5.18-simmap.nlogo

;; The MIT License (MIT)
;;
;; Copyright (c) 2011-24 David O'Sullivan and George Perry
;;
;; Permission is hereby granted, free of charge, to any person
;; obtaining a copy of this software and associated documentation
;; files (the "Software"), to deal in the Software without restriction,
;; including without limitation the rights to use, copy, modify, merge,
;; publish, distribute, sublicense, and/or sell copies of the Software,
;; and to  permit persons to whom the Software is furnished to do so,
;; subject to the following conditions:
;;
;; The above copyright notice and this permission notice shall be included
;; in all copies or substantial portions of the Software.
;;
;; THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
;; OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
;; FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
;; THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
;; LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
;; FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
;; DEALINGS IN THE SOFTWARE.
;;

globals [
  color-list        ;; list of spectral colors
  num-classes       ;; the number of suitability classes
  class-FD          ;; freq distribution of classes requested
  class-CFD         ;; cumulative freq dist of classes requested
  clusters          ;; a list of patch-sets of patches in each cluster
]

patches-own [
  class             ;; used to label initial clusters and to store final class
  in-perc-cluster?  ;; true if patch is in initial percolation cluster
]

to setup
  clear-all
  if use-seed? [ random-seed rng-seed ]
  set color-list (list 16 26 46 66 86 96 106 116 126 136)
  set clusters []
  go
end

to go
  init-patch-variables
  read-class-file
  setup-mrc
  color-patches
end

to init-patch-variables
  ask patches [
    set class -1
    set in-perc-cluster? false
  ]
end

;; Colours patches by class
to color-patches
  ask patches [
    set pcolor item class color-list
  ]
end

;; Retrieve the list of relative probabilities of
;; suitability classes from a file
to read-class-file
  carefully [
    file-open class-file
    set num-classes file-read ;; first item in file is the number of classes
    set class-CFD (list 0) ;; initialise the CFD to 0
    set class-FD [] ;; empty FD
    while [ not file-at-end? ] [
      let prev-n last class-CFD
      let next-n file-read
      set class-CFD lput (next-n + prev-n) class-CFD
      set class-FD lput next-n class-FD
    ]
    set class-CFD but-first class-CFD ;; throw away the zero
    let tot-rel-p last class-CFD
    set class-CFD map [ f -> f / tot-rel-p ] class-CFD
    set class-FD map [ f -> f / tot-rel-p ] class-FD
    file-close
  ] [ file-close ]
end

;; Internal setup based on SIMMAP algorithm
;; This is slow -- I believe due repeated use of long lists
to setup-mrc
  ;; assign patches to percolation cluster
  ask patches [
    if random-float 1 < p [
      set in-perc-cluster? true
      set pcolor white
    ]
  ]
  mark-habitat-patches
  assign-habitat-patches-by-proportion
  set clusters [] ;; throw away the list
  assign-unassigned-to-habitat-patches
  if remove-singleton-patches? [
    let singletons patches with [not any? neighbors4 with [class = [class] of myself]]
    ask singletons [
      set class [class] of one-of neighbors4
    ]
  ]
end

;; identifies and labels sequentially
;; from 0 the connected regions
;; in the percolation cluster
to mark-habitat-patches
  let patch-count 1
  let patches-to-mark sort patches with [in-perc-cluster?]
  while [length patches-to-mark > 0] [
    let this-cluster (patch-set one-of patches-to-mark)
    let current-cluster patch-set nobody
    ;; iteratively grow the patch-set that is this cluster
    while [any? this-cluster] [
      ;; mark by setting habitat-patch value
      ask this-cluster [
        set class patch-count
      ]
      set current-cluster (patch-set current-cluster this-cluster)
      ;; get the next set from the neighbours 4 of the current set
      set this-cluster (patch-set [neighbors4] of this-cluster) with [to-mark?]
    ]
    ;; increment the patch-count and reset the set to mark
    set patch-count patch-count + 1
    set patches-to-mark filter [ ptch -> [class] of ptch < 0 ] patches-to-mark
    ;; add the current cluster to the list of all clusters
    set clusters lput current-cluster clusters
  ]
end

to-report to-mark?
  report class < 0 and in-perc-cluster?
end

;; class-FD is a list of the required landscape proportion in each type
;; cells in regions of the percolation cluster should be relabelled
;; as 1, 2, 3... in the required proportions...
to assign-habitat-patches-by-proportion
  ;; make a list of the target number of patches in each class
  let num-patches-set count patches with [class > 0]
  let target-counts map [ f -> f * num-patches-set ] class-FD
  ;; iteratively assigning clusters in the percolation cluster
  ;; to a class, always adding to the class which is furthest
  ;; from its target count
  if sequentially-assign-clusters? [
    set clusters reverse sort-by [ [c1 c2] -> count c1 > count c2 ] clusters
  ]
  foreach clusters [ C ->
    let biggest-shortfall max target-counts
    let biggest-shortfall-index position biggest-shortfall target-counts
    ask C [
      set class biggest-shortfall-index
    ]
    ;; update the target counts to reflect assignment just made
    set target-counts replace-item biggest-shortfall-index target-counts (biggest-shortfall - count C)
  ]
end

;; patches so far not assigned to a class are
;; now assigned based on the classes of neighbouring assigned patches
to assign-unassigned-to-habitat-patches
  ask patches with [class < 0] [
    let N neighbors with [class >= 0]
    ifelse any? N
    [ set class one-of modes [class] of N ]
    [ let random-draw random-float 1
      let i 0
      let value-set? false
      while [ i < num-classes and not value-set? ] [
        if random-draw <= (item i class-CFD) [
          set class i
          set value-set? true
        ]
        set i i + 1
      ]
    ]
  ]
end
@#$#@#$#@
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@#$#@#$#@
## WHAT IS IT?

This model is an implementation of the SIMMAP method of neutral landscape generation reported in

+   Saura S and Martinez-Milan J 2000 Landscape pattern simulation with a modified random clusters method. _Landscape Ecology_ **15** 661-677.

This model is discussed in Chapter 5 of

+   O'Sullivan D and Perry GLW 2013 _Spatial Simulation: Exploring Pattern and Process_. Wiley, Chichester, England.

You should consult that book for more information and details of the model.

The desired number and relative proportions of habitat classes are specified in the associated file `5.18-classes.txt`.  The first line of that file specifies the number of classes required, and their relative (integer) proportions are given by the numbers (one to a line) in the remainder of the file.

Note that this implementation provides the option via the `sequentially-assign-clusters?` switch of assigning percolation clusters to habitat classes in order from largest to smallest.  This can make a substantial difference to the resulting landscapes when there are large imbalances among the proportions required, or when the percolation threshold `p` is close to or greater than the critical value _p<sub>c</sub>_.

## HOW TO CITE

If you mention this model in a publication, please include these citations for the model itself and for NetLogo

+   O'Sullivan D and Perry GLW 2013 _Spatial Simulation: Exploring Pattern and Process_. Wiley, Chichester, England.
+   Saura S and Martinez-Milan J 2000 Landscape pattern simulation with a modified random clusters method. _Landscape Ecology_ **15** 661-677.
+   Wilensky U 1999 NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

## COPYRIGHT AND LICENSE

The MIT License (MIT)

Copyright &copy; 2011-24 David O'Sullivan and George Perry

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to  permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
@#$#@#$#@
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