Simulating marry in netlogo - netlogo

In netlogo I am simulating a population and I want that individuals between 16 and 50 years old marry randomly with another single individual from the population. Each individual has an household-id and I want that the male individual change its household-id to his "wife" household id, but i don't know how to do it. For now I have this code
ask individuals [
if not married? and sex = "male" and age >= 16 and age <= 50 [
let potential-mate one-of individuals with [
not married? and age >= 16 and age <= 50
and sex = "female" and household-id != household-id
]
if potential-mate != nobody [
; this command do an Bernoulli equation,
; the relation is based on empirical data i have
ifelse random-bernoulli (- 0.765 * ln age + 2.9753) [
stop
] [
set my-mate potential-mate
set married? true
ask my-mate [ set married? true ]
ask my-mate [ set my-mate myself ]
]
]
]
]

Luke C's comment is correct: what you need is myself, as in:
household-id != [ household-id ] of myself
That being said, I would strongly suggest modelling things like marriages as links. Here is a working example:
breed [individuals individual]
individuals-own [age sex household-id]
undirected-link-breed [marriages marriage]
to setup
clear-all
create-individuals 100 [
set age random 100
set sex one-of ["male" "female"]
set household-id random 100
setxy random-xcor random-ycor
]
marry-individuals
reset-ticks
end
to marry-individuals
let bachelors individuals with [ not married? and age >= 16 and age <= 50 ]
ask bachelors with [ sex = "male" ] [
let potential-mates bachelors with [
sex = "female" and household-id != [ household-id ] of myself
]
if any? potential-mates [
if not random-bernoulli (- 0.765 * ln age + 2.9753) [
let mate one-of potential-mates
create-marriage-with mate
set household-id [ household-id ] of mate
]
]
]
end
to-report married? ; individual reporter
report any? my-marriages
end
to-report my-mate ; individual reporter
report [ other-end ] of one-of my-marriages
end
This way, you don't have to manage separate variables for married? and my-mate: a single link tells you all need to know about the relationship between these two individuals. The main advantage is that it's much less error prone: there is no risk for the values of these variables to ever become inconsistent. Notice, also, how the married? and my-mate make these concepts just as easy to access as they were before.
Another couple of comments about your code:
I usually avoid using stop if possible. The behavior of that primitive is not always intuitive, and it sometimes leads to errors.
Notice how I create a temporary bachelors agentset. This avoids checking for the age and married? conditions twice and makes the code more readable.
I don't know what you plan to do with them, but you might want to consider making households agents and representing membership in an household by creating a link to it. Using "id" numbers is not a very netlogoish way of doing things and sometimes lead to inefficient code.

Related

How can I get turtles to breed once during a defined breeding season?

In my model I have males and females. They can breed with each other to produce offspring at a specific tick every 365th day.
How can I get the adults to turn off the ability to breed once they reproduce but regain the ability the following breeding season.
ask females [
if age > 0 and age mod 365 = 0 [
reproduce
]
.
.
.
to reproduce
if count mates > 0 [ ; the number of males in a defined radius
hatch fecundity [
set mother myself
set father one-of [mates] of mother
]
One way to create a variable that counts the number of days since they last bred. Then increment that variable each tick. Then reset it once the female successfully reproduces. Something like (not tested):
females-own [days-since-child]
to go
...
ask females [ set days-since-child days-since-child + 1 ]
ask females with [days-since-child >= 365] [ reproduce ]
tick
end
to reproduce
if any? mates > 0 [ ; the number of males in a defined radius
set days-since-child 0
hatch fecundity [
set mother myself
set father one-of [mates] of mother
]
]
end

