I have just found out about GephiStreamer. https://pypi.python.org/pypi/GephiStreamer
Using this package one can send instructions from python to Gephi to create nodes and edges in Gephi.
# Create a node with a custom_property
node_a = graph.Node("A",custom_property=1)
# Create edge
edge_ab = graph.Edge(node_a,node_b,custom_property="hello")
stream.add_edge(edge_ab)
Similarly I want to do everything in Gephi through Python. Here is what I typically do.
ex:
steps:
load nodes
load edges
calculate betweeness centrality
change the size/color of nodes as per their centrality scores
change the graph layout (such as forceatlas2)
give the output graph
Below is the output I have got manually, but I want to produce the same by sending instructions from python to Gephi. Documentation doesn't tell anything beyond creating nodes, edges and graphs.
I have also found out about NetworKit. https://networkit.iti.kit.edu/data/uploads/docs/NetworKit-Doc/python/html/gephi.html
This is slightly better than gephistramer, but this requires python 3.4 or higher and most of the packages like pandas, numpy or sickit are in 2.7.
also Is there a way to send the file I have created in gephi back to python.
Please suggest.
PS: I have edited the entire question details so that it's easier to understand now (hopefully).
I found this question while looking for the answer myself. I picked Gephi as my visualizer and then wanted to build a graph that was well supported by the tool by pulling data from around my org with Python.
I found GephiStreamer and it looks a simple yet comprehensive way to build graphs in Gephi from an external python environment (command line, or IDE)
The other options at this point are:
The Gephi Python Scripting Console
Any Graph Lib that can export in a Gephi readable format
NetworkX
python-igraph
graph-tool
Any of the python GEFX writers (Google "python GEFX")
There is no simple answer to that. The people at the Facebook group might be knowing something but IMO the best way to do it would be to call the Gephi toolkit, i.e. the available jar, from jython, check here for an example use. The thing is that jython doesn't allow to install numpy and a series of other libraries but I guess you could get around this issue by piping the output of one script to the other or using a queue like Celery.
So I would write a script let's call it graph_construction.py that uses networkx, construct the graph and then write it in the standard output in gexf. Then I would write a second script, gephi.py that would execute things in gephi and let's say write the graph to a pdf and then do something like:
python graph_construction.py | jython gephi.py output.pdf
and pray for it to work.
Related
I have defined a graph by using from pyvis.network import Network and defining a network as net = Network().
I added to the net edges and nodes using the functions net.add_nodes(nodes) and net.add_edge(x, y). There is any chance to deal with this graph not only using a visualization? So for e.g. to find all paths between two specific nodes? Because searching in the documentation there is only the possibility to plot the graph. I saw other options (e.g. class) to deal with graphs (example) but is very annoying to define the graph with a dict of a dict.
From the pyvis documentation:
The pyvis library is meant for quick generation of visual network graphs with minimal python code. It is designed as a wrapper around the popular Javascript visJS library found at this link.
You probably want a library such as networkx, which you probably have tagged by accident. It's description states
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
This includes many operations, see the tutorial or to take your example: shortest path
I am using Yed to paint some graphs as shown in the picture below. Is there a way I can use python to compute a Depth-First exploration on these?
I would like the algorithm to protocol the Edges he has traveled and the nodes he visited.
Example graph:
Edit:
I would like to use this method to record actions of people in a sports game. At first you start at a base/Root, then you can run or jump (c or d). Running brings you to point 2, jumping to point 5.
The result that I need then is:
1. root, ([c,2] ,[b,3]), Descript_3
2. root, ([c,2] ,[a,4]), Descript_4
3. root, ([c,2] ,[b,2], [a,4]), Descript_4
...
I am just using yed, so I can use a graphical interface. If there is something better in pure python, I am all up for it. But lets stick to yed for now. Can I get additional attributes to the nodes?
