Since this exercise is more complex than the previous one, it has been broken down into three sub-tasks:

1. Converting a sequence of command-line arguments into an array of temperature values.
2. Sorting this array.
3. Calculating the median of the array.

Our data comes from a super high-tech thermometer which records the temperature over time, but outputs its readings in a slightly strange format. The format consists of series of symbols, of which the first is a number that represents the starting temperature, while the succeeding symbols show the change in temperature since the previous one. These symbols are decoded as follows:

• '.' means no change
• '+' means an increase of 1 degree from the previous temperature
• '-' means a decrease of 1 degree from the previous temperature

All the calculated values are to be interpreted as numbers of type int. For example, the sequence of symbols

34 . . + + . - .

would encode the following sequence of temperatures:

34 34 34 35 36 36 35 35

Our task is the calculate the median of the temperature data. We first need to sort our array of numbers. Then,

• if the array contains an odd number \( n \) of elements, the median is the middle element; i.e., the \( {(n+1)/2}^{th} \) element.
• if the array contains an even number \( n \) of elements, the median is the mean of the two middle elements: i.e., the mean of \( {n/2}^{th} \) and the \( {(n/2)+1}^{th} \) element.

For example, suppose we have an array containing the following elements:

3 6 7 8 9 3 1 2 7

First we sort the array:

1 2 3 3 6 7 7 8 9

Now, since we have nine elements in the array (i.e. an odd number), the median value is simply the middle (i.e. \( 5^{th} \)) element in the sorted array, i.e 6.

For contrast, suppose we have an array with these values:

3 6 7 8 5 5

Then we would again sort it:

3 5 5 6 7 8

This time, there are six elements. Since there is no middle element, to calculate the median we take the mean of the two central elements, i.e the \( 3^{rd} \) and \( 4^{th} \) elements and take their mean:

In the first part of this exercise, write a program TempMedian that will read the input from the command-line, and create an array of temperature values of type int. Then print out the values:

: java TempMedian 34 . . . + . + . +
34 34 34 34 35 35 36 36 37

: java TempMedian 7 - - - - . .
7 6 5 4 3 3 3

Now that you have an array of int values representing temperatures, you should extend TempMedian so that it now also prints out the sorted array of values on a new line (i.e., the second line).

To sort an array of numbers, use the Java static method Arrays.sort(). Note that this sorts the list ‘in place’; you do not have to assign the result of sorting to a new variable. For example, the following code will sort the array myValues[]:

import java.util.Arrays;

public class SortingExample {

    public static void main(String[] args) {
        int[] myValues = new int[4];
        myValues[0] = 3;
        myValues[1] = 2;
        myValues[2] = 5;
        myValues[3] = -1;

        Arrays.sort(myValues);

        // print out elements of myValues[]
    }
}

Your program should output the sorted array on the second line. For example:

: java TempMedian 34 . . . + . - - - . +
34 34 34 34 35 35 34 33 32 32 33
32 32 33 33 34 34 34 34 34 35 35

: java TempMedian 7 - - - . .
7 6 5 4 4 4
4 4 4 5 6 7

: java TempMedian 10 - + . - . - . +
10 9 10 10 9 9 8 8 9
8 8 9 9 9 9 10 10 10

Finally, your program TempMedian should output the median value of the data set. Take care to ensure that your program outputs the median as a floating-point number.

For example:

: java TempMedian 34 . . . + . - - - . +
34 34 34 34 35 35 34 33 32 32 33
32 32 33 33 34 34 34 34 34 35 35
34.0


: java TempMedian 7 - - - . .
7 6 5 4 4 4
4 4 4 5 6 7
4.5

: java TempMedian 10 - + . - . - . +
10 9 10 10 9 9 8 8 9
8 8 9 9 9 9 10 10 10
9.0

: java TempMedian 3 - - - -
3 2 1 0 -1
-1 0 1 2 3
1.0