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Cumulative Histogram with CDF line
<!DOCTYPE html> <meta charset="utf-8"> <style> svg { font: 10px sans-serif; } .bar rect { fill: steelblue; shape-rendering: crispEdges; } .axis path, .axis line { fill: none; stroke: #000; shape-rendering: crispEdges; } .line { fill: none; stroke: purple; stroke-width: 1.5px; } </style> <body> <script src="//d3js.org/d3.v3.min.js"></script> <script src="//cdn.jsdelivr.net/jstat/1.5.2/jstat.min.js"></script> <script> //Set dimensions var m = {top: 50, right: 50, bottom: 50, left: 50} , h = 500 - m.top - m.bottom , w = 960 - m.left - m.right , numBins = 10; //Using a fixed data set for demo, rather than random generated values //TODO - update fixed data set later with a larger dataset for demo/testing (and // feed in via d3.csv() or d3.json() ) var dataset = [2.4059769174850905, 2.7600000000000002, 3.8217080187144488, 2.3899284588203313, 3.7264403738739054, 7.63, 3.16, 3.1600000000000006, 3.160000000000001, 2.06, 1.9728802107932477, 1.7180599494369857, 1.747203022782844, 2.39, 2.06, 2.06]; var xScale = d3.scale.linear().domain([0, 10]).range([0, w]); var data = d3.layout.histogram().bins(xScale.ticks(numBins))(dataset); /* now update histogram bins to be cumulative to make cumulative histogram * * FYI: a cumulative histogram is a mapping that counts the cumulative number of * observations in all of the bins up to the specified bin. * * The cumulative bin frequency pattern should roughly match the CDF line? * Can compare with Python's Matplotlib cumulative histogram e.g. * import matplotlib.pyplot as plt * plt.hist(dataset, bins=(0,1,2,3,4,5,6,7,8,9), normed=True, cumulative=True) * plt.title("Cumulative Histogram") * plt.xlabel("Distance") * plt.ylabel("Probability") * plt.savefig("Cumulative Histogram.png", bbox_inches='tight') */ for(var i = 1; i < data.length; i++){ data[i].y += data[i-1].y; } /* Calculative CDF using jStat - https://github.com/jstat/jstat * We are replicating cumulative distribution/frequency line option that is * available in Excel histograms * * Can validate CDF by calculating each percentile tick/unit (0.1-0.9 or 10-90th * percentiles) against the dataset then comparing the resulting value against * the matching value on the histogram. It should roughly match up if we are * expecting Excel-like output. We can test this assertion by (1) loading same * dataset used with Excel to here using d3.csv() and comparing histograms * between the two, or (2) manually enter this sample dataset here into Excel to * plot a histogram with CDF line then compare the two histograms. */ var jstat = this.jStat(dataset); for(var i=0; i < data.length; i++){ data[i]['cum'] = jstat.normal(jstat.mean(), jstat.stdev()).cdf(data[i].x); } //Axes and scales var yhist = d3.scale.linear() .domain([0, d3.max(data, function(d) { return d.y; })]) .range([h, 0]); var ycum = d3.scale.linear().domain([0, 1]).range([h, 0]); var xAxis = d3.svg.axis() .scale(xScale) .orient('bottom'); var yAxis = d3.svg.axis() .scale(yhist) .orient('left'); var yAxis2 = d3.svg.axis() .scale(ycum) .orient('right'); //Draw svg var svg = d3.select("body").append("svg") .attr("width", w + m.left + m.right) .attr("height", h + m.top + m.bottom) .append("g") .attr("transform", "translate(" + m.left + "," + m.top + ")"); //Draw histogram var bar = svg.selectAll(".bar") .data(data) .enter().append("g") .attr("class", "bar") .attr("transform", function(d) { return "translate(" + xScale(d.x) + "," + yhist(d.y) + ")"; }); bar.append("rect") .attr("x", 1) .attr("width", w/numBins/1.3) .attr("height", function(d) { return h - yhist(d.y); }); //Draw CDF line var guide = d3.svg.line() .x(function(d){ return xScale(d.x) }) .y(function(d){ return ycum(d.cum) }) .interpolate('basis'); var line = svg.append('path') .datum(data) .attr('d', guide) .attr('class', 'line'); //Draw axes svg.append("g") .attr("class", "x axis") .attr("transform", "translate(0," + h + ")") .call(xAxis); svg.append("g") .attr("class", "y axis") .call(yAxis) .append("text") .attr("transform", "rotate(-90)") .attr("y", 6) .attr("dy", ".71em") .style("text-anchor", "end") .text("Count (Histogram)"); svg.append("g") .attr("class", "y axis") .attr("transform", "translate(" + [w, 0] + ")") .call(yAxis2) .append("text") .attr("transform", "rotate(-90)") .attr("y", 4) .attr("dy", "-.71em") .style("text-anchor", "end") .text("CDF"); </script> </body>
https://d3js.org/d3.v3.min.js
https://cdn.jsdelivr.net/jstat/1.5.2/jstat.min.js