How to select up to a maximum number of turtles using roulette wheel selection

In my model the turtles have two sexes where the males have two potential tactics. The females count the number of males in a set radius.
I want the females to weight their probability of selecting from the group of males (without replacement) depending on the relative frequency of the two male tactics.
I already have the code for the probability of selecting from the males (matingPoolProbAnad and matingPoolProbRes) but I don't know how to implement it, though the rnd extension seems the way to go, specifically rnd:weighted-n-of size agentset [ reporter ].
It's complicated by three things (1) the males can mate with more than one female but (2) only once with a given female and (3) females can only mate with a maximum of five males.
to count-mates ; ask the females to count the number of males in a 10 patch radius & then
; determine the frequency of the resident males in their patch
ask turtles with [sex = "female"]
[
if any? turtles with [sex = "male"] in-radius 10
[ set potentialMates turtles with [sex = "male"] in-radius 10
ifelse any? potentialMates with [anadromousM = 1]
[ set FA count potentialMates with [anadromousM = 1] / count potentialMates ]
[ set FA 0]
ifelse any? potentialMates with [anadromousM = 0]
[ set FR count potentialMates with [anadromousM = 0] / count potentialMates ]
[ set FR 0]
]
]
end
to mating-pool-prob ; negative frequency dependency which is based on the number of male
; resident turtles
ask turtles with [sex = "female"]
[
ifelse (FA = 1) and (FR = 0)[
set matingPoolProbAnad 1
set matingPoolProbRes 0
]
[ifelse (FA > 0) and (FR < 1)
[
set matingPoolProbRes exp(a - b * (FR - c ))/(1 + exp(a - b * (FR - c)))
set matingPoolProbAnad 1 - matingPoolProbRes
]
[
set matingPoolProbAnad 0
set matingPoolProbRes 1
]
]
]
end
This example may approach what you're getting at, but obviously would need to be adapted from this toy version. This setup sprouts 75% of males with strategy A and the rest with strategy B, and gives all turtles an empty agentset of mates to start off:
breed [ males male ]
breed [ females female ]
turtles-own [ mates ]
males-own [ strategy ]
females-own [ max-mate-count mate-count ]
to setup
ca
ask n-of 200 patches [
sprout-males 1 [
ifelse random-float 1 < 0.75 [
set strategy "A"
set color orange
] [
set strategy "B"
set color violet
]
]
]
ask n-of 50 patches with [ not any? turtles-here ] [
sprout-females 1 [
set color green
]
]
ask turtles [
set mates ( turtle-set )
]
reset-ticks
end
Use a while loop to have each female iteratively assess the strategy proportions of the males available to her, then add them to her 'mates' list. More detail in comments:
to choose-mates
ask females [
; set a cap on possible mates for females; 5, or the number
; available within the radius if less than 5
let availa-males males in-radius 10
let n-max count availa-males
set max-mate-count ifelse-value ( n-max < 5 ) [ n-max ] [ 5 ]
; Until a female has chosen up to her maximum number of mates:
while [ mate-count < max-mate-count ] [
; determine which available males are not already in her 'mates' agentset
set availa-males availa-males with [ not member? self [mates] of myself ]
; assess the proportion of B strategy in remaining available males
let prop_B ( count availa-males with [ strategy = "B" ] ) / n-max
; example probability choice, just meant to choose B males
; with a frequency disproportionate to availability
let proba_B ifelse-value ( prop_b * 2 < 0.6 ) [ prop_b * 2 ] [ 0.6 ]
; use a random float to determine which strategy type is chosen
set mates ( turtle-set mates ifelse-value ( random-float 1 < proba_B )
[ one-of availa-males with [ strategy = "B" ] ]
[ one-of availa-males with [ strategy = "A" ] ] )
; count the current mates to break the while loop once
; the maximum number of mates is reached
set mate-count count mates
]
; have the female's males add her to their own mates agentset
ask mates [
set mates ( turtle-set mates myself )
]
]
end
To check that 'B' males are being chosen disproportionately to their availability:
to check-values
let all-mates map [ i -> [strategy] of i ] [mates] of females
print word "Average proportion of 'B' mates chosen: " mean map b-proportion all-mates
print word "Actual proportion of 'B' males: " ( ( count males with [ strategy = "B" ] ) / count males )
end
to-report b-proportion [ input_list ]
let tot length input_list
let nb length filter [ i -> i = "B" ] input_list
report nb / tot
end
I'm not 100% sure that that's what you're after- maybe you can use the rnd package to clean up the loop.
Edit in response to comment
If you modify the end of the `choose-mates like so:
...
...
; have the female's males add her to their own mates agentset
ask mates [
set mates ( turtle-set mates myself )
]
if n-max < count mates [
print "Fewer available males than mates"
]
]
end
And your go looks like:
to go
choose-mates
end
You can run setup and go as many times as you like and you should never see the printout "Fewer available males than mates":
to repeat-1000
repeat 1000 [
setup
go
]
end
I ran that a few times and never had count availa-males be less than the count of mates. However, if you add in movement without allowing the females to reset their mates agentset, you do start to see it- for example, try running this a few times:
to go
choose-mates
ask turtles [ fd 1 ]
end
Now, because the turtles are moving around, you have some cases where females held on to their mates from the previous function call and then moved into a space where there were fewer availa-males. The quick and easy fix is to have females clear their mates each time. Where you do that depends on your model goals (how often do females choose mates? Do they only forget some of their previous ones? etc), but here's a very simple way:
to go
ask turtles [ set mates ( turtle-set ) ]
choose-mates
ask turtles [ fd 1 ]
end
Now you can run that as many times as you like and shouldn't see the "Fewer available males than mates" printout.

