Description
1 Project Overview
In computational geometry, algorithms often build their efficiency on processing geometric objects
in certain orders that are generated via sorting. One example is a Graham scan, which constructs
the convex hull of a collection of points in the plane in one traversal ordered by the polar angle. In
another example, intersections of a set of line segments can be found using a sweep line that makes
stops only at the segments’ endpoints and intersections. ordered by x- or y-coordinates.
In this project, you are asked to scan an input set of points in the plane in the order of their polar
angles with respect to a reference point. This reference point, called the median coordinate point
(MCP), has its x-coordinate equal to the median of the x-coordinates of the input points and its
y-coordinate equal to the median of their y-coordinates. A polar angle with respect to this point
lies in the range [0, 2π).
Finding the median x- and y-coordinates is done by sorting the points separately by the corresponding coordinate.1 Once the MCP has been constructed, a third round of sorting will be conducted
by the polar angle with respect to this point.
You need to scan the input points four times, each time using one of the four sorting algorithms
presented in class: selection sort, insertion sort, merge sort, and quicksort. Note that the same
sorting algorithm must be used in all three rounds of sorting within one scan.
We make the following two assumptions:
• All input points have integer coordinates ranging between −50 and 50, inclusive.
• The input points may have duplicates.
Integer coordinates are assumed to avoid issues with floating-point arithmetic. The rectangular
range [−50, 50] × [−50, 50] is big enough to contain 10,201 points with integer coordinates.
Since the input points will be either generated as pseudo-random points or read from an input file,
duplicates may appear. Also, it is unnecessary to test your code on more than 10,201 input points
(otherwise duplicates will certainly arise).
1.1 Point Class and Comparison Methods
The Point class implements the Comparable interface. Its compareTo() method compares the xor y- coordinates of two points. In case two points tie on their values of the selected coordinate,
the values of the other coordinate are compared to break the tie.
Point comparison can also be done using an object of the PolarAngleComparator class, which
you are required to implement. The polar angle is with respect to a point stored in the instance
variable referencePoint. The compare() method in this class must be implemented using cross
1
In Com S 311 you will learn an algorithm that can find the median of n numbers in O(n) time, but in practice
it often takes too long due to a large constant factor hidden inside the Big-O.
1
and dot products, not any trigonometric or square root functions. You need to handle special
situations where multiple points are equal to referencePoint, have the same polar angle with
respect to it, etc. Please read the Javadoc for the methods compare() and comparePolarAngle()
carefully.
1.2 Sorter Classes
Selection sort, insertion sort, merge sort, and quicksort are respectively implemented by the classes
SelectionSorter, InsertionSorter, MergeSorter, and QuickSorter, all of which extend the
abstract class AbstractSorter. The abstract class has one constructor awaiting your implementation:
protected AbstractSorter(Point[] pts) throws IllegalArgumentException
The constructor takes an existing array pts[] of points and copies it over to the array points[].
It throws an IllegalArgumentException if pts == null or pts.length == 0.
Besides having an array points[] to store points, AbstractSorter also includes three instance
variables.
• algorithm: type of sorting algorithm to be initialized by a subclass constructor.
• pointComparator: comparator used for point comparison. Set by calling setComparator().
It compares two points by their x-coordinates, y-coordinates, or polar angles with respect to
referencePoint.
• referencePoint: reference point that polar angles are taken with respect to. Set by calling
setReferencePoint().
The method sort() conducts sorting, for which the algorithm is determined by the dynamic type of
the AbstractSorter. The method setComparator() must have been called beforehand to generate
an appropriate comparator for sorting by the x-coordinate, y-coordinate, or polar angle. In the
case that the polar angle is used, referencePoint must have a value that is not null.
2
The class also provides two methods: getPoints() to get the contents of the array points[], and
getMedian() to return the element with the median index in points[].
Each of the four subclasses SelectionSorter, InsertionSorter, MergeSorter, and QuickSorter
has a constructor that needs to call the superclass constructor.
1.3 RotationalPointScanner Class
This class has two constructors. Both accept one type of sorting algorithm. The first constructor
reads points from an array. The second one reads points from an input file of integers, where each
pair of integers represents the x and y-coordinates of one point. A FileNotFoundException will
be thrown if no file by the inputFileName exists, and an InputMismatchException will be thrown
if the file consists of an odd number of integers.3
For example, suppose a file points.txt has the following content:
2Use the method setReferencePoint() to set a value.
3There is no need to check if the input file contains unneeded characters like letters since they can be taken care
of by the hasNextInt() and nextInt() methods of a Scanner object.
