Sample Distribution (Histogram/Kernel/CDF)

README.md

This sample distribution exploratory tool uses a combination of Histogram, Rug, Kernel Density and CDF plots to represent the statistical spread of input data.

Options are exposed to manipulate the width of the histogram bins and the type of value scale to use (linear vs log base 2). Enabling the CDF representation adds a secondary Y axis with the cumulative values.

Zoom on the X axis by click-dragging on the graph.

density.js

function sampleDistributionGraph($elem, data) {

	var HISTOGRAMQ = 1; // Default Q
	var DENSQ = HISTOGRAMQ/8; // Smoothing of the density function, in value units
	var DENSNORM = 0.8; // Normalizing value of the densityfunction (0-1)
	var CDFQ = HISTOGRAMQ/8;
	var MAXSAMPLEAREAPOINTS = 2000; // Max svg lines to display in the sample area (to avoid browser freeze)

	var LOGSCALEBASE = 2;
	var SHOWCDF = false; // Default value - show cdf function at startup
	var SHOWDENSITY = true; // Default value - show density function at startup

	var INITZOOMPERCENTILE = 0.98; // Which value percentile area should the initial zoom be set to

	var SVG_W = $elem.width();
	var SVG_H = Math.min(Math.round(SVG_W*0.8), window.innerHeight*0.85);
	var AXIS_MARGIN = Math.min(55, Math.round(SVG_W*0.07));
	var SAMPLE_AREA_H = Math.round(SVG_H*0.03);

	var GRAPH_W = SVG_W - AXIS_MARGIN*2;
	var GRAPH_H = SVG_H - AXIS_MARGIN*2 - SAMPLE_AREA_H;

	var TRANSITION_DUR = 750; // ms

	function getDensityDistribution(data, q, xScale, normVal, maxPoints) {

		function kernelDensityEstimator(kernel, x) {
			return function(sample) {
				return x.map(function(x) {
					return [x, d3.mean(sample, function(v) { return kernel(x - v); })];
				});
			};
		}

		function epanechnikovKernel(scale) {
			return function(u) {
				return Math.abs(u /= scale) <= 1 ? .75 * (1 - u * u) / scale : 0;
			};
		}

		var valDomain=xScale.domain()[1] - xScale.domain()[0];

		var nrPoints = Math.min(Math.round(valDomain/q*4), maxPoints);
		var points = xScale.ticks(nrPoints);

		var densityData = kernelDensityEstimator(epanechnikovKernel(q), points)(data);

		// Normalise
		var scaleFactor = normVal/d3.max(densityData, function(d) { return d[1] });

		for (var i=0,len=densityData.length;i<len;i++)
			densityData[i][1]*=scaleFactor;

		// Add termination points
		densityData.splice(0,0,[0,0]);
		densityData.push([xScale.domain()[1],0]);

		return densityData;
	}

	function getCdf(data, q, xScale, logScaleBase, maxPoints) {

		var maxQ = Math.max(q, (xScale.domain()[1]-xScale.domain()[0])/maxPoints);

		var binnedData = getHistogram(data, maxQ, logScaleBase);

		if (binnedData.length==0)
			return [];

		var xOffset = binnedData[0].dx/2;

		var cdfData=[];
		var aggr=0;
		for (var i=0, len=binnedData.length; i<len; i++) {
			aggr+=binnedData[i].y;
			cdfData.push([binnedData[i].x+xOffset, aggr]);
		}

		// Add termination points
		cdfData.splice(0,0,[xScale.domain()[0],0]);
		cdfData.push([xScale.domain()[1],1]);

		return cdfData;
	}

	function getHistogram(data, q, logScaleBase) {

		var dataRange=[0, d3.max(data)];

		logScaleBase = (logScaleBase==null?1:logScaleBase);

		var base=1/logScaleBase;
		var expQ=Math.pow(q*Math.pow(base,4) , base);  // Incremental Q

		var points = [];
		for (var p = Math.pow(dataRange[0], base),len=Math.pow(dataRange[1], base); p<len; p+=expQ)
			points.push(d3.round(Math.pow(p,1/base), 2));

		points.push(d3.round(dataRange[1], 2));

		var histogram = d3.layout.histogram()
			.frequency(false)
			.bins(points);

