Exercises

Submission

To submit your solution, you will be creating a .zip file following the exercises below and upload it on Canvas under Assignment > Lab 1: Linux, Git, Python by September 5 at midnight (11:59 EST).

Late Submission

Please email us if you want to submit later than the deadline. Otherwise late penalty will be applied.

Exercises

Git (5 pts)

In this exercise you are required to set a git repository, for example inside your own Github namespace. You will be downloading the zip file of this repository and submit it to Canvas.

  1. Create a repository for your personal submissions
    • Go to https://github.umich.edu/YOUR_USERNAME and click on “New Project” to create a new repository (replace YOUR_USERNAME with your Github namespace)
    • Create a new Private repository and call it as your UMich username, e.g. if your Umich email is astark@umich.edu, call it astark
    • Clone the repository to ~/ae740_personal (you will have a team submission later) running git clone https://github.com/YOUR_USERNAME/YOUR_UNIQUENAME.git ~/ae740_personal (replace YOUR_UNIQUENAME with your uniquename)
    • Create a folder called lab1

Shell (35 pts)

  1. Exercise 1 - Answer to the following questions
    • Download https://raw.githubusercontent.com/dlang/dmd/master/druntime/benchmark/extra-files/dante.txt (try using wget)
    • Create a file called exercise1.txt in ~/ae740_personal/lab1 and answer to the following questions
      1. How many lines does it contains?
      2. How many words does it contains?
      3. How many lines are not blank?
    • Push the file to git
  2. Exercise 2 - Output redirecting
    • Install fortune-mod using apt
    • After installation, type fortune in your terminal to see a (hopefully) interesting proverb/quote
    • Run fortune 5 more times and each time redirect the output to a file called fortunes.txt in ~/ae740_personal/lab1 (Hint: do not recreate the file 5 times - each time a new proverb should be added to the end of fortunes.txt)
    • Push the file to git

Hint: For the first exercise you might want to use the command wc (Word Count).

Python: RandomVector (40 pts)

In this exercise, you will implement a Python class called RandomVector. In the ae740_personal directory, create a Python virtual environment ae740_venv, that we will use throughout the course. Inside ~/ae740_personal/lab1, create a folder called RandomVector and clone the contents from https://github.com/UM-iRaL/ae740_labs/tree/main/lab1. This contains two files –

  • random_vector.py: Class definition.
  • main.py: Main Python file, that imports the RandomVector class.

The class RandomVector will handle a list of random floating-point numbers. You are required to implement the following methods inside random_vector.py:

  • __init__(self, size, max_val=1.0) (constructor): Initialize a list of size size with random values between 0 and max_val (default value 1.0)
  • mean(self): Returns the mean of the values in the random vector
  • max(self): Returns the maximum value in the random vector
  • min(self): Returns the minimum value in the random vector
  • print(self): Prints all the values in the random vector
  • print_histogram(self, bins): Computes the histogram of the values using bins number of bins between min() and max() and prints the histogram (see the example below)

When you’re done, create another file called main.py to test your implementation.

Note: We expect you to not use built-in functions like min(), max(), sum() or libraries like NumPy or Pandas for your implementation. Write the algorithms yourself.

If you complete the exercise correctly, when you run python main.py you should see output similar to:

$ python main.py
0.458724 0.779985 0.212415 0.066795 0.622538 0.999018 0.489585 0.460587 0.079561 0.185496 0.629162 0.328032 0.242169 0.139671 0.453804 0.083038 0.619352 0.454482 0.477426 0.090497
Mean: 0.393617
Min: 0.066795
Max: 0.999018
Histogram:
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