2
0 0 -3 -9 0 -10
8 4 3 3 -6
3 -2 1
10 5 -7 -10
5 -2
7 3 10 5
-7 -10 0 8
-1 -6
-10 0
5 5
There are 34 integers in the file. A call
RotationalPointScanner(points.txt, Algorithm.QuickSort);
will initialize the array points[] to store the following 17 points, which are plotted4 below, along
with their MCP: (0, 0), (−3, −9), (0, −10), (8, 4), (3, 3), (−6, 3), (−2, 1), (10, 5), (−7, −10), (5, −2),
(7, 3), (10, 5), (−7, −10), (0, 8), (−1, −6), (−10, 0), and (5, 5).
−12 −10 −8 −6 −4 −2 0 2 4 6 8 10 12
−10
−8
−6
−4
−2
0
2
4
6
8
x
y
Note that the points (-7, -10) and (10, 5) each appear twice in the input.
The 17 points have x-coordinates in the following sequence:
0, −3, 0, 8, 3, −6, −2, 10, −7, 5, 7, 10, −7, 0, −1, −10, 5
which, after sorted in the non-decreasing order, becomes,
−10, −7, −7, −6, −3, −2, −1, 0, 0, 0, 3, 5, 5, 7, 8, 10, 10
4They were plotted here using the LATEX package pgfplot. In this project, you are provided an implemented class
Plot using the Java graphics package Swing for display of results.
3
Since the largest index in the private array points[] storing the points is 16, the median is 0 at
the index 16/2 = 8. (Note that integer division in Java truncates the fractional part, if any, of the
result.) Similarly, the above points have y-coordinates in the following sequence:
0, −9, −10, 4, 3, 3, 1, 5, −10, −2, 3, 5, −10, 8, −6, 0, 5
which is in the non-decreasing order below.
−10, −10, −10, −9, −6, −2, 0, 0, 1, 3, 3, 3, 4, 5, 5, 5, 8
The median y-coordinate is 1 at the index 8. The median coordinate point (MCP) is therefore
(0, 1), colored blue in the plot. Notice that it does not coincide with any of the input points.
Construction of the MCP is carried out by the method scan() of the class by sorting the points
by x- and y-coordinates, respectively. After these two sorting rounds, the method sets the value
of medianCoordinatePoint to the MCP, and then calls the method setReferencePoint() of
the AbstractSorter class to set the value of its instance variable referencePoint to the MCP.
The method scan() then carries out a final round of sorting by polar angle with respect to the
MCP.
Besides using an array points[] to store points and medianCoordinatePoint to store the MCP,
the RotationalPointScanner class also includes several other instance variables.
• sortingAlgorithm: type of sorting algorithm. Initialized by a constructor.
• outputFileName: name of the file to store the sorting result in: select.txt, insert.txt,
merge.txt, or quick.txt.
• scanTime: sorting time in nanoseconds. This sums up the times spent on three rounds of
sorting. Within sort(), use the System.nanoTime() method.
In the previous example, after calling scan(), the array points[] will store the points ordered by
the polar angle with respect to the MCP: (7, 3), (8, 4), (10, 5), (10, 5), (3, 3), (5, 5), (0, 8), (−6, 3),
(−2, 1), (−10, 0), (−7, −10), (−7, −10), (−3, −9), (−1, −6), (0, 0), (0, −10), (5, −2).
Among them, (0, 0) and (0, −10) have the same polar angle. They are thus ordered by distance to
this point.
2 Compare Sorting Algorithms
The class CompareSorters uses the class RotationalPointScanner to scan points randomly generated or read from files four times, each time using a different sorting algorithm. Multiple input
rounds are allowed. In each round, the main() method compares the execution times of the four
scans of the same input sequence. The round proceeds as follows:
1. Create an array of randomly generated integers, if needed.
2. Construct four RotationalPointScanner objects over the point array, each with a different
algorithm (i.e., a different value for the parameter algo of the constructor).
3. Have every created RotationalPointScanner object call scan().
4. At the end of the round, output the statistics by having every RotationalPointScanner
object call the stats() method.
Below is a sample execution sequence with running times.
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Performances of Four Sorting Algorithms in Point Scanning
keys: 1 (random integers) 2 (file input) 3 (exit)
Trial 1: 1
Enter number of random points: 1000
algorithm size time (ns)
———————————-
SelectionSort 1000 49631547
InsertionSort 1000 22604220
MergeSort 1000 2057874
QuickSort 1000 1537183
———————————-
Trial 2: 2
Points from a file
File name: points.txt
algorithm size time (ns)
———————————-
SelectionSort 1000 3887008
InsertionSort 1000 9841766
MergeSort 1000 1972146
QuickSort 1000 888098
———————————-
…
Your code needs to print out the same text messages for user interactions. Entries in every column
of the output table should be aligned.