Subtract. SET variableX-variableY only once

I'm trying to set a resource variable. It will be time and will function like sugar in sugarscape. Its setup is: ask agentes [set time random-in-range 1 6].
The thing is... I want the agentesto participate in activities linking like we said here. But, with each participation, it should subtract a unity of agentes's time. I imagine it must be with foreachbut I seem to be unable to grasp how this works.
ask n-of n-to-link agentes with [n-t-activity = [n-t-activity] of myself] in-radius sight-radius [
while [time >= 2] [
create-participation-with myself [ set color [color] of myself ] ]
foreach (command I don't know)[
set time time - count participations]]
Essentially, I want the agentes to look if they have time to participate. If they do, they create the link and subtract 1 to their time. Only ONE per participation. If they have 3 time, they'll have 2 participations and 1 time. If they have 1 time, they won't have links at all.
EDIT
You're right. I don't need while. About foreach, every place I looked said the same thing but I can't think of other way. About colors, they're only for show purpose.
The relationship between time and participation counts is as follows: the agentes have time they can spend in activities. They participate if time>=2. But every participation (link with activity) consumes 1 time when the link is active (I didn't write the decay code yet; they'll regain their time when it is off).
EDIT V2
Nothing, it keeps subtracting even with the []. Maybe the best choice is if I give you the code so you can try it. You'll have to set 5 sliders: prob-female (53%), initial-people (around 200), num-activity (around 20), n-capacity (around 25) and sight-radius (around 7). And two buttons, setup and go. I also set a patch size of 10 with 30 max-pxcor and max-pycor. Here is the code. Sorry if I'm not clear enough!
undirected-link-breed [participations participation]
turtles-own [
n-t-activity
]
breed [activities activity]
activities-own [
t-culture-tags
shared-culture
]
breed [agentes agente]
agentes-own [
gender
time
culture-tags
shared-culture
]
to setup
clear-all
setup-world
setup-people-quotes
setup-activities
reset-ticks
END
to setup-world
ask patches [set pcolor white]
END
to setup-people-quotes
let quote (prob-female / 100 * initial-people)
create-agentes initial-people
[ while [any? other turtles-here ]
[ setxy random-xcor random-ycor ]
set gender "male" set color black
]
ask n-of quote agentes
[ set gender "female" set color blue
]
ask agentes [
set culture-tags n-values 11 [random 2]
set shared-culture (filter [ i -> i = 0 ] culture-tags)
]
ask agentes [
set time random-in-range 1 6
]
ask agentes [
assign-n-t-activity
]
END
to setup-activities
create-activities num-activity [
set shape "box"
set size 2
set xcor random-xcor
set ycor random-ycor
ask activities [
set t-culture-tags n-values 11 [random 2]
set shared-culture (filter [i -> i = 0] t-culture-tags)
]
ask activities [
assign-n-t-activity]
]
END
to assign-n-t-activity
if length shared-culture <= 4 [
set n-t-activity ["red"]
set color red
]
if length shared-culture = 5 [
set n-t-activity ["green"]
set color green
]
if length shared-culture = 6 [
set n-t-activity ["green"]
set color green
]
if length shared-culture >= 7 [
