WaningMirrorTeamReflexivity

extensions [nw csv]

directed-link-breed  [bonds bond] ; создание
patches-own [pagenum]

breed [users user]

users-own [
agentname
  t-pagenum
   community-n ;;
  degree
  in-degree
  out-degree
  betweenness
  eigenvector
  closeness
  clustering
  page-rank
  community
  phi
  visits
  rank
  new-rank
  infected
  typ
]

links-own [weight]

globals [
   diameter ;
  wikihistory ;
  wikilog ;
  pages ;; перечень созданных страниц
  communities-n ;; перечень сообществ
  Mdl ; модулярность текущего сообщества


  ]


;;; Очистили,  закрыли и обнулили все,

to setup
clear-all ;
file-close;
 ;;  set-default-shape users "person" ;
    set-default-shape users "circle" ;
   set-default-shape bonds "default" ;
  set wikihistory [] ;
  set wikilog [] ;
  set pages [] ;
end 

to wood
  ask patches

  [ set pagenum 0  if random-float 100 < Chipsdensity [ set pcolor yellow ]    ]



  create-users TNumber [ set color white setxy random-xcor random-ycor set size 2 set agentname who

  ]
end 

to go

  if length wikilog > Turns [stop] ;; ограничитель числа ходов
  search-for-chip
  find-new-pile
  put-down-chip
end 

to search-for-chip  ;; turtle procedure -- "picks up chip" by turning orange
  ifelse pcolor = yellow [
    ;; Если это палочка, которую не брали, то надо записать в журнал, что я создал эту новую палочку
     ifelse 0 = [pagenum] of patch-here [
       let newpage 1 + length pages set pages lput newpage pages
       set t-pagenum newpage ;; это номер палочки, которую создал
            set wikilog lput (se [who] of self newpage "create" ) wikilog
       ]
     [set t-pagenum [pagenum] of patch-here ;; а если палочка, которую уже кто-то создал, то я записал себе номер этой палочки
       ]
    ;;
    set pcolor black  set color orange  fd 20 ] ;; взял палочку, и с этой палочкой пошел
  [ wiggle     search-for-chip ]  ;; а если ты не нашел, то продолжай поиск
end 

to find-new-pile  ;; turtle procedure -- look for yellow patches
  ;; это он ищет новую палочку, как только найдет - остановится и запустится put-down-chip
  if pcolor != yellow
  [ wiggle find-new-pile ]
end 

to put-down-chip  ;; turtle procedure -- finds empty spot & drops chip
  ;;; смотри - вот я нашел место, где могу положить палочку - я сюда положил палочку и ушел.
  ;; И записал в журнале, что я палочку положил
  ifelse pcolor = black   ;; в первой проверке это не так, потому что я только что нашел новую палочку, я теперь покручусь вокруг, найду новое пустое место и там палочку положу
  [
    ;; Передаю пятну номер статьи, которая тут теперь лежит

    ask patch-here [set pagenum [t-pagenum] of myself]
   set wikilog lput (se [who] of self [t-pagenum] of self "edit" ) wikilog
  ;;
    set pcolor yellow
    set color white
    set t-pagenum 0
    get-away ]
  [ rt random 360
    fd 1
    put-down-chip ]
end 

to get-away  ;; turtle procedure -- escape from yellow piles
  rt random 360
  fd 20
  if pcolor != black
    [ get-away ]
end 

to wiggle ; turtle procedure
  fd 1
  rt random 50
  lt random 50
end 

to load_file
   file-open user-file
           while [ not file-at-end? ]     [
         let newline  csv:from-row file-read-line
    if not member? newline  wikihistory  [set wikihistory  lput newline wikihistory]
            ]
             file-close
foreach wikihistory [ [?1] ->
    let username item 0 ?1
    let pagename item 1 ?1
    if count users with [agentname = username] = 0 [create-ordered-users 1 [set agentname username] ] ;;; Может быть и список агентов вести
    let who_user [who] of one-of users with [agentname = username] ;
        ifelse not member? pagename pages
    [ set pages lput pagename pages
      set wikilog lput (list  who_user pagename "create") wikilog ]
    [set wikilog  lput (list  who_user pagename "edit") wikilog  ]
  ]
end 

