Maps — and other representations of the world.
// dataset organized by the TTT (Tribute to Tobler) project
data = d3.json("https://raw.githubusercontent.com/tributetotobler/ttt/main/data/dollars.json")
// compute the balance of dollar bills as the difference between
// the sum of the rows and the sum of the columns of the OD matrix
balance = d3
.zip(
d3.transpose(data.OD).map((out) => d3.sum(out)),
data.OD.map((out) => d3.sum(out))
)
.map(([p, m]) => m - p)
// The balance of each region is spread out uniformly on all the points that belong to the regions
// Select "charge" to display this vector of values on the map; NaN for points that don't participate.
values = {
const V = new Float64Array(points.length).fill(NaN);
for (let i = 0; i < points.length; i++) {
for (let p = 0; p < data.polygones.length; p++) {
const poly = data.polygones[p].geom.coordinates[0];
if (d3.polygonContains(poly, pts[i])) {
V[i] = p;
break;
}
}
}
d3.rollup(
d3.range(V.length),
(I) => I.forEach((i) => (V[i] = balance[V[i]] / I.length)),
(i) => V[i]
);
return V;
}
// see this notebook for a graph-based solution to the Poisson equation,
// which returns the potential and shows the map
import { chart, viewof blurRadius } with {
viewof display,
points,
values as C
} from "@fil/poisson-potential"
// This projection transforms Tobler's geojson to screen coordinates
projection = d3
.geoIdentity()
.reflectY(true)
.fitExtent(
[
[2, 32],
[width - 2, height - 2]
],
{
type: "GeometryCollection",
geometries: data.polygones.map((d) => d.geom)
}
)
import { pick2d } from "@fil/2d-point-distributions"
W = 72 // width of the original space
H = 46 // height of the original space
// a point distribution in Tobler’s original space
pts = [...pick2d(W, H, npoints, distributionType)]
points = pts.map(projection)
height = 550
topojson = require("topojson@3")
border = {
const topo = topojson.topology({
regions: {
type: "GeometryCollection",
geometries: data.polygones.map((d) => d.geom)
}
});
return topojson.merge(topo, topo.objects.regions.geometries);
}
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