glue and other Sticky Treats (demo/tutorial)

Date: 

Tuesday, October 31, 2017, 9:30am to 11:30am

Location: 

160 Concord Avenue 3rd floor conference room ("M 340")

Update:  So many of you are interested in this tutorial that we've decided to start early (at 9:30), and end later (at 11:30), with a plan as below.  Note, though, that if you can still only come for the 10-11 hour, that should work fine. 

  • 9:30-10:   introductory session for people who have never used glue & need to know the bascis, and/or install glue
  • 10-11: overview of glue functionality, with (at c. 10:45) an introduction to customizing glue and writing plug ins
  • 11-11:30 add-on session for people extra-interested in customizing and writing plug-ins for glue

PLEASE BRING YOUR LAPTOP if you want to try glue during these sessions.

 

Halloween Seamless Astronomy Workshop

“glue & other Sticky Treats"
10-11+ AM (10/31, at M-340, 160 Concord Ave.)

Come learn about glue—the linked-view data visualization environment that’s taking the python+GUI-loving world by storm. If you’re not familiar with glue, a quick description (from its website) is appended below. Recently added features include:
—faster 3D volume visualization
—new GUI tools for adjusting the look of 1D, 2D & 3D displays
—more user-customization options
—integration with SAMP to communicate with TOPCAT, Aladin, DS9, and more!
—integration with WorldWide Telescope
—visualization of flow fields and polarization vectors


from glueviz.org:
Glue is a Python library to explore relationships within and among related datasets. Its main features include:

  • Linked Statistical Graphics. With Glue, users can create scatter plots, histograms and images (2D and 3D) of their data. Glue is focused on the brushing and linking paradigm, where selections in any graph propagate to all others.

  • Flexible linking across data. Glue uses the logical links that exist between different data sets to overlay visualizations of different data, and to propagate selections across data sets. These links are specified by the user, and are arbitrarily flexible.

  • Full scripting capability. Glue is written in Python, and built on top of its standard scientific libraries (i.e., Numpy, Matplotlib, Scipy). Users can easily integrate their own python code for data input, cleaning, and analysis.

 

glue_halloween_demo_2017.pdf4.29 MB
See also: tutorial, workshop, Colloquium, Outreach