Transcript Computer Science 121

Computer Science 121
Scientific Computing
Winter 2012
Who Am I?
Contact: Google simon levy
Interests: Robotics / drones,
cognitive science, linguistics,
Artificial Intelligence,
philosophy of mind,
programming languages,
iPhone apps, ...
Who Are You?
• Neuroscience *********
Geology
****
Biology
****
Undecided
***
Math
**
English
*
Accounting
*
Who Are You?
• Senior
(2012)
**************
• Junior
(2013)
********
• Sophomore (2014)
*
• Firstyear (2015)
**
How Will You Do in this Course?
• A: ************************
• A-: **************
• B+:**********
• B: ******
• B-: *****
• C+:***
• C: ***
Textbook
• Based on Matlab
• Developed over 4 yaears @
Macalester College
• Barely in print; order from
http://www.lulu.com
• We'll cover Ch. 1-8 in 1st 6 weeks,
then various remaining chapters
based on interest/progress.
Purpose
from http://www.macalester.edu/~kaplan/
cs121/policies.pdf
1. “To teach you to write effective computer programs.
2. To introduce you to some of the main methodological
areas of scientific computation and provide you with
the tools you need to carry out computational tasks you
are likely to encounter in research.”
Purpose
(continued from Kaplan PDF)
●
Scientific computing (???) : Computing (programming) for the sciences
●
But skills are transferable to general programming work
●
Difficulties
– Absolute precision in specifying instructions
– Considering full range of circumstances of how a program will be
used
– Considering how your assumptions may not be shared by the user
– Systematically tracking down bugs
– Breaking down complicated problems into simple(r) sub-problems
Matlab
●
An integrated programming and graphical environment
●
Interpreted : interactive; get answer immediately
●
Also supports saving and loading large programs
●
●
Student version available for $100 from
http://mathworks.com
Free, open-source “equivalent” : Octave
http://www.gnu.org/software/octave
Matlab
●
Issues
1) Matlab vs.
a) higher-level (Excel / SPSS) package
b) lower-level (C++ / Java / Python) language
2) Matlab vs. a similar package (Mathematica, Maple)
3) Matlab vs. Python
1) Abstraction
●
Recipe analogy: How to make chocolate-chip cookies?
●
High-level (Excel / SPSS) version:
1. Make chocolate-chip dough
2. Bake cookies
●
Too abstract
1) Abstraction
●
Low-level (Java / C++) version:
1. Drive to store
2. Buy: dozen eggs, 1 lb. flour, 1lb. sugar, 1qt. milk, 1 bag chocolate chips, 1 lb.
butter, 1 lb. lard
3. Drive home
4. Turn oven dial to 375° F.
5. Take out bowl, measuring cup
6. Measure ½ cup lard, ½ cup butter
7. Put butter, lard into bowl
8. Stir butter, lard, clockwise 20 times, counter-clockwise 20 times
9. Measure 1 cup flour
10. Add flour to bowl
11. Stir clockwise 10 times, ...
●
Too concrete
1) Abstraction
●
Recipe analogy: How to make a cake?
●
“Matlab” version:
(http://www.skyport.com/rogue-press/chocchip/basic.htm)
1. Mix ½ cup lard, ½ cup butter, getting them good and creamy.
2. Mix in 1 cup flour, ¾ cup brown sugar, ¾ cup white sugar, 2
eggs, 1 tsp. vanilla, and ½ tsp. baking soda.
3. Work this over until it is thoroughly mixed, then blend in 1 ¼ cup
more flour.
4. Bake at 375 degrees 8-10 minutes.
2) Matlab vs. Mathematica / Maple
●
Features
—
Matlab: Numerical (linear algebra)
—
Maple, Mathematica: Symbolic (calculus)
from
http://www.physicsforums.com/archive/topic/
t45208_Matlab_vs_Maple_vs_Mathematica.html:
... Matlab is excellent for manipulating data, or dealing with any sort of matrix calculations..
From my experience Mathematica is ideal when it comes to symbolics such as differentiation and integration.
I've seen a few cases where Mathematica blows Maple out of the water when one compares the types of integrals
they can evaluate.
Maple and Matlab have the best graphics in my opinion. In both of them you are allowed to rotate 3D graphics
and zoom in on the spot (2D) in realtime. In Mathematica things are little more complicated, which often [elicits]
frustration. With Mathematica, in order to zoom, you must change the window that you are plotting with.
3) Matlab vs. Python
●
Python: General-purpose language popular in CS
●
Interpreted
●
Free, open-source
●
SciPy (Matplotlib): Matlab-like packages
●
Good support for parallel / high-performance
computing