Public
Edited
Nov 3, 2023
2 stars
ca55 = FileAttachment("ca55-south.csv").csv({ typed: true })
Plot.contour(ca55, {
x: "LONGITUDE",
y: "LATITUDE",
fill: "MAG_IGRF90",
interpolate: "barycentric",
blur: 2
}).plot({
color: { type: "diverging" }
})
m = 200
n = 150
x = d3.scaleLinear(
d3.extent(ca55, (d) => d.LONGITUDE),
[0, m - 1]
)
X = ca55.map((d) => x(d.LONGITUDE))
y = d3.scaleLinear(
d3.extent(ca55, (d) => d.LATITUDE),
[n - 1, 0] // 🎃 reversed because latitude is pointing UP, and SVG is pointing down.
)
Y = ca55.map((d) => y(d.LATITUDE))
V = ca55.map((d) => d.MAG_IGRF90)
gridded = Plot.interpolatorBarycentric()(d3.range(V.length), m, n, X, Y, V)
blurred = d3.blur2({ width: m, height: n, data: gridded }, 1)
contoursg = d3.contours().size([m, n])(blurred.data)
contours = contoursg.map(({ coordinates, ...rest }) => ({
coordinates: coordinates.map((polygon) =>
polygon.map((ring) => ring.map((d) => [x.invert(d[0]), y.invert(d[1])]))
),
...rest
}))
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
