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Some work graphing a few probability distributions using d3.js
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var probability = { | |
normal: function(x, mean, stddev) { | |
var y = (1 / (stddev * Math.sqrt(2 * Math.PI))) * Math.pow(Math.E, - (Math.pow(x - mean, 2) / (2 * Math.pow(stddev, 2)))); | |
//console.log('normal', x, mean, stddev, y); | |
return y; | |
}, | |
logNormal: function(x, mean, stddev) { | |
var y = (1 / (x * Math.sqrt(2 * Math.PI * Math.pow(stddev, 2)))) * Math.pow(Math.E, - (Math.pow(Math.log(x) - mean, 2) / (2 * Math.pow(stddev, 2)))); | |
//console.log('logNormal', x, mean, stddev, y); | |
y = isFinite(y) ? y : 0; | |
return y; | |
}, | |
erlang: function(x, kappa, lambda) { | |
var y = (Math.pow(lambda, kappa) * Math.pow(x, kappa - 1) * Math.pow(Math.E, - lambda * x)) / probability.factorial(kappa - 1); | |
//console.log('erlang', x, kappa, lambda, y); | |
return y; | |
}, | |
erlangScale: function(x, kappa, scale) { | |
var y = (Math.pow(x, kappa - 1) * Math.pow(Math.E, - x / scale)) / (Math.pow(scale, kappa) * probability.factorial(kappa - 1)); | |
//console.log('erlang scale', x, kappa, scale, y); | |
return y; | |
}, | |
factorial: function(n) { | |
var rval=1; | |
for (var i = 2; i <= n; i++) | |
rval = rval * i; | |
return rval; | |
} | |
}; | |
/////////////////////////// | |
var graph = function(selector) { | |
var margin = {top:20, bottom:30, left:20, right:30}; | |
var setWidth = 100; | |
var setHeight = 100; | |
var width = setWidth - margin.left - margin.right; | |
var height = setHeight - margin.top - margin.bottom; | |
var domain = [0, 1]; | |
var step = 1; | |
var max, min; | |
var paths = []; | |
var graph = d3.select(selector) | |
.append("svg:svg") | |
.attr("width", setWidth) | |
.attr("height", setHeight); | |
var g = graph.append("svg:g").attr("transform", "translate(0,0)"); | |
var x = d3.scale.linear().domain([0, 1]).range([margin.left, width]); | |
var y = d3.scale.linear().domain([0, 1]).range([height, margin.top]); | |
var line = d3.svg.line() | |
.x(function(d,i) {return x(d.x);}) | |
.y(function(d) {return y(d.y);}) | |
.interpolate('basis'); | |
var xAxis = d3.svg.axis().scale(x).tickSize(-height).tickSubdivide(true); | |
var yAxis = d3.svg.axis().scale(y).ticks(4).orient("right"); | |
var chart = function() {} | |
graph.append("svg:g") | |
.attr("class", "x axis") | |
.attr("transform", "translate(0," + height + ")") | |
.call(xAxis); | |
graph.append("svg:g") | |
.attr("class", "y axis") | |
.attr("transform", "translate(" + width + ",0)") | |
.call(yAxis); | |
chart.render = function() { | |
graph.select(".x.axis") | |
.attr("transform", "translate(0," + height + ")") | |
.call(xAxis); | |
graph.select(".y.axis") | |
.attr("transform", "translate(" + width + ",0)") | |
.call(yAxis); | |
paths.forEach(function(p) { | |
p.path.attr("d", line(p.data)); | |
}); | |
}; | |
chart.width = function(_) { | |
if (!arguments.length) return setWidth; | |
setWidth = _; | |
width = setWidth - margin.left - margin.right; | |
graph.attr("width", setWidth); | |
x.range([margin.left, width]); | |
chart.render(); | |
return chart; | |
}; | |
chart.height = function(_) { | |
if (!arguments.length) return setHeight; | |
setHeight = _; | |
height = setHeight - margin.top - margin.bottom; | |
graph.attr("height", setHeight); | |
y.range([height, margin.top]); | |
chart.render(); | |
return chart; | |
}; | |
chart.x = function(_) { | |
if (!arguments.length) return x; | |
x = _; | |
xAxis.scale(x); | |
return chart; | |
}; | |
chart.y = function(_) { | |
if (!arguments.length) return y; | |
y = _; | |
yAxis.scale(y); | |
return chart; | |
}; | |
chart.domain = function(_) { | |
if (!arguments.length) return domain; | |
domain = _; | |
x.domain(domain); | |
return chart; | |
}; | |
chart.step = function(_) { | |
if (!arguments.length) return step; | |
step = _; | |
return chart; | |
}; | |
chart.line = function() { | |
if (!arguments.length) return; | |
args = Array.prototype.slice.call(arguments, 0); | |
color = args.pop(); | |
fn = args.shift(); | |
data = []; | |
domain = x.domain() | |
for (var i = domain[0]; i <= domain[1]; i += step) { | |
args.unshift(i); | |
data.push({x: i, y: fn.apply(fn, args)}); | |
args.shift(); | |
} | |
var yVals = data.map(function(d) {return d.y;}); | |
if (max !== null) yVals.push(max); | |
if (min !== null) yVals.push(min); | |
max = Math.ceil(d3.max(yVals)); | |
min = Math.floor(d3.min(yVals)); | |
y.domain([min, max]); | |
chart.render(); | |
var path = g.append("svg:path") | |
.attr("class", "line " + fn.name) | |
.attr("d", line(data)) | |
.attr('style', "stroke:" + color); | |
paths.push({path: path, data: data}); | |
return chart; | |
}; | |
return chart; | |
}; | |
var width = 300; | |
var height = 200; | |
// http://en.wikipedia.org/wiki/Normal_distribution | |
graph('#normal').width(width).height(height) | |
.domain([-5, 5]) | |
.step(0.2) | |
.line(probability.normal, 0, 0.2, "blue") | |
.line(probability.normal, 0, 1, "red") | |
.line(probability.normal, 0, 5, "orange") | |
.line(probability.normal, -2, 0.5, "green"); | |
// http://en.wikipedia.org/wiki/Log-normal_distribution | |
graph('#logNormal').width(width).height(height) | |
.domain([0,3]) | |
.step(0.2) | |
.line(probability.logNormal, 0, 1, "blue") | |
.line(probability.logNormal, 0, 0.25, "red") | |
.line(probability.logNormal, 0, 0.5, "green"); | |
// http://en.wikipedia.org/wiki/Erlang_distribution | |
graph('#erlang').width(width).height(height) | |
.domain([0,20]) | |
.step(0.5) | |
.line(probability.erlangScale, 1, 2.0, "red") | |
.line(probability.erlangScale, 2, 2.0, "green") | |
.line(probability.erlangScale, 3, 2.0, "blue") | |
.line(probability.erlangScale, 5, 1.0, "cyan") | |
.line(probability.erlangScale, 9, 0.5, "orange"); |
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