| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <meta charset="utf-8"> | |
| <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1"> | |
| <title>Normal Plot</title> | |
| <meta name="description" content=""> | |
| <script src="http://d3js.org/d3.v3.min.js" charset="utf-8"></script> | |
| <style type="text/css"> | |
| body { | |
| font: 10px sans-serif; | |
| } | |
| .axis path, | |
| .axis line { | |
| fill: none; | |
| stroke: #000; | |
| shape-rendering: crispEdges; | |
| } | |
| /*.x.axis path { | |
| display: none; | |
| }*/ | |
| .line { | |
| fill: none; | |
| stroke: steelblue; | |
| stroke-width: 1.5px; | |
| } | |
| </style> | |
| </head> | |
| <body> | |
| </body> | |
| <script type="text/javascript"> | |
| //setting up empty data array | |
| var data = []; | |
| getData(); // popuate data | |
| // line chart based on http://bl.ocks.org/mbostock/3883245 | |
| var margin = { | |
| top: 20, | |
| right: 20, | |
| bottom: 30, | |
| left: 50 | |
| }, | |
| width = 960 - margin.left - margin.right, | |
| height = 500 - margin.top - margin.bottom; | |
| var x = d3.scale.linear() | |
| .range([0, width]); | |
| var y = d3.scale.linear() | |
| .range([height, 0]); | |
| var xAxis = d3.svg.axis() | |
| .scale(x) | |
| .orient("bottom"); | |
| var yAxis = d3.svg.axis() | |
| .scale(y) | |
| .orient("left"); | |
| var line = d3.svg.line() | |
| .x(function(d) { | |
| return x(d.q); | |
| }) | |
| .y(function(d) { | |
| return y(d.p); | |
| }); | |
| var svg = d3.select("body").append("svg") | |
| .attr("width", width + margin.left + margin.right) | |
| .attr("height", height + margin.top + margin.bottom) | |
| .append("g") | |
| .attr("transform", "translate(" + margin.left + "," + margin.top + ")"); | |
| x.domain(d3.extent(data, function(d) { | |
| return d.q; | |
| })); | |
| y.domain(d3.extent(data, function(d) { | |
| return d.p; | |
| })); | |
| svg.append("g") | |
| .attr("class", "x axis") | |
| .attr("transform", "translate(0," + height + ")") | |
| .call(xAxis); | |
| svg.append("g") | |
| .attr("class", "y axis") | |
| .call(yAxis); | |
| svg.append("path") | |
| .datum(data) | |
| .attr("class", "line") | |
| .attr("d", line); | |
| function getData() { | |
| // loop to populate data array with | |
| // probabily - quantile pairs | |
| for (var i = 0; i < 100000; i++) { | |
| q = normal() // calc random draw from normal dist | |
| p = gaussian(q) // calc prob of rand draw | |
| el = { | |
| "q": q, | |
| "p": p | |
| } | |
| data.push(el) | |
| }; | |
| // need to sort for plotting | |
| //https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/sort | |
| data.sort(function(x, y) { | |
| return x.q - y.q; | |
| }); | |
| } | |
| // from http://bl.ocks.org/mbostock/4349187 | |
| // Sample from a normal distribution with mean 0, stddev 1. | |
| function normal() { | |
| var x = 0, | |
| y = 0, | |
| rds, c; | |
| do { | |
| x = Math.random() * 2 - 1; | |
| y = Math.random() * 2 - 1; | |
| rds = x * x + y * y; | |
| } while (rds == 0 || rds > 1); | |
| c = Math.sqrt(-2 * Math.log(rds) / rds); // Box-Muller transform | |
| return x * c; // throw away extra sample y * c | |
| } | |
| //taken from Jason Davies science library | |
| // https://github.com/jasondavies/science.js/ | |
| function gaussian(x) { | |
| var gaussianConstant = 1 / Math.sqrt(2 * Math.PI), | |
| mean = 0, | |
| sigma = 1; | |
| x = (x - mean) / sigma; | |
| return gaussianConstant * Math.exp(-.5 * x * x) / sigma; | |
| }; | |
| </script> | |
| </html> |
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