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rmit-programming-club / network-vis

A tool to visualisation coding activity and collaboration within a Github Organisation
GNU General Public License v3.0
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[Trello - RZE78xkW] Basic network graph #16

Closed thundergolfer closed 7 years ago

thundergolfer commented 7 years ago

Description

This PR adds a copy-pasted force-directed network graph in D3.js that serves as a skeleton in which to pass our data.

You can see that there's a miserables.json file, which was the site's example data. I've added some more realistic data in organisation_connections.json, which shows that once you have the data it's super easy to get a graph going.

Our end product will basic end up passing in a javascript object that very much resembles organisation_connections.json to the app/assets/javascripts/d3/network.js file. Too easy.

What it currently looks like

Because I couldn't be bother to type in a lot of data manually, it looks pretty bare.

screen shot 2017-05-05 at 2 02 46 pm

References

Trello: https://trello.com/c/RZE78xkW/28-setup-basic-network-graph-in-d3-js

Risks

None: New route, new feature.

thundergolfer commented 7 years ago 
Note: This PR has a deletion of `development.log`, because we've got to get 
that shit out of the repo. It's already in the .gitignore
ghost commented 7 years ago

Where's organisation_connections.json?

thundergolfer commented 7 years ago

@Raddus forgot to push my last commit. It's in there now.

ghost commented 7 years ago

Alright, looks good. But I don't really understand what the "group" and "value" numbers mean. I'll take a proper look at them later...

thundergolfer commented 7 years ago

In the case of the example value refers the number of times two characters appear in the same scene of Les Miserables. The higher this value, the closer the two nodes will be in the graph.

In my data I just put in arbitrary stuff but the value should mean the number of times two members 'collaborated'.

group is used to colour the nodes, but I don't know what their categorisation criteria is. I used I think:

thundergolfer commented 7 years ago

I don't know whether we want this specific visualisation technique (closer means collab-ed more), but it's a good start.

In future I think we just want the algorithm to nicely space out the nodes, and more collabs will show up in the visualisation as thicker edges and bigger (brighter) nodes.