Effective Computation In Physics
A Field Guide to Research With Python
Kathryn Huff
BIDS Data Science Faire, May 5, 2015
Science
- builds and organizes knowledge
- tests explanations about the universe
- systematically,
- objectively,
- transparently,
- and reproducibly.
Otherwise it's not science.
(Anthony talked me into it.)
Getting Started
- Chapter 1 - Introduction to the Command Line
- Chapter 2 - Programming Blast Off with Python
- Chapter 3 - Essential Containers
- Chapter 4 - Flow Control and Logic
- Chapter 5 - Operating with Functions
- Chapter 6 - Classes and Objects
Getting It Done
- Chapter 7 - Analysis and Visualization
- Chapter 8 - Regular Expressions
- Chapter 9 - NumPy: Thinking in Arrays
- Chapter 10 - Storing Data: Files and HDF5
- Chapter 11 - Important Data Structures in Physics
- Chapter 12 - Performing in Parallel
- Chapter 13 - Deploying Software
Getting It Right
- Chapter 14 - Building Software Pipelines
- Chapter 15 - Local Version Control
- Chapter 16 - Remote Version Control
- Chapter 17 - Debugging
- Chapter 18 - Testing
Getting It Out There
- Chapter 19 - Documentation
- Chapter 20 - Publication
- Chapter 21 - Collaboration
- Chapter 22 - Licenses, Ownership, and Copyright
- Chapter 23 - Further Musings
Acknowledgements
Prof. Anthony M. Scopatz
Acknowledgements
This book was heavily inspired by the work of Software Carpentry and The Hacker Within. We are thrilled to see Effective Computation in Physics come to press and spread the joys of computation further into the physical sciences. In case you were wondering, the cuddly creature on the cover is a bobtail squid.
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Katy Is Supported By
THE END
Katy Huff
katyhuff.github.io/bids-faire-2015
Effective Computation In Physics? by Kathryn Huff is licensed under a Creative Commons Attribution 4.0 International License.
Based on a work at http://katyhuff.github.io/bids-faire-2015.