dc
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A multi-dimensional charting library built to work natively with crossfilter and rendered using d3.js
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HTML
<html lang="en">
<head>
<title>dc.js - Scatter Plot Brushing Example</title>
<meta charset="UTF-8">
<link rel="stylesheet" type="text/css" href="../css/bootstrap.min.css">
<link rel="stylesheet" type="text/css" href="../css/dc.css"/>
</head>
<body>
<div class="container">
<script type="text/javascript" src="header.js"></script>
<p>Plotting 20,000 data points in 2 plots. Plots may take several seconds to load. Brush on one chart to see the points filtered on the other.</p>
<div id="test1"></div>
<div id="test2"></div>
<script type="text/javascript" src="../js/d3.js"></script>
<script type="text/javascript" src="../js/crossfilter.js"></script>
<script type="text/javascript" src="../js/dc.js"></script>
<script type="text/javascript">
d3.csv('sampleData20000.csv').then(function(rowData) {
rowData.forEach(function(d) {
d.feature1 = +d.feature1;
d.feature2 = +d.feature2;
d.feature3 = +d.feature3;
d.class = +d.class;
})
// Calculate x and y binning with each bin being PIXEL_BIN_SIZE wide
const nXBins = 300; const nYBins = 300;
const binWidth = 20 / nXBins;
var ndx = crossfilter(rowData),
dim1 = ndx.dimension(function (d) {
return [Math.floor(d.feature1 / binWidth) * binWidth,
Math.floor(d.feature2 / binWidth) * binWidth, d.class];
}),
dim2 = ndx.dimension(function (d) {
return [Math.floor(d.feature2 / binWidth) * binWidth,
Math.floor(d.feature3 / binWidth) * binWidth, d.class];
}),
group1 = dim1.group(),
group2 = dim2.group();
// var ndx = crossfilter(rowData),
// dim1 = ndx.dimension(function (d) {
// return [d.feature1, d.feature2, d.class];
// }),
// dim2 = ndx.dimension(function (d) {
// return [d.feature2, d.feature3, d.class];
// }),
// group1 = dim1.group(),
// group2 = dim2.group();
var plotColorMap = {0: '#ff7f0e', 1: '#2ca02c'};
var chart1 = dc.scatterPlot("#test1").width(300)
.height(300)
.useCanvas(true)
.x(d3.scaleLinear().domain([-8, 8]))
.yAxisLabel("Feature 2")
.xAxisLabel("Feature 1")
.keyAccessor(function (d) { return d.key[0]; })
.valueAccessor(function (d) { return d.key[1]; })
.clipPadding(10)
.dimension(dim1)
.excludedOpacity(0.5)
.excludedColor('#ddd')
.highlightedSize(4)
.group(group1)
.colorAccessor(function (d) { return d.key[2]; })
.colors(function(colorKey) { return plotColorMap[colorKey]; });
chart1.legendables = function () {
return [{name: 'Class 0', chart: chart1, color: plotColorMap[0]},
{name: 'Class 1', chart: chart1, color: plotColorMap[1]}];
}
chart1.legend(dc.legend().x(200).y(10).itemHeight(13).gap(5).legendWidth(90).itemWidth(70));
var chart2 = dc.scatterPlot("#test2").width(300)
.height(300)
.useCanvas(true)
.x(d3.scaleLinear().domain([-8, 8]))
.yAxisLabel("Feature 2")
.xAxisLabel("Feature 3")
.clipPadding(10)
.dimension(dim2)
.excludedOpacity(0.5)
.excludedColor('#ddd')
.highlightedSize(3)
.group(group2)
.colorAccessor(function (d) { return d.key[2]; })
.colors(function(colorKey) { return plotColorMap[colorKey]; });
chart2.legendables = function () {
return [{name: 'Class 0', chart: chart2, color: plotColorMap[0]},
{name: 'Class 1', chart: chart2, color: plotColorMap[1]}];
}
chart2.legend(dc.legend().x(200).y(10).itemHeight(13).gap(5).legendWidth(90).itemWidth(70));
dc.renderAll();
});
</script>
</div>
</body>
</html>