		return histogram(data);
	}


	function downSampleData (data, xScale, nrPoints) {
		nrPoints = (nrPoints==null?40:nrPoints);
		var points = xScale.ticks(nrPoints);
		var resData=[];
		var pointIdx=0;
		for (var i=0, len=data.length;i<len;i++) {
			if (data[i][0]>=points[pointIdx]) {
				resData.push(data[i]);
				pointIdx++;
				if (pointIdx==points.length)
					break;
			}
		}
		return resData;
	}


	function getXScale(xVals, logScaleBase) {
		var maxX = d3.max(xVals);

		return (logScaleBase==1?d3.scale.linear():d3.scale.pow().exponent(1/logScaleBase))
			.domain([0, maxX])
			.range([0, GRAPH_W])
			.clamp(true);
	}

	function getYScale(dataH, xDomain) {
		var maxY=0;
		for (var i=0, len=dataH.length; i<len; i++) {
			if (xDomain!=null) {
				if(dataH[i].x+dataH[i].dx < xDomain[0])
					continue;
				if (dataH[i].x > xDomain[1])
					break;
			}
			if(dataH[i].y>maxY)
				maxY=dataH[i].y;
		}

		maxY=(maxY==0?1:maxY);

		return d3.scale.linear()
			.domain([0, maxY*1.05])
			.range([GRAPH_H, 0])
			.clamp(true);
	}

	function getY2Scale() {
		return d3.scale.linear()
			.domain([0, 1])
			.range([GRAPH_H, 0]);
	}

	function setInitZoomLevel() {

		var zoom = 0;
		for (var i=0, len=cdfData.length; i<len; i++) {
			zoom = cdfData[i][0];
			if (cdfData[i][1]>INITZOOMPERCENTILE) {
				break;
			}
		}

		xScale.domain([0, zoom]);
	}

	function initStatic(svg) {

		var linScale = getXScale(data, 1);

		densityData = getDensityDistribution(data, DENSQ, linScale, DENSNORM, GRAPH_W*2);

		cdfData = getCdf(data, CDFQ, linScale, 1, GRAPH_W*2);

		xScale = getXScale(data, logScaleBase);
		yScale = getYScale([]);
		y2Scale = getY2Scale();

		setInitZoomLevel();


		/**************/

		var container = svg.append('g');

		/* Grid */
		var grid = container.append('g');

		grid.append("g")
			.attr("class", "x-grid")
			.attr("transform", "translate(0," + (GRAPH_H + SAMPLE_AREA_H) + ")");

		grid.append("g").attr("class", "y-grid");

		grid.style({
			"shape-rendering": "crispEdges",
			"fill": "none",
			"stroke": "lightgrey",
			"stroke-opacity": 0.6
		});

		/* Sample Area */
		container.append('rect')
			.attr("width", GRAPH_W)
			.attr("height", SAMPLE_AREA_H)
			.attr("x", 0)
			.attr("y", GRAPH_H)
			.style({
				"stroke": 'black',
				"stroke-width": 0.5,
				"stroke-opacity": 0.7,
				"fill": 'lightgrey'
			});

		/* Axises */
		var axises = container.append('g')
			.attr("class", "axises");

		axises.append("g")
			.attr("class", "x-axis")
			.attr("transform", "translate(0," + (GRAPH_H + SAMPLE_AREA_H) + ")");

		var yAxis = axises.append("g")
			.attr("class", "y-axis");

		// y2 axis is static
		var y2Axis = axises.append("g")
			.attr("class", "y2-axis")
			.attr("transform", "translate(" + GRAPH_W + ", 0)")
			.call(
				d3.svg.axis()
					.scale(y2Scale)
					.orient("right")
					.tickFormat( function(d) { return d3.round(d*100,2) + "%" } )
			)
			.style('opacity', (showCdf?1:0));

		axises.style({
			"shape-rendering": "crispEdges",
			"font": AXIS_MARGIN*.25 + 'px sans-serif'
		});

		axises.selectAll('path, line')
			.style({
				"stroke": "black",
				"fill": "none"
		});

		/* Labels */
		container.append("text")
			.attr("x", GRAPH_W)
			.attr("y", GRAPH_H + SAMPLE_AREA_H)
			.style("text-anchor", "end")
			.attr('dy','2.5em')
			.style({
				"font": "italic "+ AXIS_MARGIN*.28 + 'px sans-serif',
				"fill": '#777'
			})
			.text(data.length + " Samples");

		yAxis.append("text")
			.attr("transform", "rotate(-90)")
			.attr("y", 8)
			.attr('dy','.8em')
			.style("text-anchor", "end")
			.text("Relative (%)");

		y2Axis.append("text")
			.attr("transform", "rotate(-90)")
			.attr("y", -12)
			.style("text-anchor", "end")
			.text("Cumulative (%)");

		y2Axis.selectAll('text')
			.style("fill", "green");

