I'm using GIS extension in Netlogo to import shapefiles, then creating turtles from attributes of the shapefile. I'm using the distance primitive to calculate the distance between turtles. I know Netlogo does converts the shapefile to netlogo space, so the distances wouldn't be reported the same b/w GIS and Netlogo. For example, in GIS distance between turtle A and B is 49550 meters. In Netlogo, it's 0.2038. Is there a way to determine what the units of measure are in Netlogo? Is the conversion always the same or does it depend on the projection? Thanks for any assistance.
The distance in a NetLogo model is entirely arbitrary. You are deciding the unit of distance implicitly when you import a GIS real-world structure into whatever number of patches there are in the NetLogo world. In your case, the easiest way to work out the conversion factor is likely to be to find a few points on your GIS and get their xcor and ycor. From your question, haven't you already done this? You have said that 0.2038 is 49550m.
There will also be problems coming out of the projection - if your model covers a large real world area, then the mismatch between the surface of a sphere and a flat model will mean the distance conversion is different at different locations.
Maybe this helps. I found a model here, which is also trying to work with space.
I quote: "Grid cell size does not represent an absolute spatial unit (e.g. meters); instead, the size of grid cells is only meaningful with respect to the step size of individuals which can vary with user input."
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After my NetLogo simulation, I would like to measure the total area covered by only the turtles. Is there a simple way to implement this in NetLogo, or will I have to do this in another program?
My simulation has clusters that form and I would eventually like to calculate the cluster agent density. 1
NetLogo is not aware of where the edge of the turtles’ shapes are. So, if you are trying to work out what proportion of the screen has shapes on it, you need to do some complicated programming to calculate where the edges of the shapes are, how they overlap and so on. However, if all you care about is where the turtles are, then it's much easier. For example, to work out the proportion of patches where there are at least one turtle, you could do:
count patches with [any? turtles-here] / count patches
I need to represent in netlogo a matrix, which is patches with number on them, in both the matrix form and the tree form (quad tree).
is it possible to have mor that one world in netlogo? i need to visualize a world of patches and a tree at the same time.
I don't think it's possible but you can try modeling a big space and use half of it for your patches and the other half for the tree.
I have a landscape that includes a road network as in the below figure.
I would like to calculate an average number of roads (or white line in the figure) that link each color polygon (for example a black polygon) between them.
In a network, a link corresponds to a road, a node corresponds to a color polygon and I think that to calculate an average number of roads between color polygons means to calculate the average node degree of the network. For example, in the figure, the two black polygons are linked by two roads. So, the degree of a black polygon is 2. Is it possible to calculate a node degree with the extension Network of Netlogo ?
Thanks in advance for your help.
Normal NetLogo contains link agents that link turtles even without an extension. Calculating degree is usually just a matter of doing [ count my-links ] of node where node is the turtle you want to know the degree of. However, in NetLogo, turtles can't be connected by more than one link. The typical workaround for this is create a links-own variable (just like turtles-own or patches-own variable) . This variable is often called weight, but you can call it whatever you want. In that case, you would do [ sum [ weight ] of my-links ] of node to calculate the degree.
This is all assuming you have a network representation of your roadways, which it doesn't sound like you do. Furthermore, I'm not sure what you're trying to represent is a network, since (as shown in your picture) roads branch at intersections. Thus more than two polygons could be connected by a single (for some definition of "single") road. This is often called a hypernetwork or hypergraph. However, this is probably a heavier weight concept than what you want.
Now, I'm not entirely sure what you're really trying to calculate. Is it:
...the number of roads connected to a polygon? The lower polygon has 4 roads connected to it, the upper has 3 (visible).
...the number of polygons directly connected to the polygon? Both polygons are connected to 1 other (visible) polygon, though I assume in the larger picture there are more.
The number of roads connected to a polygon would be pretty easy to calculate, assuming each road is 1 pixel wide. You could just do:
count (patch-set [ neighbors4 with [ is-road? ] ] of polygon)
where polygon is a patch set containing the patches of the polygon and is-road? is a reporter that returns true for road patches and false for non-road patches (this could be something pcolor = white). Note that this will break if roads are wider than 1 patch or if the same road can touch a polygon in other places. Let me know if that's the case and I'll expand this into something that can that into account.
