NCAS Introduction to Scientific Computing Course, Reading, April 13 - 17 2015

Overview Presentations:

• Algorithmic thinking

• Algorithmic thinking exercise 1

• Introduction to JASMIN/CEMS

• Managing your code

• Parallel processing big data

• Why good data curation is essential to doing good science

The Linux Shell:

1. Introduction

2. Pipes and Filters

3. Permissions

4. Finding things

5. Job control

6. Summary of 1 - 5

7. Shell scripting

8. The secure shell

9. More tricks

Exercises and solutions

Introduction to Python Programming:

1. Introduction

2. Basics

3. Python Boolean types

4. Saving your code to a script

5. Control flow

6. Lists

7. Slicing

8. Tuples

9. Input and Output

10. Strings

11. Aliasing

12. Functions

13. More on functions

14. Libraries

15. Combining scripts and modules

16. Sets

17. Dictionaries

18. Errors and exceptions

19. Logging and debugging

20. Object-oriented programming (OOP) primer

21. Classes and objects

22. Summary; Where next?

Introduction to Python - exercises and solutions

Handling arrays and visualisation in Python:

• Handling arrays in Python (numpy)

Handling arrays in Python - exercises and solutions

• Visualisation in Python (with Matplotlib)

Visualisation in Python - exercises and solutions

Reading and writing data files using Python:

• Data file formats and metadata – why?

• Reading text formats in Python

• Some common text formats (at CEDA)

• Binary formats

• Overview of NetCDF

• The Structure of NetCDF files (based on the "Classic" format)

• ncgen and ncdump to create/export NetCDF, and CDL

• Checking CF-compliance: The CF Checker

• The CF Metadata Conventions (for NetCDF)

• Reading NetCDF files with Python

• Generating NetCDF files with Python

• Reading and writing other formats

Reading and writing data files using Python - exercises and solutions

Data analysis and plotting tools in Python:

• Data processing and plotting in Python - Iris

• Data processing and plotting in Python - cfpython and cfplot

Other data processing and plotting tools:

• Working with other tools - Data analysis beyond Python

• NetCDF Operators (NCO)

• Climate Data Operators (CDO)

• Viewing NetCDF: Ncview and NcBrowse

• "R" Programming Language - statistical programming and graphics

• Command-line tools for image processing - ImageMagick

Data Logging:

• Data logging from a serial port

• Data logging exercise and solutions

Example data and code:

• Example code directory used in Python and other tools sessions (example_code.zip).

• Example data directory used in Python and other tools sessions (example_data.zip).