		/*
		// Tooltip
		container.append("div")
			.attr("class", "graphTooltip")
			.style({
				position: 'absolute',
				'text-align': 'left',
				width: '100px',
				height: '40px',
				padding: '5px',
				font: '12px sans-serif',
				background: 'lightsteelblue',
				border: '0px',
				'border-radius': '8px',
				'pointer-events': 'none',
				opacity: 0
			});
		*/

		// Traction for the zoom function
		container.append('rect')
			.attr('x', 0)
			.attr('y', 0)
			.attr('width', GRAPH_W)
			.attr('height', GRAPH_H)
			.style({
				opacity: 0,
				cursor: 'crosshair'
			});

		svg.on("mousedown", function() {
				var e = this;

				if (d3.mouse(e)[0]<0 || d3.mouse(e)[0]>GRAPH_W || d3.mouse(e)[1]<0 || d3.mouse(e)[1]>GRAPH_H)
					return;

				var rect = svg.append("rect")
					.style({
						stroke: 'blue',
						'stroke-opacity': .6,
						fill: 'blue',
						'fill-opacity': .3
					});

				var startX = d3.mouse(e)[0];

				d3.select("body").classed("stat-noselect", true);

				d3.select(window)
					.on("mousemove.zoomRect", function() {
						d3.event.stopPropagation();
						var newX = Math.max(0, Math.min(GRAPH_W, d3.mouse(e)[0]));
						rect.attr("x", Math.min(startX, newX))
							.attr("y", 0)
							.attr("width", Math.abs(startX - newX))
							.attr("height", GRAPH_H);
						})
					.on("mouseup.zoomRect", function() {
						d3.select(window).on("mousemove.zoomRect", null).on("mouseup.zoomRect", null);
						d3.select("body").classed("stat-noselect", false);
						rect.remove();

						var endX = Math.max(0, Math.min(GRAPH_W, d3.mouse(e)[0]));
						var newDomain = [startX, endX].map(xScale.invert).sort(d3.ascending);
						if ((endX !== startX) && (newDomain[1]-newDomain[0]>0.001)) {  // Zoom damper
							xScale.domain(newDomain);
							redrawX();
						}
					}, true);

				d3.event.stopPropagation();
			})
			.append('title').text('click-drag to zoom in');

		container.append('text')
			.attr("x", GRAPH_W*.99)
			.attr("y", -GRAPH_H*.03)
			.style("text-anchor", "end")
			.style({
				font: "italic " + AXIS_MARGIN*.26 + 'px sans-serif',
				fill: "blue",
				opacity: .65,
				cursor: 'pointer'
			})
			.text("Reset Zoom")
			.on("mouseup" , function() {
				xScale.domain([0,maxBwidth]);
				redrawX();
			})
			.on("mouseover", function(){
				d3.select(this).style('opacity', 1);
			})
			.on("mouseout", function() {
				d3.select(this).style('opacity', .6);
			});

		renderContainer(svg, xScale, yScale, y2Scale);

	}

	function renderContainer(svg, xScale, yScale) {

		var xAxis = d3.svg.axis()
			.scale(xScale)
			.orient("bottom");
			//.ticks(10, 2);

		var xGrid = d3.svg.axis()
			.scale(xScale)
			.orient("top")
			.tickFormat("")
			.tickSize(GRAPH_H + SAMPLE_AREA_H, 0, 0);
			//.ticks(10, 1);

		var yAxis = d3.svg.axis()
			.scale(yScale)
			.orient("left")
			.tickFormat( function(d) { return d3.round(d*100,3) + "%" } );
			//.ticks(10, 2);

		var yGrid = d3.svg.axis()
			.scale(yScale)
			.orient("right")
			.tickFormat("")
			.tickSize(GRAPH_W, 0, 0);
			//.ticks(10, 1);

		svg.select('.x-grid')
			.transition().duration(TRANSITION_DUR)
			.call(xGrid);