to logs_to_sociogram
ask patches [set pcolor 0]
  ;; пока связи идут только от редакторов к автору статьи
  foreach edits [ [?1] ->
    let friend1 item 0 ?1
    let p1 item 1 ?1
    let friend2 first first filter [ [??1] -> (p1 = item 1 ??1) and ("create" = item 2 ??1) ] wikilog
    if friend1 != friend2 [
    ask turtle friend1 [ create-bond-to turtle friend2 ]
    ]

    ]

  repeat 8 [layout-spring  turtles links 1 5 7 ]
end 

to-report edits
report filter [ [?1] -> "edit" = item 2 ?1 ] wikilog
end 




;;;   Нормированная центральности

to-report norm-betweenness
;;  if count turtles > 4 [
    report nw:betweenness-centrality /  ((count turtles - 1) *  (count turtles - 2) / 2 )
;;]
;;  report 0
end 

to-report centralization-btw
 let znm ((count turtles - 1) * (count turtles - 1) *  (count turtles - 2)) / 2 ;
 let mx  max [nw:betweenness-centrality] of turtles ;
report (sum map [ ?1 -> mx - ?1 ] [nw:betweenness-centrality] of turtles ) / znm
end 


;; Посмотреть тех, у кого максимальная центральность

to see_Btw
  ask turtles [ht]
 ;; ask links [hide-link]
 foreach sublist reverse sort-on [norm-betweenness] users 0 9
 [ ?1 -> ask ?1 [st set size 2 set label-color red set label norm-betweenness ] ]
end 


;;; Посмотреть на 1 максимальную клику
;; Только для ненаправленного графа

to see_Bcliq
  ask turtles [ht]
  ask links [hide-link]
 let BigCliq one-of nw:biggest-maximal-cliques

  ask BigCliq [st]
  let BigCliqLinks links with [(member? end1 BigCliq) and  (member? end2 BigCliq) ]
  ask BigCliqLinks [show-link]
layout-spring  BigCliq BigCliqLinks 1 10 1
end 

;;; Это мы извлекаем из графа отдельные группировки и на них смотрим

to see_Mcliq
  ask turtles [ht]
  ask links [hide-link]
   foreach nw:maximal-cliques [ ?1 -> if  (count ?1) > 12
      [
  let BigCliq ?1
    let BigCliqLinks links with [(member? end1 BigCliq) and  (member? end2 BigCliq) ]
      ask BigCliq [st set size 1.2]
       ask BigCliqLinks [show-link]
       layout-circle BigCliq  20

       ] ]
      layout-circle users with [hidden? = false]  20
end 


 ;; Региональные группы

to see_Group [CL]
 ;; show CL
  ask turtles [ht]
  ask links [hide-link]
  let NewGroup users with [color = CL]

  let GroupLinks links with [(member? end1 NewGroup) and  (member? end2 NewGroup) ]
        ask  NewGroup  [st]
       ask GroupLinks [show-link]
   layout-spring  NewGroup GroupLinks  1 10 1
end 

to shadow_group
  let ShadowCliq users with [hidden? = true]
  let shadowLink links with [hidden? = true]
  ask turtles with [hidden? = false] [ht]
  ask links with [hidden? = false] [hide-link]
     ask ShadowCliq  [st]
      ask shadowLink [show-link]
      layout-spring  ShadowCliq  shadowLink 1 10 15
end 

to-report global-clustering-coefficient
  let closed-triplets sum [ nw:clustering-coefficient * count my-links * (count my-links - 1) ] of turtles
  let triplets sum [ count my-links * (count my-links - 1) ] of turtles
  report closed-triplets / triplets
end 

