My turtles have more than 30 attributes of boolean values and I would like to use a foreach loop to compare turtles and rank them based on their similarity without the need to compare each attribute individually. I might be missing an obvious point here, I have tried having a list of attributes, but it didn't work and all turtles got the maximum similarity score.
Here's some code that calculates the Hamming distance between two lists. Note that the very clever reduce code is taken directly from the NetLogo dictionary.
to testme
let ll1 (list TRUE TRUE FALSE FALSE)
let ll2 (list TRUE FALSE TRUE FALSE)
let ll3 ( map = ll2 ll1 )
show ll3
show reduce [ [occurrence-count next-item] ->
ifelse-value (next-item) [occurrence-count + 1] [occurrence-count] ] (fput 0 ll3)
end
If you were wanting to calculate the similarity score of a pair of turtles, you could turn this into a reporter that takes the two turtles as arguments. But it's not clear that comparing two turtles is what you want to do, so I haven't written code for that.
Related
"nw:weak-component-clusters" in the Networks extension will return a list of weakly connected agentsets. I would like to output the number of turtles in the biggest of these.
So
show nw:weak-component-clusters
observer: [(agentset, 15 turtles) (agentset, 20 turtles) (agentset, 16 turtles)]
would return 20.
Is there an easy way to do this please?
This isn't pretty but it will work:
to find_max
let my_list []
let my_max 0
let turt_list nw:weak-component-clusters
foreach turt_list [x -> ask x [set my_list lput count x my_list]]
set my_max max my_list
show my_max
end
There is a simpler approach using map:
to-report count-of-largest-cluster
report max (map count nw:weak-component-clusters)
end
map takes a reporter and a list as inputs, and reports a list whose items are the result of the input reporter being run for every item of the input list.
nw:weak-component-clusters is a list of agentsets, therefore map count nw:weak-component-clusters is a list of each agentset's count. Note that the parentheses in my solution are optional and only there for readability.
I am trying to count the number of "buyer" type turtles, which have a certain surplus (turtle variable) greater than or equal to zero, and price (another turtle variable) greater than the current turtle's price (already grabbed in local variable myprice...although there may be a more direct way to put it in)
let countup count buyers with ([surplus >= 0] and [price > myprice])
NetLogo returns
Expected a TRUE/FALSE here, rather than a list or block.
let countup count buyers with (surplus >= 0 and price > myprice) returns
WITH expected this input to be a TRUE/FALSE block, but got a TRUE/FALSE instead
Close! You're looking for:
let countput count buyers with [ surplus >= 0 and price > myprice ]
with is a report that takes two arguments, like so
<turtleset> with <report block>
where the reporter block is a clump of code surrounded by [ ] that will result in either true or false. In general [ ] is netlogo's way of grouping together code so you can doing something special with it, such as having each agent in an agentset run it. Hope that helps!
Also, I assume you've got something like let myprice price on, say, the line above this one. You can combine those lines like so (not saying this code is the right way to do it, just wanted to show another option):
let countput count buyers with [ surplus >= 0 and price > [ price ] of myself ]
Checkout the docs for (the very poorly named) myself.
I would like to make the sum = the total of pollen recieved by a plant from other plants (Donnors) which is stored in a list of a list (own by each turtle = plant).
The following code make an error (when computing the sum):
OF expected input to be an agent or agentset but got the list
[[119.05593 50 50] [301.25853 50 50] [30.23906 50 50] [460.525845 50
50] [55.16717 50 50] [301.25853 50 50]] instead.
Does any one could help me about the mistake in the line "set Tot_pol sum ..." ?