		svg.select('.y-grid')
			.transition().duration(TRANSITION_DUR)
			.call(yGrid);

		svg.select('.x-axis')
			.transition().duration(TRANSITION_DUR)
			.call(xAxis);

		svg.select('.y-axis')
			.transition().duration(TRANSITION_DUR)
			.call(yAxis);

		var axises = svg.select('.axises');

		axises.selectAll('path, line')
			.style({
				"stroke": "black",
				"fill": "none"
			});

		axises.select('.y-axis').selectAll('text')
			.style("fill", "brown");
	}

	function renderSampleArea(svg, data, xScale) {

		// If there's many points, plot only a sub-sample, to avoid browser freeze
		var step = Math.ceil(data.length/MAXSAMPLEAREAPOINTS);

		var downSampleFilter = function(d, i) {
			return (i%step==0);
		};

		var scaleFilter = function(d) {
			return (d >= xScale.domain()[0] && d<=xScale.domain()[1]);
		};

		// So they don't overlap with existing vals
		var mean = meanVal + 0.00001;
		var median = medianVal + 0.00002;

		var feedData = data.filter(downSampleFilter).concat(mean, median).filter(scaleFilter);

		var samples = svg.selectAll(".bw-sample")
			.data(feedData, function(d) { return d; });

		samples.exit()
			.transition()
				.style({
					"fill-opacity": 0,
					"stroke-opacity": 0
				})
				.remove();

		var sampleOpacity = Math.min(.3, 0.05*MAXSAMPLEAREAPOINTS/Math.min(feedData.length, MAXSAMPLEAREAPOINTS));

		samples.transition().duration(TRANSITION_DUR)
			.attr("x1", function(d) { return xScale(d); })
			.attr("x2", function(d) { return xScale(d); })
			.style("stroke-opacity", function (d, i) { return (i<feedData.length-2 || (d!=mean && d!=median))?sampleOpacity:0.9; });

		var newSamples = samples.enter().append("line")
			.attr("class", "bw-sample")
			.attr("y1", GRAPH_H)
			.attr("y2", GRAPH_H + SAMPLE_AREA_H)
			.attr("x1", function(d) { return xScale(d); })
			.attr("x2", function(d) { return xScale(d); })
			.style({
				"stroke": "blue",
				"stroke-width": 1,
				"stroke-opacity": 0,
				"shape-rendering": "crispEdges"
			});

		newSamples.transition().duration(TRANSITION_DUR/2)
			.style("stroke-opacity", function (d,i) { return (i<feedData.length-2 || (d!=mean && d!=median))?sampleOpacity:0.9; });

		newSamples.filter(function(d,i) { return (i>=feedData.length-2 && (d==mean || d==median)); })
			.style({
				stroke: function (d) { return d==mean?'brown':'darkorange'; },
				'stroke-width': 2,
				cursor: 'help'
			})
			.append('title').text(function(d) { return (d==mean?('Average Value: ' + d3.round(d,3)):('Median Value: ' + d3.round(d,3))) });
	}

	function renderHistogram(svg, data, xScale, yScale) {

		var dataFilter = function(d) {
			return (d.x >= xScale.domain()[0] && (d.x+d.dx)<=xScale.domain()[1]);
		};

		var bars = svg.selectAll(".histo-bar")
			.data(data);

		bars.exit()
			.transition()
				.style({
					"fill-opacity": 0,
					"stroke-opacity": 0
				})
				.remove();

	   bars.transition().duration(TRANSITION_DUR)
		  .attr("x", function(d) { return xScale(d.x); })
		  .attr("y", function(d) { return yScale(d.y); })
		  .attr("width", function(d) { return xScale(d.x + d.dx) - xScale(d.x); })
		  .attr("height", function(d) { return GRAPH_H - yScale(d.y); });

		var newBars = bars.enter()
		  .append("rect")
		  .attr("class", "histo-bar");

		newBars
			.attr("rx", 1)
			.attr("ry", 1)
			.style({
				"fill": "lightgrey",
				"fill-opacity": .3,
				"stroke": "brown",
				"stroke-opacity": .4,
				"shape-rendering": "crispEdges",
				"cursor": "crosshair"
			})
			.attr("x", function(d) { return xScale(d.x); })
			.attr("width", function(d) { return xScale(d.x + d.dx) - xScale(d.x); })
			.attr("y", GRAPH_H)
			.attr("height", 0)
			.transition().duration(TRANSITION_DUR)
				.attr("y", function(d) { return yScale(d.y); })
				.attr("height", function(d) { return GRAPH_H - yScale(d.y); });


