n8programs N8python

Working on something different than what I was working on at the time I wrote this bio. All my work is CC0 unless otherwise specified.

N8python / Fmait.js

Created June 23, 2019 11:01

An asynchronous, concurrent function for creating efficient, easy-to-understand promise pipelines.

	async function fmait(callbacks, array) {
	for (const callback of callbacks) {
	array = await Promise.all(array.map(item => Promise.resolve(callback(item))));
	}
	return array;
	}

N8python / keybindr.js

Created August 1, 2019 20:21

Keybindr - A small and easy way to bind callbacks to keys.

	window.keybindr = (() => {
	// Declare set of keys that are pressed
	const keys = new Set();
	// Declare "associative array" of bindings to callback
	const bindings = [];
	function tokenizeKeys(keys){
	// Get array of different keys from string
	return keys.split("+");
	}
	window.addEventListener("keydown", ({key}) => {

N8python / vecTo.js

Created March 13, 2020 01:04

The following code calculates a unit vector from coordinates (x, y) to the point (x1, y1).

	const degrees = radians => radians * 180 / Math.PI;
	const radians = degrees => degrees * Math.PI / 180;
	function vecTo(x1, y1, x2, y2) {
	const xDist = x2 - x1;
	const yDist = y2 - y1;
	let direction;
	if (xDist > 0 && yDist > 0) {
	direction = degrees(Math.atan(yDist / xDist));
	} else if (xDist > 0 && yDist < 0) {
	direction = 360 + degrees(Math.atan(yDist / xDist));

N8python / seirs.R

Created July 7, 2020 15:29

SEIRS Model - A SEIRS Model with support for vital dynamics, mortality, and seasonal variance in r0.

	library(deSolve)
	library(reshape2)
	library(ggplot2)
	initial_state_values <- c(S = 0.999, E = 0, I = 0.001, R = 0, M = 0) # S = Susceptible, E = Exposed, I = Infected, R = Recovered, M = Dead
	parameters <- c(
	beta = 0.07142857142 * 3, # Contact Rate
	theta = 0.2, # 1 / (Length of Latent Period)
	gamma = 0.07142857142, # 1 / (Length of Infection)
	ro = 0.00130718954, # 1 / (Length of Immunity)
	nu = 0.00003281917, # Birth Rate

N8python / irm.R

Created July 10, 2020 13:20

	library(deSolve)
	library(reshape2)
	library(ggplot2)
	initial_state_values <- c(I = 1000000, R = 0, M = 0)
	parameters <- c(gamma = 0.1, mu = 0.2)
	times <- seq(from = 0, to = 28, by = 1)
	cohort_model <- function(time, state, parameters) {
	with (as.list(c(state, parameters)), {
	dI <- -gamma * I - mu * I
	dR <- gamma * I

N8python / sir-dynamic.R

Created July 10, 2020 14:08

N8python / covid-model.R

Last active July 16, 2020 02:01

N8python / terrainAutomata.js

Created September 3, 2020 14:54

Terrain generation using p5js and cellular automata.

	const SQUARE_SIZE = 5;
	let storage = [];

	function setup() {
	createCanvas(600, 600);
	for (let x = 0; x < width / SQUARE_SIZE; x++) {
	storage[x] = [];
	for (let y = 0; y < height / SQUARE_SIZE; y++) {
	storage[x].push((Math.random() > 0.5) ? "red" : "blue")
	}

N8python / char-lstm.js

Created September 18, 2020 12:03

	const fs = require("fs");
	const R = require("ramda");
	const tf = require("@tensorflow/tfjs-node");
	const fsExtra = require('fs-extra')
	const text = fs.readFileSync("input.txt").toString();
	const chars = Array.from(new Set(text.split("")));
	const encoding = Object.fromEntries(chars.map((x, i) => [x, i]));
	const decoding = Object.fromEntries(chars.map((x, i) => [i, x]));
	const sampleLength = 20; // when I change this to 100, my lstm's loss goes to NaN
	const epochSize = 5000;

N8python / char-lstm.js

Created September 23, 2020 21:43

	async function main() {
	const fs = require("fs");
	const R = require("ramda");
	const tf = require("@tensorflow/tfjs-node");
	const fsExtra = require('fs-extra');
	const text = fs.readFileSync("input.txt").toString();
	const chars = Array.from(new Set(text.split("")));
	const encoding = Object.fromEntries(chars.map((x, i) => [x, i]));
	const decoding = Object.fromEntries(chars.map((x, i) => [i, x]));
	const sampleLength = 50;