Many thanks for your help.
to check-pol [m] ;; we check the pollen recieved by the two morphs
set Donnors [] ;; empty list of pollen donnors
ask zsps with [morph = m] ;; morph of the pollen reciever
[
set totpol 0
;; check for pollen donnors and morph for compatiblity within a radius :
ask zsps with[distance myself <= 20 and morph != m]
[
set totpol (NMaleFlowers * 100 * item round (distance myself) pollination-list) ;; the farther the less pollen
set Donnors lput [ (list totpol NMaleFlowers NFemFlowers)] of myself Donnors
]
set Tot_pol sum [ item (position 0 Donnors) Donnors ] of Donnors ;; total of pollen recieved
]
end
Luke's answer is good and should fix your problem. I suspect, however, that you are going to be doing lots of these types of sums. You may wish to set up a to-report that you can use for whichever item you want to sum over, just by passing the item number and the name of the list of lists. It would look like this:
to-report sum-item [#pos #listoflists ]
let items map [ x -> item #pos x ] #listoflists
report reduce [ [a b] -> a + b] items
end
The first line extracts the relevant item (remember index from 0) into a new list which the second line sums.
You would then use it with set Tot_pol sum-item 0 Donnors
Here's an answer that is not actually responding to your question. Instead, it is a more NetLogo-ish way of doing what I think you are trying to do with your code.
to check-pol [m]
ask zsps with [morph = m]
[ let senders zsps with [distance myself <= 20 and morph != m]
set totpol sum [NMaleFlowers * 100 * round (distance myself)] of senders
]
end
Your code gets into levels of ask that I think are unnecessary. What I think you are doing with your list is keeping track of the pollen donors. But an agentset is a cleaner approach and then you can simply pull out the information you want from the agentset using of.
Further, when you ask zsps with[distance myself <= 20 and morph != m] to set variable values in your code, then THOSE agents (not the receiving agent) are the ones having their variables changed. I think you are trying to take the perspective of the receiver of pollen, who looks around and received pollen from the other agents that are close enough. So the receiving agent should have the value changed.
This is not tested.
I'm not 100% sure what you're after here (you may want to look at the Minimum, Complete, and Verifiable Example guidelines), but if I'm reading you right you want the sum of the first item for each entry in the Donners list.
As to why your approach didn't work- NetLogo is telling you with that error that you've used of with a list, but of only works with agents or agentsets. Instead, you have to use a list processing approach. The simplest way might be to use sum in conjunction with map first in order to get what you need:
to sum-first-item
let example-list [ [ 1 2 3 ] [ 4 5 6 ] [ 7 8 9 ] ]
let sum-of-firsts sum map first example-list
print sum-of-firsts
end
To translate to Donnors, try:
set Tot_pol sum map first Donnors
That should work, but without reproducible a code example I can't check.
This is what i want to do:
patches-own[
trait1
trait2
trait3
]
let similarityCounter 0
ask one-of patches[
ask one-of neighbors[
**for-each trait[
if neighborTrait = patchTrait**[
set similarityCounter (similarityCounter + 1)
]
]
]
]
The part between ** is what I'm unsure about. How does one iterate over the patch-own parameters and compare between patch and neighbor?
How about you create a list for each patch of their trait values and count matches in the two lists? It would looks something like this.
to testme
let similarityCounter 0
ask one-of patches
[ let mytraits (list trait1 trait2 trait3)
let theirtraits [(list trait1 trait2 trait3)] of one-of neighbors
set similarityCounter length filter [ xx -> xx ] (map = mytraits theirtraits)
]
end
The final line is a little dense. What it does is compare the two lists of traits using the map function with the = operator, which will return a list of true and false values indicating whether that specific trait matches. The filter then creates a list of just the true values and the length counts the number of those true values.
Unfortunately, NetLogo doesn't do the trick of treating a true as 1 and false as 0 that you see in some languages, so you can't simply sum the match results list.
I really like Jen's answer, but just for fun, I'd like to provide an alternative way to approach the problem that uses Jen's idea of treating true as 1 and false as 0.
But first, I think that, depending on the rest of your model, it could have been a good idea for you to store your traits directly in a list instead of separate variables. In programming, having variable names with a numeric suffix like trait1, trait2, etc. is usually a hint that a list should be used instead.
Nevertheless, we will leave your general design alone for now and just provide a small function that makes it easy to package your traits into a list:
to-report traits ; patch reporter
report (list trait1 trait2 trait3)
end
Once you have that, you can write something like [ traits ] of one-of patches to get a list of the patche's traits.
