This is an exam. You may not speak with anybody other than Jeff Ondich about its contents. You may, however, use your book, your notes, the books in the library, the Internet, and divine guidance (should any be offered to you). If you obtain information from some source other than your own brain, cite your source and use quotation marks where appropriate.
Hand your exam in on paper.
(8 points) Sections 11.6.1 through 11.6.3 of your textbook include a discussion of an important Python structure called a dictionary. Your job for this problem is to read about dictionaries, and then write a Python program that does the following:
Hand in a copy of your program on paper, but also hand it in electronically in the usual way. Please call it dictionary.py.
(6 points) I have a list of positive integers, and I want to know the largest product that can be formed by two of the integers. For example, if the list is [3, 5, 1, 8, 10, 6], then the product I'm looking for is 80 (i.e. the product of 8 and 10). Elmo suggests the following code, which does the job:
def elmo(theList): N = len(theList) biggestProduct = 0 for k in range(N): for j in range(N): if theList[j] * theList[k] > biggestProduct: biggestProduct = theList[j] * theList[k] return biggestProduct
(8 points) In this problem, you will use sorter.py to compare the performance of Selection Sort and Insertion Sort.
As we discussed in class, selection sort and insertion sort are members of a class of sorting algorithms whose performance is usually measured by counting the number of list element comparisons that need to be done to complete the sorting of the list. That is, we count the number of times something like "a[j] < a[k]" gets executed during the run of the algorithm. When we count comparisons, we are counting the number of iterations of the inner loop, and by counting inner loop iterations, we are counting the most time-consuming portion of the algorithm.
To see how this plays out, try running "python sorter.py selection 10 verbose" or "python sorter.py selection 1000" to see a report of the sorting times and number of comparisons for a 10-element list or a 1000-element list. (The "verbose" causes the program to print out the list before and after sorting, to help you believe that sorting is actually taking place.) To try this with Insertion Sort, replace "selection" with "insertion".
In what follows, you're going to count comparisons and measure running times for the two algorithms and several values of N.
Fill in the following chart. For the "Unshuffled" columns, you should comment out the line that calls the shuffle function. This will measure the running times and comparison counts when you sort a list that is already sorted before you begin (an admittedly odd thing to do).
N | Comp. count for Sel. Sort | Running time for Sel. Sort | Comp. count for Sel. Sort Unshuffled | Running time for Sel. Sort Unshuffled | Comp. count for Ins. Sort | Running time for Ins. Sort | Comp. count for Ins. Sort Unshuffled | Running time for Ins. Sort Unshuffled |
---|---|---|---|---|---|---|---|---|
5000 | ||||||||
10000 | ||||||||
15000 | ||||||||
20000 |
(8 points) Steganography is the art of hiding messages in places where people will be unaware there is a message at all, let alone an encoded message. In this exercise, you will work with a form of steganography that involves hiding messages in digital images.
The image ox-with-message.png is my usual Babe the Blue Ox photograph, with a slight modification. The red values of the pixels in the leftmost column have been altered to hold a message consisting of a sequence of 8-bit ASCII characters. Each character is represented by 8 pixels, where an even red value represents a 0 bit, and an odd red value represents a 1 bit. For example, if the top 8 pixels in the left column of the photograph have red values equal to 50, 51, 48, 48, 50, 52, 52, 51 (i.e. even, odd, even, even, even, even, even, odd), then the first character in the hidden message is the character whose binary ASCII representation is 01000001 (that is, the capital letter A).
Your job is to write a program to extract the hidden message from the modified ox photograph. Write the message on your test paper, and submit your program as usual. Please call the program problem5.py.