The number of polygons directly connected to the polygon is more difficult. The basic idea would be to follow the roads out until you hit other polygons and count the number that you hit. Code for this is somewhat tricky. I think the best way to go about it would be to have two patch-sets, frontier and explored and list of found polygons. frontier should initialize to every road patch touch the polygon. Each iteration, get the polygons touching the frontier and add them to the list of found polygons if they're not already in there. Add the frontier to explored. Get all the road patches touching the frontier that are not in explored. Set the frontier to this new set of patches. Keep going until frontier is empty. This is a version of breadth-first search. There could be a better way to do this.
There are a lot of similar questions but I can't get a clear answer out of them. So, I want to represent latitude and longitude in a 2D space such that I can calculate the distances if necessary.
There is the equirectangular approach which can calculate the distances but this is not exactly what I want.
There is the UTM but it seems there are many zones and letters. So the distance should take into consideration the changing of zone which is not trivial.
I want to have a representation such that i can deal with x,y as numbers in Euclidean space and perform the standard distance formula on them without multiplying with the diameter of Earth every time I need to calculate the distance between two points.
Is there anything in Matlab that can change lat/long to x,y in Euclidean space?
I am not a matlab speciallist but the answer is not limited to matlab. Generally in GIS when you want to perform calculations in Euclidean space you have to apply 'projection' to the data. There are various types of projections, one of the most popular being Transverse Mercator
The common feature of such projections is the fact you can't precisely represent whole world with it. I mean the projection is based on chosen meridian and is precise enough up to some distance from it (e.g. Gauss Krueger projection is quite accurate around +-500km from the meridian.
You will always have to choose some kind of 'zone' or 'meridian', regardless of what projection you choose, because it is impossible to transform a sphere into plane without any deformations (be it distance, angle or area).
So if you are working on a set of data located around some geographical area you can simply transform (project) the data and treat it as normal Enclidean 2d space.
But if you think of processing data located around the whole world you will have to properly cluster and project it using proper zone.
So, this is going to be pretty hard for me to explain, or try to detail out since I only think I know what I'm asking, but I could be asking it with bad wording, so please bear with me and ask questions if need-be.
Currently I have a 3D vector field that's being plotted which corresponds to 40 levels of wind vectors in a 3D space (obviously). These are plotted in 3D levels and then stacked on top of each other using a dummy altitude for now (we're debating how to go about pressure altitude conversion most accurately--not to worry here). The goal is to start at a point within the vector space, modeling that point as a particle that can experience physics, and iteratively go through the vector field reacting to the forces, thus creating a trajectory of sorts through the vector field.
Currently what I'm trying to do is whip up code that would allow me to to start a point within this field and calculate the forces that the particle would feel at that point and then establish a resultant force vector that would indicate the next path of movement throughout the vector space.
Right now I'm stuck in the theoretical aspects of the code, as I'm trying to think through how the particle would feel vectors at a distance.
Any suggestions on ways to attack this problem within MatLab or relevant equations to use?
In order to run my code, you'll need read_grib.r4 and to compile that mex file here is a link to a zip with the code and the required files.
https://www.dropbox.com/s/uodvixdff764frq/WindSim_StackOverflow_Files.zip
I would try to interpolate the wind vector from the adjecent ones. You seem to have a regular grid, that should be no problem. (You can use interp3 for this)
Afterwards, you can use any differential-equation solver for your problem, as you have basically a field of gradients and an initial value. Forward euler would be the simplest one but need a small step size. (N.B.: Your field should be a gradient field)
You may read about this in Wikipedia: http://en.wikipedia.org/wiki/Vector_field#Flow_curves
In response to comment #1:
Yes. In a regular grid, any (arbitrary chosen) point will have eight neighbors. interp3 will so a trilinear interpolation to determine an interpolated gradient vector.
If you use forward-euler, you will then move a small distance in that direction. There you interpolate a gradient and go a small step into this new direction and so on. What happens are two things:
You get a series of points that lie on a streamline and thus form the trajectory of a particle moving along the field
Get large errors, the further you move and the larger the step size is. Use a small step size or use a better solver (Runge-Kutta comes to my mind)
If all you want is plotting, then the streamline function might help.