		newBars
			.on("mouseover", function() {
				d3.select(this)
					//.transition().duration(70)
					.style({
						"stroke-opacity": .9,
						"fill-opacity": .7
					});
			})
			.on("mouseout", function() {
				d3.select(this)
					//.transition().duration(250)
					.style({
						"stroke-opacity": .4,
						"fill-opacity": .3
					});
			});

		newBars.append('title');

		bars.select('title')
			.text(function(d) {
				return d.x + '-' + (d.x+d.dx) + " bin: " + d3.round(d.y*100,2) + "% (" + d.length + " samples)";
			});
	}

	function renderDensity(svg, data, xScale, yScale) {

		var dataFilter = function(d) {
			return (d[0] >= xScale.domain()[0] && d[0]<=xScale.domain()[1]);
		};

		var thisData = showDensity?data.slice(0):[];

		// Add termination points
		thisData.splice(0,0,[xScale.domain()[0],0]);
		thisData.push([xScale.domain()[1],0]);

		var line = d3.svg.line()
			.x(function(d) { return xScale(d[0]); })
			.y(function(d) { return yScale(d[1]); })
			.interpolate("basis");

		var lines = svg.selectAll('.density-line')
			.data([thisData]);

		lines.enter()
			.append("path")
			.attr("class", "density-line")
			.style({
				"fill": "blue",
				"fill-opacity": .13,
				"stroke": "none"
			});

		lines
		  //.datum(function(d) { return d; })
		  .transition().duration(TRANSITION_DUR)
			  .attr("d", line);
	}

	function renderCdf(svg, data, xScale, yScale) {

		var dataFilter = function(d) {
			return (d[0] >= xScale.domain()[0] && d[0]<=xScale.domain()[1]);
		};

		// CDF line
		var line = d3.svg.line()
			.x(function(d) { return xScale(d[0]); })
			.y(function(d) { return yScale(d[1]); })
			.interpolate("basis");

		var lines = svg.selectAll('.cdf-line')
			.data([(showCdf?data:[])]);

		lines.enter()
			.append("path")
			.attr("class", "cdf-line")
			.style({
				"fill": "none",
				"stroke": "green",
				"stroke-opacity": .4,
				"stroke-width": "2px"
			})
			.on("mouseover", function() {
				var coords= d3.mouse(this);
				var x = xScale.invert(coords[0]);
				var y = yScale.invert(coords[1]);

				d3.select(this).select('title')
					.text('<' + d3.round(x,2) + ': ' + d3.round(y*100, 2) + '%');

				d3.select(this)
					.transition()
					.style({
						"stroke-width": "3px",
						"stroke-opacity": .9
					})
			})
			.on("mouseout", function() {
				svg.select('.cdf-line')
					.transition()
					.style({
						"stroke-width": "2px",
						"stroke-opacity": .4
					})
			})
			.append('title');


		lines
		  .transition().duration(TRANSITION_DUR)
			.attr("d", line);
	}

	function redraw() {

		histogramData = getHistogram(data, histQ, logScaleBase);
		yScale = getYScale(histogramData, xScale.domain());

		renderContainer(svg, xScale, yScale, y2Scale);
		renderSampleArea(svg, data, xScale);
		renderDensity(svg, densityData, xScale, y2Scale);
		renderHistogram(svg, histogramData, xScale, yScale);
		renderCdf(svg, cdfData, xScale, y2Scale);
	}

	function redrawX() {

		yScale = getYScale(histogramData, xScale.domain());

		renderContainer(svg, xScale, yScale, y2Scale);
		renderSampleArea(svg, data, xScale);
		renderDensity(svg, densityData, xScale, y2Scale);
		renderHistogram(svg, histogramData, xScale, yScale);
		renderCdf(svg, cdfData, xScale, y2Scale);
	}

	var redrawNewBin = _.throttle(function (newQ) {
		histQ = newQ;
		histogramData = getHistogram(data, histQ, logScaleBase);
		yScale = getYScale(histogramData, xScale.domain());

		renderContainer(svg, xScale, yScale, y2Scale);
		renderHistogram(svg, histogramData, xScale, yScale);
	}, 200, { leading: false });

	function addControls ($elem) {

		//// Bin control
		var binStepper = $('<input>')
			.css('width', 100);

