Land_Market_6_1.nlogo

extensions [array table gis csv]

globals
[
  ;reporters
  mean-white-saving              ;average developer saving
  mean-yellow-saving             ;average developer saving
  mean-orange-saving             ;average developer saving
  mean-violet-saving             ;average developer saving
  mean-gray-saving               ;average developer saving
  mean-professional-saving       ;average professionals saving
  mean-nonprofessional-saving    ;average non-professionals saving
  mean-professional-housing      ;average professionals housing
  mean-nonprofessional-housing   ;average non-professionals housing
  innercity-professional         ;number of inner-city professionals
  innercity-nonprofessional      ;number of inner-city non-professionals
  suburbia-professional          ;number of suburbia professionals
  suburbia-nonprofessional       ;number of suburbia non-professionals
  white-noi                      ;developer NOI
  yellow-noi                     ;developer NOI
  orange-noi                     ;developer NOI
  violet-noi                     ;developer NOI
  gray-noi                       ;developer NOI
;  gentrified_population          ;number of agents that have been gentrified
  sprawl_population              ;number of agents that have been sprawled
  emigration_population          ;number of agents that have been removed signifiying out-migration
  urban_growth_population        ;number of agents that have been added to the model
  ; ESRI related variables
  themap
  neighborhoods-dataset
  zones-dataset      ;ESRI
  studyarea-dataset

]

turtles-own          ;using Jackson's gentrification model
[
  ;developer          ;if true the agent is either yellow, violet, white, orange and gray
  ;professional       ;if true the person is green, red or blue (economic class)
  ;non-professional   ;if true the person is green, red or blue (economic class)
  tID                ; agent turtle ID
  budget             ;69% of annual income is annual budget, using Devisch agent decision-making
  ttype               ; dev;pro;nonpro
  income             ;average annual of 75628
  housing            ;28% of budget is housing (based on a 14868 annual housing cost)
  saving             ;every agent's income-budget
  lowerbound         ;mean - std of income distribution
  upperbound         ;mean + std of income distribution
  ;A-age             ;random between 0 and 85
  happy?             ;happy if neighboring same color and class agents >= 10%
  pID                ;it is the patch ID that this turtle resides
  similar-color      ;neighbors with similar colors
  similar-income     ;neighbors with similar incomes
  NOI                ;Net Operating Income of a project (NOI = Value * Cap Rate)
  near-CBD           ;preference to be near CBD
  low-rent           ;preference to pay lower rent
]


patches-own[
 ID           ;each patches ID related to a neighborhood, patch ID is identical with polygon ID_ID, using Yang Zhou's Segregation model
 properties
 occupied?    ;if it is occupied by a turtle
 density      ;number of agents in one area
 zID          ;each patches ID related to a zone
 nID          ;neighborhood ID
 p-age        ;property age up to 100 years old (using 0.04 lambda for property decay)
 psize        ;property size as square footage
 ptype        ;property type (C.condo/coop, S.detached/attached single family houses)
 price        ;overall value of the property for selling and buying
 PR           ;potential rent that arrived from the price factor using 32.03 price-to-rent ratio for DC
 CR           ;capitalized rent
 ;NR           ;neighborhood rent
 Rent-gap     ;RG based on Neil Smith's CR and PR
 ;vacancy-rate ;vacant properties divided by total properties
]



to setup
  clear-all
  random-seed 47820              ;random seed to make the experiments consistent when testing different parameters
 ; set gentrified_population 0    ;initialize reporters
  set sprawl_population 0        ;initialize reporters
  set emigration_population 0    ;initialize reporters

  load_data                      ;load map information and patch data
  setup-properties               ;initialize properties of each patch (house)
  setup-patches                  ;initialize properties of each patch (house)
  setup-developer                ;initialize developers properties
  setup-professional 1.0         ;add (1.0 * initial_population) number of professional agents
  setup-nonprofessional 1.0      ;add (1.0 * initial_population) number of non-professional agents
  update-turtles                 ;update agent properties
  reset-ticks
end

to go
  if all? turtles [ happy? ] [ stop ]                                    ;if all agents are happy, stop the program. Schelling's segregation model by Uri Wilensky
  emigration                                                             ; run emigration model in each iteration
  ;;; <<<calculate the density of each patch>>> ;;;
  let max_nID (max [nID] of patches with [zID > 30]) + 1
  let density_list array:from-list n-values max_nID [0]
  foreach n-values max_nID [ ?1 -> ?1 ] [ ?1 ->
    let number_of_turtles count turtles-on patches with [nID = ?1]
    let dens (number_of_turtles / (count patches with [nID = ?1]))
    array:set density_list ?1 dens
  ]
  ;;; <<<calculate the density of each patch>>> ;;;

  sprawl density_list                                                    ;pass density of each patch to see if we need sprawl

  move-turtles                                                           ;move agents based on their preferences

  developer-buy                                                          ;developers buy vacant places based on their saving

  update-turtles                                                         ;update turtles properties
  ;;; <<< update the housing price based on density and CR >>> ;;;
  ask patches with [zID > 30][
    set density array:item density_list nID
    set p-age p-age + 1
    set CR (PR * exp (-0.04 * min (list 100 p-age)))
    set Rent-gap ((PR - CR) / PR)
    set price (price-change-by-density density) * (CR * 12 * 32.02) ; more dense area have higher prices
  ]
  ;;; <<< update the housing price based on density and CR >>> ;;;

  get-info
  ;;; <<< urban growth every 15 years >>> ;;;
  ;if ticks != 0 and (remainder ticks 15) = 0
  ;changed to one year rate
  setup-professional ug_rate / 15
  setup-nonprofessional ug_rate / 15

