modelo t-types c-types

extensions [ ]
globals
[
  a ; parámetro del t-type

  b ; parámetro de la cantidad de neighbors con el mismo c-type

  c ; parámetro de la cantidad de neighbors con distinto c-type

  tt_opciones
]
patches-own
[
  c-type ;; crowding type

  c-type_old ; crowding type del período anterior

  t-type ;; taste type

  total_1
  total_2
  total_3
  total_4
  total_5
  u_1
  u_2
  u_3
  u_4
  u_5
  cluster
  clus
  dato_cluster
]

to setup

  clear-all
 set tt_opciones ct_opciones ; para tener la misma cantidad de crowding types y de taste types

if ( comport = "Pavloviano" ) [
  set a 1
  set b 1
  set c 1
  ]
if  ( comport = "conformista" )
  [ set a 0
    set b 0
    set c 1
  ]
 if ( comport = "averso_perdida" )
 [ set a 1
   set b 1
   set c 2
  ]
if ( comport = "exclusivo" )
 [ set a 1
   set b -1
   set c -1
  ]

ask patches [
   set cluster nobody ; para contar los grupos

   ifelse ( c_type_valor? ) [ ; le damos un porcentaje de agentes con c-type 1 y el resto se divide aleatoriamente

    ifelse ( random-float 1.000 <= c-type_1 ) [ set c-type 1 ] [ set c-type ( 2 + random ((ct_opciones - 1)))]
      set t-type 1 + random ( tt_opciones ) ; los taste types se dividen de manera aleatoria

      recolor-patch ]
   ; en este caso, el porcentaje de crowding types también se genera de manera aleatoria

    [ set c-type 1 + random ( ct_opciones )
      set t-type 1 + random ( tt_opciones )
      recolor-patch ]
    ]
; en este caso, se setea el modelo para las vecindades de Moore o Von Neumann

ask patches
[ if ( vecindad = "Moore" )
     [ set total_1 count neighbors with [ c-type = 1 ]
       set total_2 count neighbors with [ c-type = 2 ]
       set total_3 count neighbors with [ c-type = 3 ]
       set total_4 count neighbors with [ c-type = 4 ]
       set total_5 count neighbors with [ c-type = 5 ]
      ; ahora, para cada individuo se calcula la utilidad de cada c-type

      ; notar que cuando coincide el t-type con el c-type, es mayor la utilidad

       set u_1 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 1 ) [ 1 ] [ 0 ] ) + b * ( total_1 / count neighbors ) - c * ( count neighbors with [ c-type != 1 ] / count neighbors )
       set u_2 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 2 ) [ 1 ] [ 0 ] ) + b * ( total_2 / count neighbors ) - c * ( count neighbors with [ c-type != 2 ] / count neighbors )
       set u_3 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 3 ) [ 1 ] [ 0 ] ) + b * ( total_3 / count neighbors ) - c * ( count neighbors with [ c-type != 3 ] / count neighbors )
       set u_4 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 4 ) [ 1 ] [ 0 ] ) + b * ( total_4 / count neighbors ) - c * ( count neighbors with [ c-type != 4 ] / count neighbors )
       set u_5 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 5 ) [ 1 ] [ 0 ] ) + b * ( total_5 / count neighbors ) - c * ( count neighbors with [ c-type != 5 ] / count neighbors ) ]
   if (vecindad = "VN")
     [ set total_1 count neighbors4 with [ c-type = 1 ]
       set total_2 count neighbors4 with [ c-type = 2 ]
       set total_3 count neighbors4 with [ c-type = 3 ]
       set total_4 count neighbors4 with [ c-type = 4 ]
       set total_5 count neighbors4 with [ c-type = 5 ]
       set u_1 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 1 ) [ 1 ] [ 0 ] ) + b * ( total_1 / count neighbors4 ) - c * ( count neighbors with [ c-type != 1 ] / count neighbors4 )
       set u_2 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 2 ) [ 1 ] [ 0 ] ) + b * ( total_2 / count neighbors4 ) - c * ( count neighbors with [ c-type != 2 ] / count neighbors4 )
       set u_3 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 3 ) [ 1 ] [ 0 ] ) + b * ( total_3 / count neighbors4 ) - c * ( count neighbors with [ c-type != 3 ] / count neighbors4 )
       set u_4 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 4 ) [ 1 ] [ 0 ] ) + b * ( total_4 / count neighbors4 ) - c * ( count neighbors with [ c-type != 4 ] / count neighbors4 )
       set u_5 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 5 ) [ 1 ] [ 0 ] ) + b * ( total_5 / count neighbors4 ) - c * ( count neighbors with [ c-type != 5 ] / count neighbors4 ) ]
]
  reset-ticks
end 

to go
; para guardar los valores anteriores

ask patches
[  set c-type_old c-type
   set cluster nobody
   if ( clus > 0 ) [ set dato_cluster clus ]
   set clus  0
]

