Use case:
nodes are documents
Links are links between documents that have an associated correlation (e.g., 0 to 1)
Being new, it is not clear how to apply those correlations or "weights' so that the document cluster in a logical manner.
Can anyone point me to an existing example?
Thanks in advance.
Positioning nodes is done by the layout. Use any force-directed (physics) layout, like CoSE or Cola. Those layouts allow your to specify how strongly nodes should be pulled towards one another on a per-edge basis.
Try some of the force-directed layouts to see which one gives results that you like. Each one has different trade-offs (speed, aesthetics, etc.).
Just make sure to set the edge force for whatever layout, e.g. edgeElasticity for CoSE, to be proportional to edge.data('weight').
Example: http://js.cytoscape.org/demos/7b511e1f48ffd044ad66/
Related
I want to calculate a route from A to B using only a subset of the routes available in a city, as long as it is possible (if A or B is not on the subset of roads I still need to calculate the route). I tried to use avoidareas but it's quite difficult to define rectangles to avoid outside of the roads (and I saw somewhere the number of boxes is limited).
Can you please explain what do you mean by "subset of the routes". Do you mean to avoid a particular kind of road?
if you want to always include a certain road(s) you can always use waypoints to direct the route through those roads. Generally, Routing algorithms are designed to "avoid" not "prefer" an area.
Various examples on how to avoid a rectangle(s) is explained here- https://developer.here.com/documentation/routing/topics/example-route-avoiding-an-area.html
How to use a waypoint is explained here - https://developer.here.com/documentation/routing/topics/resource-param-type-waypoint.html
How to avoid a certain road type is explained here - https://developer.here.com/documentation/routing/topics/avoiding-certain-road-types.html
My combination chart has two y-axes, one for price and one for value. This data is being pulled from the same table.
Is it possible to filter each of the two axes differently? Whenever I filter the table as a whole, it obviously affects both axes. Is there a way around this?
I don't think you can do that, the underlying data set for any visualization is the same no matter the split or the way you choose to display it (in your case, two axes).
If you need the two to react differently to filtering, I suggest you make two visualizations and apply 2 different filtering schemes to them (you will need that, as they are both coming from the same data table).
If this does not meet the requirements, please specify the rationale behind it, we might be able to come up with better idea.
I have the following graph with 2 different parameters called p and t.
Their relationship is experimentally found. Manually by knowing (t,p), you can simply find the area number (group) of the point based on where it is located. For example, point M(t,p), locates in area 3 and belongs to group number 3. However, I would like to write a code/logical approach which automatically finds the group numbers. therefore when it reads (t,p) it will find the location of the point and give the group/Area number it belongs.
Is there any solution in Matlab for this scope? Graph
If you have the Image Processing Toolbox and your contours are closed, you can use imfill to fill them up (a bit like the bucket tool in Paint) and assign different values to each filled up region. Does this make sense to you? Let me know if you would like more detail.
Marta
I am trying to write a highly scalable system with titandb. I have a situation where some nodes are highly connected.
Imagine the following example at much larger scale.
Now I have the following situations:
I want to find all the freinds of node X.
I want to find a specific friend of node X for example 5.
For scenario 1 I do: g.V(X).out(friend).toList(). For scenario 2 I do: g.V(X).out(friend).hasId(5).next(). Both of these traversals will work but scale poorly as X gets more friends. Can I optimise this situation by putting more information on the edge label ? For example if on the edge between X and 5 I change the label to freind_with_5 will the following be faster:
`g.V(X).out(freind_with_5).next()`
From my understanding this will be faster as only 1 edge will be traversed. However, if I make such a change to my edge labels how would I find all the friends of X ?
You could encode data into your edge label, but I would say that do that at the cost of complicating your graph schema considerably and, as you note, make it hard to do simple things like "find all my friends". I don't think you should take that approach.
The preferred method for dealing with this is with vertex-centric indices. If you denormalize any data to your edges, you should do it with those indices in mind (and not by encoding that data into the edge label). Put some unique identifier for the friend on the "friend" edge and index that.
If your supernodes are especially large (millions+ edges) you should also consider Titan's vertex partitioning feature.
I'm currently writing an optimization algorithm in MATLAB, at which I completely suck, therefore I could really use your help. I'm really struggling to find a good way of representing a graph (or well more like a tree with several roots) which would look more or less like this:
alt text http://img100.imageshack.us/img100/3232/graphe.png
Basically 11/12/13 are our roots (stage 0), 2x is stage1, 3x stage2 and 4x stage3. As you can see nodes from stageX are only connected to several nodes from stage(X+1) (so they don't have to be connected to all of them).
Important: each node has to hold several values (at least 3-4), one will be it's number and at least two other variables (which will be used to optimize the decisions).
I do have a simple representation using matrices but it's really hard to maintain, so I was wondering is there a good way to do it?
Second question: when I'm done with that representation I need to calculate how good each route (from roots to the end) is (like let's say I need to compare is 11-21-31-41 the best or is 11-21-31-42 better) to do that I will be using the variables that each node holds. But the values will have to be calculated recursively, let's say we start at 11 but to calcultate how good 11-21-31-41 is we first need to go to 41, do some calculations, go to 31, do some calculations, go to 21 do some calculations and then we can calculate 11 using all the previous calculations. Same with 11-21-31-42 (we start with 42 then 31->21->11). I need to check all the possible routes that way. And here's the question, how to do it? Maybe a BFS/DFS? But I'm not quite sure how to store all the results.
Those are some lengthy questions, but I hope I'm not asking you for doing my homework (as I got all the algorithms, it's just that I'm not really good at matlab and my teacher wouldn't let me to do it in java).
Granted, it may not be the most efficient solution, but if you have access to Matlab 2008+, you can define a node class to represent your graph.
The Matlab documentation has a nice example on linked lists, which you can use as a template.
Basically, a node would have a property 'linksTo', which points to the index of the node it links to, and a method to calculate the cost of each of the links (possibly with some additional property that describe each link). Then, all you need is a function that moves down each link, and brings the cost(s) with it when it moves back up.