  ;;; <<< gentrification by demand every 15 years >>> ;;;
  ; if ticks != 0 and (remainder ticks 15) = 0 [
    ;  gen_demand
  ; ]
  export-patches-vals
  export-turtles-vals

  tick
end

;;; load the map from shape file
to load_data
    set neighborhoods-dataset gis:load-dataset "data/Neighborhoods.shp"
    set zones-dataset gis:load-dataset "data/Zones.shp"
    set studyarea-dataset gis:load-dataset "data/StudyArea.shp"
    gis:set-world-envelope gis:envelope-of studyarea-dataset
    gis:set-drawing-color white
    gis:draw neighborhoods-dataset 1
    gis:draw zones-dataset 1
    gis:apply-coverage zones-dataset "BUFF_DIST" zID
    gis:apply-coverage neighborhoods-dataset "INPUT_FID" nID
    ;print gis:property-names zones-dataset

end


;;; for each patch (house), set a specific size, price, and PR
to setup-properties          ;using Smith's rent gap theory (capitalized & potential rent and decay factor)
  ask patches with [zID = 60] [set ptype "C"              ;inner-city condo/coop
                                             set psize random-normal 926.96 31.26
                                             set price random-normal 492867 14715.43
                                             set PR (1.0 * price / (12 * 32.02))] ; bid rent theory (1.0)

  ask patches with [zID = 90] [set ptype "S"              ;suburban dettached/attached single family house
                                             set psize random-normal 1650.40 504.14
                                             set price random-normal 769387 201379.80
                                             set PR (0.95 * price / (12 * 32.02))] ; bid rent theory (0.95)

  ask patches with [zID > 30] [set p-age random 100
                               set CR (PR * exp (-0.04 * p-age))   ;decline of CR through time. (Diappi and Bolchi model)
                               set Rent-gap ((PR - CR) / PR)
                               ]

end


;;; for each patch (house), set their color to defaul and make the vacant
to setup-patches
  (foreach (sort patches) (n-values count patches [ ?1 -> ?1 ]) [ [?1 ?2] ->
    ask ?1 [ set id ?2 ]
  ])
  ask patches with [ ptype = "C" or ptype = "S"] [set pcolor 3]
  ask patches with [ zID = 30] [set pcolor black]
  ask patches with [ID >= 0] [set occupied? false]

end

;;; setup properties of each developer
to setup-developer
  crt 1 [set color yellow set ttype "dev" set ID who]
  crt 1 [set color violet set ttype "dev" set ID who]
  crt 1 [set color white set ttype "dev" set ID who]
  crt 1 [set color orange set ttype "dev" set ID who]
  crt 1 [set color gray set ttype "dev" set ID who]
  ask turtles with [ttype = "dev"] [
    set tID who
    set shape "person"
    set size 5
    set happy? true
    set income random-normal 5000000 4000000       ;assuming developers have an initial income between 1 million and 10 million
    while [income < 0] [set income random-normal 5000000 4000000]
    set saving income
    set budget (income * 0.69)
    set NOI 0
  ]
  ask turtles with [ttype = "dev"] [move-to one-of patches with [zID = 30]]
end

