Provisional proceedings for SciPy2014

Presenters of talks and posters at SciPy2014: as in previous years, authors of accepted talks and posters are invited to submit a full-length paper (8 pages) expanding on their abstracts for inclusion in the SciPy2014 proceedings.

The proceedings are aimed at highlighting significant contributions to scientific computing in Python, such as:

  • new software packages that support the Scientific Python Stack
  • significant improvements to existing software packages
  • Descriptions of how to solve hard computational problems with Python
  • Hardware systems designed to support the Python stack


Multidimensional Data Exploration with Glue

By Christopher Beaumont, Thomas Robitaille, Alyssa Goodman, Michelle Borkin Abstract   PDF   BibTex

Modern research projects incorporate data from several sources, and new insights are increasingly driven by the ability to interpret data in the context of other data. Glue is an interactive environment built on top of the standard Python science stack to visualize relationships within and between datasets. With Glue, users can load and visualize multiple related datasets simultaneously. Users specify the logical connections that exist between data, and Glue transparently uses this information as needed to enable visualization across files. This functionality makes it trivial, for example, to interactively overplot catalogs on top of images. The central philosophy behind Glue is that the structure of research data is highly customized and problem-specific. Glue aims to accommodate this and simplify the "data munging" process, so that researchers can more naturally explore what their data have to say. The result is a cleaner scientific workflow, faster interaction with data, and an easier avenue to insight.



Copyright © 2014. The articles in the Proceedings of the Python in Science Conference are copyrighted and owned by their original authors This is an open-access publication and is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For more information, please see: http://creativecommons.org/licenses/by/3.0

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