Edit:
Since I cannot get this thing to work for myself, I am setting a bounty for an example program. The example program should do the following:
1. Parse the graphml-File and build up the tree
2. Compute all Roundtrip-Path with Node-Coverage
3. write all paths into a table: Name of the node, Text on the arrow
From there I can figure the rest out myself. If its done by using librarys, then that's cool too, but I need to be able to extend it myself. I would also have it to be able to handle graphs, instead of trees.
You can use the networkx module (need to be installed pip install networkx). This module is a powerfull library for working with graphs. It can read the graphml format which yed produces and has algorithems for traversing a graph. Have a look at the documentation of it: networkx
I am a meteorologist, and lately I am trying to investigate the possibility of building my one sondes.
In order to do that, I have the following work plan :
I would like to generate 3D models pyformex. An alternative is openSCAD. But I start with pyformex - to generate simple cylindrical sonde shapes with associated extra features, e.g. intake tube or such.
Next, I will like to split it in Meshes, using PyDistMesh; as well as prepare a raytraced point cloud model with Xrt.
In the third step, I would like to perform the CFD works.
Now, my questions :
Are there some other simple Python Libraries to generate 3D models? I would like a very simple system, where i can issue commands like p = Parallelogram (length, height, width), or p.position(x,y,z) etc. It would be nice to have built in mouse interaction - that is, a built in drawing component, which I can use to display the model, and rotate/ zoom/pan with mouse.
Any other mesh generation tools?
For this step, I would need a multiphysics system. I tried to use OpenFOAM, it is too huge (to hack through). I have taken a look at SU2, but it seems to focus more on aerospace engineering, than Fluid Dynamics (I would like to simulate the flight of the sonde - which is closer to aerospace engineering, as well as the state of the atmosphere). Fluidity seems to suit my needs better, but I dont find a python fork thereof. So are there some general purpose, not too bloated up, multiphysics python library for geophysical and general hydrodynamic simulations? I have taken a look a MOOSE, also dont find a python binding for it.
Scientific visualization : Are there some 3 or 4 (or may be higher dimensional) visualization libraries? I would prefer to issue simple commands as Plot instead of first generating a window / form, and then putting the graphs on it, if possible.
FINALLY, and most importantly, if the same can be done by C++ or Fortan, or some other language besides java, I would also consider using those.
Have a look at http://freecadweb.org/. This seems to be under active development. It is a fairly complete open source CAD package written in python. I believe it also has tools for meshing.
For cfd, you might want to consider openfoam - http://www.openfoam.com/. This is an open source cfd package with the obligatory steep learning curve. There seem to be some python libraries to be available that link to it, however I'm not sure how active these are:
http://openfoamwiki.net/index.php/Contrib/PyFoam
http://pythonflu.wikidot.com/
I need some graph algorithms for a project. I could implement them from scratch, but before I do so I wanted to see if there was something out there that I could use. I've looked at networkx and igraph. Networkx turns out to be memory inefficient for the size of the graphs I have to deal with. I think I'm using igraph incorrectly because it seems to just hang. I'll get more information on igraph if anyone's interested.
Networkx seemed promising because it is implemented in pure Python. The problem is that building the graph eats up all the memory. I have the graph in an SQLite database as an adjacency list.
So what I wanted to do was modify the code so that it can work directly with the SQLite representation instead of the networkx representation. Has anybody ever tried this successfully?
If that does not work, it goes back to the question in the title. Are there any graph implementations in Python that are reasonably decoupled from the graph representation?
I want to implement a driving direction in Python using something like Djikstra's shortest path. The algorithm requires the data to be represents in graph structure. Raw GIS data (e.g. shape files or OpenStreetMap data, however, represent their data differently. Therefore, I was wondering is there any Python library that can convert GIS data to graph structure?
In Java I found that GeoTools has exactly what I described. Is there any similar library in Python?
Haven't used it yet, but there's a function that generates directed graphs from shapefiles in Networkx: http://networkx.lanl.gov/reference/readwrite.nx_shp.html. If it doesn't do exactly what you need, it might suggest a solution. Uses OGR's Python bindings to read data.
See also Graphserver http://bmander.github.com/graphserver/.