Projet_14.nlogo_3d.nlogo3d

extensions [sound nw] ;; For using soune and Network package

globals [
  min-prevalence ;; minimale value of prevalence
  max-prevalence ;; maximal value of prevalence
  meta-influencers-droit ;; Method of sélection for meta-influencers right field
  meta-influencers-gauche ;; Methode of sélection for meta-influencers left field
  iter change total try major
  ordonnee abcisse profondeur
  list_data file-in in_data in repet_data
  opinion-previous
]

turtles-own [
  opinion ;; Opinion value of agent, between -1 and 1
  prevalence ;; Prevalence of agent, between min-prevalence and max-prevalence
  agent-type ;; Agent type : "Right side" or "Left side"
  influence ;; Agent level of influence, between  0 and 1
  infl_list
]

to setup
  clear-all
  set repet_data false
  set iter 0
  set min-prevalence 0
  set max-prevalence 99
  set-default-shape turtles "person"
  set try 1
  set major 0
  create
  rapport
end 

to create
  ;; Créer les agents Right sides
  create-turtles pop / 2 [
    set agent-type "Right side"
    set opinion random-float 1 ;; Agent random opinion attribution between 0 and 1
    if opinion > 0 [set color blue]
    set prevalence random-float (opinion * 100) ;; Agent random prevalence attribution in function of opinion polarization
    set influence random-float 1 ;; Agent random influence attribution between 0 and 1
    set abcisse opinion * 16
    set ordonnee prevalence / 5.9
    set profondeur influence * 16
    setxyz abcisse ordonnee profondeur
  ]

  ;; Créer les agents Left sides
  create-turtles pop / 2 [
    set agent-type "Left side"
    set opinion random-float 1 - 1 ;; Agent random opinion attribution between -1 and 0
    if opinion < 0 [set color red]
    set prevalence random-float ((abs(opinion)) * 100) ;; Agent random prevalence attribution in function of opinion polarization
    set influence random-float 1 ;; Agent random influence attribution between 0 and 1
    set abcisse opinion * 16
    set ordonnee prevalence / 5.9
    set profondeur influence * 16
    setxyz abcisse ordonnee profondeur
  ]

influenceurs ;; create metas-influencers
  reset-ticks
  ;; Créer un réseau social
  if random_links = true [ask turtles [
    ask other turtles [
      if random-float 1 < 0.1 [
        create-link-with myself
      ]
    ]
    ask links [hide-link]
  ]]
  if random_links = false [
    update-networks update-networks]
  set total 0
  set change 0
end 

to rapport
   ;; titles for Statistics or Values inside compute-statistics
   if output = "Statistics" [
      output-print (word "Try ; " "Iter ; " "Opinion global ; " "Opinion right side ; " " Opinion left side ; " "Prevalence right side ; " "Prevalence left side ; " "Influence right side ; " "Influence left side ; "  "Major")
  ]
  if output = "Values" [output-print (word "Try ; " "Ticks ; "  "Agents ; " "Prevalence ; " "Opinion ; " "Influence ;" " meme droit") ]

  if output = "File" [
     ask turtles [
    let pre prevalence
    let mem opinion
    let infl influence
    let ti ticks
    output-print (word ti " " pre " " mem " " infl )
    ]
  ]
end 

to influenceurs
  ;; create status of meta-influencers
  if meta-influencers-selection = "All" [
    ask n-of (round (count turtles * meta-influencers)) turtles [
      set influence 1 ;; maximal influence  (1) to X % of agents
    set color yellow
  ]
  ]
  if meta-influencers-selection = "Right side" [
    set meta-influencers-droit round (count turtles * meta-influencers)
    ask n-of meta-influencers-droit turtles with [opinion > 0 ] [
      set influence 1 ;; maximal influence  (1) to X % of agents from type "Right side"
       set color yellow
    ]
  ]
  if meta-influencers-selection = "Left side" [
   set meta-influencers-gauche round (count turtles * meta-influencers)
    ask n-of meta-influencers-gauche turtles with [opinion < 0] [
      set influence 1 ;; maximal influence  (1) to X % of agents from type "Left side"
      set color yellow
    ]
  ]
end 

