Data and Code
On this page, I plan to provide access to various codes that I have used throughout my research. I aim to release two different types of code: (i) tools that may be of use to others in their own work and (ii) scripts, Jupyter notebooks, etc. used to generate my results, in the interest of scientific reproducibility.
I’m making an active effort to build GitHub repositories for my various projects.
- SatGen: A semi-analytical satellite galaxy and dark matter halo generator
- nbodipy: An NFW N-body simulation initial condition generator
- pyPPCA: A Python module for probabilistic principle component analysis, a robust method for imputing missing data based on the inferred principle components
I have put the code and data up on GitHub for some of my older projects, and I plan to focus on being more systematic on current and future projects so that all necessary materials for reproducing my published results are make publicly available.
Codes used for generating a trained random forest model for predicting mock Magneticum X-ray cluster masses and the Jupyter notebooks used to generate results and figures in Green et al. (2019b): GitHub Repository
I’ve been exploring some additional ML/AI/NLP projects using Kaggle. Check out my Kaggle user profile.
I’m working with text data from the r/wallstreetbets subreddit to do some sentiment analysis on stock prices. Here is my working GitHub Repository.