []
set tduni4 []
;If it is required to draw districts lines we draw them
;To distribute A nodes
repeat persons_party1 ;Repeat participante1 times
[
set z random N ; 0 <= z <= 9999
ask item z npixel [set pcolor 2 set partido 1 set influencia 1] ;Selects a random patch in npixel list then change its attributes
set npixel replace-item z npixel item (N - 1) npixel ;
set tduni1 sentence tduni1 item z npixel
set N N - 1
]
;To distribute B nodes
;Last N value comes in the previous cycle then it has N - persons_party1
repeat persons_party2
[
set z random N
ask item z npixel [set pcolor 8 set partido 2 set influencia 1]
set npixel replace-item z npixel item (N - 1) npixel
set tduni2 sentence tduni2 item z npixel
set N N - 1
]
;To distribute C nodes, takint in account if C is or not #V(R)/2
;Last N value comes in the previous cycle then it has N - persons_party1 - persons_party2
ifelse persons_party3 = nnodos / 2
[
ask patches with [pcolor = black] [ set pcolor white set partido 3 set influencia 1 ]
;set N 0
;set i pxcor
;set j pycor
;set tduni3 sentence tduni3 patch i j ]
]
[
; to enter here persons_party3 is less (or more) than #V(R)
repeat persons_party3
[
set z random N
ask item z npixel [set pcolor white set partido 3 set influencia 1]
set npixel replace-item z npixel item (N - 1) npixel
set tduni3 sentence tduni3 item z npixel
set N N - 1
]
;stop
]
;If persons_party1 + persons_party + persons_party3 not equal to network order, by floors and
;we have no null nodes, then assign the node to party3
if N - persons_party4 > 0 and persons_party4 > 0
[
ask (patches with [pcolor = black]) [set pcolor white set partido 3 set influencia 1]
]
if persons_party4 > 0
[
ask patches with [pcolor = black] [
set i pxcor
set j pycor
set tduni4 sentence tduni4 patch i j
]
]
set blacks count patches with [pcolor = black]
;Contamos los individuos de cada partido
set tparty_1 count patches with [partido = 1]
set tparty_2 count patches with [partido = 2]
set tparty_3 count patches with [partido = 3]
set tparty_4 count patches with [partido = 4]
set tparty_5 count patches with [pcolor = 8 or pcolor = 2]
;Variable to count draws under main MR
set contempate-mr 0
set contempate-ab 0
;Variables para contar cada actualización realizada
set contadorAct 0 ;Este contador nos permite contar el numero de pasos de actualizacion y se usa al dibujar la cuadricula
set contadorActNull 0 ;Este contador nos permita contar el numero de ciclos antes de acabar con indecisos
;To know minimum and maximum size party and to fix initial proportion.
;I = Im / Ig
ifelse tparty_1 < tparty_2
[
set menorav 2 ;minor is party1
set mayorav 8 ;mayor is party2
set propini tparty_1 / (tparty_2)
set propiniab tparty_1 / (tparty_1 + tparty_2)
]
[
set menorav 8 ;minor is party2
set mayorav 2 ;mayor is party1
set propini tparty_2 / (tparty_1)
set propiniab tparty_2 / (tparty_1 + tparty_2)
]
set propfin 0 ; initially we set propfin to 0
reset-ticks ; reset tick counter variable to count the number of entrances to setup procedure
end
;INICIO PROCEDURE. Apply repetition scheme and inspection of patches
;-------------------------------------------------------------------
to inicio
;A repetition or a cycle is a selection of totaladistribuir nodes with or without repetition, here, following Redner we use 600 as the maximum number of repetitions
repeat 1400 ;Stripe
[
;Condicion para terminar el la dinámica del modelo, escencialmente es que se llege al concenso o que se efectuen todos los 600 ciclos
if (tparty_1 = nnodos) or (tparty_2 = nnodos) or (tparty_3 = nnodos) or (tparty_4 = nnodos) or (tparty_5 = nnodos) [stop]
set N nnodos
set npixel Caux ; Return npixel to the previos before modified in setup procedure.
