Assignment A02: C++ and Make (25 points)

Overview

In this assignment, students will extend their previous Monte Carlo implementation for calculating π (pi.cc) to create a new program autopi.cc. This new program will automatically calculate π to 1, 2, 3, 4, 5, 6, 7, and 8 significant digits. Students will measure the computational effort (iterations and time) required for each level of precision and output this data to a file. Additionally, students will write a Python script to parse the output file and generate a plot following best practices for data visualization.

Students will also build a Makefile for the new program that compiles the code into an executable named autopi and includes a make clean target.

Objective and Expected Learning Outcomes

The primary objectives of this assignment are:

  • Automate the Monte Carlo method for calculating π to different levels of precision.
  • Measure and analyze the computational effort required for increasing precision.
  • Visualize the relationship between precision and computational effort using a Python-generated plot.

Outcomes:

  1. Enhanced Programming Skills in C++:
    • Modify and extend existing C++ code to add automated calculations and data output.
  2. Makefile Proficiency:
    • Write a Makefile from scratch to manage the build process for the updated program.
  3. Performance Measurement:
    • Implement time tracking in C++ to measure computation time for different levels of precision.
    • Save iteration counts and timing data to a file for analysis.
  4. Data Visualization with Python:
    • Write a Python script to read the output file and generate a plot illustrating the relationship between significant digits and computational effort.
  5. Best Practices for Coding and Visualization:
    • Follow clean coding standards in both C++ and Python.
    • Adhere to principles of effective data visualization, including labeling, scaling, and formatting.

Instructions

Part 1: Extending the C++ Program

  1. Edit file named autopi.cc by copying your previous pi.cc implementation.
  2. Modify autopi.cc to:
    • Automatically calculate π to 1 through 8 significant digits.
    • For each level of precision:
      • Record the number of iterations required to achieve the precision.
      • Measure the time taken for the computation using std::chrono.
    • Output the results in the following format to a file named autopi.csv: 
      Precision, Iterations, Time, Pi
1, <iterations>, <time>, <value of pi calculated>
2, <iterations>, <time>, <value of pi calculated>
...
8, <iterations>, <time>, <value of pi calculated>
  3. Include proper error handling and comments in your code.

Part 2: Makefile

  1. Create a Makefile to:
    • Compile autopi.cc into an executable named autopi.
    • Include a make clean target to remove build artifacts and executables.
  2. Test the Makefile on the UIC CS resources (systems{1-4}.cs.uic.edu) to ensure it works correctly.

Part 3: Python Visualization

  1. Write a Python script autopiPlot.py to:
    • Read autopi.csv.
    • Generate a plot with:
      • x-axis: Significant Digits (1 to 8)
      • y-axis: Computational Effort (iterations and time on separate plots or a dual-axis plot).
      • Proper labels, legends, titles, and gridlines.
    • Save the plot as autopi.png (dual-axis plot) or autopi00.png and autopi01.png (separate plots).
  2. Follow best practices for graphing:
    • Use clear, descriptive labels.
    • Ensure the plot is readable and well-formatted.

Submission Guidelines and Evaluation Criteria

  • Add and/or edit the following files to your GitHub repository:
    • autopi.cc
    • Makefile
    • autopi.csv (sample run with results for all 8 significant digits)
    • autopiPlot.py
    • autopi.png (generated by your script)
  • Include a short reflective statement in autopi.txt, summarize the challenges faced and lessons learned in this assignment.
  • When your program is ready for grading, commit and push your local repository to the remote git classroom repository and follow the Assignment Submission Instructions.
  • You will be evaluated on your ability to follow instructions, correctly name files, quality and completeness of code, and reflection on the assignment.

Additional Resources