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Python for Scientific Computing
Preface
Python with Numpy and Matplotlib
1. Introduction to Python and Jupyter notebooks
2. Python Variables, Including Lists and Tuples, and Arrays from Package Numpy
3. Decision Making With if, else, and elif
4. Defining and Using Python Functions
5. Code Files, Modules, and an Integrated Development Environment
6. Iteration with
for
7. Iteration with
while
8. Iteration refinements:
break
and
continue
9. Recursion (vs iteration)
10. Plotting Graphs with Matplotlib
11. Numpy Array Operations and Linear Algebra
12. Summation and Integration
13. Random Numbers, Histograms, and a Simulation
Appendices
Formatted Output and Some Text String Manipulation
Classes, Objects, Attributes, Methods: Very Basic Object-Oriented Programming in Python
Displaying Python Code in Markdown Text Cells
Exceptions and Exception Handling
Package Scipy and More Tools for Linear Algebra
The Romberg Method
Index