# HOTnet (a)

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Model was written in NetLogo 5.0.3
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extensions [ nw ] ;; the number of hops from a fixed center of the tree turtles-own [ nhop ] ;;;;;;;;;;;;;;;;;;;;;;;; ;;; Setup Procedures ;;; ;;;;;;;;;;;;;;;;;;;;;;;; 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) ;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;; 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 ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;;; Save Nodes Degrees to file ;;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; 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.

There is only one version of this model, created over 7 years ago by Marcello Tomasini.

## Attached files

File | Type | Description | Last updated | |
---|---|---|---|---|

nw-ext-beta-0.02.zip | extension | new Network Extension | over 7 years ago, by Marcello Tomasini | Download |

**Parent:** HOTnet

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