set n-t-activity ["black"]
set color black
]
END
to go
move-agentes
participate
tick
end
to move-agentes
ask agentes [
if time >= 2 [
rt random 40
lt random 40
fd 0.3
]
]
end
to participate
ask activities [
if count my-links < n-capacity [
let n-to-link ( n-capacity - count my-links)
let n-agentes-in-radius count (
agentes with [
n-t-activity = [n-t-activity] of myself ] in-radius sight-radius)
if n-agentes-in-radius < n-to-link [
set n-to-link n-agentes-in-radius
]
ask n-of n-to-link agentes with [
n-t-activity = [n-t-activity] of myself] in-radius sight-radius [
if time >= 2 [
create-participation-with myself [
set color [color] of myself ]
ask agentes [set time time - count my-participations] ]
]
ask activities [
if not any? agentes in-radius sight-radius [
ask participations [die]
]
]
]
]
end
to-report random-in-range [low high]
report low + random (high - low + 1)
END
EDIT V3
I asked Bill Rand to help me and he solved the problem. The issue was in this line: let candidates agentes with [ n-t-activity = [n-t-activity] of myself ] in-radius sight-radius. He solved the problem this way: let candidates agentes with [ n-t-activity = [n-t-activity] of myself and not participation-neighbor? myself ] in-radius sight-radius. Being this and not participation-neighbor? myself the condition to make sure that the agente is not already a part of that activity.
You almost never need foreach in NetLogo. If you find yourself thinking you need foreach, your immediate reaction should be that you need ask. In particular, if you are iterating through a group of agents, this is what ask does and you should only be using foreach when you need to iterate through a list (and that list should be something other than agents). Looking at your code, you probably don't want the while loop either.
UPDATED FOR COMMENTS and code - you definitely do not need while or foreach.
Your problem is the following code. You ask agentes that satisfy your conditions to create the links, but then you ask ALL AGENTES to change their time (line I have marked), not just the agentes that are creating participation links.
ask n-of n-to-link agentes with [
n-t-activity = [n-t-activity] of myself] in-radius sight-radius [
if time >= 2 [
create-participation-with myself [
set color [color] of myself ]
ask agentes [set time time - count my-participations] ] ; THIS LINE
]
The following code fixes this problem. I have also done something else to simplify reading and also make the code more efficient - I created an agentset (called candidates) of the agentes that satisfy the conditions. In this code, the candidates set is only created once (for each activity) instead of twice (for each activity) because you are creating it to count it and then creating it again to use for participation link generation.
to participate
ask activities
[ if count my-links < n-capacity
[ let candidates agentes with [
n-t-activity = [n-t-activity] of myself ] in-radius sight-radius
let n-to-link min (list (n-capacity - count my-links) (count candidates ) )
ask n-of n-to-link candidates
[ if time >= 2
[ create-participation-with myself [ set color [color] of myself ]
set time time - count my-participations ] ; REPLACED WITH THIS LINE
]
ask activities [
if not any? agentes in-radius sight-radius [
ask participations [die]
]
]
]
]
end