;;;

to clustC
  nw:set-context users links
let Centr max-one-of users [nw:betweenness-centrality]

layout-radial users links Centr
  ask Centr [set label-color 9.9 set label agentname]
end 

to NewClustC
    nw:set-context users links
let Centr max-one-of users [nw:betweenness-centrality]
ask Centr  [die]
ask users with [count my-links = 0] [die]
set Centr max-one-of users [nw:betweenness-centrality]
  layout-radial users links Centr
  ask Centr [set label-color 9.9   set label agentname]
end 



 ;;;

to biggestClust

  ask turtles [ht]
  ask links [hide-link]
    let BigCliq one-of   nw:bicomponent-clusters
  ask BigCliq [st]
  let BigCliqLinks links with [(member? end1 BigCliq) and  (member? end2 BigCliq) ]
  ask BigCliqLinks [show-link]
layout-circle users with [hidden? = false]  20
end 

to ColorCommunity
  ask users [home st set label "" set color 9.9]
  ask links [hide-link]
  set communities-n nw:louvain-communities
   set communities-n filter [x1 -> count x1 > 2] communities-n
  set communities-n sort-by [[ x1 x2] -> count x1 > count x2] communities-n
  if length communities-n > 14 [set communities-n sublist communities-n  0 13 ]
  let colors sublist  base-colors 0 (length communities-n)
  let radius max-pxcor * 3 / 4
  let dist  n-values length communities-n [ i -> i ]

  ask turtles [set heading 0]
  let angle 360 / length colors

  (foreach reverse communities-n reverse colors dist [ [community1 col dist1] ->
  ask community1 [      set color col set label ""

    rt angle * dist1
      fd (radius   )
   ;;   rt random 360
    ]
;; let Centr max-one-of community1 [nw:betweenness-centrality]

    ask links with [(member? end1 community1) and  (member? end2 community1) ] [show-link]
 repeat 3 [layout-spring community1 links with [(member? end1 community1) and  (member? end2 community1) ]  0.5 0.1 0.2 ]
    ;; попробуй ставить их в точки, зависящие от col
])
end 

to CentralCommunity
    ask users [home st set color 9.9 set label ""]
  ask links [hide-link]
  set communities-n nw:louvain-communities
   set communities-n filter [x1 -> count x1 > 2] communities-n
  set communities-n sort-by [[ x1 x2] -> count x1 > count x2] communities-n
  if length communities-n > 14 [set communities-n sublist communities-n  0 14 ]
  let colors sublist  base-colors 0 (length communities-n)
  let radius max-pxcor - 30
  ask turtles [set heading 0]
 let angle 360 / length colors
  (foreach communities-n colors [ [community1 col] ->
    ask community1 [
     set color col
    ]
 let Centr max-one-of community1 [nw:betweenness-centrality]
     layout-radial community1  links with [(member? end1 community1) and  (member? end2 community1) ] Centr
    ask links with [(member? end1 community1) and  (member? end2 community1) ] [show-link]
  ])
end 

to See_Community [group]
 ;; show CL
  ask turtles [ht set label "" set size 1]
  ask links [hide-link]
  let NewGroup group

  let GroupLinks links with [(member? end1 NewGroup) and  (member? end2 NewGroup) ]
        ask  NewGroup  [
    st set size 0.8
    set label agentname
 ;;  set label who
  ]
       ask GroupLinks [show-link
  ]
;;  repeat 7 [ layout-spring  NewGroup GroupLinks  1 10 7 ]
end 

to comm_output

  file-open user-new-file

  foreach  communities-n [
     ?1 ->
set Mdl nw:modularity (list ?1 ?1 )
    file-print csv:to-row
    (list
      count  ?1
   precision   Mdl  3

