Public
Edited
Dec 25, 2023
2 stars
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c_to_dim = d3.rollup(
computed_dimensions,
(a) => format(a[0].dim),
(o) => `${format(o.re)} ${format(o.im)}`
)
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computed_dimensions = {
let computed_dimensions = await FileAttachment(
"julia_dimensions-005@3.csv"
).csv({
typed: true
});
let flipped = computed_dimensions
.filter((o) => o.im > 0)
.map(function (o) {
let oo = Object.assign({}, o);
oo.im = -oo.im;
return oo;
});

return computed_dimensions.concat(flipped);
}
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format = d3.format("0.3f")
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tippy_style = html`<div style="display: hidden">
<link rel="stylesheet" href="${await require.resolve(
`tippy.js/themes/light.css`
)}"></div>`
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tippy = require("tippy.js")
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math = require("mathjs")
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import { QuadraticJuliaSet } from "3897c7fe05d9fd50"
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import { Legend } from "@d3/color-legend"
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Plot = import("https://esm.run/@observablehq/plot@0.6.13")
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Plot.version
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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.
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