Hello! My name is Eitan Lees. I am a graduate student in the department of Scientific Computing at Florida State University. I enjoy data visualization, open science, and programming.
Note: This is a slightly edited reposting of an Observable notebook originally published in 2021. I had not really understood what Lambda-calculus was or why it was important until I saw David Beazley’s talk Lambda Calculus from the Ground Up . I watched in amazement as Beazley turned a few simple functions into a universal computing machine. My goal here is to share that same experience with you.…
Note: This is a slightly edited reposting of an article I originally published on the Matplotlib Blog Cellular automata are discrete models, typically on a grid, which evolve in time. Each grid cell has a finite state, such as 0 or 1, which is updated based on a certain set of rules. A specific cell uses information of the surrounding cells, called its neighborhood , to determine what changes…
Recently I was working on a translation project to turn a bunch of old lecture notes into a quarto book . The project has been really fun and hopefully one day it will be complete. What I have finished so far can be found here . During the project I came across this figure. A parabola used as an example to explain minimization methods. Fine enough in the context but for this project I want to…
It recently came to my attention that my old post on numpy polynomial fitting needed to be updated. There is a much more natural way to do this using the numpy.polynomial submodule which I will outline in this post. %matplotlib inline %config InlineBackend.figure_format = 'svg' import numpy as np import matplotlib.pyplot as plt Generating data We will create some different mock data this time #…
Motivation Recently I came across a blog post by Éric Marty titled The D3 / Vega “stack” , in which he outlines the many packages and tools surrounding the Vega ecosystem. His post and visuals have directly inspired my post below. Standing on the Shoulders of Giants After leading multiple workshops and showing off Altair to friends and family, I have come across a few similar questions: “Can I do…
In the previous post I discussed my strategy for building a large modular latex project. I realized I never shared any of the actual work I did. I was the TA for a course called ISC-4933: Iterative and Direct Solvers for Linear Systems . It was the first time the course was taught and I was tasked with typing up the lecture notes. I took the opportunity sharpen my LaTeX skills and to finally…
Modular Latex Recently I was tasked with typing up the notes for a course in my department. Each week I would attend class, typeset notes, and distribute them to students. At the end of the semester I compiled the notes into a single document. I wanted this document to be built in a modular way rather than a large monolithic tex file. I mostly referred to a wiki LaTeX/Modular Documents for advice…
Recently I rebooted my configuration files and wanted to document the process. The Goal I would like a set up that is portable, concise, and version controlled. The dream is I can sit down at a new machine, clone my dot files, and be up an running quickly. Why Now Over the past few months I have been experimenting with different editors to get a feel of what other options are out there. I gave…
Note: This post has been updated. See Numpy Polynomial Fitting Redux Given data out in the wild a common task is to fit a polynomial function. Numpy offers some convenient functions to get the job done. % matplotlib inline % config InlineBackend . figure_format = 'svg' import numpy as np import matplotlib.pyplot as plt Generating data We will create some mock data to explore polynomial fitting #…
I recently was the TA for a Monte Carlo methods course which involved sampling many statistical distributions. Often students would write standalone functions to draw samples which was prone to error. While knowing how to code up an exotic distribution can be useful, I encourage students not to re-invent the wheel every assignment. The scipy.stats package contains many probability distributions…