    )
    ]

 file-close
end 

to tmm
  show nw:modularity (list (turtles with [ color = 5 ])
    (turtles with [ color = 15 ]) (turtles with [ color = 25 ])  (turtles with [ color = 35 ]) (turtles with [ color = 45 ])  (turtles with [ color = 55 ]) (turtles with [ color = 65 ])
    (turtles with [ color = 75 ])
   (turtles with [ color = 85 ])
    (turtles with [ color = 95 ])
   (turtles with [ color = 105 ])
  (turtles with [ color = 115 ])
 ;;   (turtles with [ color = 9.9 ])
  )
end 



; Auxiliary reports to split a string using a substring

to-report split-aux [s s1]
  ifelse member? s1 s
  [ let p position s1 s
    report (list (substring s 0 p) (substring s (p + (length s1)) (length s)))
  ]
  [ report (list s "")
  ]
end 

to-report split [s s1]
  ifelse member? s1 s
  [
    let sp split-aux s s1
    report (fput (first sp) (split (last sp) s1))
  ]
  [ report (list s) ]
end 

to-report join [s c]
  report reduce [[s1 s2] -> (word s1 c s2)] s
end 

to-report replace [s c1 c2]
  report join (split s c1) c2
end 

to-report store [val l]
  report lput val l
end 

to inspect-user
  if mouse-down? [
    ask users [stop-inspecting self]
    let selected min-one-of users [distancexy mouse-xcor mouse-ycor]
    if selected != nobody [
      ask selected [
        if distancexy mouse-xcor mouse-ycor < 1 [inspect self]
      ]
    ]
    wait .2
  ]
end 

to plotTable [Lx Ly]
  set-current-plot "General"
  clear-plot
  set-plot-x-range (min Lx) (max Lx)
  set-plot-y-range (min Ly) (max Ly)
  (foreach Lx Ly
    [ [x y] ->
      plotxy x y
    ])
end 

;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;; Centrality Measures
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;


;; Takes a centrality measure as a reporter task, runs it for all users
;; and set labels, sizes and colors of turtles to illustrate result

to compute-centralities
  nw:set-context users links
  ask users [
    set degree (count my-links)
    set in-degree (count my-in-links)
        set out-degree (count my-out-links)
  ;; set betweenness nw:betweenness-centrality
 set betweenness norm-betweenness
    set eigenvector nw:eigenvector-centrality
    set closeness nw:closeness-centrality
    set clustering nw:clustering-coefficient
    set page-rank nw:page-rank
  ]
  update-plots
end 

to plot-degree
  Let Dk [degree] of users
  let M max Dk
  set-current-plot "Degree Distribution"
  set-plot-x-range 0 (M + 1)
  set-plot-y-range 0 1
  histogram Dk
end 

to plot-page-rank
  Let Dk [page-rank] of users
  let M max Dk
  set-current-plot "PageRank Distribution"
  set-plot-x-range 0 (M + M / 100)
  set-plot-y-range 0 1
  set-histogram-num-bars 100
  histogram Dk
end 

to plot-betweenness
;; Let Dk [nw:betweenness-centrality] of users
  Let Dk [norm-betweenness] of users
  let M max Dk
  set-current-plot "Betweenness Distribution"
  set-plot-x-range 0 (ceiling M)
  set-plot-y-range 0 1
  set-histogram-num-bars 100
  histogram Dk
end 

to plot-eigenvector
  Let Dk [nw:eigenvector-centrality] of users
  let M max Dk
  set-current-plot "Eigenvector Distribution"
  set-plot-x-range 0 (ceiling M)
  set-plot-y-range 0 1
  set-histogram-num-bars 100
  histogram Dk
end 

to plot-closeness
  Let Dk [nw:closeness-centrality] of users
  let M max Dk
  set-current-plot "Closeness Distribution"
  set-plot-x-range 0 (ceiling M)
  set-plot-y-range 0 1
  set-histogram-num-bars 100
  histogram Dk
end 

to plot-clustering
  Let Dk [nw:clustering-coefficient] of users
  let M max Dk
  set-current-plot "Clustering Distribution"
  set-plot-x-range 0 (ceiling M)
  set-plot-y-range 0 1
  set-histogram-num-bars 100
  histogram Dk
end 

to plots
  clear-all-plots
  compute-centralities
  carefully [plot-page-rank][]
  carefully [plot-degree][]
  carefully [plot-betweenness][]
  carefully [plot-eigenvector][]
  carefully [plot-closeness][]
  carefully [plot-clustering][]
 carefully [set diameter compute-diameter 1000][]
end 

