How to create a image file from a graph through the gremlin console?

[Marlon]

For example, given this graph:

gremlin> graph = TinkerFactory.createModern() (1) ==>tinkergraph[vertices:6 edges:6] gremlin> g = graph.traversal(standard()) (2) ==>graphtraversalsource[tinkergraph[vertices:6 edges:6], standard] gremlin> g.V().has('name','marko').out('knows').values('name') (3)

How to print and save the graph into a file for visualization? I want a PNG or JPG file.

I am new to this and thanks for help.

[Stephen Mallette]

Answered on SO:

https://stackoverflow.com/q/48107585/1831717

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[Kelvin Lawrence]

If you use Python at all, the networkx and matploitlib libraries can read a GraphML file and render it. I have used this in a Python Notebook with Gremlin Python running where I extracted a subgraph to GraphML and rendered it using Python.

The code would be along the lines of:

"import matplotlib

import matplotlib.pyplot as plt

import networkx as nx

G = nx.parse_graphml(mygraph)

label = nx.get_node_attributes(G, "code")
plt.figure(figsize=(11,11))
nx.draw(G, node_color="#ffaa00",node_size=1200,labels=label,arrows=False)

Apologies in advance if my Python is ugly I'm more of a Ruby and Groovy guy :-)

Cheers

Kelvin

On Friday, January 5, 2018 at 6:05:17 AM UTC-6, Stephen Mallette wrote:

Answered on SO:

https://stackoverflow.com/q/48107585/1831717

On Fri, Jan 5, 2018 at 12:33 AM, Marlon <marl...@gmail.com> wrote:

For example, given this graph:

gremlin> graph = TinkerFactory.createModern() (1) ==>tinkergraph[vertices:6 edges:6] gremlin> g = graph.traversal(standard()) (2) ==>graphtraversalsource[tinkergraph[vertices:6 edges:6], standard] gremlin> g.V().has('name','marko').out('knows').values('name') (3)

How to print and save the graph into a file for visualization? I want a PNG or JPG file.

I am new to this and thanks for help.

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[Marlon]

Hi, Stephen:

I it works. However, the default visualization looks very bad.  I imported the "tinkerpop-classic.xml"  from the TinkerPop gremlin's sample data directory and it looks very ugly. Please see the attached.

How difficult to make it looks like the "tinkerpop-modern.png" in the attachment.

Thanks.

On Friday, January 5, 2018 at 4:05:17 AM UTC-8, Stephen Mallette wrote:

Answered on SO:

https://stackoverflow.com/q/48107585/1831717

On Fri, Jan 5, 2018 at 12:33 AM, Marlon <marl...@gmail.com> wrote:

For example, given this graph:

gremlin> graph = TinkerFactory.createModern() (1) ==>tinkergraph[vertices:6 edges:6] gremlin> g = graph.traversal(standard()) (2) ==>graphtraversalsource[tinkergraph[vertices:6 edges:6], standard] gremlin> g.V().has('name','marko').out('knows').values('name') (3)

How to print and save the graph into a file for visualization? I want a PNG or JPG file.

I am new to this and thanks for help.

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[Stephen Mallette]

gephi is a visualization tool. you have to apply layouts (and sometimes configure those layouts) to get it to look nice. dig into the gephi documentation a bit to find answers on how to do that. The "nice" pic you see was done by hand in omnigraffle - no special magic there.

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[Ling]

Yes, I wanted to create a graph by hand for presentation. Gephi seems quite hard to use to make it look nice.

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[Stephen Mallette]

You can move all those vertices around manually if you like in gephi. You should be able to create presentation quality graphs with that tool. 

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[Zeph]

Is there a way to do this on larger graphs?

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[Stephen Mallette]

I guess it depends on what you mean by "large". With Gephi and just about any visualization tool that i know of, your ability to deal with "large" is constrained by how much memory you have. Aside from memory issues, larger graphs will also take a longer time to get layouts executed and sensible for interpretation and presentation. So - I think the answer is that you can visualize just about any graph of any size provided you have the memory and time to do it.

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[Ashley E.]

Yes, I am definitely running out of memory with this command. 

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[Stephen Mallette]

perhaps you've already done this but you can increase your -Xmx settings for Gephi to give it more memory if you have some available:

https://github.com/gephi/gephi/wiki/Troubleshooting

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