3 Random Point Generation
To test your code, you may generate random points within the range [−50, 50] × [−50, 50]. Each
random point has its x- and y-coordinates generated separately as pseudo-random numbers within
the range [−50, 50]. You already had experience with random number generation from Project 1.
Import the Java package java.util.Random. Next, declare and initiate a Random object with
Random generator = new Random();
Then, the expression generator.nextInt(101) 50 will generate a pseudo-random number between -50 and 50 every time it is executed.
4 Display of a Point Scan
The sorted points will be displayed using Java graphics package Swing. The display will help you
visually check that the points are correctly sorted. The fully implemented class Plot is for this
purpose. A few things about the implementation to note below:
• The JFrame class is a top level container that embodies the concept of a “window.” It allows
you to create an actual window with customized attributes like size, font, color, etc. It can
display one or more JPanel objects at the same time.
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• JPanel is for painting and drawing, and must be added to the JFrame to create the display.
A JPanel represents some area in a JFrame in which controls such as buttons and text fields
and visuals such as figures, pictures, and text can appear.
• The Graphics class may be thought of like a pen that does the actual drawing. The class
is abstract and often used to specify a parameter of some method (in particular, paint()).
This parameter is then downcast to a subclass such as Graphics2D for calling the latter’s
utility methods.
• The paint() method is called automatically when a window is created. It must be overridden
to display your drawings.
The results of the four scans are displayed in separate windows. For display, a separate thread is
created inside the method myFrame() in the class Plot. Please do not modify the Plot class for
better display unless you understand what is going on there.
The class Segments has been implemented for creating specific line segments to connect the input
points so you can see the correctness of the sorting result.
4.1 Drawing Data Preparation
The output of each scan can be displayed by calling the partially implemented method draw() in
the RotationalPointScanner class, only after scan() is called, via the statement
Plot.myFrame(points, segments, sort);
where the first two parameters have types Point[] and Segment[], respectively, and the third
parameter is a string name for the sorting algorithm used. By this time, the array points[] stores
the points in the order of scan. You will need to create an array segments[] to store some line
segments which, when drawn, can visually reveal the order among the points. Create line segments
to connect:
• every pair of consecutive points in points[] that are distinct from each other,
• the first (index 0) and last points in points[] if they are distinct, and
• medianCoordinatePoint to every point in points[].
The order among the elements in segments[] may be arbitrary. Consider the same 17 input points
(with duplicates) that were plotted above. After a scan, segments[] would consist of the following
30 segments, the last 15 of which share an endpoint at medianCoordinatePoint == (0, 1):
((7, 3),(8, 4)) ((8, 4),(10, 5)) ((10, 5),(3, 3)) ((3, 3),(5, 5)) (5, 5),(0, 8))
((0, 8),(−6, 3)) ((−6, 3),(−2, 1)) ((−2, 1),(−10, 0)) ((−10, 0),(−7, −10)) ((−7, −10),(−3, −9))
((−3, −9),(−1, −6)) ((−1, −6),(0, 0)) ((0, 0),(0, −10)) ((0, −10),(5, −2)) ((5, −2),(7, 3))
((0, 1),(7, 3)) ((0, 1),(8, 4)) ((0, 1),(10, 5)) ((0, 1),(3, 3)) ((0, 1),(5, 5))
((0, 1),(0, 8)) ((0, 1),(−6, 3)) ((0, 1),(−2, 1)) ((0, 1),(−10, 0)) ((0, 1),(−7, −10))
((0, 1),(−3, −9)) ((0, 1),(−1, −6)) ((0, 1),(0, 0)) ((0, 1),(0, −10)) ((0, 1),(5, −2))
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4.2 Displaying the Result From a Scan
−12 −10 −8 −6 −4 −2 0 2 4 6 8 10 12
−10
−8
−6
−4
−2
0
2
4
6
8
x
y
For the 30 segments listed in Section 4.1, the corresponding display window will show a triangulation
like the one above. (You don’t need to use different colors to emulate this plot.)
The outer boundary of the triangulation is a simple polygon (drawn in blue) with the 15 distinct
input points as vertices. A counterclockwise traversal of the polygon vertices starting at (7, 3) will
never decrease the polar angle with respect to the median coordinate point (0, 1). Fifteen orange
line segments connect (0, 1) to the vertices. If your scanning result is correct, no two line segments
should intersect at a point in their interiors.
5 Submission
Write your classes in the edu.iastate.cs228.hw2 package. Turn in the zip file, not your class
files. Follow the Submission Guide posted on Canvas. Include the Javadoc tag @author in each
class source file. Your zip file should be named Firstname_Lastname_HW2.zip
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