CompSciWeek1
From Predictive Chemistry
Required reading for this week is Beginning Python, chapters 1-4. Be sure to try out the examples in python, not just read.
Class 1
- Pretest
- Basic Shell Usage
- pwd, ls, directory structure
- Access to Resources
- Logging into the lab computers
- Explanation of dual boot, OS evolution
- opening terminals, and terminals through terminals
- Logging into circe.rc.usf.edu
- Moving files
- Running python on your own machine
- Windows: Python Idle + easy_install ()
- alt: Cygwin
- OSX / Linux: Package managers (OSX: fink, Debian (deb): apt-get, RH (RPM): yum)
- Logging into the lab computers
- First-order data types:
- int(1.1), float(-3), string(4) [essentially all languages]
- (and 2nd order) tuple([5]), list((6,)), dict([(6,7)]) [python-specific]
Class 2
- What is a Turing machine?
- The infinite loop and other control structures.
- First algorithms (Horner, Euclid, Babylonian)
- Code walk-through for a poorly designed Euclids algo.
- The KISS, DRY, and incremental principles
- Higher-order constructs:
- functions
- functional code
Homework I
This assignment will be due in 2 weeks, on Monday, Sept. 8.
- Create a program that reads in strings with raw_input() until a string containing a single '.' is sent. After that, the program should print out the strings it has read in reverse order (hint: use list.pop()).
- Implement the Babylonian/Heros method to approximate the square root of 2 using 10 iterations. Plot the error in the approximation against iteration number. Is there a good way to automatically guess when to stop iterating?
- Edit 9/5/14 A printed list of the error at each iteration can be included in place of a plot.
- Imagine Bassetts Ice Cream has a data set of daily ice cream sales for 3 different flavors stretching back to 1893. Write pseudocode for an algorithm that finds the largest and smallest sales over daily, weekly, monthly, and yearly time-scales. Use steps like `add together 7 days sales` and `get the smallest number in the list`. If each test or addition step for each number takes 0.1 microseconds (10^-7 seconds), estimate how many microfortnights (1 microfortnight = 1.2096 s) the code will take to run?
- Edit 9/5/14 One final result should be output for each timescale. For the monthly timescale, for example, the result would be the (flavor, month number) pair with the highest and lowest numbers. -- Congrats to Christine McNiff for forcing a formal specification of the result. Ambiguities like this are a common source of conflict in programming vs. specifications...
- Obfuscation challenge: Write (in the most complicated unreadable way you can stand) a code that prints out the first 20 or so prime numbers. The code is limited to 100 lines, cannot use external packages, and must always finish running in less than 1 minute.
Answer to Bassett's Ice Cream Problem (both pseudocode and code) <source lang="python"> from numpy import *
days = (2014-1893)*365.25 # for "starting this day in 1893" test_sales = (random.random((days,3))*10000).astype(int) # test data
- 1. find max/min over days
- 2. create weekly sums
- - find max/min over weekly sums
- 3. create monthly sums
- - find max /min over monthly sums
- 4. create yearly sums
- - find max/min over yearly sum
- combination!
- 2-4: create sums over subsets
- - find max/min over sum
- this also covers 1 (with n = 1)
- input - daily sales data array (days, 3)
- - length scale (combined data size)
- output min/max over subset
- def subset_stat(sales, starts, extents):
- 0, 31, 31+28, ...
- run-time cost = f(L, n) = 3*L adds, 6*L/n comparisons
- 3*L + 6/n *L = (3+6/n) * L -- linear time.
def subset_stat(sales, n):
L = len(sales) sub = [] for i in range(0, L, n): # loop over all subsets L/n y = sum(sales[i:i+n], 0) # access whole subset (n) sub.append(y) # L*3 additions sub = array(sub) # 6* L/n min/max return max(sub[:,0]), max(sub[:,1]), max(sub[:,2]), \ min(sub[:,0]), min(sub[:,1]), min(sub[:,2])
- max : [number] -> number
subset_stat(test_sales, 1) subset_stat(test_sales, 7) subset_stat(test_sales, 30) subset_stat(test_sales, 365) </source>