;;; add and setup properties of professionals
to setup-professional [rate]
  ; for each color (red, green, blue), we create initial_population/2 agents for professionals
  crt round (rate * initial_population / 2) [   ; half the initial_population is professional and half of them are non-professional
    set tID who
    set ttype "pro"
    set color green
    set happy? false
    set lowerbound 117086
    set upperbound 158542
    set income random-normal 137814 20728
    set budget (income * 0.69)
    set housing (budget * 0.28)
    set saving (income - budget)
    set shape "person"
    set size 5
    let CBD-interest random 100  ;setting the near-CBD preference
    ifelse CBD-interest > 30     ;if number is more than 30% then the agent has a preference to be near CBD, if less than 30%, the agent doesn't prefer that
     [set near-CBD 1]
     [set near-CBD 0]
    let low-rent-perc random 100  ;setting the near-CBD preference
    ifelse low-rent-perc < 30     ;if number is more than 30% then the agent has a preference to pay low rent, if less than 30%, the agent doesn't prefer that
     [set low-rent 1]
     [set low-rent 0]
    let target one-of patches with [zID > 30 and occupied? = false]
    let moved-price [price] of target
    move-to target
    ;if this patch is already developed by a developer, add the price to its saving
    ask patch-here[
      set occupied? true
      if pcolor != 3 [ask turtles with [color = pcolor] [set saving (saving + moved-price)]]
    ]
    set housing (housing - moved-price)
    set pID [ID] of patch-here
  ]
  crt round (rate * initial_population / 2) [
    set tID who
    set color red
    set ttype "pro"
    set happy? false
    set lowerbound 117086
    set upperbound 158542
    set income random-normal 137814 20728
    set budget (income * 0.69)
    set housing (budget * 0.28)
    set saving (income - budget)
    set shape "person"
    set size 5
    let CBD-interest random 100  ;setting the near-CBD preference
    ifelse CBD-interest > 30     ;if number is more than 30% then the agent has a preference to be near CBD, if less than 30%, the agent doesn't prefer that
     [set near-CBD 1]
     [set near-CBD 0]
    let low-rent-perc random 100  ;setting the near-CBD preference
    ifelse low-rent-perc < 30     ;if number is more than 30% then the agent has a preference to pay low rent, if less than 30%, the agent doesn't prefer that
     [set low-rent 1]
     [set low-rent 0]
    let target one-of patches with [zID  > 30 and occupied? = false]
    let moved-price [price] of target
    move-to target
    ;if this patch is already developed by a developer, add the price to its saving
    ask patch-here[
      set occupied? true
      if pcolor != 3 [ask turtles with [color = pcolor] [set saving (saving + moved-price)]]
    ]
    set housing (housing - moved-price)
    set pID [ID] of patch-here
  ]
  crt round (rate * initial_population / 2) [
    set tID who
    set color blue
    set ttype "pro"
    set happy? false
    set lowerbound 117086
    set upperbound 158542
    set income random-normal 137814 20728
    set budget (income * 0.69)
    set housing (budget * 0.28)
    set saving (income - budget)
    set shape "person"
    set size 5
    let CBD-interest random 100  ;setting the near-CBD preference
    ifelse CBD-interest > 30     ;if number is more than 30% then the agent has a preference to be near CBD, if less than 30%, the agent doesn't prefer that
     [set near-CBD 1]
     [set near-CBD 0]
    let low-rent-perc random 100  ;setting the near-CBD preference
    ifelse low-rent-perc < 30     ;if number is more than 30% then the agent has a preference to pay low rent, if less than 30%, the agent doesn't prefer that
     [set low-rent 1]
     [set low-rent 0]
    let target one-of patches with [zID  > 30 and occupied? = false]
    let moved-price [price] of target
    move-to target
    ;if this patch is already developed by a developer, add the price to its saving
    ask patch-here[
      set occupied? true
      if pcolor != 3 [ask turtles with [color = pcolor] [set saving (saving + moved-price)]]
    ]
    set housing (housing - moved-price)
    set pID [ID] of patch-here
  ]
end

;;; add and setup properties of professionals
to setup-nonprofessional [rate]
  ; for each color (red, green, blue), we create initial_population/2 agents for non-professionals
  crt round (rate * initial_population / 2) [
    set tID who
    set color red
    set ttype "nonpro"
    set lowerbound 31876
    set upperbound 53752
    set income random-normal 42814 10938
    set budget (income * 0.69)
    set housing (budget * 0.28)
    set saving (income - budget)
    set shape "person"
    set size 5
    let CBD-interest random 100  ;setting the near-CBD preference
    ifelse CBD-interest > 30     ;if number is more than 30% then the agent has a preference to be near CBD, if less than 30%, the agent doesn't prefer that
     [set near-CBD 1]
     [set near-CBD 0]
    let low-rent-perc random 100  ;setting the near-CBD preference
    ifelse low-rent-perc < 30     ;if number is more than 30% then the agent has a preference to pay low rent, if less than 30%, the agent doesn't prefer that
     [set low-rent 1]
     [set low-rent 0]
    let target one-of patches with [zID  > 30 and occupied? = false]
    let moved-price [price] of target
    move-to target
    ;if this patch is already developed by a developer, add the price to its saving
    ask patch-here[
      set occupied? true
      if pcolor != 3 [ask turtles with [color = pcolor] [set saving (saving + moved-price)]]
    ]
    set housing (housing - moved-price)
    set pID [ID] of patch-here
  ]
  crt round (rate * initial_population / 2) [
    set tID who
    set color green
    set ttype "nonpro"
    set lowerbound 31876
    set upperbound 53752
    set income random-normal 42814 10938
    set budget (income * 0.69)
    set housing (budget * 0.28)
    set saving (income - budget)
    set shape "person"
    set size 5
    let CBD-interest random 100  ;setting the near-CBD preference
    ifelse CBD-interest > 30     ;if number is more than 30% then the agent has a preference to be near CBD, if less than 30%, the agent doesn't prefer that
     [set near-CBD 1]
     [set near-CBD 0]
    let low-rent-perc random 100  ;setting the near-CBD preference
    ifelse low-rent-perc < 30     ;if number is more than 30% then the agent has a preference to pay low rent, if less than 30%, the agent doesn't prefer that
     [set low-rent 1]
     [set low-rent 0]
    let target one-of patches with [zID  > 30 and occupied? = false]
    let moved-price [price] of target
    move-to target
    ;if this patch is already developed by a developer, add the price to its saving
    ask patch-here[
      set occupied? true
      if pcolor != 3 [ask turtles with [color = pcolor] [set saving (saving + moved-price)]]
    ]
    set housing (housing - moved-price)
    set pID [ID] of patch-here
  ]
  crt round (rate * initial_population / 2) [
    set tID who
    set color blue
    set ttype "nonpro"
    set lowerbound 31876
    set upperbound 53752
    set income random-normal 42814 10938
    set budget (income * 0.69)
    set housing (budget * 0.28)
    set saving (income - budget)
    set shape "person"
    set size 5
    let CBD-interest random 100  ;setting the near-CBD preference
    ifelse CBD-interest > 30     ;if number is more than 30% then the agent has a preference to be near CBD, if less than 30%, the agent doesn't prefer that
     [set near-CBD 1]
     [set near-CBD 0]
    let low-rent-perc random 100  ;setting the near-CBD preference
    ifelse low-rent-perc < 30     ;if number is more than 30% then the agent has a preference to pay low rent, if less than 30%, the agent doesn't prefer that
     [set low-rent 1]
     [set low-rent 0]
    let target one-of patches with [zID  > 30 and occupied? = false]
    let moved-price [price] of target
    move-to target
    ;if this patch is already developed by a developer, add the price to its saving
    ask patch-here[
      set occupied? true
      if pcolor != 3 [ask turtles with [color = pcolor] [set saving (saving + moved-price)]]
    ]
    set housing (housing - moved-price)
    set pID [ID] of patch-here
  ]
end


