Arachnid

import math

def between(a, b, c):
  return a <= b and b <= c


class Region(object):
  def intersects(self, other):
    raise NotImplemented(
        "%s does not know how to check for intersection with %s"

tixxit

# Chan's Convex Hull O(n log h) - Tom Switzer <thomas.switzer@gmail.com>

TURN_LEFT, TURN_RIGHT, TURN_NONE = (1, -1, 0)

def turn(p, q, r):
    """Returns -1, 0, 1 if p,q,r forms a right, straight, or left turn."""
    return cmp((q[0] - p[0])*(r[1] - p[1]) - (r[0] - p[0])*(q[1] - p[1]), 0)

def _keep_left(hull, r):
    while len(hull) > 1 and turn(hull[-2], hull[-1], r) != TURN_LEFT:

adammiller

var simplifyPath = function( points, tolerance ) {

	// helper classes 
	var Vector = function( x, y ) {
		this.x = x;
		this.y = y;
		
	};
	var Line = function( p1, p2 ) {
		this.p1 = p1;

MoritzStefaner

license: apache-2.0

s-l-teichmann

#!/usr/bin/env/python
#
# Little script to play around with the code and
# data of H. Tropf, H. Herzog's paper 1981 paper
#    "Multidimensional Range Search in Dynamically
#    Balanced Trees".
#
# Thanks to Bernhard Herzog (unrelated to H. Herzog)
# for having a second look at the code.
#

elijahmanor

describe("getTweets - Server", function () {
    var server, fakeData = [ /* ... */ ];

    before(function () {
        // Doesn’t work :( It’s JSONP!
        server = sinon.fakeServer.create();
        server.respondWith(
            "GET", 
            "https://api.twitter.com/.../elijahmanor.json?count=5",
            [200, { "Content-Type": "application/json" }, JSON.stringify(fakeData)]

DmitrySoshnikov

/**
 * Depth-first and Breadth-first graph traversals.
 *
 * In this diff we implement non-recursive algorithms for DFS,
 * and BFS maintaining an explicit stack and a queue.
 *
 * by Dmitry Soshnikov <dmitry.soshnikov@gmail.com>
 * MIT Style license
 */

marcin-chwedczuk

#!/usr/bin/env node

const NKEYS = 4;

function arrayOfSize(size) {
    var a = Array(size);

    for (var i = 0; i < size; i += 1)
        a[i] = null;

veltman

Smooth transitioning US tour in the same vein as this example. Steps:

1. Compares both shapes and adds evenly-spaced points to whichever polygon has fewer so that both have the same number of points
2. Picks the winding of the first polygon that minimizes the sum of the squared distances between point pairs

Some possible improvements:

• Adding additional points to both shapes first such that every segment longer than a certain distance is bisected
• Tweaking the placement of added points with simulated annealing
• Using a cost function that factors in self-intersections at the halfway mark in addition to distance traveled

armollica