With the availability of powerful but relatively low-level plotting libraries like d3.js, plot.ly, and matplotlib, it is easier than it has ever been to create beautiful visualizations. However, these plotting libraries must be very general and thus quite complicated to accommodate arbitrarily complex plotting and visualization tasks.In this talk, I describe the plotting system used by yt, an analysis and visualization platform for volumetric data written in python. The yt plotting system wraps matplotlib, creating a domain-specific API for creating publication quality plots that matches users' intuition for how they would like to explore and visualize their data. I will provide tips for designing and testing domain-specific plotting APIs so that the resulting plots are beautiful by default, but still modifiable with the full power of the underlying plotting library.
Nathan Goldbaum is a graduate student in astrophysics at the University of California Santa Cruz where he studies the formation, evolution, and destruction of star forming regions under the influence of stellar radiation and supernova explosions. He is a core contributor to the yt project, a python library for analysis and visualization of multi-resolution volumetric data.
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