;to gen_demand
 ; let sorted_turtles sort-on [income] turtles with [zID = 90]                                            ;sort the agents in suburbia based on their income
  ;let sublist_sorted_turtles sublist sorted_turtles 0 round (gen_rate * count turtles with [zID = 90])   ;select the lowest income agent based on gen_rate
  ;set gentrified_population gentrified_population + (round (gen_rate * count turtles with [zID = 90]))   ;update the reporter for the number of gentrified agents
  ;;; <<< start moving low income agents to inner-city >>> ;;;
  ;foreach sublist_sorted_turtles[
   ; ask ?1 [
    ;  let turtle-saving housing
     ; let target one-of patches with [zID = 60 and occupied? = false and price < turtle-saving]
      ;if target != nobody [
       ; ask patch-here[set occupied? false]
        ;move-to target
        ;let moved-price [price] of target
        ;if this patch is already developed by a developer, add the price to its saving
        ;ask patch-here [
         ; set occupied? true
          ;if pcolor != 3 [ask turtles with [color = pcolor] [set saving (saving + moved-price)]]
        ;]
        ;set pID [ID] of patch-here
        ;set housing (housing - moved-price) ;developer sell
      ;]
    ;]
  ;]
;end


to sprawl [density_list]
  foreach n-values (array:length density_list) [ ?1 -> ?1 ][ ?1 ->
    let patch_density array:item density_list ?1
    if patch_density > sprawl_density_threshold[                                  ;if density of a specific patch is greater than the threshold, we have to move them
      let turtles_in_patch turtles-on patches with [nID = ?1]
      let number_turtles_in_patch count turtles_in_patch
      let sprawl_count round (sprawl_moving_rate * number_turtles_in_patch)       ; update the number of sprawled agents
      set sprawl_population sprawl_population + sprawl_count
      ;;; <<< start moving turtles >>> ;;;
      ask n-of sprawl_count turtles_in_patch[
        let turtle-saving housing
        let turtle-size [psize] of patch-here
        ; agents should move to a place that is vacant, its price is lower than their saving, it's less crowded, and the property size is greater than their current place

        let current-CR ([PR] of patch-here * exp (-0.04 * min (list 100 [p-age] of patch-here))) ; capping the age of a building to 100
        let current-price (price-change-by-density [density] of patch-here) * (current-CR * 12 * 32.02) ; more dense area have higher prices
        let current-nID [nID] of patch-here
        let target one-of patches with [occupied? = false and zID > 30 and price < (turtle-saving + current-price) and density < patch_density and psize > turtle-size]
        if target != nobody [
          ask patch-here [set occupied? false]
          move-to target
          let moved-price [price] of target
          ;if this patch is already developed by a developer, add the price to its saving
          ask patch-here [
            set occupied? true
            if pcolor != 3 [ask turtles with [color = pcolor] [set saving (saving + moved-price)]]
          ]
          set pID [ID] of patch-here
          ; selling price + agent's saving
          set housing (current-price + housing - moved-price) ;developer sell
          ; we need to set the pcolor of this house to 3 showing that an agent lives in this house and is not controlled by developers anymore
          set pcolor 3
        ]
      ]
    ]
  ]
end

to emigration
  let dying_count round (emigration_rate * count turtles with [zID > 30])     ;randomly remove agents from the model based on emigration-rate
  set emigration_population emigration_population + dying_count
  ask n-of dying_count turtles with [zID > 30] [
    ask patch-here [set occupied? false]
    die  ;RIP
  ]
end

to-report price-change-by-density [dens]     ;implement the "f(d) = 1+d" function
  report exp(1 + dens) ; exponential growth for the price according to density
end

