The Problem
- Scientists are using computers to do amazing things, like
- predict the physics of aircraft,
- develop atomic and molecular models to better understand matter,
- simulate the motion of planets, stars and galaxies, and
- study the biological processes that form the building blocks of life.
The Problem
But for every successful simulation of global climate, there are a dozen more groups struggling just to get their program to run.
Many of them tweak and tinker for months, or years, till their code does something more than produce zeros, or grind to a halt.
The Solution
- All of this pain can be avoided by
- writing programs that are well-documented,
- properly reusing code in programs,
- automating tasks that are done often, and
- systematically finding and fixing bugs when they appear.
The Solution
- The good news is that none of this is rocket science.
- Like callibrating an oscilloscope, or titrating a solution, they are skills that are quickly picked up, and become easier with practice
- …and they will be the focus of today’s lesson.
Why MATLAB?
- We use MATLAB in our lesson because
- we have to use something for our lesson,
- it’s well documented,
- it has a large user base among scientists in academia and the industry, and
- it has a large library of packages for performing diverse tasks.
Today’s Lesson
- In today’s lesson, we’ll learn how to
- load, analyze and visualize data in MATLAB,
- get our program to repeat tasks by writing loops,
- get our programs to make decisions using conditionals,
- make our code reusable by writing scripts and functions,
- write programs that check themselves for bugs,
Today’s Lesson
- …and along the way, learn some good programming practices, that will save us plenty of time, sweat and tears in the long run.
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