chart = {
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height])
.attr("id", "chart");
svg.append("g")
.call(xAxis);
svg.append("g")
.call(yAxis);
svg.append("g")
.selectAll("path")
.data(data.series)
.join("path")
.attr("d", d => area(d.y_bounds))
.attr("data-index", (d, i) => i)
.attr("data-name", d => d.name)
.attr("fill", (d, i) => colors[i][0])
.attr("stroke", "none")
.attr("class", "area");
svg.append("g")
.selectAll("path")
.data(data.series)
.join("path")
.attr("d", d => line(d.y))
.attr("data-index", (d, i) => i)
.attr("data-name", d => d.name)
.attr("fill", "none")
.attr("stroke", (d, i) => colors[i][0])
.attr("stroke-width", 1.5)
.attr("stroke-linejoin", "round")
.attr("stroke-linecap", "round")
.attr("class", "line");
svg.append("g")
.selectAll("text")
.data(lineLabels)
.enter().append("text")
.text(d => d.text)
.attr("fill", (d, i) => colors[i][1])
.attr("x", d => margin.left + (width * d.x))
.attr("y", d => margin.top + (height * d.y))
.attr("alignment-baseline", "middle")
.attr("text-anchor", "middle")
.attr("class", "small-copy");
return svg.node();
}
height = {
if (width > 800) {
return 450 + margin.top + margin.bottom
} else {
return width * 9/16 + margin.top + margin.bottom
}
}
margin = ({top: 20, right: 0, bottom: 40, left: yTickSize})
yTickSize = 40
yLabelOffset = -yTickSize + 30
colors = [ // [light, dark] colors for each line
["#5C94D0", "#3775B8"], // multi-agent
["#C4C4D0", "#9191A4"], // baseline
["#E2AB43", "#C78D21"], // count-based
]
lineLabels = [
{text: "Multi-agent", x: 0.45, y: 0.22}, // x and y are percentages
{text: "Baseline", x: 0.50, y: 0.50},
{text: "Count-based", x: 0.30, y: 0.10},
]
xLabel = "Samples"
yLabel = "Normalized Reward"
x = d3.scaleLinear()
.domain(d3.extent(data.x))
.range([margin.left, width - margin.right])
y = d3.scaleLinear()
.domain([0, 1]).nice()
.range([height - margin.bottom, margin.top])
xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x)
.ticks(width / 140)
// .tickFormat(d3.format(".0s"))
.tickFormat(d3.formatPrefix(".0", 1e6))
.tickSizeOuter(0))
.call(g => g.selectAll(".tick text") // tick labels
.attr("class", "xsmall-copy"))
.call(g => g.select(".tick:first-of-type text").clone() // unit label
.attr("y", 28)
.attr("class", "xsmall-copy font-bold font-sans-serif")
.text(`${xLabel}`))
yAxis = g => g
.attr("transform", `translate(${margin.left + 1},0)`)
.attr("stroke-opacity", 0.05)
.call(d3.axisLeft(y)
.ticks(height / 100)
.tickSize(yTickSize)) // left axis
.call(g => g.selectAll(".tick line").clone() // grid lines
.attr("stroke-opacity", 0.05)
.attr("x2", width - margin.left - margin.right))
.call(g => g.select(".tick:first-of-type") // first tick opacity
.attr("stroke-opacity", 1))
.call(g => g.selectAll(".tick text") // tick labels
.style("text-anchor", "start")
.attr("x", -yTickSize)
.attr("y", -9)
.attr("class", "xsmall-copy"))
.call(g => g.select(".domain").remove()) // remove domain line
.call(g => g.select(".tick:last-of-type text").clone() // unit label
.attr("x", `${yLabelOffset}`)
.attr("text-anchor", "start")
.attr("class", "xsmall-copy font-bold font-sans-serif")
.text(`${yLabel}`))
area = d3.area()
// .defined(d => !isNaN(d))
.x((d, i) => x(data.x[i]))
.y0(d => y(d[0]))
.y1(d => y(d[1]))
line = d3.line()
// .defined(d => !isNaN(d))
.x((d, i) => x(data.x[i]))
.y(d => y(d))
data = {
const data = await d3.json("https://gist.githubusercontent.com/justinjaywang/f550f718980f2057b6e939c7f008e025/raw/f1b5463667faddc1f17f329beb215b971b347037/object_counting.json");
data.series = Object.keys(data).map(k => ({
name: k,
y: data[k].y,
y_bounds: [data[k].y_lower, data[k].y_upper],
}));
data.series.forEach(s => {
s.y_bounds = transpose(s.y_bounds)
}); // transpose y_bounds from 2 by l array into l by 2
data.x = data[Object.keys(data)[0]].x;
return data;
}
d3 = require("d3@5")
transpose = {
return (array) => array[0].map((col, i) => array.map(row => row[i]));
}
openaicss = {
return html`<link rel="stylesheet" type="text/css" href="https://cdn.openai.com/miscellaneous/observable-1.3.5/styles/openai-css.css">`
}
html`<style>
svg, g {
color: var(--black);
font-size: 1rem;
}
#chart .area {
opacity: 0.1;
}
</style>`
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.