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def euclidean_distance(p, q):
    """ Calculate distance between 2 points in n-dimensional space

        >>> euclidean_distance((3, 0), (0, 4))
        5.0
    """
    n = len(p) # dimensions
    return sum([(p[i] - q[i]) ** 2 for i in xrange(n)]) ** 0.5

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/**
 * @param {list} data List of integers sorted ascending
 * @param {int} find Integer to search for
 * @param {int} start Min array index
 * @param {int} end Max array index
 * @return {int} Index of 'find' or -1 if not found
*/
var binarySearch = function (data, find, start, end) {

    var mid = start + (end - start) / 2;

martinogden

/**
 * Create a google map and populate it with markers and infoboxes
 *
 * @requires underscore.js @link http://documentcloud.github.com/underscore/
 * @param options {object} Override default settings
 * @return {object} this
 */
var MapPopulator = function (options) {

    var defaults = {

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// Requires jQuery Rotate Plugin - http://wilq32.googlepages.com/wilq32.rollimage222
$(function()
{
		var angle;
		function begin_rotation(override_angle)
		{
			// Generate random number between 15 and 35 for rotation distance
			amount = Math.floor(Math.random()*36);
			while(amount < 15)
			{