to go
   ifelse iter < max_iter [set iter iter + 1
   if auto_event = true [if tick-event = iter [event]]
    update-opinions
  if output = "Statistics" [ let avg-opinion mean [opinion] of turtles
  let positive-opinion median [opinion] of turtles with [opinion >= 0]
  let negative-opinion median [opinion] of turtles with [opinion < 0]
  let positive-prevalence median [prevalence] of turtles with [opinion >= 0] / 100
  let negative-prevalence median [prevalence] of turtles with [opinion < 0] / 100
  let negative-influence median [influence] of turtles with [opinion < 0]
  let positive-influence median [influence] of turtles with [opinion >= 0]
  Let Maj Major
  let ti iter
  output-print (word try " ; " ti " ; " avg-opinion " ; " positive-opinion " ; " negative-opinion " ; " positive-prevalence " ; " negative-prevalence " ; " positive-influence " ; " negative-influence " ; " Maj)
  ]
  tick
  if cumulative = False [set change 0
      set total 0]
  colorer
  ;;rafraichir le graphique
  if refresh = true [if ticks > 200 [reset-ticks
      clear-plot]]
  ;set iter iter + 1
    if threshold <= (count turtles with [opinion > 0]) / (pop / 100) [set major major + 1]
    ] [ifelse try < nb_try [set try try + 1 set major 0 clear-turtles clear-plot ifelse repet_data = true [data] [create]
  set iter 0
  set Major 0
  set min-prevalence 0
  set max-prevalence 99]
    [sound:play-note "Tubular Bells" 60 64 1 stop]]
end 

to update-opinions
  ask turtles [
    let target one-of link-neighbors ;; Selecting a neighbor randomly in the social network
    if target != nobody [ ;; verifying that this neighbor exist
      let difference-in-prevalence [prevalence] of self - [prevalence] of target ;; Calculer la différence de prégnance entre les deux agents
      ;; If the prevalence of the agent is lower than that of the neighbour, the agent adopts the opinion of the neighbor with a probability proportional to the difference of prevalence
      if difference-in-prevalence < 0 [
        let probability-of-adoption abs difference-in-prevalence / max-prevalence ;; Calculate the probability of adoption based on the difference in prevalence
        let opinion-difference abs (opinion - [opinion] of target) ;; Calculate the difference of opinion between the agent and the neighbor
         set opinion-difference opinion-difference * [influence] of target

        ;; Change adoption likelihood based on bias and influence
        set probability-of-adoption probability-of-adoption * (1 - polarization-factor * opinion-difference)

        ;filter the probability of adoption based on neighbor influence and agent influence.
        if ([influence] of target > probability-of-adoption or [influence] of self < probability-of-adoption ) [set opinion-previous opinion ;random-float 1
          set opinion [opinion] of target ;Adopt the neighbor's opinion
          set total total + 1 ;print total

          ;make the influence of the agent evolve according to the change of opinion of the agent
          if vary-influence = true [if abs(opinion-previous) > abs (opinion) [set influence (influence + rate-infl) if influence > 1 [set influence 1]]
              if abs(opinion-previous) < abs (opinion) [set influence (influence - rate-infl)  if influence < 0 [set influence 0]]] ; faire varier l'influence
          if (opinion < 0 and opinion-previous > 0) or (opinion > 0 and opinion-previous < 0) [set change change + 1]
        ]]
        ]

   ;;modulation of the prevalence according to the difference of opinion
   if modulation-prevalence = true [
      if prevalence > abs opinion * 100 [set prevalence prevalence - abs (opinion - opinion-previous) * [influence] of self * Rate-modulation]
      if prevalence < abs opinion * 100 [set prevalence prevalence + abs (opinion - opinion-previous)  * [influence] of self * Rate-modulation]
  ]
    ;; add stochastic noise to each iteration
    if random-float 1 < noise [
      ;; Change the agent's opinion by adding or subtracting a random value less than noise
      set opinion opinion + (random-float 0.4 - 0.2)
      ;; Make sure the opinion stays in the interval [-1, 1]
      if opinion > 1 [ set opinion 1 ]
        if opinion < -1 [ set opinion -1 ]
    ]
    ;;position agents on the chart based on opinion and influence
    set abcisse opinion * 16
    set ordonnee prevalence / 5.9 * 4 / 5
    set profondeur influence * 16
    setxyz abcisse ordonnee profondeur
    if output = "Values" or output = "File" [compute-statistics]
  ]
end 

