Miscellaneous

These are just some random things I coded in my free time.

• Bash
  • check_large_pack_files.sh: I wrote a script to sort through large objects in the pack of Git repositories. It identifies the largest NUMFILES blobs in the pack, reports its size, commit hash it was introduced in, and checks their containment in the specified BRANCH. The default arguments are the 10 largest files and containment in origin/main.
• C++
  • quicksorter.cpp: I coded the quicksort algorithm as my first C++ program. It takes in integers from the command line.
• C
  • bootstrap.c: I coded statistical bootstrapping to determine the distribution in which C picks values for its rand() function. I sampled 100 values between 0 and 10000, bootstrapped 100000 times, and got a Gaussian distribution nearly perfectly centered at 5000, as seen in the included graph.
  • brainfuck.c: This is an interpreter for the esoteric language Brainfuck. I included two sample programs, hello.bf which is a Hello World program and reverse.bf which reads in a string from user input and prints its reverse. You can run programs like ./brainfuck filename.
• JavaScript
  • snake.html: I coded a simple JavaScript snake game inspired by this YouTube video. I coded it with different data structures in my own style and added pause and restart functionality, as well as other minor tweaks. You can run it in a browser.
• Python
  • SIR.py: I used the classical fourth-order Runge-Kutta method to numerically solve the SIR epidemiological model. I became interested in this because of the current COVID-19 pandemic. The computed solutions can be seen in the included diagram.
  • denoising_images.ipynb: A student asked for a little coding sample of what an autoencoder can do so I put it here so the class could easily see it. A deep ReLU autoencoder is used to denoise MNIST images with keras. The image reconstructed.png shows the noisy images on the left and denoised images on the right.
  • gameoflife.py: I implemented Conway's Game of Life using a SciPy backend and the redirect module to print outputs to the console. A requirements.txt file is included and can be installed with pip. To use: python gameoflife.py n_rows n_cols n_alive where n_rows and n_cols refer to the size of the board while n_alive refers to the initial number of living cells.
  • death_probability.ipynb: Based on the actuarial life table published by the Social Security Administration, I wrote a method to calculate the probability an individual will die in the next given amount of years based on their age and sex.