Allow turtle moves around a specific patch

I want to build a model of a city with hospitals. There are people, and people who are employees of specific hospital.
I want the employees to be moving without exceeding a maximum distance from the hospital where they work.
persons-own [
hospital-employees? ; true if work in hospital
hospital-position-cordx ; xcor of the hospital where he works
hospital-position-cordy ; ycor of the hospital where he works
]
to move
; they can move only around the hospital (max distance 5 patch)
ask persons with[hospital-employees?][
...........
]
; other people can move free
ask persons with[not hospital-employees?][
rt random 180
lt random 180
fd 1
]
end
It this possible?
I'm sure there are many ways to approach that problem. Here is a simple one:
breed [hospitals hospital]
breed [employees employee]
employees-own [my-hospital]
to setup
clear-all
set-default-shape hospitals "house"
set-default-shape employees "person"
ask n-of 5 patches [
sprout-hospitals 1 [
hatch-employees 5 [
set my-hospital myself
]
]
]
reset-ticks
end
to go
let max-distance 5
ask employees [
ifelse distance my-hospital > max-distance - 1 [
face my-hospital
] [
rt random 180
lt random 180
]
fd 1
]
end

Controlling lives of turtles in NetLogo

For a project, I'm developping a simulation in NetLogo dealing with rabies diseases in dogs and humans. I have some turtles-humans with dogs that can be vaccinated or not. At the beginning I create a dog with rabie and, in according to the fase (1 or 2) of the disease, it can spread the disease to other dogs with a probability. At the end the dog can die either for paralysis (if a probability is higher than 75%) or for other complications. Here's the code:
http://pastebin.com/esR75G3T
In the end you can see that a dog not dying for paralysis will die after some days (between 4 or 6). In other words when the days_infected are equal to end-life.
To check if everything is ok at the beginning I tried to set that NONE of the dog is vaccinated so everyone is supposed to get the disease. In fact when the dog is in phase 2 it will bite anyone. The problem is that if I delete the last line of the code, everything works and some dogs die of paralysis and the other remain alive. If I enable also the last line to let the other dogs die too, nothing works...no dog is infected. why?
This is not a problem with your code: this is a problem with the dynamics of your model. What's happening is that your initial sick dog dies before actually infecting another dog. This is why removing the if (days_infected = end-life) [die] "fixes" the problem.
When I tried your model with a huge population (e.g., 5000 people) so that encounters are more frequent, the infection does spread. You could also increase the probability of infection, or increase the duration of the "furious" phase, I guess.
Another unrelated suggestion, if I may: you should have distinct persons and dogs breeds. Trying to cram everything inside regular turtles makes your code much more complicated than it should be. The way I would approach this would be to create a link from the person to her dog, and then use tie so that the dog is automatically moved when you move the person.
Edit:
OK, here is a version of your code slightly modified to use breeds:
globals [
total_dogs_infected
total_dogs
dead_humans
dead_dogs
]
breed [ persons person ]
persons-own [
sick?
]
breed [ dogs dog ]
dogs-own [
sick?
vaccinated?
rabies_phase
days_infected
end-incubator
end-furious
end-life
]
to setup
clear-all
initialize-globals
setup-turtles
reset-ticks
end
to initialize-globals
set dead_humans 0
set dead_dogs 0
set total_dogs_infected 0
end
to setup-turtles
set-default-shape persons "person"
set-default-shape dogs "wolf"
create-persons people [
setxy random-xcor random-ycor
set size 1.5
set sick? false
ifelse random 100 < 43 [
set color green
hatch-dogs 1 [
set color brown
set heading 115 fd 1
create-link-from myself [ tie ]
set days_infected 0
set vaccinated? (random 100 > %_not_vaccinated)
if not vaccinated? [ set color orange ]
]
]
[
set color blue ;umano sano senza cane
]
]
set total_dogs count dogs
ask one-of dogs [ get_sick ]
end
to get_sick
set sick? true
set color white
set rabies_phase 1
set end-incubator 14 + random 57
set end-furious (end-incubator + random 5)
set end-life (end-furious + 4 + random 2)
set total_dogs_infected total_dogs_infected + 1
end
to go
move
infect
get-older-sick-dog
tick
end
to move
ask persons [
rt random 180
lt random 180
fd 1
]
end
to infect
ask dogs with [ sick? ] [
if (rabies_phase = 1 and (random 100) <= 2) or rabies_phase = 2 [
ask other dogs-here with [ not sick? and not vaccinated? ] [ get_sick ]
]
]
end
to get-older-sick-dog
ask dogs with [ sick? ] [
set days_infected days_infected + 1
;the incubator phase ends after at least 14 days + random(57) and then we have phase 2 (furious)
if (days_infected = end-incubator) [ set rabies_phase 2 ]
;when the main furious phase finishes we have 75% of probability that a secondary furious phase continues for other 4 - 6 days until death ;or we have a probability of 25% that the disease end in paralysis with a fast death
if (days_infected = end-furious and (random 100 > 75)) [
set dead_dogs dead_dogs + 1
die
]
if (days_infected = end-life) [
die
]
]
end
; These last reporters are not used,
; they just illustrate how to get the
; dog from the owner or vice-versa:
to-report my-dog ; person reporter
report one-of out-link-neighbors
end
to-report has-dog? ; person reporter
report any? out-link-neighbors
end
to-report my-owner ; dog reporter
report one-of in-link-neighbors
end
Not only does it simplify some expressions (e.g., ask dogs with [ sick? ] instead of ask turtles with [ has_dog? and sick_dog? ]), it opens up all sorts of possibilities: a dog could run away from its owner, the owner could die without the dog dying, an owner could have two dogs, etc.