; find the developer that is most frequent in a specific nID
to-report max-developer [current-nID]
  let dev-colors array:from-list (list yellow white violet gray orange)
  let yellow-patches count patches with [nID = current-nID and pcolor = yellow]
  let white-patches count patches with [nID = current-nID and pcolor = white]
  let violet-patches count patches with [nID = current-nID and pcolor = violet]
  let gray-patches count patches with [nID = current-nID and pcolor = gray]
  let orange-patches count patches with [nID = current-nID and pcolor = orange]
  let max-dev max (list yellow-patches white-patches violet-patches gray-patches orange-patches)
  let max-item-index position max-dev (list yellow-patches white-patches violet-patches gray-patches orange-patches)
  report array:item dev-colors max-item-index
end

to move-turtles                                      ;using Yang Zhou's segregation model
  ask turtles with [color = green or color = red or color = blue] [
    if happy? = false [
      let turtle-saving housing
      ; getting current price of the house based on property age (p-age), PR, CR
      let current-CR ([PR] of patch-here * exp (-0.04 * min (list 100 [p-age] of patch-here))) ; capping the age of a building to 100
      let current-price (price-change-by-density [density] of patch-here) * (current-CR * 12 * 32.02) ; more dense area have higher prices
      let current-nID [nID] of patch-here
      if near-CBD = 1 [
         ifelse low-rent = 1 [
            let target item 0 sort-on [price] patches with [occupied? = false and zID = 60]
            ; selling the property managed by current-price of the house added to the saving of the agent
            if target != nobody and [price] of target < (turtle-saving + current-price) [
               ; start buying
               ask patch-here [set occupied? false]
               move-to target
               let moved-price [price] of target
               ;if this patch is already developed by a developer, add the price to its saving
               ask patch-here [
                 set occupied? true
                 ; if the patch that agent is moving has already been developed, add the price to the saving of the developer
                 ; else add the price of the house to the most frequent developer in this nID
                 if pcolor != 3 [ask turtles with [color = pcolor] [set saving (saving + moved-price)]]
                 ;[ask turtles with [color = (max-developer current-nID)] [set saving (saving + moved-price)]]
               ]
               set pID [ID] of patch-here
               ; selling price + agent's saving
               set housing (current-price + housing - moved-price) ;developer sell
               ; we need to set the pcolor of this house to 3 showing that an agent lives in this house and is not controlled by developers anymore
               set pcolor 3
           ]
         ]
         [
          let target one-of patches with [occupied? = false and zID = 60 and price < turtle-saving + current-price ]
          if target != nobody [
            ask patch-here [set occupied? false]
            move-to target
            let moved-price [price] of target
            ;if this patch is already developed by a developer, add the price to its saving
            ask patch-here [
              set occupied? true
                 if pcolor != 3 [ask turtles with [color = pcolor] [set saving (saving + moved-price)]]
                 ;[ask turtles with [color = (max-developer current-nID)] [set saving (saving + moved-price)]]
            ]
            set pID [ID] of patch-here
            ; selling price + agent's saving
            set housing (current-price + housing - moved-price) ;developer sell
            set pcolor 3
          ]
        ]
      ]
      if near-CBD = 0 [
         ifelse low-rent = 1 [
            let target item 0 sort-on [price] patches with [occupied? = false and zID > 30]
            if target != nobody and [price] of target < turtle-saving + current-price [
               ; start buying
               ask patch-here [set occupied? false]
               move-to target
               let moved-price [price] of target
               ;if this patch is already developed by a developer, add the price to its saving
               ask patch-here [
                 set occupied? true
                 if pcolor != 3 [ask turtles with [color = pcolor] [set saving (saving + moved-price)]]
                 ;[ask turtles with [color = (max-developer current-nID)] [set saving (saving + moved-price)]]
               ]
               set pID [ID] of patch-here
               ; selling price + agent's saving
               set housing (current-price + housing - moved-price) ;developer sell
               set pcolor 3
           ]
         ]
         [
           let target one-of patches with [occupied? = false and zID > 30 and price < turtle-saving + current-price ]
           if target != nobody [
             ask patch-here [set occupied? false]
             move-to target
             let moved-price [price] of target
             ;if this patch is already developed by a developer, add the price to its saving
             ask patch-here [
               set occupied? true
                 if pcolor != 3 [ask turtles with [color = pcolor] [set saving (saving + moved-price)]]
                 ;[ask turtles with [color = (max-developer current-nID)] [set saving (saving + moved-price)]]
             ]
             set pID [ID] of patch-here
             ; selling price + agent's saving
             set housing (current-price + housing - moved-price) ;developer sell
             set pcolor 3
           ]
         ]
       ]
    ]
  ]
end

;;; update properties of each agent after one run
to update-turtles                                ;using Benenson's CA model, deciding based on economic status
  ask turtles [
    set saving (income - budget + saving)
    set housing (housing + budget * 0.28)
    ]       ;increasing the saving and housing every year
  ask turtles with [color = green or color = red or color = blue]
    [
      let current-pID pID
      let current-patch-nID [nID] of patch-here
      ;let num-neighbors count patches with [nID = current-patch-nID]
      let neighbors-in-nID patches with [nID = current-patch-nID]
      let num-neighbors count turtles-on neighbors-in-nID

      set similar-color count (turtles-on neighbors-in-nID)  with [ color = [ color ] of myself ]
      ;set similar-income count (turtles-on neighbors-in-nID) with [ income <= [lowerbound] of myself and income >= [upperbound] of myself and housing > 0]
      set similar-income count (turtles-on neighbors-in-nID) with [ ttype = [ttype] of myself and housing > 0]
      ;show (word "patch ID: " current-pID " patch nID: " current-patch-nID " num neighbors: " num-neighbors " similar-color: " similar-color " similar-income: " similar-income)
      set happy? (housing > 0) and (similar-color / num-neighbors > 0.5 or similar-income / num-neighbors > 0.5) ; happy if housing is greater than 0, meaning the agent is not under debt
    ]
end

