HOTnet (a)

extensions [ nw ]
;; the number of hops from a fixed center of the tree
turtles-own [ nhop ]

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;;; Setup Procedures ;;;
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to setup
  clear-all
  set-default-shape turtles "circle"
  ;; make the initial network of two turtles and an edge
  crt 1 
  [
    set color green
    set nhop 0 
  ] ;; first node unattached is the root of the tree

  crt 1 
  [ 
    setxy random-xcor random-ycor
    set color red
    create-link-with turtle 0 [ set color green ]
    set nhop 1
  ]
  
  reset-ticks
end 

;;;;;;;;;;;;;;;;;;;;;;;
;;; Main Procedures ;;;
;;;;;;;;;;;;;;;;;;;;;;;

to go
  ;; it takes a static picture of the network at the time you call it. 
  ;; All subsequent network operations will use this static picture, even if turtles or links have been created or died 
  ;; in the meantime, until you call set-snapshot again.
  nw:set-snapshot turtles links
  ;; new edge is green, old edges are gray
  ask links [ set color gray ]  
  ;; The behavior of the model depends crucially on the value of alfa:
  ;; if alfa is less than a particular constant depending on the shape of the region, 
  ;; then Euclidean distances are not important, and the resulting network is easily seen to be a star,
  ;; the ultimate in degree concentration, and, depending on how you look at it, the exact opposite, or absurd extreme, of a power law.
  ;; If alfa grows at least as fast as sqrt(n), where n is the final number of points, then Euclidean distance becomes too important, 
  ;; and the resulting graph is a dynamic version of the Euclidean minimum spanning tree, in which high degrees do occur, 
  ;; but with exponentially vanishing probability.
  ;; If, however, alfa is anywhere in between — is larger than a certain constant, but grows slower than sqrt(n) if at all —
  ;; then, almost certainly, the degrees obey a power law.
  ;;let alfa 100
  let x random-xcor
  let y random-ycor
  let partner nobody
  ;; Node i attaches itself to the node j that minimizes the weighted sum of the two objectives:
  ;; alfa * dij + hj
  ;; where dij is the /normalized/ Euclidean distance, and hj is some measure of the “centrality” of node j, such as 
  ;; (a) the average number of hops from other nodes; 
  ;; (b) the maximum number of hops from another node; 
  ;; (c) the number of hops from a fixed center of the tree;
  ;; all three measures result in similar power laws, in this case we use (a).
  set partner min-one-of turtles
  [ 
    alfa * 
    sqrt 
    ( 
      ;;( (x - min-pxcor + 0.5) / (max-pxcor - min-pxcor) - (xcor - min-pxcor + 0.5) / (max-pxcor - min-pxcor) ) ^ 2 + 
      ( (x - xcor) / (max-pxcor - min-pxcor) ) ^ 2 +
      ;;( (y - min-pycor + 0.5) / (max-pycor - min-pycor) - (ycor - min-pycor + 0.5) / (max-pycor - min-pycor) ) ^ 2 
      ( (y - ycor) / (max-pycor - min-pycor) ) ^ 2
    ) 
    + avg-distance self
  ]
  crt 1
  [
    setxy x y
    set color red
    if partner != nobody
    [ 
      create-link-with partner [ set color green ]
      set nhop 1 + [ nhop ] of partner
    ]
  ]
 
  tick
end 
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;; Compute heuristic (a) ;;;
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to-report avg-distance [me]
  let avg-dist 0
  ask me
  [
    let dist n-values count turtles [ nw:distance-to turtle ? ]
    set avg-dist (sum dist) / count turtles 
  ]
  report avg-dist
end 
;;;;;;;;;;;;;;;;;;;;
;;; Compute s(g) ;;;
;;;;;;;;;;;;;;;;;;;;

to-report log-likelihood
  let s 0
  ;; for each link compute di*dj and sum it to s
  ask links 
  [ 
    set s s + [ count link-neighbors ] of end1 * [ count link-neighbors ] of end2 
  ]
  report s
end 
;;;;;;;;;;;;;;;;;;;;;;;;
;;; Compute S-metric ;;;
;;;;;;;;;;;;;;;;;;;;;;;; 

to-report relative-log-likelihood
  let smax 0
  let counter 0
  let di 0
  let child 0

  ;; D = { d1, d2, d3, ..., dn }, d1 >= d2 >= d3 >= ... >= dn
  let degree-sequence sort-by > [ count  link-neighbors ] of turtles
  set di item 0 degree-sequence
  set degree-sequence remove-item 0 degree-sequence
  foreach degree-sequence
  [
    set smax smax + di * ?
    set counter counter + 1
    if di = counter ;; we have iterated through all di's childs; if di = 0 select the highest degree.
    [
      set counter 1 ;; count the parent if it's not the root
      set di item child degree-sequence ;; select child; child = 0 is the root.
      set child child + 1
    ]
  ]

  report log-likelihood / smax
end 

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;;; Save Nodes Degrees to file ;;;
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to save-node-degree-to-file
  if file-exists? "NodeDegrees.txt" [ file-delete "NodeDegrees.txt" ]
  
  file-open "NodesDegree.txt"
  
  ;; save in descending orders
  ;; D = { d1, d2, d3, ..., dn }, d1 >= d2 >= d3 >= ... >= dn
  foreach sort-by > [ count link-neighbors ] of turtles
  [
    file-print ?
  ]
  file-close
end 

;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;; Export Graph Connectivity to txt ;;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

to export-graph
  if file-exists? "HOTGraph.txt" [ file-delete "HOTGraph.txt" ]
  
  file-open "HOTGraph.txt"
  
  ;; write each linked couple of tourtles and their degree
  ask links 
  [ 
    file-type [who] of end1 ;; writes without blank spaces
    file-write [who] of end2 ;; write a space value space
    file-print "" ;; write carriage return
  ]
  file-close
end 

;;;;;;;;;;;;;;
;;; Layout ;;;
;;;;;;;;;;;;;;
;; resize-nodes, change back and forth from size based on degree to a size of 1

to resize-nodes
  ifelse all? turtles [size <= 1]
  [
    ;; a node is a circle with diameter determined by
    ;; the SIZE variable; using SQRT makes the circle's
    ;; area proportional to its degree
    ask turtles [ set size sqrt count link-neighbors ]
    ask turtles with [ size >= 4 ] [ set color violet ]
  ]
  [
    ask turtles 
    [ 
      set size 1 
      set color red
    ]
  ]
end 

to layout
  ;; the number 3 here is arbitrary; more repetitions slows down the
  ;; model, but too few gives poor layouts
  repeat 2 [
    ;; the more turtles we have to fit into the same amount of space,
    ;; the smaller the inputs to layout-spring we'll need to use
    let factor sqrt count turtles
    ;; numbers here are arbitrarily chosen for pleasing appearance
    layout-spring turtles links (3 / factor) (5 / factor) (0.5 / factor)
    display  ;; for smooth animation
  ]
  ;; don't bump the edges of the world
  let x-offset max [xcor] of turtles + min [xcor] of turtles
  let y-offset max [ycor] of turtles + min [ycor] of turtles
  ;; big jumps look funny, so only adjust a little each time
  set x-offset limit-magnitude x-offset 0.1
  set y-offset limit-magnitude y-offset 0.1
  ask turtles [ setxy (xcor - x-offset / 2) (ycor - y-offset / 2) ]
end 

to-report limit-magnitude [number limit]
  if number > limit [ report limit ]
  if number < (- limit) [ report (- limit) ]
  report number
end 

; Copyright 2012 Tomasini Marcello.
; See Info tab for full copyright and license.