Now let's attack the problem of turning true and false into ones and zeros in a similar way. It's true that NetLogo doesn't provide that conversation automatically (which I think is a good thing) but it's easy to write our own function for that:
to-report bool-to-int [ yes? ]
report ifelse-value yes? [ 1 ] [ 0 ]
end
We are now ready to write our main function. We will use Jen's approach of mapping over the = operator to convert our lists of traits to a list of boolean (i.e., true/false) values, and we will then use map again to convert that list into a list of 1 and 0. Once we have that, all that is left is to sum it! Here we go:
to-report similarity-with [ other-patch ] ; patch reporter
report sum map bool-to-int (map = traits [ traits ] of other-patch)
end
Having that reporter makes it really easy to get the similarity between two patches. You can now say things like:
print [ similarity-with one-of neighbors ] of one-of patches
Notice how I have approached the problem by building small pieces that be combined together. I really like this way of proceeding: it allows me to concentrate on one part of the problem at a time, but it's also more easy to test and results in code that I find very readable. NetLogo's to-report procedures are a great tool to achieve that kind of modularity.
I hope this is a simple solution, but I'm having a difficult time with it.
Problem:
I would like to weight the probability of something occurring by an variable not a constant
Setup
My agent is a farm.
Farms own four variables that represent the
number of cows, goats, pigs, and sheep on it.
When a farm wants to
remove an animal, I'd like the likelihood to remove a member of a
particular species to be directly proportional to quantity of each
species on the farm (i.e. if there are 7 goats, 2 cows, and 1 pig,
there is a 70% probability of taking a goat and a zero percent
probability of taking a sheep)
I have found formula like this for when you know the exact numerical weight that each value will have:
to-report random-weighted [values weights]
let selector (random-float sum weights)
let running-sum 0
(foreach values weights [
set running-sum (running-sum + ?2) ; Random-Weighted Created by NickBenn
if (running-sum > selector) [
report ?1
]
])
end
and the methods described in the rnd extension. But both of these throw the "expected a constant" error when i put "Cow" in instead of a constant.
Something like:
to example1
let values ["Cow" "Sheep" "Goat" "Pig"]
let probabilities [2 0 7 1]
let indices n-values length values [ ? ] ; Made by Nicolas Payette
let index rnd:weighted-one-of indices [ item ? probabilities ]
let loca item index values
end
works well, but if I were to replace it with:
to example1
let values ["Cow" "Sheep" "Goat" "Pig"]
let probabilities [Num-Cows Num-Sheep Num-Goats Num-Pigs]
let indices n-values length values [ ? ] ; Made by Nicolas Payette
let index rnd:weighted-one-of indices [ item ? probabilities ]
let loca item index values
end
it fails.
Alan is right: you need to use the list primitive (as opposed to just brackets) when you want to construct a list from anything else than constants.
I would add two things to that:
The latest version of the rnd extension has two sets of primitives: one for agentsets, and one for lists. So you should probably update and use the rnd:weighted-one-of-list primitive.
Your code is based around using indices to pick an item. That's fine, but that's not the only way to do it.
You could also have something like:
to example1
let values ["Cow" "Sheep" "Goat" "Pig"]
let probabilities (list Num-Cows Num-Sheep Num-Goats Num-Pigs)
let loca first rnd:weighted-one-of-list (map list values probabilities) last
end
This may be a bit trickier to understand, but here is the gist of it:
The (map list values probabilities) expression takes both your values list and your probabilities list and "zips" them together using the list primitive, resulting in a list of pairs: [["Cow" 2] ["Sheep" 0] ["Goat" 7] ["Pig" 1]].
We pass the last reporter to the rnd:weighted-one-of-list primitive to tell it that the last (i.e., second) item of each of these pairs should be used as the probability.
Since rnd:weighted-one-of-list operates on a list of pairs, the item it returns will be a pair (e.g., ["Goat" 7]). We are only interested in the first item of the pair, so we extract it with the first reporter.
Note that we use the NetLogo's concise syntax for tasks when passing list as an argument to map and last as an argument to rnd:weighted-n-of. You could replace list with [ (list ?1 ?2) ] and last with [ last ? ], but it would be uglier.