;Repeat nnodos - lattice network order - A CYCLE
repeat nnodos
[
;Choose a random item for patch list
set z random N ;0 <= z <= nnodos-1
;Computations over the 4-neighbourhood for patche (xi,yj)
ask item z npixel
[
;Choose a patch with coordinates (xi,yj) then save it in personas list
set personas sentence personas item z npixel
;To determinate how is theh neighbourhood of patch (xi,yj) in termos of number of nodes per party
ask item z npixel [set sum-color1 sum ([influencia] of neighbors4 with [pcolor = 2])] ;Party 1
ask item z npixel [set sum-color2 sum ([influencia] of neighbors4 with [pcolor = 8])] ;Party 2
ask item z npixel [set sum-color3 sum ([influencia] of neighbors4 with [pcolor = white])] ;Party 3
set sum-color4 4 - sum-color1 - sum-color2 - sum-color3 ;Party 4, the null node arround patch xi yj, they has influencia = 0
;To count number of inspections we made
set contadorAct contadorAct + 1
;To know the number of cycles when null nodes desapair
if tparty_4 > 0
[
set contadorActNull contadorActNull + 1
]
;Party 1 = A color soft black code 2, party 2 = B color gray code 8, party 3 = C color white code white, null = 0 color black code 0
;To add central node and take it in account
if (pcolor = 2)
[
set sum-color1 sum-color1 + 1
]
if (pcolor = 8)
[
set sum-color2 sum-color2 + 1
]
if (pcolor = white)
[
set sum-color3 sum-color3 + 1
]
if (pcolor = black)
[
set sum-color4 sum-color4 + 1
]
;To enter into the 4-neighbourhood analysis excluding cases when only have C's or only have A's and B's
;if (sum-color3 > 0 and (sum-color1 > 0 or sum-color2 > 0)) or (sum-color4 > 0 and (sum-color1 > 0 or sum-color2 > 0) or (sum-color4 > 0 and sum-color3 > 0)) [
;To enter here, we considering a 4-neighbourhood AB, C excluding C's or only A's and B's
;To enter and inspect a group G: we consider a 4-neighbourhood with AB, C, 0 excluding C's or only A's and B's or only 0's
;The logic negation is sum-color3=0 or (sum-color1=0 and sum-color2=0) which means only C's and only A's and B's then is correct!
if(sum-color3 > 0 and (sum-color1 > 0 or sum-color2 > 0) or (sum-color3 > 0 and sum-color4 > 0) or ((sum-color1 > 0 or sum-color2 > 0) and sum-color4 > 0))
[
;Mayority rule for AB VS C and 0
if (sum-color1 + sum-color2 > sum-color3)
[
;AB wins and exist A's and B's with at least one C or one 0 then use a sedond MR between AB's group.
;2rm + aleatorio with central A
if sum-color1 > sum-color2 ; A's > B's
[
ask item z npixel [set pcolor 2 set partido 5 set influencia 1]
ask neighbors4 [set pcolor 2 set partido 5 set influencia 1]
]
if sum-color1 < sum-color2 ; A's < B's
[
ask item z npixel [set pcolor 8 set partido 5 set influencia 1]
ask neighbors4 [set pcolor 8 set partido 5 set influencia 1]
]
if sum-color1 = sum-color2 ; if A's = B's then do random selection between {A,B}
[
;Empate coalicion bajo regla de mayoria
ifelse random 2 = 1
[set colorempate2rm 2] ;
[set colorempate2rm 8] ;
ask item z npixel [set pcolor colorempate2rm set partido 5 set influencia 1]
ask neighbors4 [set pcolor colorempate2rm set partido 5 set influencia 1]
;Just delete random rule for the variation
set contempate-ab contempate-ab + 1
;Count cases with 0's here
if(sum-color1 = 1 and sum-color2 = 1 and sum-color4 = 3) ;AB000
[set c7 c7 + 1]
if(sum-color1 = 1 and sum-color2 = 1 and sum-color3 = 1 and sum-color4 = 2) ;ABC00
