mbostock’s Scatterplot Matrix Brushing, ported to d3v4 by @Fil.
The scatterplot matrix visualizations pairwise correlations for multi-dimensional data; each cell in the matrix is a scatterplot. This example uses Anderson's data of iris flowers on the Gaspé Peninsula. Scatterplot matrix design invented by J. A. Hartigan; see also R and GGobi. Data on Iris flowers collected by Edgar Anderson and published by Ronald Fisher.
See also this simpler static version without brushing.
forked from Fil's block: Scatterplot Matrix Brushing d3v4
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<meta charset="utf-8">
<style>
svg {
font: 10px sans-serif;
padding: 10px;
}
.axis,
.frame {
shape-rendering: crispEdges;
}
.axis line {
stroke: #ddd;
}
.axis path {
display: none;
}
.cell text {
font-weight: bold;
text-transform: capitalize;
fill: black;
}
.frame {
fill: none;
stroke: #aaa;
}
circle {
fill-opacity: .7;
}
circle.hidden {
fill: #ccc !important;
}
.extent {
fill: #000;
fill-opacity: .125;
stroke: #fff;
}
.contour {
/*fill: red;*/
stroke: blue;
stroke-width: 0.5;
}
</style>
<body>
<script src="https://d3js.org/d3.v4.min.js"></script>
<script src="https://d3js.org/d3-contour.v1.min.js"></script>
<script>
function distance(p, set){
return Math.sqrt(
d3.min(set.map(q => {
var dx = p[0] - q[0],
dy = p[1] - q[1];
return dx * dx + dy * dy;
}))
);
}
function encircle_path(points, radius) {
radius = 4;
var p2 = points.map(d => [d[0] / radius, d[1] / radius])
var X = d3.extent(p2.map(d => d[0])),
Y = d3.extent(p2.map(d => d[1])),
width = Math.ceil(X[1] - X[0]) + 4,
height = Math.ceil(Y[1] - Y[0]) + 4,
data = [];
d3.range(width).map(i => d3.range(height).map(j => {
data[i + width * j] = -distance([i,j], p2);
}));
var path = d3.geoPath(d3.geoIdentity().scale(radius));
return d3.contours()
.size([width, height])
.thresholds([-15/radius])
(data)
.map(path);
}
var width = 960,
size = 230,
padding = 20;
var x = d3.scaleLinear()
.range([padding / 2, size - padding / 2]);
var y = d3.scaleLinear()
.range([size - padding / 2, padding / 2]);
var xAxis = d3.axisBottom()
.scale(x)
.ticks(6);
var yAxis = d3.axisLeft()
.scale(y)
.ticks(6);
var color = d3.scaleOrdinal(d3.schemeCategory10);
d3.csv("flowers.csv", function(error, data) {
if (error) throw error;
var domainByTrait = {},
traits = d3.keys(data[0]).filter(function(d) { return d !== "species"; }),
n = traits.length;
traits.forEach(function(trait) {
domainByTrait[trait] = d3.extent(data, function(d) { return d[trait]; });
});
xAxis.tickSize(size * n);
yAxis.tickSize(-size * n);
var brush = d3.brush()
.on("start", brushstart)
.on("brush", brushmove)
.on("end", brushend)
.extent([[0,0],[size,size]]);
var svg = d3.select("body").append("svg")
.attr("width", size * n + padding)
.attr("height", size * n + padding)
.append("g")
.attr("transform", "translate(" + padding + "," + padding / 2 + ")");
svg.selectAll(".x.axis")
.data(traits)
.enter().append("g")
.attr("class", "x axis")
.attr("transform", function(d, i) { return "translate(" + (n - i - 1) * size + ",0)"; })
.each(function(d) { x.domain(domainByTrait[d]); d3.select(this).call(xAxis); });
svg.selectAll(".y.axis")
.data(traits)
.enter().append("g")
.attr("class", "y axis")
.attr("transform", function(d, i) { return "translate(0," + i * size + ")"; })
.each(function(d) { y.domain(domainByTrait[d]); d3.select(this).call(yAxis); });
var cell = svg.selectAll(".cell")
.data(cross(traits, traits))
.enter().append("g")
.attr("class", "cell")
.attr("transform", function(d) { return "translate(" + (n - d.i - 1) * size + "," + d.j * size + ")"; })
.each(plot);
// Titles for the diagonal.
cell.filter(function(d) { return d.i === d.j; }).append("text")
.attr("x", padding)
.attr("y", padding)
.attr("dy", ".71em")
.text(function(d) { return d.x; });
cell.call(brush);
function plot(p) {
var cell = d3.select(this);
x.domain(domainByTrait[p.x]);
y.domain(domainByTrait[p.y]);
cell.append("rect")
.attr("class", "frame")
.attr("x", padding / 2)
.attr("y", padding / 2)
.attr("width", size - padding)
.attr("height", size - padding);
cell.selectAll("circle")
.data(data)
.enter().append("circle")
.attr("cx", function(d) { return x(d[p.x]); })
.attr("cy", function(d) { return y(d[p.y]); })
.attr("r", 4)
.style("fill", function(d) { return color(d.species); });
var contours = encircle_path(data.map(d => [x(d[p.x]), y(d[p.y])]), 10);
cell.selectAll("path.contour")
.data(contours)
.enter()
.append('path')
.classed("contour", true)
.attr('d', d => d)
}
var brushCell;
// Clear the previously-active brush, if any.
function brushstart(p) {
if (brushCell !== this) {
d3.select(brushCell).call(brush.move, null);
brushCell = this;
x.domain(domainByTrait[p.x]);
y.domain(domainByTrait[p.y]);
}
}
// Highlight the selected circles.
function brushmove(p) {
var e = d3.brushSelection(this);
svg.selectAll("circle").classed("hidden", function(d) {
return !e
? false
: (
e[0][0] > x(+d[p.x]) || x(+d[p.x]) > e[1][0]
|| e[0][1] > y(+d[p.y]) || y(+d[p.y]) > e[1][1]
);
});
}
// If the brush is empty, select all circles.
function brushend() {
var e = d3.brushSelection(this);
if (e === null) svg.selectAll(".hidden").classed("hidden", false);
}
});
function cross(a, b) {
var c = [], n = a.length, m = b.length, i, j;
for (i = -1; ++i < n;) for (j = -1; ++j < m;) c.push({x: a[i], i: i, y: b[j], j: j});
return c;
}
</script>
https://d3js.org/d3.v4.min.js
https://d3js.org/d3-contour.v1.min.js