Working as a scientific software engineer in Max Planck Institute of Molecular Cell Biology and Genetic
Public
Edited
Apr 24, 2023
1 fork
draw = {
const d = data();
const className = d.map((d) => d.class);
const color = d3.scaleOrdinal().domain(className).range(d3.schemeAccent);
return Plot.plot({
x: {
label: null,
tickSize: 0
},
marks: [
Plot.ruleY([0]),
Plot.ruleX(d, { x: "time", y: "viability", fill: color("class") }),
Plot.dot(d, { x: "time", y: "viability", fill: color("class"), r: 4 })
]
});
}
chart = LineChart(data(), {
x: (d) => d.time,
y: (d) => d.viability,
z: (d) => d.class,
yLabel: "↑ Viability ($)",
width,
height: 500,
color: "steelblue"
})
cell_chart = LineChart(data(), {
x: (d) => d.time,
y: (d) => d.cell_size,
z: (d) => d.class,
yLabel: "↑ Cell Size ($)",
width,
height: 500,
color: "crimson"
})
Plotly = require("https://cdn.plot.ly/plotly-1.41.1.min.js")
{
const d = dat;
const time = [],
classes = [],
viability = [],
cell_size = [],
text = [];
for (let i = 0; i < d.length; i++) {
let row = d[i];
time.push(row.time);
classes.push(row.class);
viability.push(row.viability);
cell_size.push(row.cell_size);
text.push(
"<b>" +
row.class +
"</b><br>time:" +
row.time.toLocaleString() +
"<br>viability:" +
row.viability +
"<br>cell size:" +
row.cell_size
);
}
var trace2 = {
x: time,
y: viability,
text: "Viability",
name: "Viability",
marker: {
size: cell_size,
sizeref: (2 * d3.max(cell_size)) / 17 ** 2,
sizemode: "area"
},
transforms: [{ type: "groupby", groups: classes }],
hovertext: text,
hoverinfo: "text",
mode: "lines+markers",
type: "scatter"
};
var traces = [trace2];
const div = DOM.element("div");
Plotly.newPlot(div, traces, {
width: width,
hovermode: "closest",
hoverlabel: { bgcolor: "#FFF" },
yaxis: { title: "Viability (%)" },
yaxis2: { title: "Cell Size (um)" }
});
return div;
}
{
const d = dat;
const time = [],
classes = [],
viability = [],
cell_size = [],
text = [];
for (let i = 0; i < d.length; i++) {
let row = d[i];
time.push(row.time);
classes.push(row.class);
viability.push(row.viability);
cell_size.push(row.cell_size);
text.push(
"<b>" +
row.class +
"</b><br>time:" +
row.time.toLocaleString() +
"<br>viability:" +
row.viability +
"<br>cell size:" +
row.cell_size
);
}
var trace3 = {
x: time,
y: cell_size,
transforms: [{ type: "groupby", groups: classes }],
hovertext: text,
hoverinfo: "text",
mode: "lines+markers",
type: "scatter"
};
var traces = [trace3];
const div = DOM.element("div");
Plotly.newPlot(div, traces, {
width: width,
hovermode: "closest",
hoverlabel: { bgcolor: "#FFF" },
yaxis: { title: "Cell Size (um)" }
});
return div;
}
import { LineChart } from "@d3/multi-line-chart"
data1 = FileAttachment("data.json").json()
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.