Culled from the Mists of Time by David Salzman John von Neumann National Supercomputer Center
AG Add Gibberish
AGO Allow Games Only
AII Add Insult to Injury
APX Apply Power and eXplode
body { | |
text-align: center; | |
} | |
.yay { | |
font-size: 70px; | |
} |
View this code at http://livecoding.io/7467367
View this code at http://livecoding.io/7469740
module.exports = | |
collections: | |
countries: -> | |
@getCollection('html') | |
.getFilesAtPath('countries') | |
.on 'add', (model) -> | |
console.log(model) | |
model.set 'layout', 'country' |
In probability theory, the central limit theorem (CLT) states that, given certain conditions, the arithmetic mean of a sufficiently large number of iterates of independent random variables, each with a well-defined expected value and well-defined variance, will be approximately normally distributed.[1] That is, suppose that a sample is obtained containing a large number of observations, each observation being randomly generated in a way that does not depend on the values of the other observations, and that the arithmetic average of the observed values is computed. If this procedure is performed many times, the central limit theorem says that the computed values of the average will be distributed according to the normal distribution (commonly known as a "bell curve").
var $now = Date.now(); | |
var pi = Math.PI; | |
function sinc(x) => (x==0)?1:Math.sin(pi*x)/(pi*x); | |
proc source(start, end, step) { | |
var N = (end - start) / step, HZ = 1 / step; | |
emitter -hz HZ -limit N -start (start*1000) -reset 1 } | |
source(-5,5,0.1) | put x=time/1000, y=(sinc(3*x)+1)*10 | |
-> timechart -duration 10 -columns y |
var data = [ | |
[ | |
{ | |
time: new Date(2000, 1, 1), | |
value: 10 | |
}, | |
{ | |
time: new Date(2000, 1, 2), | |
value: 20 | |
}, |