[set c8 c8 + 1]
if(sum-color1 = 2 and sum-color2 = 2 and sum-color4 = 1) ;AABB0
[set c9 c9 + 1]
if(sum-color1 = 2 and sum-color2 = 2 and sum-color3 = 1) ;AABBC
[set c10 c10 + 1]
]
] ;END coalition AB wins to C in the 4-neighbourhood with central A
;If C wins
if (sum-color3 > sum-color1 + sum-color2)
[
ask item z npixel [set pcolor white set partido 3 set influencia 1]
ask neighbors4 [set pcolor white set partido 3 set influencia 1]
]
;The system has 0's and MR no decides
if (sum-color3 = sum-color1 + sum-color2)
[
;ifelse random 2 = 1
;[set colorempate1rm white
; set p 3]
;[ ifelse random 2 = 1
; [set colorempate1rm 8
; set p 5]
; [set colorempate1rm 2
; set p 5]
;];
;ask item z npixel [set pcolor colorempate1rm set partido p set influencia 1]
;ask neighbors4 [set pcolor colorempate1rm set partido p set influencia 1]
set contempate-mr contempate-mr + 1 ;count mr-draw
if(sum-color4 = 5) ;00000
[set c1 c1 + 1]
if(sum-color1 = 1 and sum-color3 = 1 and sum-color4 = 3) ;AC000
[set c2 c2 + 1]
if(sum-color2 = 1 and sum-color3 = 1 and sum-color4 = 3) ;BC000
[set c3 c3 + 1]
if(sum-color1 = 2 and sum-color3 = 2 and sum-color4 = 1) ;AACC0
[set c4 c4 + 1]
if(sum-color2 = 2 and sum-color3 = 2 and sum-color4 = 1) ;BBCC00
[set c5 c5 + 1]
if(sum-color1 = 1 and sum-color2 = 1 and sum-color3 = 2 and sum-color4 = 1) ;ABCC0
[set c6 c6 + 1]
]
] ;End if, conditions to enter in 4-neighbourhood analysys
if repeticion = false
[ set npixel replace-item z npixel item (N - 1) npixel ;remplace item z of npixel list with item N-1 of npixel, puts final npixel's item on z place
set N N - 1 ]
] ;END ask item z npixel
] ;END repeat nnodos END 1 CYCLE
;To count number of patches per color, after cycle.
set tparty_1 count patches with [pcolor = 2]
set tparty_2 count patches with [pcolor = 8]
set tparty_3 count patches with [pcolor = white ]
set tparty_4 count patches with [pcolor = black]
set tparty_5 count patches with [pcolor = 8 or pcolor = 2]
;To stablish final proportion
if ((menorav = 2) and (tparty_2 != 0)) ;party A is the minimum size party
[
set propfin tparty_1 / tparty_2
]
if ((menorav = 8) and (tparty_1 != 0)) ;party B us the minimum size party
[
set propfin tparty_2 / tparty_1
]
] ;END repeat 600
stop
end
;Color codes: 45 es white , 55 es 8, 105 es 2, black es 0
; REPORTERS
; proportional report colors 2, 8
to-report proportional
let h random-float 1
if menorav = 2 and h <= propiniab
[report 2]
if menorav = 2 and h > propiniab
[report 8]
if menorav = 8 and h <= propiniab
[report 8]
if menorav = 8 and h > propiniab
[report 2]
end
@#$#@#$#@
GRAPHICS-WINDOW
231
10
439
219
-1
-1
1.0
1
10
1
1
1
0
1
1
1
0
199
0
199
0
0
1
ticks
30.0
BUTTON
799
37
862
70
NIL
setup\n
NIL
1
T
OBSERVER
NIL
NIL
NIL
NIL
1
BUTTON
862
37
926
70
NIL
inicio\n
NIL
1
T
OBSERVER
NIL
NIL
NIL
NIL
1
SLIDER
801
128
988
161
persons_party1
persons_party1
0
(netorder + 1)*(netorder + 1)
10000.0
1
1
NIL
HORIZONTAL
SLIDER
801
168
988
201
persons_party2
persons_party2
0
(netorder + 1)*(netorder + 1)
10000.0
1
1
NIL
HORIZONTAL
INPUTBOX
222
567
377
627
tparty_1
10172.0
1
0
Number
INPUTBOX
389
567
544
627
tparty_2
10089.0
1
0
Number
INPUTBOX
556
568
711
628
tparty_3
19739.0
1
0
Number
SLIDER
802
207
989
240
persons_party3
persons_party3
0
(netorder + 1)*(netorder + 1)
20000.0
1
1
NIL
HORIZONTAL
INPUTBOX
222
635
377
695
tparty_4
0.0
1
0