;;; developers buy vacant places randomly based on their current saving
to developer-buy
  let vacant patches with [occupied? = false and zID > 30 and zID <= 90 and pcolor = 3 and p-age > 60]
  let sorted-vacant sort-on [(- Rent-gap)] vacant
  let developers turtles with [ttype = "dev"]
  foreach sorted-vacant[ ?1 ->
    let vacant-price [price] of ?1
    let vacant-id [ID] of ?1
    let vacant-age [p-age] of ?1
    let vacant-PR [PR] of ?1
    let target one-of developers with [saving > vacant-price]
    if target != nobody[
      ask target[
        set saving saving - vacant-price
        let dv-color color
        ask one-of patches with [ID = vacant-id] [set pcolor dv-color
                                                  set p-age 0
                                                 ]
        set NOI NOI + ((vacant-PR * 12 * 32.02) * Cap-Rate / 100)   ; 32.02 is the price-to-rent ratio
      ]
    ]
  ]
end


;;;; <<< REPORTERS SECTION >>> ;;;;


to-report developer-reporter-white
  let list-white-saving []
  ask turtles with [color = white][set list-white-saving lput saving list-white-saving]
  set mean-white-saving mean list-white-saving
  report mean-white-saving
end
to-report developer-reporter-yellow
  let list-yellow-saving []
  ask turtles with [color = yellow][set list-yellow-saving lput saving list-yellow-saving]
  set mean-yellow-saving mean list-yellow-saving
  report mean-yellow-saving
end

to-report developer-reporter-orange
  let list-orange-saving []
  ask turtles with [color = orange][set list-orange-saving lput saving list-orange-saving]
  set mean-orange-saving mean list-orange-saving
  report mean-orange-saving
end

to-report developer-reporter-violet
  let list-violet-saving []
  ask turtles with [color = violet][set list-violet-saving lput saving list-violet-saving]
  set mean-violet-saving mean list-violet-saving
  report mean-violet-saving
end

to-report developer-reporter-gray
  let list-gray-saving []
  ask turtles with [color = gray][set list-gray-saving lput saving list-gray-saving]
  set mean-gray-saving mean list-gray-saving
  report mean-gray-saving
end

to-report nonprofessional-housing-reporter
  ;nonprofessional
  let list-nonprofessional-housing []
  ask turtles with [lowerbound = 31876 and upperbound = 53752][set list-nonprofessional-housing lput housing list-nonprofessional-housing]
  set mean-nonprofessional-housing mean list-nonprofessional-housing
  report mean-nonprofessional-housing
end

to-report professional-housing-reporter
  ;professional
  let list-professional-housing []
  ask turtles with [lowerbound = 117086 and upperbound = 158542][set list-professional-housing lput housing list-professional-housing]
  set mean-professional-housing mean list-professional-housing
  report mean-professional-housing
end

to-report professional-saving-reporter
  ;professional
  let list-professional-saving []
  ask turtles with [lowerbound = 117086 and upperbound = 158542][set list-professional-saving lput saving list-professional-saving]
  set mean-professional-saving mean list-professional-saving
  report mean-professional-saving
end

to-report nonprofessional-saving-reporter
  ;nonprofessional
  let list-nonprofessional-saving []
  ask turtles with [lowerbound = 31876 and upperbound = 53752][set list-nonprofessional-saving lput saving list-nonprofessional-saving]
  set mean-nonprofessional-saving mean list-nonprofessional-saving
  report mean-nonprofessional-saving
end

to-report innercity-professional-reporter
  set innercity-professional count turtles with [lowerbound = 117086 and upperbound = 158542 and zID = 60]
  report innercity-professional
end

to-report innercity-nonprofessional-reporter
  set innercity-nonprofessional count turtles with [lowerbound = 31876 and upperbound = 53752 and zID = 60]
  report innercity-nonprofessional
end

to-report suburbia-professional-reporter
  set suburbia-professional count turtles with [lowerbound = 117086 and upperbound = 158542 and zID = 90]
  report suburbia-professional
end

to-report suburbia-nonprofessional-reporter
  set suburbia-nonprofessional count turtles with [lowerbound = 31876 and upperbound = 53752 and zID = 90]
  report suburbia-nonprofessional
end

to-report white-developer-noi-reporter
  set white-noi sum [NOI] of turtles with [color = white]
  report white-noi
end

to-report yellow-developer-noi-reporter
  set yellow-noi sum [NOI] of turtles with [color = yellow]
  report yellow-noi
end

to-report orange-developer-noi-reporter
  set orange-noi sum [NOI] of turtles with [color = orange]
  report orange-noi
end

to-report violet-developer-noi-reporter
  set violet-noi sum [NOI] of turtles with [color = violet]
  report violet-noi
end

to-report gray-developer-noi-reporter
  set gray-noi sum [NOI] of turtles with [color = gray]
  report gray-noi
end

to-report ug-population-reporter
  set urban_growth_population 3 * count turtles with [color = green]
  report urban_growth_population
end