; con las preferencias individuales (t-types) y los c-types

  ask patches
    [ set c-type ifelse-value (( u_1 > u_2 ) and (u_1 > u_3) and (u_1 > u_4) and (u_1 > u_5)) [ 1 ][
       ifelse-value ((u_2 > u_1) and (u_2 > u_3) and (u_2 > u_4) and (u_2 > u_5)) [ 2 ] [
        ifelse-value ((u_3 > u_1) and (u_3 > u_2) and (u_3 > u_4) and (u_3 > u_5))[ 3 ] [
         ifelse-value ((u_4 > u_1) and (u_4 > u_2) and (u_4 > u_3) and (u_4 > u_5)) [ 4 ] [
          ifelse-value ((u_5 > u_1) and (u_5 > u_2) and (u_5 > u_3) and (u_5 > u_4)) [ 5 ] [ 1 + random ct_opciones ]]]]]
     recolor-patch ]

; mutaciones (existe una probabilidad que ocurra un cambio en las elecciones del agente)

ask patches
 [ if ( random-float 1.000 <= prob_mut ) [ set c-type 1 + random ct_opciones ]
     recolor-patch ]

; Para exportar la pantalla o el gráfico

;      export-interface (word "frame_23" but-first (word (100 + ticks)) ".png")

;      export-plot (word ticks ".png")

;      export-interface (word ticks ".png")


      tick

; ahora se calculan utilidades de cada opción, luego de la elección del producto

ask patches
[ if ( vecindad = "Moore" )
     [ set total_1 count neighbors with [ c-type = 1 ]
       set total_2 count neighbors with [ c-type = 2 ]
       set total_3 count neighbors with [ c-type = 3 ]
       set total_4 count neighbors with [ c-type = 4 ]
       set total_5 count neighbors with [ c-type = 5 ]
       set u_1 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 1 ) [ 1 ] [ 0 ] ) + b * ( total_1 / count neighbors ) - c * ( count neighbors with [ c-type != 1 ] / count neighbors )
       set u_2 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 2 ) [ 1 ] [ 0 ] ) + b * ( total_2 / count neighbors ) - c * ( count neighbors with [ c-type != 2 ] / count neighbors )
       set u_3 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 3 ) [ 1 ] [ 0 ] ) + b * ( total_3 / count neighbors ) - c * ( count neighbors with [ c-type != 3 ] / count neighbors )
       set u_4 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 4 ) [ 1 ] [ 0 ] ) + b * ( total_4 / count neighbors ) - c * ( count neighbors with [ c-type != 4 ] / count neighbors )
       set u_5 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 5 ) [ 1 ] [ 0 ] ) + b * ( total_5 / count neighbors ) - c * ( count neighbors with [ c-type != 5 ] / count neighbors ) ]
   if (vecindad = "VN")
     [ set total_1 count neighbors4 with [ c-type = 1 ]
       set total_2 count neighbors4 with [ c-type = 2 ]
       set total_3 count neighbors4 with [ c-type = 3 ]
       set total_4 count neighbors4 with [ c-type = 4 ]
       set total_5 count neighbors4 with [ c-type = 5 ]
       set u_1 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 1 ) [ 1 ] [ 0 ] ) + b * ( total_1 / count neighbors4 ) - c * ( count neighbors with [ c-type != 1 ] / count neighbors4 )
       set u_2 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 2 ) [ 1 ] [ 0 ] ) + b * ( total_2 / count neighbors4 ) - c * ( count neighbors with [ c-type != 2 ] / count neighbors4 )
       set u_3 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 3 ) [ 1 ] [ 0 ] ) + b * ( total_3 / count neighbors4 ) - c * ( count neighbors with [ c-type != 3 ] / count neighbors4 )
       set u_4 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 4 ) [ 1 ] [ 0 ] ) + b * ( total_4 / count neighbors4 ) - c * ( count neighbors with [ c-type != 4 ] / count neighbors4 )
       set u_5 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 5 ) [ 1 ] [ 0 ] ) + b * ( total_5 / count neighbors4 ) - c * ( count neighbors with [ c-type != 5 ] / count neighbors4 ) ]
]

if (ticks = 1 or ticks = 5 or ticks = 10 or ticks = 15 or ticks = 20 or ticks = 25 or ticks = 30 or ticks = 35 or ticks = 40 or ticks = 45 or ticks = 50 or ticks = 55 or ticks = 60) [ find-clusters ]
end 

to go-global
; este caso sirve para mostrar el desarrollo del modelo cuando los individuos toman en cuenta la información de todos los agentes

