Question

Write a sort function for a list of 4 -tuples. Below is a list of the nearest stars and some of their properties. The list elements are 4 -tuples containing the name of the star, the distance from the sun in light years, the apparent brightness, and the luminosity. The apparent brightness is how bright the stars look in our sky compared to the brightness of Sirius A. The luminosity, or the true brightness, is how bright the stars would look if all were at the same distance compared to the Sun. The list data are found in the file stars. list, which looks as follows: The purpose of this exercise is to sort this list with respect to distance, apparent brightness, and luminosity. To sort a list data, one can call sorted(data), which returns the sorted list (cf. Table 2.1). However, in the present case each element is a 4 -tuple, and the default sorting of such 4 -tuples result in a list with the stars appearing in alphabethic order. We need to sort with respect to the 2nd, 3rd, or 4th element of each 4 -tuple. If a tailored sort mechanism is necessary, we can provide our own sort function as a second argument to sorted, as in sorted(data, mysort). Such a tailored sort function mysort must take two arguments, say a and b, and returns \(-1\) if a should become before \(\mathrm{b}\) in the sorted sequence, 1 if \(\mathrm{b}\) should become before a, and 0 if they are equal. In the present case, a and \(b\) are 4-tuples, so we need to make the comparison between the right elements in a and b. For example, to sort with respect to luminosity we write def mysort \((a, b):\) if \(a[3]b[3]:\) return 1 else: return 0 Write the complete program which initializes the data and writes out three sorted tables: star name versus distance, star name versus apparent brightness, and star name versus luminosity. Name of program file: sorted_stars_data.py.

Short answer

Define sort functions for distance, apparent brightness, and luminosity, and use them to sort the tuples.

Step-by-step solution

Import the Required Modules

Start by importing the Python `functools` module which is needed to use the custom sorting function.

Initialize the Data List

Create a list containing 4-tuples for each star. Each tuple will have the star's name, distance, apparent brightness, and luminosity.

Define Sort Functions

Define functions that will be used as keys for sorting. These functions will determine what element of the tuple we are sorting by. We will create three separate functions for distance, apparent brightness, and luminosity.

Sort by Distance

Use the `sorted()` function with a lambda expression as the sorting key to sort the list based on the second element of the tuple (distance). Store the result in a separate list.

Sort by Apparent Brightness

Use the `sorted()` function with a lambda expression to sort the list based on the third element of the tuple (apparent brightness). Store the result in a separate list.

Sort by Luminosity

Use the `sorted()` function with a lambda expression to sort the list based on the fourth element of the tuple (luminosity). Store the result in a separate list.

Print the Sorted Lists

Print each of the sorted lists, showing the star name and the respective sorted criterion (distance, apparent brightness, luminosity).

Key concepts

Sorting Algorithms

Sorting algorithms are fundamental concepts in computer programming, used to rearrange data in some specific order. This could be in ascending or descending order based on numerical or alphabetical criteria. In Python, the `sorted()` function is a quick and easy way to sort items.

• `sorted(data)`: This will sort the data in ascending order by default, based on the type of data in the list.
• Custom sorting: You can tailor the sorting order by providing a function that determines the criteria.

To sort a list of 4-tuples where each tuple has multiple sortable elements such as distance, apparent brightness, and luminosity, custom sorting functions are particularly useful. By defining specific sorting functions using the `key` parameter in `sorted()`, you can sort your tuples on these different elements. For example, if you need to sort based on the second item of each tuple (say distance), a lambda function `lambda x: x[1]` can be used.

Data Structures

Data structures are ways of organizing and storing data so that we can efficiently perform operations on them. In this exercise, we are dealing specifically with tuples, which are immutable sequences in Python.
A tuple can store multiple items, and is defined by its immutability, which means the data inside a tuple cannot be changed after it is created. This feature is useful when you want to ensure that data remains constant during execution.

• Tuples are accessed by indexing: `tuple[index]`.
• Used to store related pieces of data, like a star's details in our problem: name, distance, apparent brightness, and luminosity.

Python's flexibility allows for tuples to contain mixed data types, which makes them highly versatile data structures for handling complex datasets like the list of stars.

Tuple Operations

Tuple operations involve working with the data stored in tuples. Since tuples are immutable, many operations involve transformation or accessing data rather than changing it.

• Accessing elements: You can access elements in a tuple using indexing. For example, `star[1]` accesses the distance of the star in our 4-tuple.
• Sorting by tuple elements: You can sort a list of tuples by any element using the `sorted()` function with a key argument.
• Tuple unpacking: Useful for assigning tuple elements to individual variables, which simplifies specific operations.
• Comparisons: While sorting, comparing specific elements using a comparison function is common.

Understanding these operations allows effective data manipulation using tuples, ensuring efficient use of resources and code readability.

Function Definitions

Defining functions in Python is important for code reuse and organization. Functions allow you to execute the same block of code multiple times without having to rewrite it. In this exercise, we define functions to tailor how lists of tuples are sorted.

• Syntax: Use `def function_name(parameters):` to define a function.
• Return values: Functions can return values to the caller using the `return` statement.
• Custom keys for sorting: Define a function that provides a specific sorting logic, such as sorting by distance or brightness.
• Lambda functions: For concise function definitions, especially as single-use, consider defining them using the lambda keyword.

By defining explicit functions, you ensure that sorting methods are flexible and reusable, providing clarity to the sorting process. This capability makes handling data in programming tasks organized and systematic.