CSCI 1060 - Scientific Programming

Spring 2019

1. Course Description
2. Prerequisites
3. Assignments
4. Course Schedule
5. Textbooks and Other Resources
6. Grading
7. Links
8. Academic Honesty
9. Academic Support
10. Disability Services
11. Title IX Statement

Course Description

Computing allows scientists and engineers to quantify and analyze problems to a terrific degree. The particulars of how computers are used will vary from field to field and problem to problem, but the process of computer programming (or more generally- computer-aided problem solving) is similar for everybody. Computers are machines that are incapable of original thought or imagination. Using one effectively requires a solid understanding of what a computer is and is not capable of, and then the mental plasticity to transform the real-world problem into a computer model that (hopefully) bears some significance to the original problem that must be solved. The goal of this course is to teach students this process of solving real-world scientific and engineering problems via computer programming.

Learning Outcomes- At the end of this course, students should be able to:

• Solve word problems with a computer
• Write a program to solve a parameterized problem (i.e. solve a class of word problems)
• Simulate simple physical situations deterministically and stochastically
• Use computer data to support the selection of a solution out of several competing alternatives
• Use functions to divide a program into small, easy to read and maintain pieces of code
• Use appropriate control structures (if-else statements, for loops, while loops, etc.) to achieve a desired result and structure code

Topical Outline- the topics we will cover in this course (not necessarily in this order) are:

• What is a program, what is an algorithm
• Variables: declaring, initializing, using, and modifying
• Vector/array data: declaring, initializing, using, and modifying
• Plotting and visualizing data
• Control structures (if-then/else, for loops, while loops, switch statements)
• Functions
• Structuring code effectively
• Reading/writing data to files
• Text data and string handling
• Deterministic simulation
• Stochastic simulation
• Analyzing datasets with programming

Catalog Description: Elementary computer programming concepts with an emphasis on problem solving and applications to scientific and engineering applications. Topics include data acquisition and analysis, simulation and scientific visualization.

Prerequisites

• Calculus I or concurrent enrollment in same

Textbook

Recommended course textbook: MATLAB An Introduction with Applications by Amos Gilat, Published by Wiley

Note: The textbook is recommended as a supplementary resource for those who wish but is not required. Any recent edition of the book is suitable.

(book's website - supplementary videos, example problems, and errata)

Assignments

There will be approximately 10 assignments for this course and a course project. These are a mix of written and programming assignments whose purpose is to apply course concepts.

Assignments submitted on time will be given full credit. Assignments submitted up to 24 hours late will be given a ten percent penalty. Assignments submitted between 24 hours and 48 hours late will be given a twenty percent penalty. Assignments submitted after 48 hours late will not be given credit, except in the case of extenuating circumstances pre-approved by the instructor.

Course Schedule

A tentative course schedule is below. Note that this schedule may change over the course of the semester. When changes occur, students will be given enough advance notice so that readings and other preparation may be accommodated.

Grading

Your grade will be determined as follows:

Grading is done on a straight scale (uncurved). The following scores are guaranteed. The grading scale may be curved upwards (in your favor) at the discretion of the instructor.

• 93% guarantees an A
• 90% guarantees an A-
• 87% guarantees a B+
• 83% guarantees a B
• 80% guarantees a B-
• 77% guarantees a C+
• 73% guarantees a C
• 70% guarantees a C-
• 60% guarantees a D

Links / Resources

MATLAB

The majority of this course is centered around using MATLAB, an industry standard software for scientific and engineering computing. You can access this software in at least the following ways:

• You can install MATLAB on your personal machine and use it via SLU's license via the instructions here. You will need to scroll down the page and expand the tab for "MathWorks and MATLAB". Then click through the link there and you will be taken to a Google Doc with instructions for downloading and installing MATLAB. You will need to use your SLU username and ID to login to this Google Doc.

• Computer labs: The computers in McDonnell Douglas Hall should all have access to MATLAB.

• Departmental server: You can use MATLAB from most personal machines by connecting to the Computer Science department server called Hopper. When you are enrolled in this course you should automatically be emailed login credentials. (If not, contact Dennis Thomas.) You can then login by:

  1. Download and install the free software NoMachine
  2. Manually create a new connection. The connection protocol is SSH over port 22. The server/hostname you to connect to is "hopper.slu.edu"
  3. Click to connect- the first time you will have to accept the server's SSH key.
  4. Find "Terminal" or "XTerm" in the applications menu. In the terminal type "matlab" and press enter.
  5. Note- please LOG OUT of Hopper when you are done using it. DO NOT just hit the red X at the top of the NoMachine window. This second method will not actually close your virtual desktop- it will continue to run and consume department resources, making the system admin very upset! (He will probably close your desktop for you as well.) Individually you won't cause a big problem, but a hundred idle desktop sessions can cause noticeable problems for other users.

Great reads that deal with computing in an engineering context:

• Skunk Works: A Personal Memoir of My Years at Lockheed by Ben Rich - Discusses (among other things) how computers helped the F117 stealth fighter achieve a stealthy radar cross section the size of a 3mm ball bearing.

• Failure Is Not an Option: Misson Control From Mercury to Apollo 13 and Beyond by Gene Kranz - Discusses (among other things) the evolution of the computer command and control technology from the early Redstone rocket program through the Apollo program. Includes a great discussion of the infamous 1201 and 1202 program alarms that ocurred in the Apollo Guidance Computer during the Apollo 11 lunar descent phase.

• What Really Happened on Mars? by Mike Jones and a follow up first person account by Mars Pathfinder software team lead Glenn Reeves of NASA's Jet Propulsion Laboratory. Both discuss the cause and resolution of a computer failure that threatened the wildly successful Mars Pathfinder mission. Relatively technical.