Number
INPUTBOX
556
637
711
697
nnodos
40000.0
1
0
Number
INPUTBOX
388
636
545
696
tparty_5
20261.0
1
0
Number
MONITOR
26
75
157
140
2#Draw AC000
c2
17
1
16
MONITOR
26
140
157
205
3#Draw CB000
c3
17
1
16
MONITOR
26
204
157
269
4#Draw AACC0
c4
17
1
16
MONITOR
26
269
157
334
5#Draw BBCC0
c5
17
1
16
MONITOR
725
569
806
614
#Empate MR
contempate-mr
17
1
11
SLIDER
994
87
1175
120
totaladistribuir
totaladistribuir
0
(netorder + 1) * (netorder + 1)
40000.0
1
1
NIL
HORIZONTAL
SLIDER
996
129
1175
162
porcentA
porcentA
0
1
0.25
0.001
1
NIL
HORIZONTAL
SLIDER
997
167
1175
200
porcentB
porcentB
0
1
0.25
0.001
1
NIL
HORIZONTAL
SLIDER
996
206
1175
239
porcentC
porcentC
0
1
0.5
0.001
1
NIL
HORIZONTAL
MONITOR
25
435
191
500
AB#Draw AB000
c7
17
1
16
MONITOR
25
498
191
563
AB#Draw ABC00
c8
17
1
16
MONITOR
24
563
191
628
AB#Draw AABB0
c9
17
1
16
MONITOR
23
628
191
693
AB#Draw AABBC
c10
17
1
16
MONITOR
1187
128
1349
173
#MINOR ini / #MAYOR ini
propini
17
1
11
MONITOR
1187
218
1349
263
#MINOR fin / #MAYOR fin
propfin
17
1
11
MONITOR
802
295
949
340
MinorPartyAB
menorav
17
1
11
MONITOR
956
295
1107
340
Criterio Propor Inicial
propiniab
17
1
11
MONITOR
975
568
1208
613
Num de actualizaciones A = nnodos x #Ciclos
contadorAct
17
1
11
MONITOR
909
569
965
614
# Ciclos
contadorAct / nnodos
17
1
11
SWITCH
942
37
1054
70
repeticion
repeticion
1
1
-1000
MONITOR
802
344
928
389
GreatPartyAB
mayorav
17
1
11
CHOOSER
1067
37
1159
82
netorder
netorder
49 74 99 114 149 199 249 499 999
5
SWITCH
1169
37
1303
70
districtdraw
districtdraw
1
1
-1000
MONITOR
26
10
183
75
1#Draw 00000 )(
c1
17
1
16
MONITOR
25
333
158
398
6#Draw ABCC0
c6
17
1
16
MONITOR
817
569
898
614
#Empate AB
contempate-ab
17
1
11
TEXTBOX
806
397
987
482
2 = Soft Black -> tparty1\n8 = Gray -> tparty2\nwhite -> tparty3\n0 = Black -> tnull\n
16
14.0
1
SLIDER
802
247
989
280
persons_party4
persons_party4
0
(netorder + 1) * (netorder + 1)
0.0
1
1
NIL
HORIZONTAL
@#$#@#$#@
## WHAT IS IT?
This is a opinion dynamics model evolving in a system composed of a finite toroidal lattice network R, three active parties (A,B,C) and a possibly a set of uncommited
inactive voters (0). Parties A,B form the coalition AB. We are under assumption of no external influence into the system.
R is a square lattice network with 50,75,100,....,10000 nodes per side, its boundary conditions embbed R on a torus and can be modified by NetLogo by editing the world. R has orders 2500,5620,...,1000000.
he model goal is to shows and update rule which statistically led profit to the
party with high initial voters.
## HOW IT WORKS
This is a opinion dynamics model evolving in a system composed of a finite toroidal lattice network R, three active parties (A,B,C) and a possibly a set of uncommited
inactive voters (0). Parties A,B form the coalition AB. We are under assumption of no external influence into the system.
R is a square lattice network with 50,75,100,....,10000 nodes per side, its boundary conditions embbed R on a torus and can be modified by NetLogo by editing the world. R has orders 2500,5620,...,1000000.
The model goal is to shows and update rule which statistically led profit to the
party with high initial voters.
## HOW IT WORKS
The model starts by setting the initial conditions: number of coalition nodes (A nodes plus B nodes), third party C nodes, and uncommited nodes O.
