Fall Semester 2018; second half MWF, 9:40AM-10:30AM; WBB711
| Instructor | Phone Number | Office Hours | Office Location | |
|---|---|---|---|---|
| Chris Galli | chris.galli@utah.edu | 801-647-2263 | by appointment | 482 INSCC |
| Sally Benson | sally.benson@utah.edu | 801-859-1644 | by appointment | 603 WBB |
Copy of the Syllabus can be found here
Environmental scientists need the ability to acquire, process and display environmental data, imagery, and gridded fields. This course is designed to develop the skills necessary to solve physically-based problems relating to atmospheric science data sets. After a review of basic programming concepts, students will develop code to solve problems using programming languages and data sources relevant to their ongoing or future research. The course is particularly relevant for first-year graduate students as they begin research leading towards their thesis proposal.
It is assumed students have exposure and practical experience working with a common programming language used within physical sciences, such as Python, MatLab, or IDL. There is no requirement for using one language over another. However, it is important the student is comfortable working in a language that has available module/API bindings to common data libraries; specifically, NetCDF4, HDF, and CSV parsing.
By the end of this course, you will be able to:
- Write computer programs for analyzing data.
- Acquire and use data in multiple file formats.
- Create custom ways to display data.
Check out CHPC's Intro to Python Series
October 15, Lecture 1: Introduction
October 17, Lecture 2: Data types
- IDL example file lecture02_variables_datatypes.pro
- Homework assignment 1
October 19, Lecture 3: Basic programs and arrays
October 22, Lecture 4: I/O part I
October 24, Lecture 6: I/O NetCDF and HDF
October 26, Lecture 6: I/O part II
October 29, Lecture 7: Final Project Review
October 31, Lecture 8: Basic Control Structures
November 2, Lecture 9: Arrays part I
November 5, Lecture 10: Code design and more arrays
November 7, Project reviews. Approach discussions. Questions.
November 9, Lecture 11: Arrays part II
November 12, Lecture 12: Optimization
November 14, Lecture 13: Numerical Applications
November 16, Lecture 14: Intro to debugging