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Scientific Visualization and Programming with Matplotlib
From exploration to publication
3 hours
This course starts with exploratory data analysis of a (simulated) physical system and ends with figures suitable for publication. Along the way we will develop a mini-library for visualizing and analyzing the data. We will discuss the reasoning behind the API choices made and the trade-offs to get a set of composable, reusable, tools that will be adaptable for both future data and alternative visualization needs, such as re-making the figures for a talk or poster.
Starting with exploratory data analysis design and build tools to make a publication-ready figure.
- Learn how to write re-usable and composable function for visualization.
- Learn how to approach the explicit Matplotlib API and wrap it for your needs.
- Learn the basic considerations of API design for scientific programming.
- This course demonstrates how to convert exploratory visualization (and analysis) into publication quality figures.
- Learning outcomes (these will be displayed as bullet points under the heading “What You will Learn”)
- Keywords
Instructor details needed:
- Thomas A Caswell
- Computation Scientist and Matplotlib Project Lead
- Brookhaven National Laboratory
- Short biography
- Photo