;to-report gentrified-population-reporter
 ; report gentrified_population
;end

to-report sprawl-population-reporter
  report sprawl_population
end

to-report emigration-population-reporter
  report emigration_population
end

to get-info
  ;developer saving

  let list-white-saving []
  let list-yellow-saving []
  let list-orange-saving []
  let list-violet-saving []
  let list-gray-saving []

  ask turtles with [color = white][set list-white-saving lput log saving 10 list-white-saving]
  ask turtles with [color = yellow][set list-yellow-saving lput log saving 10 list-yellow-saving]
  ask turtles with [color = orange][set list-orange-saving lput log saving 10 list-orange-saving]
  ask turtles with [color = violet][set list-violet-saving lput log saving 10 list-violet-saving]
  ask turtles with [color = gray][set list-gray-saving lput log saving 10 list-gray-saving]

  ;set mean-white-saving mean list-white-saving
  ;set mean-yellow-saving mean list-yellow-saving
  ;set mean-orange-saving mean list-orange-saving
  ;set mean-violet-saving mean list-violet-saving
  ;set mean-gray-saving mean list-gray-saving

  set mean-white-saving 0
  set mean-yellow-saving 0
  set mean-orange-saving 0
  set mean-violet-saving 0
  set mean-gray-saving 0

  ;professional

  let list-professional-saving []

  ask turtles with [lowerbound = 117086 and upperbound = 158542][set list-professional-saving lput saving list-professional-saving]

  set mean-professional-saving mean list-professional-saving

  ;nonprofessional

  let list-nonprofessional-saving []

  ask turtles with [lowerbound = 31876 and upperbound = 53752][set list-nonprofessional-saving lput saving list-nonprofessional-saving]

  set mean-nonprofessional-saving mean list-nonprofessional-saving

  ;number of professionals and nonprofessionals in inner city

  set innercity-professional count turtles with [lowerbound = 117086 and upperbound = 158542 and zID = 60]
  set innercity-nonprofessional count turtles with [lowerbound = 31876 and upperbound = 53752 and zID = 60]

  ;number of professionals and nonprofessionals in suburbia

  set suburbia-professional count turtles with [lowerbound = 117086 and upperbound = 158542 and zID = 90]
  set suburbia-nonprofessional count turtles with [lowerbound = 31876 and upperbound = 53752 and zID = 90]

  ;developer NOIs

  set white-noi sum [NOI] of turtles with [color = white]
  set yellow-noi sum [NOI] of turtles with [color = yellow]
  set orange-noi sum [NOI] of turtles with [color = orange]
  set violet-noi sum [NOI] of turtles with [color = violet]
  set gray-noi sum [NOI] of turtles with [color = gray]

  set urban_growth_population 3 * count turtles with [color = green]

end

to-report get-turtle-attributes ;turtle proc
  report (list ticks tID budget ttype income housing saving lowerbound upperbound happy? pID similar-color similar-income NOI near-CBD low-rent)
end

to-report get-patches-attributes ;turtle proc
  report (list ticks ID properties occupied? density zID nID p-age psize ptype price PR CR Rent-gap pcolor)
end

to export-turtles-vals ;turtle proc
  ask turtles [
    file-open "turtles.csv"
    file-print csv:to-row get-turtle-attributes
    file-close
  ]
end

to export-patches-vals ;turtle proc
  ;ask patches with [occupied? = true]
  ask patches [
    file-open "patches.csv"
    file-print csv:to-row get-patches-attributes
    file-close
  ]
end

to output [basepath]
  let interface-filename (word basepath "interface_ip-" initial_population "_ug-" ug_rate "_cr-" Cap-Rate "_gr-" gen_rate "_sdt-" sprawl_density_threshold "_smr-" sprawl_moving_rate "_sr-" emigration_rate "_" date-and-time ".png")
  let world-filename (word basepath "world_ip-" initial_population "_ug-" ug_rate "_cr-" Cap-Rate "_gr-" gen_rate "_sdt-" sprawl_density_threshold "_smr-" sprawl_moving_rate "_sr-" emigration_rate "_" date-and-time ".png")
  export-interface interface-filename
  export-view world-filename
end

to output-time [basepath tick-time]
  let interface-filename (word basepath "time_" tick-time "_interface_ip-" initial_population "_ug-" ug_rate "_cr-" Cap-Rate "_gr-" gen_rate "_sdt-" sprawl_density_threshold "_smr-" sprawl_moving_rate "_sr-" emigration_rate "_" date-and-time ".png")
  let world-filename (word basepath "time_" tick-time "_world_ip-" initial_population "_ug-" ug_rate "_cr-" Cap-Rate "_gr-" gen_rate "_sdt-" sprawl_density_threshold "_smr-" sprawl_moving_rate "_sr-" emigration_rate "_" date-and-time ".png")
  export-interface interface-filename
  export-view world-filename
end
@#$#@#$#@
GRAPHICS-WINDOW
279
13
689
424
-1
-1
2.0
1
10
1
1
1
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1
1
1
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100
-100
100
0
0
1
ticks
30.0