Network size can be selected with netorder global variable through selector button by choosing its number of nodes per side among 49 (50x50 nodes), 74 (75x75), 99 (100x100),
114 (115x115) or 149 (150x150), or even network sizes of 499 (500x500) and
999 (1000000). But this model has a slow behaviour setting randomly party opinions
with network sizes greater than 150x150. After selecting netorder variable the world is resized.
The model needs as entries C value (usually fixed to .5#V(R)). C is a value
in [0,1] to indicate the proportion of nodes to be assigned for party C, then we need to indicate A (party A proportion) value having in account that B=C-A thus 0 <= A <= C. Once we have fixed C,A we have B (party B proportion).
With A,B, and C, SETUP procedure determinates persons_party1 = A*#V(R), persons_party2 = B*#V(R), and persons_party3 = C*#V(R).
The repetition scheme can be: with repetition or without, in this case is the selection scheme is WITHOUT REPETITION. In the former it means the model inspect #V(R) nodes per cycle but may repeat nodes (faster option), in the later is inspected exactly #V(R) nodes per cycle (low speed option).
If global variable totaladistribuir is less than V(R) then initialization process distribute a total of V(R)-totaladistribuir null nodes.
It has two main procedures: SETUP and INICIO
SETUP
Setup procedure initialize the world conditions by distributing active agents
into the network, this with an uniform distribution fashion.
Starts computing an order list of patches npixel starting from (patch 0 1)
and finishing with (patch netorder netorder).
SETUP initialize i=j=0 then creates npixel list by set (netorder + 1)^2 = #V(R)
thus an exterior cycle of (netorder + 1) repetitions for j=0,...,99 each
value for j, enters in a cycle of (netorder + 1) repetitions for i=0,...,99 and
fill list npixel with patch i j, i.e:
npixel = [(0 0) (0 1) ... (0 99) (1 0) (1 1) ... (1 99) ... (99 0) (99 1) ... (99 99)]
Using npixel list SETUP distributes randomly voters for A, by repeating persons_party1
times the selection of a random index z for npixel, this is acomplished by
set z random N (with N<-#V(R)), then setting patch at item z npixel its variables party = 1, pcolor = 2, influencia = 1, after that interchange item z npixel with
item N npixel, and decreasing N to N-1, with this erasing item z npixel,
After initialize A's N has the value N-persons_party1, then applies same mechanism
for B: repeat a cycle of persons_party2 lenght then, select a random index
set z random N, then change its party, pcolo and influence of patch at item z of npixel.
At this point N has value N - pensons_party1 - persons_party2. Finally, by same
way distribute C patches.
Initialize tparty_1,...,tparty3, with the number of patches with color A,B and C
and tparty_4, tparty_5 with the number of 0's and A+B's respectively.
Initialize variables contempate-mr (mayority rule draws) and contempate-ab (coalition draws) to 0.
Initialize actualization variables contadorAct (number of patches supposed to
be inspected) and contadorActNull (number of patches inspected before 0's disappear).
Initialize list P1,P2,P3, negro, blanco, to empty list.
Those list saves the number of A,B,C,O, and A+B patches
after each cycle.
Decides by comparing cardinalities tparty_1 and tparty_2, who is the minor population party, and saves it in menorav, mayorav variables.
Then compute initial proportion in variable propini: minor party / mayorp party,
and propiniab: minor party / (mayor party + minor party).
INICIO
Then INICIO procedure starts the dynamics on nodes, mainly according to MR.
Exists several monitor buttons which helps to the observer to follow
the evolution of the variables constantly.
Initially set N again to #V(R) and recover npixel list through Caux list
It has a cycle of 1400 out of what the model evolution is consider to be a stripe
configuration. Previous to enter one cycle we recover npixel list trough Caux
and set N to #V(R).
In one cycle, the procedure
selects #V(R) (leading repetition) patches one by one, ask to any patche
to count its 4-neighbourhood G. At the beginning of one cycle we select randomly
a number z between 0 and N-1 (N stores nnodos = #V(R)), then select the patch
z in npixel list and examine it and its neighbourhood G.
Variables sum-color1, sum-color2, sum-color3, sum-color4 stores A's, B´s and C's in G. Since sum-colori with i=1,...,4
not takes in accout patche itself the procedure looks at patche inspected and its
color then depending the case, sum-colori increases by 1.
set sum-colori sum-colori + 1
After 4-neighbourhood inspection, procedure select if changes to G would be needed,