; es igual que "GO" pero la vecindad es el conjunto de todos los individuos

ask patches
  [ set total_1 count patches with [ c-type = 1 ]
    set total_2 count patches with [ c-type = 2 ]
    set total_3 count patches with [ c-type = 3 ]
    set total_4 count patches with [ c-type = 4 ]
    set total_5 count patches with [ c-type = 5 ]
    set u_1 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 1 ) [ 1 ] [ 0 ] ) + b * ( total_1 / count patches ) - c * ( count patches with [ c-type != 1 ] / count patches )
    set u_2 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 2 ) [ 1 ] [ 0 ] ) + b * ( total_2 / count patches ) - c * ( count patches with [ c-type != 2 ] / count patches )
    set u_3 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 3 ) [ 1 ] [ 0 ] ) + b * ( total_3 / count patches ) - c * ( count patches with [ c-type != 3 ] / count patches )
    set u_4 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 4 ) [ 1 ] [ 0 ] ) + b * ( total_4 / count patches ) - c * ( count patches with [ c-type != 4 ] / count patches )
    set u_5 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 5 ) [ 1 ] [ 0 ] ) + b * ( total_5 / count patches ) - c * ( count patches with [ c-type != 5 ] / count patches ) ]

ask patches
[  set c-type_old c-type ]
  ask patches
    [ set c-type ifelse-value (( u_1 > u_2 ) and (u_1 > u_3) and (u_1 > u_4) and (u_1 > u_5)) [ 1 ][
       ifelse-value ((u_2 > u_1) and (u_2 > u_3) and (u_2 > u_4) and (u_2 > u_5)) [ 2 ] [
        ifelse-value ((u_3 > u_1) and (u_3 > u_2) and (u_3 > u_4) and (u_3 > u_5))[ 3 ] [
         ifelse-value ((u_4 > u_1) and (u_4 > u_2) and (u_4 > u_3) and (u_4 > u_5)) [ 4 ] [
          ifelse-value ((u_5 > u_1) and (u_5 > u_2) and (u_5 > u_3) and (u_5 > u_4)) [ 5 ] [ 1 + random ct_opciones ]]]]]
     recolor-patch ]

; mutaciones

ask patches
 [ if ( random-float 1.000 <= prob_mut ) [ set c-type 1 + random ct_opciones ]
     recolor-patch ]

; Para exportar la pantalla

;      export-interface (word "frame_2" but-first (word (100000 + ticks)) ".png")

;      export-plot (word ticks ".png")



      tick


;      export-interface (word ticks ".png")

  ask patches
     [ set total_1 count patches with [ c-type = 1 ]
       set total_2 count patches with [ c-type = 2 ]
       set total_3 count patches with [ c-type = 3 ]
       set total_4 count patches with [ c-type = 4 ]
       set total_5 count patches with [ c-type = 5 ]
       set u_1 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 1 ) [ 1 ] [ 0 ] ) + b * ( total_1 / count patches ) - c * ( count patches with [ c-type != 1 ] / count patches )
       set u_2 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 2 ) [ 1 ] [ 0 ] ) + b * ( total_2 / count patches ) - c * ( count patches with [ c-type != 2 ] / count patches )
       set u_3 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 3 ) [ 1 ] [ 0 ] ) + b * ( total_3 / count patches ) - c * ( count patches with [ c-type != 3 ] / count patches )
       set u_4 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 4 ) [ 1 ] [ 0 ] ) + b * ( total_4 / count patches ) - c * ( count patches with [ c-type != 4 ] / count patches )
       set u_5 a * ( 1 / ct_opciones ) * ( ifelse-value (t-type = 5 ) [ 1 ] [ 0 ] ) + b * ( total_5 / count patches ) - c * ( count patches with [ c-type != 5 ] / count patches )

       ]
end 

to recolor-patch  ;; colores diferentes para cada c-type

  ifelse c-type = 1 [ set pcolor red + 1] [
   ifelse c-type = 2 [ set pcolor green + 1 ][
    ifelse c-type = 3 [ set pcolor blue ][
     ifelse c-type = 4 [ set pcolor yellow ] [ set pcolor magenta ]
   ]
  ]
 ]
end 

;;; para contar la cantidad de clusters


to find-clusters
  loop [
    ;; pick a random patch that isn't in a cluster yet

    let seed one-of patches with [cluster = nobody]
    ;; if we can't find one, then we're done!

    if seed = nobody
    [ show-clusters
      stop ]
    ;; otherwise, make the patch the "leader" of a new cluster

    ;; by assigning itself to its own cluster, then call

    ;; grow-cluster to find the rest of the cluster

    ask seed
    [ set cluster self
      grow-cluster ]
  ]
 display
end 

to grow-cluster  ;; patch procedure

  ask neighbors4 with [(cluster = nobody) and
    (pcolor = [pcolor] of myself)]
  [ set cluster [cluster] of myself
    grow-cluster ]
end 

;; once all the clusters have been found, this is called

;; to put numeric labels on them so the user can see

;; that the clusters were identified correctly


to show-clusters
  let counter 1
  loop
  [ ;; pick a random patch we haven't labeled yet

    let p one-of patches with [ clus = 0 ]
    if p = nobody
      [ stop ]
    ;; give all patches in the chosen patch's cluster

    ;; the same label

    ask p
    [ ask patches with [cluster = [cluster] of myself]
      [ set clus counter ] ]
    set counter counter + 1 ]
end