BUTTON
14
30
78
63
Setup
setup
NIL
1
T
OBSERVER
NIL
NIL
NIL
NIL
1

BUTTON
100
32
163
65
Go
go
T
1
T
OBSERVER
NIL
NIL
NIL
NIL
1

BUTTON
170
34
245
67
go once
go
NIL
1
T
OBSERVER
NIL
NIL
NIL
NIL
1

SLIDER
22
143
194
176
Cap-Rate
Cap-Rate
4.75
7.75
7.5
0.25
1
NIL
HORIZONTAL

MONITOR
23
82
155
127
Developed Properties
count patches with [pcolor = yellow or pcolor = orange or pcolor = violet or pcolor = gray or pcolor = white]
17
1
11

PLOT
730
13
990
147
Developer Av. Saving
Years
Saving
0.0
30.0
0.0
10.0
true
true
"" ""
PENS
"White" 1.0 0 -16777216 true "" "plot mean-white-saving"
"Yellow" 1.0 0 -1184463 true "" "plot mean-yellow-saving"
"Orange" 1.0 0 -955883 true "" "plot mean-orange-saving"
"Violet" 1.0 0 -8630108 true "" "plot mean-violet-saving"
"Gray" 1.0 0 -7500403 true "" "plot mean-gray-saving"

PLOT
734
284
991
417
P & NP Saving
Years
Saving
0.0
100.0
0.0
10.0
true
true
"" ""
PENS
"P" 1.0 0 -16777216 true "" "plot mean-professional-saving"
"NP" 1.0 0 -7500403 true "" "plot mean-nonprofessional-saving"

PLOT
732
148
992
282
Developer NOI
Years
NOI
0.0
30.0
0.0
10.0
true
true
"" ""
PENS
"White" 1.0 0 -16777216 true "" "plot white-noi"
"Yellow" 1.0 0 -1184463 true "" "plot yellow-noi"
"Orange" 1.0 0 -955883 true "" "plot orange-noi"
"Violet" 1.0 0 -8630108 true "" "plot violet-noi"
"Gray" 1.0 0 -7500403 true "" "plot gray-noi"

PLOT
469
427
728
557
Inner City P & NP
Years
People
0.0
10.0
0.0
10.0
true
true
"" ""
PENS
"P" 1.0 0 -16777216 true "" "plot innercity-professional"
"NP" 1.0 0 -7500403 true "" "plot innercity-nonprofessional"

PLOT
208
427
466
557
Suburbia P & NP
Years
People
0.0
30.0
0.0
10.0
true
true
"" ""
PENS
"P" 1.0 0 -16777216 true "" "plot suburbia-professional"
"NP" 1.0 0 -7500403 true "" "plot suburbia-nonprofessional"

SLIDER
23
189
195
222
ug_rate
ug_rate
0
1
0.17
0.1
1
NIL
HORIZONTAL

SLIDER
23
233
195
266
initial_population
initial_population
100
5000
300.0
50
1
NIL
HORIZONTAL

SLIDER
23
274
195
307
gen_rate
gen_rate
0
1
0.1
0.1
1
NIL
HORIZONTAL

SLIDER
23
317
196
350
sprawl_density_threshold
sprawl_density_threshold
0
1
0.2
0.1
1
NIL
HORIZONTAL

SLIDER
25
360
197
393
sprawl_moving_rate
sprawl_moving_rate
0
1
0.1
0.1
1
NIL
HORIZONTAL

SLIDER
24
398
196
431
emigration_rate
emigration_rate
0
1
0.005
0.001
1
NIL
HORIZONTAL

PLOT
734
424
992
556
Population Over Time
Time
Population
0.0
600.0
0.0
9000.0
true
true
"" ""
PENS
"Growth" 1.0 0 -14439633 true "" "plot urban_growth_population"
"Sprawl" 1.0 0 -5298144 true "" "plot sprawl_population"
"Emigration" 1.0 0 -7500403 true "" "plot emigration_population"

@#$#@#$#@
## WHAT IS IT?

(a general understanding of what the model is trying to show or explain)

## HOW IT WORKS

(what rules the agents use to create the overall behavior of the model)

## HOW TO USE IT

(how to use the model, including a description of each of the items in the Interface tab)

## THINGS TO NOTICE

(suggested things for the user to notice while running the model)

## THINGS TO TRY

(suggested things for the user to try to do (move sliders, switches, etc.) with the model)

## EXTENDING THE MODEL

(suggested things to add or change in the Code tab to make the model more complicated, detailed, accurate, etc.)

## NETLOGO FEATURES

(interesting or unusual features of NetLogo that the model uses, particularly in the Code tab; or where workarounds were needed for missing features)

## RELATED MODELS

(models in the NetLogo Models Library and elsewhere which are of related interest)

## CREDITS AND REFERENCES

(a reference to the model's URL on the web if it has one, as well as any other necessary credits, citations, and links)
@#$#@#$#@
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