Run the server:
npm run start
Test the server by loading http://localhost:8080/ in a browser, or run
time curl http://localhost:8080/
| <!DOCTYPE html> | |
| <head> | |
| <meta charset="utf-8"> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.15/lodash.min.js"> </script> | |
| <script src="https://d3js.org/d3.v5.min.js"></script> | |
| <style type="text/css"> | |
| .timeline { | |
| pointer-events: all; | |
| } |
| #!/usr/bin/env python | |
| import itertools | |
| import numpy as np | |
| N = 1000 | |
| d = 500 | |
| x_normal = np.random.multivariate_normal([0], [[1]], [N, d]).reshape([N, d]) | |
| x_spherical = x_normal / np.linalg.norm(x_normal, axis=1)[:, np.newaxis] |
| import copy | |
| # fun from Ernest! | |
| # | |
| # Given two strings s and t, determine whether some anagram of t is a substring of s. | |
| # For example: if s = "udacity" and t = "ad", then the function returns True. | |
| # Your function definition should look like: question1(s, t) and return a boolean True or False. | |
| def q_mike(s, t): | |
| def add_to_hist(c, hist): |
| /* global d3, _ */ | |
| var CONFIG = { | |
| transitionDuration: 0, | |
| stepDelay: 10, | |
| // learning rate | |
| alpha: 0.1, | |
| // deviation from greediness | |
| epsilon: 1e-2, | |
| // reward discount factor |
| file=$(pbpaste); git diff -b -M :1:$file :2:$file >~/tmp/left.diff; git diff -b -M :1:$file :3:$file >~/tmp/right.diff; vim -O ~/tmp/left.diff ~/tmp/right.diff # ;three-way |
| vim +/"^[<>|=]\{7}" $(git status -sb | grep "^UU" | cut -d' ' -f 2) # ;edit-conflicted |
| head -c 15 </dev/random | python3 -c "import sys, base64; sys.stdout.write('{}\n'.format(base64.b85encode(sys.stdin.buffer.read()).decode('utf-8')))" # ;b85-pass |
Run the server:
npm run start
Test the server by loading http://localhost:8080/ in a browser, or run
time curl http://localhost:8080/
A letter scrambling and object constancy demo based on Mike Bostock's General Update Pattern III.
10,000 poisson-disc samples of Van Gogh’s The Starry Night. Compare to uniform random samples.
Forked from Poisson-Disc III