I've imported nodes with edges in gephi and now I'm trying to get partitions containing four nodes , connected only to each-other(multiple connections are allowed), creating rectangle.
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I have a grid of points like a single channel picture. I find the connected components using openCV with python. I want to get polygons of the connected components as shown below
Is there anyway to get something like shapely polygons from the grid and connected components labels? Also polygons can have holes in them.
I was recently going through Topological Sort and DFS from CRLS. They have this entry/exit time concept by which we can classify graph edges into
tree edge
forward edge
back edge
cross edge
So the question is - does Topological sort using DFS try to remove forward edges from the tree keeping only tree edges to arrive at the sorted result?
Note that if a graph has a back-edge, it is not a DAG (Directed Acyclic Graph) since it contains a cycle and hence cannot be topologically sorted.
When we're topologically sorting, we are not removing any edge, we're simply providing a linear order so that edges only travel in one direction: from nodes that appear earlier in the order to nodes that appear later. Forward edges are certainly allowed to exist is such an order. What kind of topological order do you believe the following graph exhibits?
Is there a way to manually set the minimum and maximum node size and colour ranking based on attributes such as node degree or weighted degree)? In Gephi, when I want to use this ranking, it automatically takes the minimum and maximum of the parameter (which in my case is either degree or weighted degree). I have multiple network files and I want to compare them and every network has a different min and maximum for degree and weighted degree so when I plot them, I cannot compare them because they are plotted based on min and max of every network and only relative to individual network. Is there a way to manually enter an attribute minimum and maximum values for node ranking? I am using Gephi 0.9.2 on Mac.
Hope this helps. This is for In-Degree but it generalises for all attributes
I managed to get it done. What I did is, first import the network file into Gephi and compute weighted degree or Degree statistics. Go to Data tab and look for min and maximum value of these attributes. I check such min and max values in all my networks. then I choose the lowest min value and highest max value out of all my networks. These values you will use in the next step. Next, I import a single network in Gephi, computed Degree and weighted degree statistics. Then went to Data tab and there I added manually two nodes (with any label of your own choice) and then input the min values estimated in the previous step of the required attributes to one node and max values to the second node. When ordering nodes or assigning color or setting size of nodes based on attributes, Gephi then considers those nodes into account and plot the network accordingly. Then I go to filter tab and go to partition tab and select partition by range. There I exclude the nodes based on the attribute values that I manually specified as min and max. Those nodes will disappear from your network and there you have the final network. This way, I was able to compare different networks together visually.
What is the graph layout algorithm that is used in Neo4j?
I would like to have the paper that explain the graph layout algorithm that is shown in NEO4J.
I wan to know why the nodes are organized in the way Neo4j presents them.
The layout algorithm used for visualizing graphs in the Neo4j browser is a force directed algorithm. From Wikipedia:
Their purpose is to position the nodes of a graph in two-dimensional or three-dimensional space so that all the edges are of more or less equal length and there are as few crossing edges as possible, by assigning forces among the set of edges and the set of nodes, based on their relative positions, and then using these forces either to simulate the motion of the edges and nodes or to minimize their energy.
For academic references, there is a chapter from the Handbook of Graph Drawing and Visualization that covers much of the literature here.
In addition to the Neo4j Browser code linked in stdod--'s answer there is a D3 example of force directed layout here.
To visualize a graph in the neo4j-browser is used d3 library.
View implementation of d3.layout.force here: layout.ts.
In ESRI's ARCGIS software, the Spatial Join tool has various "Match Options" for joining your data. I would like to know the most rapid and reliable Match Option for the following scenario:
Target features: Point Class
Join Features: Polygon class
-The points are within the polygons
-No polygons overlap
-All points are within a polygon
-Some polygons have many points
The ones I am considering (unless a different one is better) are:
Closest, Intersect, Within, and Have Their Centers In
Once I choose the fastest of those, will it be faster to include a search radius? Or is ARC smart enough that if you leave that blank it will assume a search radius of 0.