Editing IVAJ/Level1 (section)

==<font color="#0000DD">Introduction</font>==

Researchers in the open source community are steadily improving scientific visualization tools.  These tools are providing a wider array of sophisticated probes for data analysis and a wider assortment of effective user-friendly interfaces.  They're also making it easier for researchers in the computational science community &#8212; across many disciplines &#8212; to effectively analyze huge datasets by drawing on the human brain's acute ability to sort through complex and time-varying visual patterns.  The astrophysics group at Louisiana State University (LSU), for example, routinely uses volume-rendering and ray-tracing algorithms in conjunction with animation techniques to examine the time-varying behavior of isodensity surfaces that arise in computational fluid dynamic (CFD) simulations of mass-transferring and merging binary star systems.  Although such analyses generally provide only a qualitative identification and assessment of structure within a given dataset, the insight gained from visual inspection can nevertheless be extremely valuable.  For example, it was through visual inspection that researchers at LSU initially spotted the nonlinear development of triangular-, square-, and pentagonal-shaped tidal resonances in recent simulations.

LSU's astrophysics group has begun to incorporate [http://www.vistrails.org VisTrails] into its arsenal of scientific visualization and data analysis tools.  [http://www.vistrails.org VisTrails] primarily interested the group a few years ago because it provides a user-friendly workflow interface to the [http://www.vtk.org/ extensive VTK software library].  It also automatically tracks the provenance of data analysis efforts.  However, what most impresses us now is the ease with which [http://www.vistrails.org VisTrails] facilitates the insertion of home-grown analysis modules into an otherwise VTK-based workflow.  Taking advantage of this additional programming versatility, we have gained a greater appreciation of the role that visualization tools can play in the quantitative assessment of results from large-scale simulations.  In this article, we first describe the VTK-based workflow that we initially constructed in [http://www.vistrails.org VisTrails] to view streamlines within each binary mass-transfer simulation.  We then describe the Python module, whose insertion into this workflow has permitted us to identify values of key rotational frequencies associated with such flows.