I have the code :
if color of patch-here = blue [set heading towards one-of patches in-radius 180 with pcolor = grey ( do that or ) die ]
What I want to be able to do is to allow each turtle to randomly select one of the two options. I appreciate I could assign each command a number and then use a random number generator to select one of the two commands, but I am wondering whether there is a combination of commands that I could use to replace ( do that or ).
Thanks.
Roll a dice, if dice < 5, do something, else do the other thing. Example:
if pcolor = blue [
let dice random 10
ifelse dice < 5 [
set heading towards one-of patches in-radius 180 with pcolor = grey]
[die]
]
Related
I'm working on a smaller project and got stuck on an issue, I'm not really sure if it's possible to solve it in NetLogo but I want to give StackOverflow a go!
I got a model that divides the world into different parts and randomly add physical features (such as rivers). If a feature goes through the whole region, I want it to separate the region and make into two regions. As an example, in the picture below, I want to separate the purple region into two unique regions accordingly to the physical feature (black).
The code I used to generate the picture above, can be found below.
to setup
ca
;Setting world.
resize-world 0 19 0 19
;Creating regions.
let x 5
let y 5
let col 45
while [y <= max-pycor + 1][
while [x <= max-pxcor + 1 ][
ask patches with [pxcor < x and pxcor >= x - 5 and pycor < y and pycor >= y - 5][
set pcolor col
]
set x x + 5
set col col + 10
]
set x 5
set y y + 5
]
;Generating physical features.
ask n-of 5 patches[ sprout 1[
set pcolor black]
]
let i 0
while [ i < (max-pycor * 2 )][
ask turtles [
fd 1
set pcolor black
ifelse (random 20 <= 1)
[
rt one-of [-90 0 90]
forward 1
]
[
fd 1
set pcolor black
fd 1
set pcolor black
]
set pcolor black
set i i + 1]
]
ask turtles [die]
end
My strategy for handling this is to realize that all we really need to do is "flood" a patch out by color and tag all the found adjacent patches, then repeat for any un-tagged, non-black patches until they are all done.
NetLogo does not have a "flood" command to get all patches adjacent to a patch meeting a criteria, so we make a special reporter of our own to handle it, patches-adjacent. Then it's just easy to ask those patches-adjacent to set their region to the currently chosen region.
I don't love this code, it's a little finicky and would be prone to infinite loops if tweaked incorrectly, but it should work. I bet there is a cleaner way to do this that I'm not thinking of at the moment.
; add a variable to track the different regions
; the default value will be `0` for each patch when `clear-all` is called
patches-own [ region ]
to set-regions
let current-region 1
; only act on non-black patches that haven't yet been assigned a region
let untagged patches with [ region = 0 and pcolor != black ]
while [any? untagged] [
ask one-of untagged [
ask patches-adjacent [
set region current-region
]
]
; update the region and the untagged patches we have left to process
set current-region current-region + 1
set untagged patches with [ region = 0 and pcolor != black ]
]
; this is just to get a view of the regions to quickly see if our code worked, it can be removed
ask patches [ set plabel region ]
end
to-report patches-adjacent
report patches-adjacent-ex (patch-set self) pcolor
end
to-report patches-adjacent-ex [found pc]
let newly-found neighbors4 with [ (not member? self found) and pcolor = pc and region = 0 and pcolor != black ]
set found (patch-set found newly-found)
ask newly-found [
; use recursion to find the patches adjacent to each newly-found one
; relying on updating the `found` agentset as we go to avoid duplicates
; or looping forwarder
set found (patches-adjacent-ex found pc)
]
report found
end
I solved this by using the Patch Clusters model that can be found in the NetLogo model library.
I'm modeling a cityscape for looking at movement, where patches equate to buildings and have different influence values. I need to use a reporter function that calculates the value of each patch with something like:
(its own influence) plus (the influence of neighbors) divided by the
distance to a specific turtle (max-one-of distance myself)
The turtle will then move towards the patch with the highest influence value, but along a defined street.
I'm new to using netlogo and have gotten completely stuck.
I've included a portion of what I have so far, but I can't figure out how to write the reporter function that will compute each patches influence value (in-cone) so that the turtles can then move towards the best option.
to setup-influence-field
ask patches with [pcolor = green] [set influence commercial-influence]
ask patches with [pcolor = orange] [set influence production-influence]
ask patches with [pcolor = yellow] [set influence domestic-influence]
ask patches with [pcolor = pink] [set influence religious-influence]
ask patches with [pcolor = blue] [set influence public-influence]
end
to go
move-serapis
end
to move-serapis
ask serapis [set-procession-heading]
repeat 2 [ ask serapis [ fd .25 ] display ]
tick
end
;;;;; the reporter values are need for this part of the code so that the turtles (serapis) can move towards the patches with the highest influence value;;;;
to set-procession-heading
let direction patches in-cone 4 40 with [influence-field > 0]
if any? influence-field
[face max-one-of influence-field] ;;;; face towards the highest computed influence value
ifelse any? patches with [pcolor = black] in-cone 1 25
[process]
end
Any help would be greatly appreciated!
I don't think this is completely correct and I can't test it, but it should start you off and maybe someone here can fix it if you let us know the errors.
to set-procession-heading
let direction-targets patches in-cone 4 40 with [influence-field > 0]
if any? direction-targets
[ face max-one-of direction-targets [ influence-amount self ] ]
end
to-report influence-amount [ target-node ]
report ( [ influence-field ] + sum [ influence-field] of neighbors ) / distance target-node
end
What I have done is set up a separate procedure to report the results of your calculation. That procedure takes an argument (named target-node) because you need to be able to pass the identity of the turtle being influenced. Once you have that procedure, then you can simply pass the agent-set of potential directions to the calculation procedure and pick the one with the largest value.
