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Sightings
This page is a place to capture Toyplot sightings around the web. Keep a sharp eye about you, mateys!
LDAV 2017 Best Paper - "Scalable Web-Embedded Volume Rendering"
http://web.eecs.utk.edu/~ahota/pdfs/tapestry-ldav-2017.pdf
"ATCA detections of massive molecular gas reservoirs in dusty, high-z radio galaxies"
https://arxiv.org/pdf/1610.07699v2.pdf
Toyplot Appears at Vis Lies 2015 (not in a bad way)
http://www.vislies.org/2015/gallery/
Toyplot Graphics Composited with Images and Video
https://github.com/sandialabs/toyplot/pull/150#issuecomment-207659528
"Color Map Advice for Scientific Visualization"
http://www.kennethmoreland.com/color-advice/
Some Favorite Tweets
Goecks, Jeremy (@jgoecks) "Toyplot is pretty awesome for flexible and powerful plotting in Python. Bonus: can render to image, PDF, or HTML!" August 17, 2015.
Morgan (@rhoark) "@Sargent I abandoned matplotlib in favor of generating my own commands to pipe to gnuplot. If I were starting fresh, I'd look at toyplot" August 14, 2015.
Said, Chris (@Chris_Said) "Data viz documentation written with a sense of mission: The Toyplot Ethos." August 5, 2015.
Bressert, Eli (@astrobiased) "Toyplot is quite possibly one of my favorite plotting packages in Python. It's young, but wow - it's impressive." August 4, 2015.
DrKJam (@drkjam) "Toyplot is the first Python dataviz library I actually like, both aesthetically and in API terms. Excellent for IPython notebook." July 8, 2015.
Sardelich (@SardelichM) "Love the animation part of this Python library: Toyplot, a Python plotting library from Sandia Labs." July 7, 2015.
Kula, Maciej (@Maciej_Kula) "Toyplot, new plotting library for Python. Looks very good, let's hope this spells the end for matplotlib." July 7, 2015.
The future of the Scientific Python ecosystem
https://khinsen.wordpress.com/2015/07/16/the-future-of-the-scientific-python-ecosystem/
Toyplot mentioned in the SciPy 2015 "State of the Tools" keynote by Jake Vanderplas
https://www.youtube.com/watch?v=5GlNDD7qbP4&list=PLYx7XA2nY5Gcpabmu61kKcToLz0FapmHu&index=2
Interactive visualization of RADseq data
http://nbviewer.ipython.org/gist/dereneaton/c8292a8febc758eb0438/toy_heatmap.ipynb
"Formal Metrics for Large-Scale Parallel Performance"