		// Linear/log scale
		var logRadio = $('<input type="radio" name="scaleType" value="' + LOGSCALEBASE + '">');
		var linearRadio = $('<input type="radio" name="scaleType" value="1">');

		(logScaleBase==1?linearRadio:logRadio).attr('checked', 'checked');

		var logAddedMult = $('<span>')
			.html(logScaleBase==1?'':'(*' + logScaleBase + '<sup>n</sup>)');

		var scaleRadio=$('<span>').append(
				$('<label>').append(linearRadio, ' Linear').css('cursor', 'pointer'),
				$('<label>').append(logRadio, ' Log scale').css({'cursor': 'pointer', 'margin-left': 5})
		).css('margin-left', 20);

		// CDF
		var cdfCb = $('<input type="checkbox">');

		if (showCdf)
			cdfCb.attr('checked', 'checked');

		// Density
		var densCb = $('<input type="checkbox">');

		if (showDensity)
			densCb.attr('checked', 'checked');

		$('<div>').appendTo($elem).append([
			$('<span>').append(
				$('<label>').append('Bin width:').css('margin-right', 5),
				binStepper,
				$('<span>').append(logAddedMult).css('margin-left', 3)
			).css('margin-left', 7),
			scaleRadio,
			$('<label>').append(densCb, ' Show density')
				.css({'cursor': 'pointer', 'margin-left': 25}),
			$('<label>').append(cdfCb, ' Show cdf')
				.css({'cursor': 'pointer', 'margin-left': 15})
		]).css({
			'text-align': 'center',
			'margin-top': 5
		});

		binStepper.slider({
			step: 0.1,
			max: 5,
			min: 0.1,
			value: HISTOGRAMQ,
			tooltip: 'always'
		}).on('change', function(e) {
			redrawNewBin(e.value.newValue);
		});

		$.each([linearRadio, logRadio], function() {
			$(this).change( function() {
				logScaleBase=parseInt($(this).val());
				logAddedMult.html(logScaleBase==1?'':'(*' + logScaleBase + '<sup>n</sup>)');
				xScale = getXScale(data, logScaleBase);
				setInitZoomLevel();
				redraw();
			})
		});

		cdfCb.change( function() {
			showCdf=this.checked;
			renderCdf(svg, cdfData, xScale, y2Scale);
			svg.select('.y2-axis')
				.transition().duration(TRANSITION_DUR)
				.style('opacity', (showCdf?1:0));
		});

		densCb.change( function() {
			showDensity=this.checked;
			renderDensity(svg, densityData, xScale, y2Scale);
		});

	}

	var svg = d3.select($elem[0]).append("svg")
		.attr("width", SVG_W)
		.attr("height", SVG_H)
		.append('g')
			.attr("transform", "translate(" + AXIS_MARGIN + "," + AXIS_MARGIN + ")");

	var histQ=HISTOGRAMQ;
	var logScaleBase=1;  // use =LOGSCALEBASE to start as log scale
	var showCdf = SHOWCDF;
	var showDensity = SHOWDENSITY;
	//var zoomedPerc = $('<span>');

	var maxBwidth=d3.max(data);

	var xScale = null;
	var yScale = null;
	var y2Scale = null;
	var histogramData = null;
	var densityData = null;
	var cdfData = null;
	var meanVal = d3.mean(data);
	var medianVal = d3.median(data);

	addControls($elem);

	initStatic(svg);
	redraw();
}

index.html

<script src="//code.jquery.com/jquery-3.1.0.min.js"></script>
<script src="//cdnjs.cloudflare.com/ajax/libs/d3/3.5.17/d3.min.js"></script>
<script src="//cdnjs.cloudflare.com/ajax/libs/lodash.js/4.14.2/lodash.min.js"></script>
<script src="//cdnjs.cloudflare.com/ajax/libs/bootstrap-slider/9.1.3/bootstrap-slider.min.js"></script>
<script src="density.js"></script>

<link rel="stylesheet" href="//maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css">
<link rel="stylesheet" href="//cdnjs.cloudflare.com/ajax/libs/bootstrap-slider/9.1.3/css/bootstrap-slider.min.css">

<script>
    d3.json('values.json', function(vals) {
        sampleDistributionGraph($('body'), vals);
    });
</script>

thumbnail.png

values.json

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