I have a question about Netlogo.
Is there any smart way how to find block of patches (in my case, I need to find block of three patches with yellow color => more precisely, I need to find row or column with three yellow patches next to each other).
Is there any Netlogo function I could use or is it neccessary to use loops and work as I would with two-dimensional array?n
blckbird is correct, if you want you can extract all coordinates of yellow patches and process those coordinates to figure out which patches are adjacent.
If all you need is to know where your rows or columns of threes are, however, you could also get all the yellow patches to check the color of neighboring patches and tell you if a row or column is formed. For an example, see the code below.
to setup
ca
reset-ticks
ask n-of 150 patches [
set pcolor yellow
]
end
to find-threes
;; for rows
ask patches with [ pcolor = yellow ] [
if ( [pcolor] of patch-at 1 0 = yellow ) and ( [pcolor] of patch-at -1 0 = yellow ) [
;; do whatever you need
set pcolor pcolor - 3
show ("I am the center of a row of three")
]
]
;; for columns
ask patches with [ pcolor = yellow ] [
if ( [pcolor] of patch-at 0 1 = yellow ) and ( [pcolor] of patch-at 0 -1 = yellow ) [
;; do whatever you need
set pcolor pcolor - 3
show ("I am the center of a column of three")
]
]
end
With ask patches you can loop over all patches. Further a condition can be applied to the ask statement by using with. So you are looping over all the patches meeting that condition. Here I just put the x and y coordinates of the patches in a list which you can then further process.
let yellow_patches []
ask patches with [pcolor = yellow] [
set yellow_patches lput [pxcor pycor] yellow_patches
]
I am new at net logo and I want to write a model based on tragedy of the commons in the case of an overfished pond. The purpose is to find an equilibrium between fishers and fishes based on an economic model with demand and supply. If there are less fishers, more fishes will be in the pond, then after a certain time (ticks) the number of fishers increases and less fishes will be in the pond. Maybe set like a number of fishes per day that can be fished. Thus, the solution is to find a convenient number of fishers as the fishes can still reproduce. I want to have a box in the interface where I can type in a number and see what happens with the number of fishes.
I have no idea how to set this up. I hope to hear from you :)
I started with this code:
breed [fishers fisher]
breed [fishes fish]
to setup
clear-all
reset-ticks
ask patches [set pcolor blue ] ;; lake/pond in form of a rectangle in color
ask patches [ if pxcor > 8 [ set pcolor green ]]
ask patches [ if pycor > 8 [ set pcolor green ]]
ask patches [ if pycor < -8 [ set pcolor green ]]
ask patches [ if pxcor < -8 [ set pcolor green ]]
ask one-of patches with [ pcolor = blue ] [ sprout 20 [set shape "fish" set color pink set size 1.5 ]] ;; creates fishes
ask one-of patches with [ pcolor = green ] [ sprout 2 [set shape "person" set color black set size 3 ] ] ;; creates fishers
end
to go
tick
;;fishes
ask turtles with [ shape = "fish" and color = pink ]
[ right random 360 forward 1
if [pcolor] of patch-ahead 1 = green [ right 180 fd 1 ]]
;; fishers
ask turtles with [ shape = "person" and color = black]
[;right random 360 forward 1
if any? patches with [pcolor = blue]
[set heading towards one-of patches with [pcolor = blue] forward 1]
if [pcolor] of patch-ahead 1 = blue [ right 180 fd 2 ]]
ask turtles with [shape = "person" and color = black]
[if any? turtles with [shape = "fish" and color = pink] in-radius 2
[ask turtles with [shape = "fish" and color = pink] in-radius 2 [die]]]
end
Firstly, I suggest you look through existing models in the Netlogo library (Wolf-sheep-predation model may help). You roughly have the right idea in your current code, but you should look at other models to improve. You've already set your different breeds of turtles, but you should also set up their respective shapes under 'setup'. This would help you a great deal later - instead of calling for
ask turtles with [ shape = "fish"...]
you can simply
ask fishes [do sth...]
For that 'box at the interface', you can have a slider at the interface determining the number of fishers you want your run to start with. With another slider, you can set the fishing pressure in your simulated run (i.e. how many fish each fisher will catch) and I suppose you can also consider how this changes when population of fish decreases.
Finally, for a model like yours, you can observe the supply and demand trend by plotting the curves of no. of fishers over time and no. of fishes over time. Again, look at the wolf-sheep-predation model to have an idea of how to do this.
I can't give you more than this I'm afraid since I'm no pro myself but hope this helps a little. Hope someone else would be able to give you a clearer idea.
I want to move my turtle to the nearest red or green color patch in its vision.I tried this code but it doesnt move.What is wrong?
while [collectedDirt = 5]
[
ask turtle 0 [
let nearest-patch min-one-of (patches with [pcolor = red or pcolor = green] in-cone 15 20)[distancemyself]
face nearest-patch
fd distance nearest-patch
]
set collectedDirt collectedDirt + 1
search-dirt ;; research whether there is red patch in-cone because of new position
]
You might want to provide us with a little bit more context, but my guess would be that you need something like while [collectedDirt < 5] instead of while [collectedDirt = 5]. If this block is the only way your turtles can "collect dirt", the code probably never even gets executed...
Edit:
You also might want to add a condition in case there is no red/green patch in the cone of vision:
if is-patch? nearest-patch [
face nearest-patch
fd distance nearest-patch
set collectedDirt collectedDirt + 1
]