to colorer ; change the color of agents who have changed sides
  ask turtles [ifelse opinion >= 0 [
      set color blue
    ] [
      set color red
    ]
     if influence = 1 [set color yellow]
  ]
end 

to update-networks
  ;; Remove links between agents with opinions that are too different
  ask links [
    if abs ([opinion] of end1 - [opinion] of end2) > link-removal-threshold [
      die
    ]
  ]

  ;; Form bonds between like-minded agents
  ask turtles [
    let potential-friends other turtles with [abs (opinion - [opinion] of myself) <= link-formation-threshold]
    let friend one-of potential-friends
    if friend != nobody and not link-neighbor? friend [
      create-link-with friend
  ]]
end 

to compute-statistics
 if output = "Values" [
  ;ask turtles [
    let pre prevalence
    let mem opinion
    let infl influence
    let ag who
    let ti ticks
    let ess try
    let memed (count turtles with [opinion > 0]) / (pop / 100)
    let maj major
    output-print (word ess " ; " ti " ; "  ag " ; " pre " ; "  mem " ; " infl " ; " memed)
  ;]
]
  if output = "File" [
     ;ask turtles [
    let pre prevalence
    let mem opinion
    let infl influence
    let ti ticks
    output-print (word ti " " pre " " mem " " infl )
    ;]
  ]
end 

;;reading an input file of list of agents

to in_file ;File d'entrée
  carefully [
    set file-in user-file
    if (file-in != false) [
      set list_data []
      file-open file-in
      while [not file-at-end?] [
        set list_data sentence list_data (list (list file-read file-read file-read file-read))
      ]
      file-close ;; Add this line to close the File after reading it
      user-message "File uploaded!"
      set in true
    ]
  ] [
    user-message "File read error"
  ]
  data
end 

to data
  clear-turtles
  clear-links
  let tick_to_load choice_iter

  ifelse (is-list? list_data) [
    let filtered_data filter [row -> first row = tick_to_load] list_data

    create-turtles length filtered_data [
      let my_index who
      let agent_data item my_index filtered_data

      set prevalence item 1 agent_data
      set opinion item 2 agent_data
      set influence item 3 agent_data
      setxy opinion prevalence

      if opinion < 0 [set color red set agent-type "Left side"]
      if opinion > 0 [set color blue set agent-type "Right side"]
      if influence = 1 [set color yellow]
    ]
  ] [
    set in false user-message "Read error"
  ]
if random_links = true [ask turtles [
    ask other turtles [
      if random-float 1 < 0.1 [
        create-link-with myself
      ]
    ]
  ]]
  if random_links = false [update-networks update-networks]
  influenceurs
update-opinions
set repet_data true
end 

to event ; moving agents to the right or left side by increasing or decreasing the prevalence
  ask turtles [
    ifelse meme_set = true [ if to_left = false [if agent-type = "Right side" [if opinion < 0 [set opinion opinion + event_size if opinion > 1 [set opinion 1]]]]
      if to_left = true [if agent-type = "Left side" [if opinion > 0 [set opinion opinion - event_size if opinion < -1 [set opinion -1]]]]]
    [if to_left = false [if opinion < high_meme and opinion > low_meme and  prevalence < high-prev and prevalence > low-prev [set opinion opinion + event_size
      if prev_change != 0  [set prevalence prevalence + prev_change] if opinion > 1 [set opinion 1]]]
      if to_left = true [if opinion > low_meme  and opinion < high_meme and prevalence > low-prev  and prevalence < high-prev  [set opinion opinion - event_size
      if prev_change != 0  [set prevalence prevalence + prev_change] if opinion < -1 [set opinion -1]]]
    ]]
end