# Visual Analytics Course

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bordeaux20142015:bordeaux_edition

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## Visual Analytics Course

Instructors: Guy Melançon (email: Guy dot Melancon at labri dot fr), Bruno Pinaud (email: Bruno dot Pinaud at labri dot fr)

### Bordeaux roadmap 2014-2015 / Session by session cutdown

Have a look at the page describing the course organization: assignments, term projects and evaluation, deadlines, etc.

You are requested to work on a term project. You are expected to form a team with another colleague and select a project topic from a list.

Remember that Tulip in installed in the CREMI in /net/ens/tulip4. It should always be the latest svn version compiled by hand. It can be launched with /net/ens/tulip4/bin/tulip or to directly launch the graph manipulation perspective /net/ens/tulip4/bin/tulip_perspective -p Tulip. If you find a bug, do not hesitate to show it to us!!

#### Friday, September 19 (week 38, Bruno Pinaud)

This first portion of the course is meant to introduce the topic of the course, motivate this still new research field although examples are there to indicate ideas go back to ancient times.

Have a look at the slides showed in the class.

It does include a comprehensive course on Tulip so students are able to work by themselves using the framework.

#### Friday, September 26 (week 39, Bruno Pinaud)

Because we want to actually 'do' things, we need to devote time learning how to use the Tulip framework (developed here at LaBRI). We worked on several examples showing many tulip functionalities:

The Python part of the course or lesson will consists in:

• getting a graph (File/Import)
• we will start by making our own graph (a grid graph)
• you may also want to try the Grid, or Grid Approximation Tulip plugin
• computing a spanning tree out of it (python script)
• use a simple data structure like a stack or queue to drive the computation of a spanning tree, it's a few lines algorithm (python has a handy Queue library)
• applying a layout algorithm to the tree subgraph
• your spanning tree algorithm could well use a boolean property to select what edges (and all nodes) are selected to form the tree. Once you have that, use the addSubGraph method to build a subgraph
• apply a tree layout algorithm to the tree. Use the applyLayoutAlgorithm method. It requires that you hand it a layout property. Use the getLayoutProperty to grasp the viewLayout property so the new positions for nodes will automatically be transferred to the whole graph (this is automagically done by Tulip. See the beginning of main Python function in the Python script view.
• playing with node/edge properties to make this as readable as possible
• grasp the color property viewColor. Create and instance a light gray color tlp.Color(192, 192, 192) or tlp.Color.Gray for instance. iterate over edges and turn the non selected edges to gray (viewColor.setEdgeValue(edge, tlp.Color.Gray))

Here is a solution (will be available after the course). Have fun.

#### Friday, October 3 (week 40, Guy Melançon)

Network metrics This lecture was partly based on the chapter concerning network metrics. Half of the course was devoted to defining a few metrics on graphs: node degree (obvious while easily interpretable and extremely useful); clustering coefficient (also quite informative although more tedious to compute on some graphs); node betweenness centrality. We then looked into random walk version of node degree and (second order) centrality to scale the se metrics to large graphs.

TBA

TBA

#### Friday, November 7 (week 45, Bruno Pinaud)

Divide and conquer - drawing and manipulating graph hierarchies with Tulip We will use the following file to play with graph hierarchies infovis_clean.tlpx. The work to do is described in this document hierarchies.pdf.

Graph clustering

#### Friday, November 21 (week 47, Bruno Pinaud)

Let's continue to work on Multilevel graph navigation

#### Friday, November 28 (week 48, Guy Melançon)

Text mining & Document visualization

Project coaching

Project coaching

#### January XX (week X, Guy Melançon and Bruno Pinaud)

Project evaluation