;; We want the size of the turtles to reflect their centrality, but different measures
;; give different ranges of size, so we normalize the sizes according to the formula
;; below. We then use the normalized sizes to pick an appropriate color.

to normalize-sizes-and-colors [c]
  if count users > 0 [
    let sizes sort [ size ] of users ;; initial sizes in increasing order
    let delta last sizes - first sizes ;; difference between biggest and smallest
    ifelse delta = 0 [ ;; if they are all the same size
      ask users [ set size 1 ]
    ]
    [ ;; remap the size to a range between 0.5 and 2.5
     ask users [ set size ((size - first sizes) / delta) * 10.5 + 0.4
     ;   ask users [ set size ((size - first sizes) / delta) * 5.5 + 0.4

      ]
    ]
    ask users [ set color c ]
  ;;  lput 200 extract-rgb scale-color c size 3.8 0
  ;; ] ; using a higher range max not to get too white...
  ]
end 

; The diameter is cpmputed from a random search on distances between users

to-report compute-diameter [n]
  let s 0
  repeat n [
    ask one-of users [
      set s max (list s (nw:distance-to one-of other users))
    ]
  ]
  report s
end 

to-report Average-Path-Length
  report nw:mean-path-length
end 

to-report Average-Clustering
  report mean [clustering] of users
end 

to-report Average-Betweenness
  report mean [betweenness] of users
end 

to-report Average-Closeness
  report mean [closeness] of users
end 

to-report Average-PageRank
  report mean [page-rank] of users
end 

to-report Average-Eigenvector
  report mean [eigenvector] of users
end 

to-report Average-Degree
  report mean [count my-links] of users
end 

to-report Number-users
  report count users
end 

to-report Number-Links
  report count Links
end 

to-report Density
  report 2 * (count links) / ( (count users) * (-1 + count users))
end 

to-report All-Measures
  report (list Number-users
               Number-Links
               Density
               Average-Degree
               Average-Path-Length
               Diameter
               Average-Clustering
               Average-Betweenness
               Average-Eigenvector
               Average-Closeness
               Average-PageRank
               )
end 

to post-process
  ask links [
    ;set color black
    set color [100 100 100 100]
  ]
  set diameter compute-diameter 1000
end 

;; Mutual Links

to-report Mutual
end 


;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;; Page Rank
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

to PRank [n]
  let damping-factor 0.85
  ;ask links [ set color gray set thickness 0 ]
  ask users [
    set rank 1 / count users
    set new-rank 0 ]
  repeat N [
    ask users
    [
      ifelse any? link-neighbors
      [
        let rank-increment rank / count link-neighbors
        ask link-neighbors [
          set new-rank new-rank + rank-increment
        ]
      ]
      [
        let rank-increment rank / count users
        ask users [
          set new-rank new-rank + rank-increment
        ]
      ]
    ]
    ask users
    [
      ;; set current rank to the new-rank and take the damping-factor into account
      set rank (1 - damping-factor) / count users + damping-factor * new-rank
    ]
  ]

  let total-rank sum [rank] of users
  let max-rank max [rank] of users
  ask users [
    set size 0.2 + 2 * (rank / max-rank)
  ]
end 

to spring_all
    let factor sqrt count turtles

  repeat 15 [layout-spring turtles links (1.5 / factor) (7 / factor) (1 / factor)]
 ;; repeat 50 [ layout-spring (turtles with [any? link-neighbors]) links 0.4 6 1 ]
end 


;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;