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ShadyStats

ShadyStats. Project Update Mike Cora November 16, 2005 533C: Information Visualization. Background and Motivation. Spent the last year developing the high-level AI for Super Mario Strikers (decisions and positioning)

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ShadyStats

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  1. ShadyStats Project Update Mike Cora November 16, 2005 533C: Information Visualization

  2. Background and Motivation • Spent the last year developing the high-level AI for Super Mario Strikers (decisions and positioning) • Coding, tuning and testing a video game’s AI involved gathering a lot of multidimensional statistics • An interactive visualization can: • Show trends, and correlations, compare teams and difficulty levels • Help with finding bugs during development • Help with tuning a well balanced game • Aid communication with the publisher (across potential language barriers for example)

  3. Target Users • Mostly me, greatly simplifying requirements gathering and evaluation..  • Other AI and gameplay programmers • Designers and producers • Testers / QA

  4. Dataset • Generated by the upcoming Super Mario Strikers, a 5-on-5 arcade soccer game, starring all your favorite Nintendo characters.

  5. Dataset Details • 2400 games played by the AI, at 4 difficulty levels per side (home / away) • Recorded at 6 different dates over the last 2 months of development • 14 dimensions (ie. passes, shots, hits, steals) • ~ 2400 games * 14 dim * 2 sides = 67,200 numbers

  6. Proposal: ShadyStats 2) Hierarchical parallel coordinates 1) Dataset history 4 – Dynamic filtering 3 – Zoomable, detailed graphs

  7. Feature Goals • Maintain history of datasets for easy comparison during development lifecycle • Use XmdvTool1 for parallel coordinates: • Hierarchical aggregation, with fancy shading • Extend with interactive drag reordering of dimensions • Generate detailed graphs on demand, using Zedgraph2, by interacting with the parallel coordinates component

  8. Feature Goals 2 • In depth, dynamic filtering and highlighting options • Various statistical measures (mean, variance) • Highly interactive, tooltip information everywhere (data values, dimension names, etc). • Contextual zooming of individual graphs

  9. Enviornment • Platform is Windows • Language changed from Java to C# & C++. Why? • XmdvTool1 is written in C++ • Zedgraph2 is a C# control with full source, excellent customization, tutorials and documentation • C# and C++ are buddies, and play nice • C# is very UI friendly, fast develpment time • I have less (and outdated) experience with Java

  10. Progress • Compiled and poked through XmdvTool1: • Minor compilation issues with non-standard iostream.h • Uses OpenGL for rendering • Uses Tcl/Tk6 for its UI, meaning the code is nicely setup for external interface, so isolating the parallel coordinate canvas and creating a C# interface around it should be doable • Very little implementation documentation

  11. Progress 2 • Compiled and poked through Zedgraph2: • Very customizable, with a tonne of graph styles and annotations • supports autoscaling, panning, zooming • Very well documented, with a tonne of sample code • Created bare-bones skeleton UI layout in C# • Read some papers on stuff [3][4][5]

  12. Challenges • Have never actually created a C# friendly control from C++ before, nor played with Managed C++. • Isolating the parallel coordinate canvas from XmdvTool1 may pose some challenges. • Several areas will be ongoing challenges, and will be heavily iterated on, to maximize usage of the tool: • Good set of dynamic and interactive filters • High interactivity and linking between all components • Variety of visualizations and graphs for different dimensions

  13. Bibliography • XmdvTool: http://davis.wpi.edu/~xmdv/ • Zedgraph: http://zedgraph.sourceforge.net/ • Edward J. Wegman. Hyperdimensional Data Analysis Using Parallel Coordinates, Journal of the American Statistical Association, Vol. 85, No. 411. (Sep., 1990), pp. 664-675. • Ying-Huey Fua, Matthew O. Ward, and Elke A. Rundensteiner, Hierarchical Parallel Coordinates for Visualizing Large Multivariate Data Sets, IEEE Visualization '99. • Jing Yang, Wei Peng, Matthew O. Ward and Elke A. Rundensteiner, Interactive Hierarchical Dimension Ordering, Spacing and Exploration of High Dimensional Datasets, Proc. InfoVis 2003. • John K. Ousterhout, Tcl and the Tk Toolkit, Addison Wesley,1994.

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