SciPy and NumPy

Eli Bressert was born in Tucson, Arizona. He worked as a science imager for NASA's Chandra X-ray Space Telescope optimizing science images which are frequently seen on book covers, newspapers, television, and other media. Afterward, Eli obtained his PhD in astrophysics at the University of Exeter and is currently a Bolton Fellow at CSIRO Astronomy and Space Science in Sydney, Australia. For the past six years Eli has been programming in Python and giving Python lectures at Harvard University, the European Space Astronomy Centre, and the European Southern Observatory. He is one of the founding developers for two well-known astrophysics Python packages: ATpy and APLpy.

Chapter 1 Introduction
1.1 Why SciPy and NumPy?
1.2 Getting NumPy and SciPy
1.3 Working with SciPy and NumPy
Chapter 2 NumPy
2.1 NumPy Arrays
2.2 Boolean Statements and NumPy Arrays
2.3 Read and Write
2.4 Math
Chapter 3 SciPy
3.1 Optimization and Minimization
3.2 Interpolation
3.3 Integration
3.4 Statistics
3.5 Spatial and Clustering Analysis
3.6 Signal and Image Processing
3.7 Sparse Matrices
3.8 Reading and Writing Files Beyond NumPy
Chapter 4 SciKit: Taking SciPy One Step Further
4.1 Scikit-Image
4.2 Scikit-Learn
Chapter 5 Conclusion
5.1 Summary
5.2 What’s Next?
Appendix About the Author